Phylogeny and population genetics of the fish performing the largest migration known in freshwater, the Amazonian catfish Brachyplatystoma rousseauxii: revelations from the Upper Madera Basin

Fernando M. Carvajal-Vallejos

The migratory catfish Brachyplatystoma vaillantii is one of the most important fishery resources in the Amazon. Intense capture occurs associated to its life cycle. In order to know the genetic status, we sequenced the mitochondrial DNA control region from 150 individuals of B. vaillantii, collected in five fishing landing locations, covering the length of the Solimões-Amazonas River in Brazil. Genetic diversity parameters suggest there is no genetic differentiation between the five localities. Population's expansion indicated by R 2 and Fu's Fs tests was also confirmed by the high number of unique haplotypes found. The Analyses of molecular variance indicated that nearly all variability was contained within locations (99.86%), and estimates of gene flow among B. vaillantii were high (F ST = 0.0014). These results suggest that Brachyplatystoma vaillantii forms a panmitic population along the Solimões-Amazonas River and, has greater genetic variability than other species of the Brachyplatystoma genus available so far. Although the influence of different tributaries on B. vaillantii migration patterns remains uncertain, a single population in the main channel should be consider in future policies for management of this resource. However, since the species' life cycle uses habitats in several countries, its management and conservation depend greatly of internationally joined efforts.

The Bolivian part of the Amazon Basin contains a mega diverse and well-preserved fish fauna. Since the last decade, this fish fauna has received an increasing attention from scientists and the national authorities as fishes represent one of the most important sources of proteins for local human communities. However, this fish fauna still remains poorly documented. Here, we present a database for fishes from the Bolivian Amazon. To build the database, we conducted an extensive literature survey of native and non-native (exotic) fishes inhabiting all major sub-drainages of the Bolivian Amazon. The database, named Fish-AMAZBOL, contains species lists for 13 Amazonian hydrological units, covering 100% of the Bolivian Amazon and approximately 65% (722,137 km2) of the all territory. Fish-AMAZBOL includes 802 valid species, 12 of them being non-native, that have been checked for systematic reliability and consistency. To put this number in perspective, this represents around 14% of the all Neotropical ichthyofauna and around 6% of all strictly freshwater fishes inhabiting the planet. This database is currently the most comprehensive database of native and non-native fish species richness available so far for the Bolivian Amazon.

Biogeography of Amazonian fishes (2,500 species in vastly disjunct lineages) is complex and has so far been approached only partially. Here, we tackle the problem on the basis of the largest database yet on geographical distribution and phylogenetic relationships of Amazonian fishes, including all information available. Distributions of 4,095 species (both Amazonian and outgroups) and 84 phylogenetic hypotheses (comprising 549 phylogenetically-informative nodes) were compiled, qualified and plotted onto 46 areas (29 Amazonian and 17 non-Amazonian). The database was analyzed with PAE, CADE, BPA and BPA 0 , yielding largely congruent results and indicating that biogeographic signal is detectable on multiple dimensions of fish distribution, from single species ranges to cladistic congruence. Agreement is especially pronounced in deeper components, such as Trans-Andean, Cis-Andean, Western Amazon and Orinoco basins. Results show that all major Amazonian tributaries, as well as the Amazon basin itself, are non-monophyletic and constitute hybrid sets of heterogeneous biotic partitions. Amazonian drainages should not be assumed a priori as historically cohesive areas, contrary to widespread practice. Our hypothesis allows re-evaluation of broader issues in historical biogeography, such as the predictive power of biogeographic hypotheses, the vicariant/ dispersal duality, the significance of widely distributed taxa, and the need for temporal dimension in biogeographic patterns. A biogeografia dos peixes amazônicos (2.500 espécies de diferentes linhagens) é complexa e até agora foi abordada apenas parcialmente. Aqui abordamos o problema com base no maior banco de dados já feito sobre a distribuição geográfica e as relações filogenéticas dos peixes amazônicos, incluindo todas as informações disponíveis. A distribuição de 4.095 espécies (tanto amazônicas como de grupos-externos) e 84 hipóteses filogenéticas (que incluíam 549 nós filogeneticamente informativos) foram compiladas e qualificadas em 46 áreas (29 amazônicas e 17 não-amazônicas). O banco de dados foi analisado a partir das metodologias PAE, CADE, BPA e BPA0, resultando em topologias amplamente congruentes e indicando que o sinal biogeográfico é detectável em múltiplas dimensões, desde a simples distribuição de peixes até em congruência cladística. A concordância topológica é especialmente pronunciada em componentes mais profundos, como as bacias Trans-Andina, Cis-Andina, Amazonas Ocidental e Orinoco. Os resultados demonstram que todos os principais afluentes amazônicos, bem como a própria bacia amazônica, não são monofiléticos e constituem conjuntos híbridos formados a partir de parcelas bióticas heterogêneas. As drenagens amazônicas não devem ser consideradas a priori como áreas historicamente coesas, contrariamente à prática generalizada. Nossa hipótese permite a reavaliação de questões mais amplas na biogeografia histórica, como o poder preditivo de hipóteses biogeográficas, a dualidade vicariante/dispersão, significância de táxons amplamente distribuídos e a necessidade da dimensão temporal em padrões biogeográficos.

UNIVERSITÉ MONTPELLIER II SCIENCES ET TECHNIQUES DU LANGUEDOC THÈSE Pour obtenir le grade de DOCTEUR DE L’UNIVERSITÉ DE MONTPELLIER II Discipline: Écologie et Évolution École Doctorale : SIBAGHE (Systèmes Intégrés en Biologie, Agronomie, Géosciences, Hydrosciences, Environnement) Présentée et soutenue publiquement par Fernando Marcelo CARVAJAL VALLEJOS le 18 Janvier 2013 Titre PHYLOGENY AND POPULATION GENETICS OF THE FISH PERFORMING THE LARGEST MIGRATION KNOWN IN FRESHWATER, THE AMAZONIAN CATFISH Brachyplatystoma rousseauxii: REVELATIONS FROM THE UPPER MADERA BASIN Jury: Dr. Jean-François RENNO (IRD) Dr. Fabrice DUPONCHELLE (IRD) Dr. Anne CHENUIL (CNRS) Dr. Didier AURELLE (Université de Marseille) Pr. François MEUNIER (MNHN) Dr. Patric BERREBI (CNRS) Directeur de Thèse Co-directeur de Thèse Rapporteur Rapporteur Examinateur Examinateur (président) Drawn of the cover: Camilo CARVAJAL i To Camilo, Agustín and América To My Family ii ACKNOWLEDGEMENTS Special thanks to my advisors, Jean-François RENNO and Fabrice DUPONCHELLE, for their advice and support throughout this study and for sharing their experiences and reflections on the evolution and life histories of Amazonian fishes. To the Institute de Recherche pour le Development (IRD) and the World Wildlife Foundation (WWF - Russell E. Education for Nature Program) for the scholarships granted to conduct this study. To the Instituto de Investigaciones de la Amazonía Peruana (IIAP) for institutional support, and to the Laboratory of Molecular Biology and Biotechnology (Laboratorio de Biología Molecular y Biotecnología – LBMB, Iquitos), which held a significant portion of the analysis for this study. To Eric DESMARAIS from the Institut des Sciences de l'Evolution de Montpellier (ISEM, France), for his technical advice and collaboration to obtain microsatellite genotypes. To Carmen GARCÍA (director of LBMB, IIAP) and her staff for their cooperation during the work done in the LBMB. To Diana CASTRO (IIAP) for logistical support during the last years of work in the LBMB. To Susana SIRVAS from the Facultad de Oceanografía, Pesquería y Ciencias Alimentarias (FOPCA) at the Federico Villarreal University, for the institutional support and advice. To Juan Pablo TORRICO (former PhD student of IRD) for advice on the treatment of genetic data. To Nicolas HUBERT (IRD) for advice on CO1 sequence analysis and phylogenetic tree construction. To Jesús NUÑEZ (IRD) for logistical support during the stay at the Federico Villarreal University. To Andrea SANTY (WWF-EFN) for logistical assistance during the first two years of thesis. Special thanks to World Fisheries Trust, Monica MCISAAC, Donald MENTON, Joachim CAROSFELD, Tiffanie RAINVILLE, Fabrice DUPONCHELLE for their help in translating the document from Spanish to English. To Dylian CASTELLÓN and Mabel MALDONADO, from the Unidad de Limnología y Recursos Acuáticos (ULRA), Mayor de San Simón University iii (UMSS – Cochabamba, Bolivia), and to Paul VAN DAMME, from the FAUNAGUA Association (Cochabamba – Bolivia), for institutional support and sponsorship for obtaining the PhD scholarships with the IRD and WWF. To all fishermen, government and academic authorities in the Bolivian Amazon who kindly helped me with the sampling and permits during the years of fieldwork in the Madera, Beni, Madre de Dios, Mamoré and Ichilo rivers. Ronald PALACIOS, Mariano PALACIOS, Rene MAOLO and his family, Marcial MERCADO (Villa Bella), Manuel OHARA (Cachuela Esperanza), Bernardino MIRANDA (Guayaramerín), Wilfredo CHIPUNAVI and his family, Nixon GUARI (Riberalta), Fátima SOSA, Marcela CUELLAR, Alfredo PARADA (Trinidad), Ever RUELAS (San Buenaventura – Rurrenabaque), and Pascual MONTEJO (Puerto Villarroel), had a valuable participation in the sampling and field trips. I thank the fishermen with whom I worked, for sharing their experiences and knowledge during the long passages in which I participated. To my parents, Aurora and José, for their constant motivation and support during my professional formation. To my brothers Javier, Patricia and Maribel for the advice and ongoing collaboration. To Camilo CARVAJAL, ‘le petit’ Agustín CARVAJAL and América ZEBALLOS for the company and support over the years. iv - The scholarship was funded by IRD (3 years) and WWF-EFN (2 years). - The field work was funded by IRD and WWF-EFN. - The ademic training was funded by WWF-EFN. - The laboratory work was funded by IRD. - Several institutions participated in the field work in Bolivia: IRD, WWF-EFN, ULRA (San Simón University), CIRA (Autónoma del Beni University); Cochabamba, Beni and Pando governments, ASOPESAR, ASPECO, FAUNAGUA NGO. - The IRD and IIAP (Perú) assisted in the logistic and laboratory work in Iquitos. - The microsatellites genotypes were obtained with the kind collaboration of Dr. Eric DESMARAIS (Institute des Sciences de l'Evolution de Montpellier, France). v No other aspect of the living world is as fascinating and full of riddles as is evolution Fared D. DIAMOND (2001) vi TABLE OF CONTENTS ACKNOWLEDGES ....................................................................................................................................................... III ABSTRACT .................................................................................................................................................................. IX RÉSUMÉ ...................................................................................................................................................................... XI PREFACE ..................................................................................................................................................................... 1 CHAPTER 1 ................................................................................................................................................. 3 GENERAL INTRODUCTION ................................................................................................................... 3 1.1 Biological and migratory traits of freshwater fishes in the Neotropical region: the Plateado (Brachyplatystoma rousseauxii) as a case study ............................................................................................. 3 1.2 Questions and hypotheses about the population structure of Plateado (Brachyplatystoma rousseauxii) in relation to its migratory behavior along the Amazon and Madera rivers................................................. 12 1.3 Election of molecular descriptors used in evolutionary genetics and conservation ............................... 18 CHAPTER 2 ............................................................................................................................................... 23 Phylogeny of the family Pimelodidae and phylogenetic position of the Plateado (Brachyplatystoma rousseauxii) as revealed by mitochondrial (RC and CO1) and nuclear (F-reticulon4) sequences ...... 23 2.1 Introduction ............................................................................................................................................ 23 2.2 Methods ................................................................................................................................................. 27 2.2.1. Sample collection ........................................................................................................................... 27 2.2.2 Laboratory methodology and DNA extraction ................................................................................ 32 2.2.3 Molecular markers selection........................................................................................................... 33 2.2.3.1 Control Region (RC) - mtDNA .................................................................................................. 33 2.3.3.2 Cytochrome c Oxidase 1 (CO1) – mtDNA ................................................................................ 34 2.2.3.3 Introns (Freticulon-4) – nDNA ................................................................................................. 36 2.2.4 DNA amplification and sequencing ................................................................................................. 36 2.2.5 Genetic analysis .............................................................................................................................. 37 2.2.6 Molecular clock test and estimation of evolutionary distance ....................................................... 39 2.3 Results .................................................................................................................................................... 39 2.3.1 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on CR – mt DNA sequences ................................................................................................................................................ 39 2.3.2 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on CO1 – mtDNA sequences ................................................................................................................................................ 43 2.3.3 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on Freticulon-4 – nDNA squences ........................................................................................................................................ 46 2.3.4 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on concatenated mtDNA and nDNA sequences (CR, CO1, Freticulon-4) ............................................................................. 49 2.3.5 Comparison of our results on the molecular phylogeny of the Pimelodidae family with Lundberg et al.’ study, carried out in parallel .............................................................................................................. 52 2.4 Discussion ............................................................................................................................................... 53 CHAPTER 3 ............................................................................................................................................... 58 POPULATION GENETIC STRUCTURE OF PLATEADO (BRACHYPLATYSTOMA ROUSSEAUXII) IN THE UPPER MADERA (BOLIVIA) AND UPPER AMAZON RIVERS (PERU) AS SHOWN BY MICROSATELLITE (NUCLEAR DNA) ALLELIC VARIATION ANALYSIS AND CONTROL REGION (MITOCHONDRIAL DNA) SEQUENCES ....................................................................................................................................... 58 3.1 Introduction ............................................................................................................................................ 58 3.2 Material and Methods ............................................................................................................................ 63 Study Area ............................................................................................................................................... 63 Sample collection design ......................................................................................................................... 67 Laboratory Methodology and DNA Extraction......................................................................................... 74 Genetic Analysis ....................................................................................................................................... 75 Nuclear (microsatellite) DNA Analysis................................................................................................. 75 Identification of panmitic units (cluster analysis) and population structure ...................................... 78 Intrapopulational genetic diversity, Hardy-Weinberg equilibrium and linkage disequilibrium .......... 80 vii Indirect estimation of migrants........................................................................................................... 81 Mitochondrial DNA analysis (Control Region - CR) ............................................................................. 81 Phylogeographic analysis of the Control Region - CR .......................................................................... 82 Analysis of population structure according to the Control Region - CR .............................................. 83 Demographic history of the clusters defined by BAPS ........................................................................ 83 Coalescence ........................................................................................................................................ 84 3.3 Results .................................................................................................................................................... 85 3.3.1 Nuclear DNA (microsatellites) ......................................................................................................... 85 Genetic distance tree (Rousset 1997) established by microsatellites polymorphism for the geographical locations in each of the two main clusters .................................................................... 98 3.3.2 Mitochondrial DNA (Control Region - CR) ....................................................................................... 99 Genetic distance tree (Rousset 1997) established according to the variation in haplotype frequencies for the geographical locations in each of the two main clusters ...................................................... 107 Genetic distance tree (Rousset 1997) established according to microsatellite polymorphism: combination of the microsatellite (clusters) and haplotypes (haplogroups) results ........................ 109 Demography ..................................................................................................................................... 111 Differences between pairs (mismatch) ............................................................................................. 111 Demographics inferred through coalescence ................................................................................... 113 3.4 Discussion ............................................................................................................................................. 113 3.4.1 Nuclear DNA (microsatellite) ........................................................................................................ 113 3.4.2 Mitochondrial DNA (Control Region -CR) ...................................................................................... 117 3.4.3 Discrepancy between nuclear and mitochondrial DNA data ........................................................ 119 Hypothetical scenarios that could explain the discrepancies observed between mtDNA - CR and nDNA – microsatellites ...................................................................................................................... 119 CHAPTER 4 ............................................................................................................................................. 121 CONCLUSIONS AND PERSPECTIVES ................................................................................................. 121 Phylogeny of the Pimelodidae family (Siluriformes) and the phylogenetic position of the Plateado (Brachyplatystoma rousseauxii), as revealed by mitrocondrial (Control Region and Cytochrome Oxidase 1) and nuclear (F-reticulon4) sequences ........................................................................................................ 121 Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by nuclear DNA (microsatellites) .......................................................................................................................................... 122 Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by mitochondrial DNA (Control Region - CR) .................................................................................................................................. 123 Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by nuclear DNA (microsatellites) and mitochondrial DNA (Control Region - CR) ................................................................. 124 Perspectives................................................................................................................................................ 127 REFERENCES .......................................................................................................................................................... 131 viii ABSTRACT The Plateado or Dorado - Brachyplatystoma rousseauxii (Pimelodidae, Siluriformes) is a commercial migratory catfish species with one of the most surprising and enigmatic life histories in the Amazon basin, involving the largest migration known for a freshwater species, between the estuary and the head waters in the Andean piedmont. Phylogenetic relationships and genetic variability of the species have begun to be studied in the recent years and information is scarce in the literature, in spite of their relevance for the species’ conservation. The aim of the present work was to determine the molecular phylogenetic position of the Plateado in the Pimelodidae family and its population genetic structure in the Upper Madera (Villa Bella – VB, Cachuella Esperanza – CE, Puerto Maldonado – PM, Rurrenabaque – RU, Puerto Villarroel - PV) and Western Amazon (Iquitos - IQ) basins (Bolivia and Peru). The phylogenetic relationships were defined through a Maximum Likelihood (ML) analysis of nucleotide sequences of two mitochondrial (Control Region – CR, ~ 900 pb, 32 taxa; Cytochrome Oxidase 1 – CO1, ~ 650 bp, 61 taxa), and a nuclear fragment (F-reticulon4 - RTN4, ~1700 bp, 38 taxa). The population genetic structure was evaluated through the length polymorphism of nine microsatellites (284 inds) and CR sequence variations (461 inds + 45 from Brazil available in GenBank). Microsatellites frequencies variations were used to identify through a Bayesian approach (BAPS) the most probable panmictic units (clusters) in the whole data, after previous demonstration of a deviation to Hardy-Weinberg Equilibrium (HWE). The ML phylogenetic concatenated analysis showed the Pimelodidae family as a monophyletic group, with the genera Phractocephalus and Leiarius as basal lineages. The Calophysus-Pimelodus group was recovered consistently (100%), and the Sorubiminae group (83%) was relatively well supported. Inside the Sorubiminae, Platysilurus and Platystomatichthys showed a strong relationship. The most notable results in the phylogeny were the not wellsupported monophyly (77%) of the tribe Brachyplatystomatini and the nonmonophyly of Brachyplatystoma. Only the morfologically defined subgenus Malacobagrus (B. rousseauxii + (B. filamentosum + B. capapretum)) was recovered as monophyletic. B. vaillantii + Platynematichthys were positioned as the sister group to Malacobagrus (77%), and B. juruense + B. platynemum showed a strong relationship in a poorly supported (53%) group that included B. tigrinum, whose position was unresolved. These results suggest that Brachyplatystoma could contain Platynematichthys or be restricted to the subgenus Malacobagrus, and the other species be related to distinct (earliest) genera, in agreement with another study carried out in parallel with other markers. Therefore, a re-evaluation of the nominal Brachyplatystoma species should be carried out considering both morphological and molecular data. Microsatellite analysis of the whole data (Western Amazon + Upper Madera) showed a significant departure of the HWE expectations, as well as the analysis of the whole data from the Upper Madera region. In the light of these results, the Bayesian approach has been implemented, showing that at least three clusters are present in the Upper Madera and Western Amazon basins with partial overlapping distribution. Cluster 1 (83 ind) was observed only in the five localities from the Upper Madera, whereas the other clusters were observed in all sampled localities. Cluster 2 was the most important and Cluster ix 3 the least in terms of numerical abundance with 184 and 17 individuals, respectively. Cluster 3 was the most differentiated. To the margin of the cluster identification, it was evident the significant difference between Western Amazon (Iquitos region) and the Upper Madera basin. The genealogical analysis (ML) of the CR sequences showed a generalized comb-like topology without group of haplotypes with common ancestry. On the other hand, CR frequency analysis showed the conformation of four haplogroups associated to geography. One haplogroup was identified along the main axis of the Amazonas-Solimões, from Belem (Brazil) to Iquitos (Peru), and three other haplogroups were observed in the Upper Madera basin (VB; CE+PM; RU+PV), positioned in a downstream - upstream pattern. The Mismatch analysis and Bayesian Skyline Plot of the haplotypes in clusters 1 and 2 suggested that both clusters went through population expansions between 200 000 – 100 000 and 250 000 – 50 000 years ago, respectively. Hence, we observed on the one hand three genetic populations (clusters), distributed in partially overlapping geographical areas, and on the other hand four haplogroups, positioned according to a geographical pattern. In order to explain this complex genetic organization and the apparent discrepancy between mtDNA and nDNA markers, some theoretical scenarios are explored and a hypothesis of differential behavior between females and males is proposed, where females are more sedentary than males within their populations. The most probable scenario involves a homing behavior of individuals from cluster 1 (homing at the scale of large watersheds), which prefer or tend to return to the Madera basin, with the three populations coexisting within the upper Madera because they reproduce at different moments (phenology) or different places (spatial segregation). These results highlight the importance of geography, but also of behavior aspects in the evolution of B. rousseauxii population structure. The extent of homing occurrence in the Amazon basin remains unknown. The role of the white-water tributaries’ upper reaches as spawning areas (e.g. Madera River), however, is determinant for the species persistence, hence of its fisheries. Finally, the results are discussed in the light of previous results in the Amazon basin and the threats to the species in the Madera basin (p.e. fragmentation by dams, overfishing, climate variability, among other). x RÉSUMÉ Le plateado ou dorado - Brachyplatystoma rousseauxii (Pimelodidae, Siluriformes) est un grand poisson-chat Amazonien d’intérêt commercial, qui présente un des cycles de vie les plus surprenants et énigmatiques, avec la plus grande migration connue en eaux douces, entre l’estuaire de l'Amazone et les têtes de fleuves en Amazonie occidentale. Les relations phylogénétiques et la variabilité génétique de cette espèce ont commencé à être étudié récemment, et les informations sont rares dans la littérature, malgré leur importance pour la conservation de cette espèce, très fortement exploitée. Le but de ce travail était de déterminer, au niveau moléculaire, la position phylogénétique du plateado dans la famille Pimelodidae ainsi que sa structure génétique dans le Haut Madera (Villa Bella - VB, Cachuella Esperanza - CE, Puerto Maldonado - PM, Rurrenabaque - RU, Puerto Villarroel – PV) et ouest de l'Amazonie (Iquitos - IQ) bassins (Bolivie et Pérou). Les relations phylogénétiques ont été définies par une analyse du maximum de vraisemblance (ML) des séquences nucléotidiques de deux gènes mitochondriaux (Région de Contrôle - CR, ~ 900 pb, 32 taxons; Cytochrome Oxydase 1 - CO1, ~ 650 pb, 61 taxons), et d’un gène nucléaire (F-reticulon4 RTN4, ~ 1700 pb, 38 taxons). La structure génétique des populations a été évaluée par le polymorphisme de longueur de neuf microsatellites (284 inds) et par les variations de séquence de la CR (461 inds + 45 en provenance du Brésil, disponibles dans GenBank). Les variations de fréquences des microsatellites ont été utilisées pour identifier les unités panmictiques (clusters) les plus probables dans l'ensemble des données, à travers une approche bayésienne (BAPS), après avoir démontré une déviation significative à l'équilibre de Hardy-Weinberg (HWE) quand l’ensemble des données étaient analysé comme faisant partie d’une seule unité. L’analyse phylogénétique concaténée (ML) a montré que la famille Pimelodidae était un groupe monophylétique, avec les genres Phractocephalus et Leiarius comme lignées basales. Le groupe Calophysus-Pimelodus était complètement soutenu (100%), et le groupe Sorubiminae relativement bien soutenu (83%). A l'intérieur des Sorubiminae, Platysilurus et Platystomatichthys ont montré une forte relation. Les résultats les plus notables de la phylogénie sont la monophylie peu soutenue (77%) de la tribu Brachyplatystomatini et la nonmonophylie des Brachyplatystoma. Seul le sous-genre Malacobagrus (B. rousseauxii + (B. filamentosum + B. capapretum)), défini morphologiquement, s’est avéré monophylétique. B. vaillantii + Platynematichthys ont été positionnés comme groupe frère de Malacobagrus (77%). B. juruense + B. platynemum ont montré une forte relation au sein d’un groupe mal supporté (53%) incluant B. tigrinum, dont la position reste non résolue. Ces résultats suggèrent que le genre Brachyplatystoma pourrait contenir Platynematichthys ou pourrait être limité au sous-genre Malacobagrus et que les autres espèces pourraient être ré attribuées à leur genres d’origine, en accord avec les résultats d’une étude menée en parallèle, sur d’autres marqueurs. Par conséquent, une nouvelle évaluation des espèces nominales de Brachyplatystoma devrait être réalisée en considérant à la fois les données morphologiques et moléculaires. L'analyse des microsatellites sur l'ensemble des échantillons (ouest Amazone + haut Madera) a montré un écart significatif á la panmixia, ainsi que sur xi l'ensemble des échantillons du haut Madera. A la lumière de ces résultats, l’approche bayésienne a été développée, montrant qu'au moins trois groupes (clusters) sont présents dans les bassins du haut Madera et de l'ouest de l'Amazone, avec des répartitions qui se chevauchent partiellement. Le cluster 1 (83 ind) n'a été observé que dans les cinq localités du haut Madera, tandis que les deux autres clusters étaient présent dans toutes les localités. Le cluster 2 était le plus abondant numériquement et le cluster 3 le moins abondant, avec respectivement 184 et 17 individus. Le cluster 3 était le plus différencié. En parallèle á l'identification des clusters, il a été mis en évidence une différence significative au sein de B. rousseauxii entre l’ouest de l'Amazonie (région d'Iquitos) et le haut Madera bassin. L'analyse généalogique (ML) des séquences de la région de contrôle (CR) a montré une topologie en peigne, sans groupe d'haplotypes montrant une histoire commune. En revanche, l'analyse des fréquences haplotypiques a révélé l’existence de quatre haplogroupes, liés à la géographie. Un haplogroupe a été identifié le long de l'axe principal de l’Amazonas-Solimões (entre Belem-Brésil et Iquitos-Pérou) et trois autres dans le haut Madera (VB; CE + MD; RU + PV), organisés selon une tendance aval - amont. Les analyses Mismatch et Skyline Plot des haplotypes des clusters 1 et 2 ont suggéré que les deux clusters avaient traversé des périodes d’expansion populationnelle, il y a environ 200000-100000 ans et 250000-50000 ans, respectivement. Ainsi, nous observons d’un coté trois populations (clusters) avec une distribution géographique partiellement chevauchante, et de l’autre quatre haplogroupes positionnés selon une logique géographique. Pour expliquer cette organisation génétique complexe et l'écart apparent entre les résultats obtenus à partir de l'ADNmt et de l’ADNn, différents scénarii théoriques sont explorés et une hypothèse de comportement différentiel entre mâles et femelles est proposée, dans laquelle les femelles sont plus sédentaires que les males à l’intérieur de leurs populations. Le scenario le plus probable implique un comportement de homing des individus du cluster 1 (homing à l’échelle des grands sous-bassins), qui préfèrent ou tendent à retourner dans le sous-bassin du Madera. Les trois populations (clusters) coexisteraient alors dans le haut Madera en se reproduisant à des périodes (phénologie) ou à des endroits différents (ségrégation spatiale). Ces résultats soulignent l’importance de la géographie, mais aussi des aspects comportementaux dans l’évolution de la structure génétique de B. rousseauxii. La fréquence potentielle des phénomènes de homing dans le bassin amazonien demeure inconnue. En revanche, le rôle des têtes de fleuves d’eaux blanches comme zones de reproduction (e.g. le Madera) est déterminant pour la persistance de l’espèce et par conséquent de son exploitation. Enfin, les résultats sont discutés à la lumière des résultats précédemment publiés dans le bassin de l'Amazone et des menaces qui pèsent sur l'espèce dans le bassin du Madera (p.e. fragmentation par les barrages, surpêche, changements climatiques, entre autres). xii PREFACE The Central and South American Neotropical zone possesses high (specific) species richness. Actual numbers range from over 4400 up to 6000, according to experts (Reis et al. 2003). Several of these species undertake migrations for reproductive or feeding purposes as a key trait of their life strategies (Harvey & Carosfeld 2003). In the Amazon basin, the most extensive of the continent, larger species undertake both longitudinal and lateral migratory movements at distinct scales (Araujo-Lima & Goulding 1997; Araujo-Lima & Ruffino 2003; Castello 2008). These species have high commercial value (Goulding 1980; Almeida et al. 2001; Van Damme et al. 2011b) and basically belong to the Siluriformes and Characiformes groups. Within the Silurids, the Pimelodidae family is one of the most commercially representative (Ferreira et al. 1998; Van Damme et al. 2011b) and little is known about their phylogenetic relationships and molecular identification. Among Pimelodid, Brachyplatystoma rousseauxii (previously B. flavicans), known as Plateado, Dorado, or Dourada, presents the most extensive migratory movements known in continental waters. According to Barthem & Goulding (1997, 2007), the species reproduces near to the Andean foothills, is raised in the estuary of the Amazon River, and grows in the central Amazon. Based on this model, the Plateado migrates over 4 000 kilometers from the estuary to reach the headwaters of the turbid waters (white) to complete their life cycle. If the mature individuals are able to recognize their birthplace (homing), as suggested in a preliminary study (Batista & AlvesGomes 2006), the species could potentially be structured in distinct populations, in relation to the spatial and temporal variability in the basin. Hence, the present study focused on two principal objectives: (a) to establish the molecular phylogenetic relationships of Plateado in the Brachyplatystoma genus and the Pimelodidae family using two mitochondrial descriptors and one nuclear descriptor; and (b) to determine the population structure of Plateado in the upper basin of the Madera River and the Western Amazon using a reproductive homing model and design. The following study was divided into four chapters. The first is dedicated to the introduction of the research problems surrounding the phylogeny and genetics of the Plateado populations. The chapter provides a brief synthesis of the biology of the species, the molecular descriptors used, and establishes the research questions and hypotheses. The second chapter investigates the Plateado’s phylogenetic positioning in the Pimelodidae family and the Brachyplatystoma genus, based on information obtained from two mitochondrial descriptors (Control region - RC and Citocromo Oxidasa 1-CO1) and one nuclear (Freticulon-4). This chapter centers on reviewing the monophyletic nature of the B. rousseauxii species and the establishment of its evolutionary interrelations with the species which morphologically form part of the genus sensu Lundberg & Akama (2006). In doing so, the study evaluates the integrity of the Brachyplatystoma genus as a natural group, and compares its relations with those from other taxa which form part of the Pimelodidae family. The third chapter examines the population genetics of the Plateado in the upper basin of the Madera River and the Ucayali-Amazonas River system using nuclear descriptors (microsatellites), and one mitochondrial descriptor 1 (Control region- RC). This chapter focuses on the identification of haplotipical (haplogroups) and panmictic (clusters) units within the study area (Upper Madera and Ucayalí-Amazonas), and on the evaluation of a homing strategy at distinct scales (e.g. tributaries of the upper basin of the Madera River). Finally, chapter four responds to the research questions and suggests perspectives for future research. The impacts of these results for the conservation of the species are emphasized, considering present threats (e.g. overfishing), and future threats (e.g. hydroelectric dams) in a region which is still poorly understood and facing increasing destruction. 2 Chapter 1 GENERAL INTRODUCTION 1.1 Biological and migratory traits of freshwater fishes in the Neotropical region: the Plateado (Brachyplatystoma rousseauxii) as a case study There is a large variety of migratory fish species in the rivers of South America, with remarkably diverse forms and life history traits. Most migratory species correspond to two major taxonomic groups: the Characiformes – fishes with scales (e.g. genus Colossoma, Piaractus, Prochilodus, Salminus), and the Siluriformes – fishes with skin and whiskers (e.g. genus Brachyplatystoma, Pseudoplatystoma, Zungaro) (Harvey & Carosfeld 2003, Appendix A; Van Damme et al. 2011a). Their life history strategies fit into the periodic definition (r2), which consists of late maturity at a medium to large body size, high fecundity, small oocytes, a single and short episode of reproduction, rapid larval and juvenile growth and prevalence of juvenile fish during the rainy season (Winemiller & Taphorn 1989; Winemiller & Rose 1992). These migratory species have different diets and occupy a large range of trophic levels in the in the food webs. Some species predominantly feed on detritus (e.g. Prochilodus, Semaprochilodus), fruit (e.g. Piaractus, Mylossoma), plankton (e.g. Hypophthalmus) and others on fish (e.g. Brachyplatystoma) (Harvey & Carosfeld 2003). Most migratory species in the Amazon basin perform their reproductive movement up-stream and their nutritive movements downstream and laterally into adjacent environments (e.g. flood plain, Filho & Schulz 2003). The migration strategies vary according to taxonomic groups and river basins. Migrations undertaken throughout the river or stream channels are usually referred to as longitudinal, while those between the main channels and floodplain are referred to as lateral (Fernandes 2006). According to Lucas and Baras (2001), fish migrations have mainly reproductive or nutritional aims, but can also be motivated by the need for refuge. The reproductive strategy of most migratory species in the Amazon basin consists in releasing eggs in the main rivers or streams channels. There, the resulting larvae drift passively through the waters, following the predictable annual dynamics of expansion (flooding) and contraction movements, to reach favorable habitats for shelter, feeding and growth (Lowe-McConnel 1987; Lucas and Baras 2001). Floodplains, flooded forests and the estuary zone are essential areas for the development of larvae and juveniles for the vast majority of both migratory species and resident fish species in the Amazon basin (Araujo-Lima & Goulding 1997; Baumgartner et al. 1997; Rodríguez et al. 2007; Daga et al. 2009; Jiménez-Segura et al. 2010; Viana et al. 2010). In these same environments, adults encounter the resources and energy required to start a new reproductive cycle. Current knowledge indicates that the reproduction of many species is activated by and depends almost entirely on the signals or variables associated with the flooding period (e.g. Lowe-McConnell 1964, 1987; Goulding 1980; Muñoz and Van Damme 1998; Lucas & Baras 2001; Robinson et al. 2002; Stassen et al. 2010). Reproductive migration occurs mostly in large schools of fish; it has been frequently observed for medium to small species of Characiformes (e.g. Prochilodus, Brycon), yet very rarely observed for Siluriformes (e.g. 3 Brachyplatystoma, Pseudoplatystoma in areas with rapids). It is estimated that the larger species (catfish), generally migrate distances near or superior to 1000 km for reproductive and/or nutritive purposes (Barthem & Goulding 1997, 2007; Van Damme et al. 2011a). Basically, the migration model consists in an upstream movement in schools of adults followed by a downstream transport of eggs and larvae, and ultimately the dispersal of adults into the floodplains, streams, or deeper portions of the rivers. However, migration models are variable and complex, especially in the Amazon basin. Species in large rivers may be comprised of more than one population with distinct adaptation mechanisms, for example populations in different areas of a basin (e.g. Calcagnotto & DeSalle 2009), or localized populations in tributaries with different water qualities (e.g. Huergo 2009). These situations demonstrate that migration patterns can be much more complex than expected, even within the same species. Perceptions and spatial representation of migration patterns of a given species in larger systems of the continent is hampered by the paucity of detailed information on its movements and genetic demarcations (Harvey & Carosfeld et al. 2003). Indeed, the genetic tools that delimit or distinguish populations or species (e.g. Renno et al. 1990; Formiga 2004; Turner et al. 2004; Moyer et al. 2005; Batista 2009; Pereira et al. 2009; Farias et al. 2010; Carvalho de Costa et al. 2011), and telemetry techniques that track fish movements (e.g. Godinho & Kynard 2006; Alves et al. 2007), are being used only since a few decades. Such tools, and their ability to provide sketches of the migration patterns, are undoubtedly important to predict and to understand the effects produced by disturbances or threats such as changes in flow dynamics, pollution (e.g. mining, pesticides), deforestation, hydroelectric dams, climate change, overfishing, introduction of non-native species, among others (Harvey & Carolsfeld 2003; McClain & Naiman 2008; Murchie et al. 2008; Barletta et al. 2010; Esguícero & Arcifa 2010; Kemp et al. 2011). In absence of sound data on the migratory patterns of most fish species, the true effects of these alterations on their life histories can only be imagined and evaluated as potential scenarios (e.g. Van Damme et al. 2011c). Yet, it is evident that South American migratory fishes play an important role in the maintenance of aquatic systems given their participation in several ecological processes, such as the transfer of nutrients (e.g. Winemiller & Jepsen 1998; Winemiller & Jepsen 2004; Flecker et al. 2010), the carbon flows (e.g. Taylor et al. 2006) and the dispersion of organisms (plant seeds – e.g. Strap et al. 2007; Lucas 2008; Anderson et al. 2009; Parolin et al. 2010; hematophagous fish – e.g. Zuanon & Sazima 2005), among others. Migratory species, which additionally hold great economic value – e.g. five of these species account for 70% of the fish landings in Central Amazonia (Ferreira 2009) – should therefore be a priority in conservation and management policies at the regional scale. One of the groups of migratory fish in the Neotropical region that has received most attention by the scientific community is that of the family Pimelodidae. This family is composed of 30 genera and more than 80 species (Reis et al. 2003; Ferraris Jr. 2007; Parisi & Lundberg 2009). It contains the most representative and economically important fish species of rivers and lagoons in the South American continent. Several of these species reach well over 100 cm 4 in length and 10 kg of body weight, and are among the largest Neotropical fish species after the Osteoglossiform, Arapaima gigas (Berra 2001; Nelson 2006). Within the same family, the genus Brachyplatystoma represents a particular case as it contains the largest catfish (e.g. B. filamentosum, >2m and >100kg), and the catfish species that performs the largest known migration in inland waters (B. rousseauxii), possibly also with B. platynemum, although the evidence for the later species is less robust (Barthem & Goulding 1997, 2007). Figure 1.2. 1 Specimens of Brachyplatystoma rousseauxii captured by the commercial fleet of Santarem on the Amazon River in February 2011. The specimen below measures approximately 26 cm in standard length; the dark bar represents 4 cm. Given its great economic importance in both the artisanal and industrial fishing operations in the Amazon basin (Araujo-File & Ruffino 2003; Carvalho & Barros 2008), B. rousseauxii (formerly B. flavicans) has been the object of genetic (Batista and Gomes 2006, Batista et al. 2009, Batista 2010), and life history traits studies (Barthem & Goulding 1997, 2007; Alonso & Fabré 2003; Alonso & Pirker 2005; Garcia et al. 2009). This species has compensated the consumer’s unsatisfied demand (owing to its over-exploitation in the estuary) for piramutaba (Brachyplatystoma vaillantii) in Brazil, and catch volumes have risen from 1 547 t in 1994 – 1996, to approximately 18 000 t in 2002 – 2003 (Barthem et al. 1991; Parente et al. 2005). 5 Barthem & Goulding (1997 (1997) were the first to propose that B. rousseauxii rou performed long migrations along the main channel and major tributarie utaries of the Amazon River as part of a complex life cycle. Their hypothesis was as ba based on the fishing intensity and nd th the size-class distributions that the fishing fishin fleets periodically exploited through roughout the main channel of the Amazon basin. basin In the lower part of the Amazon (estuary) (es and its vicinity, individuals as small as 6 cm (total length) could be observ observed and commercial fishing exploited juveniles juven and pre-adults measuring around round 60 – 70 cm (fork length) (Figure 1.2.1). .1). A Adults in this area were scarce or absent. abse Higher up in the vicinity of the Central ntral Amazon and the Madera River, the average catch size was between 80 – 90 cm, c and only in the highest parts (Up (Upper Amazon) did catch size reach betwee etween 90 – 110 cm. Fishing focused sed m more intensively on this species upstream tream of the basin, in rivers such as the M Madera (Cachuela of Teotônio, Brazil, Figure 2.2.2), the Ucayali (Peru) and the Caqueta (Colombia), where juvenile and the preadult fish were scarce. Expe Experimental fishing data showed that this species spec was not present in the floodpla odplain, and that adults and pre-adults visited visite these habitats sporadically. Additio dditionally, it was observed that individualss with mature gonads were mostly captured ptured only in the upper parts of the basin. Figure 1.2. 2 Left: the right bank of the M Madera River, at the Teotônio rapids, a place frequented by fishermen fishe (using harpoons) from Porto Velho fishing dora dorado during the upstream migration season. Center: an aerial view of the Teotônio rapids using Google Earth (April (A 2011). Right: Porto Velho fisherman holding an adult dult specimen s of Brachyplatystoma rousseauxii captured in the Madera River (near Porto Velho). Based on these observat ervations, it was proposed that the estuary estuar area represented a refuge and breeding bre ground for juveniles born in the e upp upper parts of the western tributaries. Later, La juveniles to pre-adults move in shoals hoals towards the Central Amazon to spend around one or two years feeding on the a available resources (fish), in this vast area which includes the lower part of the Madera River and the extensive pre-Andean pre plains. At the beginning of high hig water season, the fish that spent ent at least a year in the Central Amazon, and are a close to the size at maturity, move a second time to the highest parts off the basin to reproduce. The fertilized d egg eggs in the water current hatch as they descend desce with the flow, and the larvae that develop travel for 13 – 20 days to the he estuary es of the Amazon. There, the e larvae larva find refuge and food in abundance,, and remain until they reach a minimum nimum size that allows them to start a new cycle c of 6 upstream migration. The gen generalized model of B. rousseauxii migratio igration under this hypothesis is outlined in Figure 1.2.3. Figure 1.2. 3 Generalized model of the m migration pattern of Brachyplatystoma flavicans (now B. rousse usseauxii) in the Amazon basin following Barthem & Gould Goulding (1997). Red circle: Nursery area; Yellow area: Food area of o adults and pre-adults; White oval: Hypothetical regio region of spawning grounds. The white area delineated shows s the hypothetical area adjusted of spawning grounds propo proposed by Barthem & Goulding (2007). Diagram extracted and modified m from Barthem & Goulding (1997; 2007). Alonso & Fabre (2003) noted that juvenile B. rousseauxii spent att leas least a year in the estuary before movin moving (first migration) to the Central Amazon. azon. There, individuals of both sexes es w which are caught by fishing have an average avera age class that borders two year years, while in the Upper Amazon (around und Iquitos reached in the second migra migration), the average age class is aboutt three years. The authors estimated d tha that sexual maturity was reached at a size of approximately 76 cm when hen tthe fish are 1.9 years of age (mean for males ma and females). traits, Garcia et al. (2009) provide the most ost complete c Describing life history traits synthesis and most robust parameters published to date. These authors author found that females of B. rousseau seauxii in the Peruvian Amazon reached larger large sizes than males. The maximum um ssize observed for females was 150.1 cm and an 137.3 cm for males, but there e are records in Colombia (Caquetá River, Muñoz-Sosa Muño 1996) and Brazil (Upper Am Amazon, Barthem & Goulding 1997) for the th same species, showing larger sizes size close to 190 cm. The breeding season eason begins approximately between May to June, peaking in July – September, r, and ending in October – November.. The reproductive period can vary depend epending on environmental variables that influence rainfall and the hydrological al cycle. cyc The gonadal maturation beginss during high water season and the spawning wning period 7 two months later, with the drop in water levels. The spawning peak occurs during the low water season and ends with the water’s ascent, corresponding to the next hydrologic cycle. It is important to note, that spawning during decreasing water level may reduce the risk of having the eggs and larvae swept out into the floodplain; an uncommon feature within this group. Indeed, entering the floodplain would prevent larvae to successfully reach the nursery area in the Amazon estuary, located several thousands of kilometers downstream. The average size of females at first maturity was 91 cm, and 83 cm for males. Both males and females reach maturity between 2.5 to 3.0 years (as opposed to 1.9 years reported by Alonso and Fabre 2003), but males generally mature earlier than females. Based on the analysis of 12 mature females, it was estimated that the relative fecundity was 24 302 oocytes per kilogram of body mass. This species grows rapidly during the first two to three years, reaching 50 cm in the first year only. The growth rate then declines to a value of less than 10 cm per year until the fifth year, and less than 5 cm per year after the sixth year of life. Conclusively, this study suggests that most fisheries are supported by immature specimens in the Brazilian sector of the Amazon basin, as suggested by other authors in previous works (e.g. Alonso & Fabre 2003; Alonso & Pirker 2005; Barthem & Goulding 2007). The exact area of reproduction of B. rousseauxii in the Amazon basin is poorly understood. Barthem & Goulding (1997, 2007) indicated in preliminary estimates that the spawning area is in the western part of the basin between 300 – 2 000 meters over sea level (m.s.l.), over an extended surface of the main Amazon River tributaries that runoff from the Andes (Figure 1.2 .1). Garcia et al. (2009) observed that in the Upper Amazon, an important fishing area for the fishery fleets of Iquitos, females were captured with ready to spawn and spent gonads. It is unknown if spawning actually occurs around this area located at about 100 m.s.l. and which contains similar ecological characteristics to the Central Amazon (e.g. hydrological cycles with predictable and prolonged pulses; absence of turbulent waters), or if the fish move rapidly towards the higher regions in a few days. It is worth noting that the fishery fleet from Iquitos can fish several hundred kilometers upstream from Iquitos. With regard to the reproduction zones, Van Damme et al. (2011a) recently conducted an estimate of the spawning area in the Upper Madera Basin, and a summary of the features and characteristics of the species in this basin. Unlike the proposal of Barthem & Goulding (1997, 2007, Figure 1.2.1), widely referred to in the literature, these authors estimated that the spawning grounds of B. rousseauxii are much narrower in the Upper Madera basin and depends on the geomorphology of the systems. In the headwaters of the Mamoré River (Ichilo River), spawning area are between 250 to 300 m.s.l. (Puerto Villarroel – Puerto Grether), before arriving at the steep slopes and rocky substrates in the foothills of the Andes. On the other hand, in the headwaters of the Beni River, species spawn in a higher band, between 280 to 330 m.s.l. (up to Rurrenabaque), due to the gradual slope and the considerable size that this river keeps into the Andes (Figure 1.2.4). 8 Figure 1.2. 4 Estimated distribution of Brachyplatystoma rousseauxii in the Bolivian Amazon. The darker narrow strip below the foothills represents the possible spawning area of the species. The medium dark band below the dark area in m.s.l., represents the area where individuals with ripe gonads are located. The lighter area, which corresponds to the bottom of the basin, shows the location of non-sexually active individuals. The question marks represent areas with high uncertainty about the presence of the species. The red points represent the locations (Rurrenabaque, Puerto Villarroel, Puerto Grether) near the foothills leading to the upper reaches of the rivers Beni and Mamoré (Ichilo). Figure extracted and modified from Van Damme et al. (2011a, in press). The estimated breeding season takes place between the months of January – February to May – June, with a peak at the end of the period of high water during March – April. The spawning period of this species is delayed in comparison to four other commercially important migratory species in the river basin (Colossoma macropomum, Pseudoplatystoma fasciatum and P. tigrinum) (Figure 1.2.5). The estimated length is partially different from that observed by Garcia et al. (2009) for the Amazon River (Peru), where reproduction intensifies during the low water period. This behavior may occur to ensure the arrival of larvae to the estuary of the Amazon (traveling alone through the river channel) and in response to an abundance in available food for them (contribution of the floodplain to the river channel). Van Damme et al. (2011a), in turn, suggest that once floodplain waters have reached their maximum levels (saturation) and begin to retreat out into river channels, it is unlikely that the water from the final floods enter the floodplains once again. This will increase the likelihood that eggs and larvae travel downstream along the river channel toward favorable environments (e.g. mouth of the Madera River, estuary). This apparent discrepancy could be caused by different hydrobiological and / or limnological conditions within each system. 9 Figure 1.2. 5 Estimated spawning season for Brachyplatystoma rousseauxii in the Upper Ichilo Basin and its relationship with four other migratory species in the system (two characids and two pimelodids), with commercial importance. The water level corresponds to Ichilo River in the town of Puerto Villarroel (1999 - 2000). Figure extracted and modified from Van Damme et al. (2011a). The relative abundance in commercial fishing catches and the residence time of the species throughout the year seem greater in the Beni River than in the Mamoré River. The catches of this species in the Ichilo River (Upper Mamoré) occur between the beginning (November) and the end (May) of the high water season, but not during low water season. Intuitively, this could be because there is a greater amount of suitable habitat (turbulent zones) and a higher food supply (higher productivity owing to higher amount of sediments) apparent in the Beni River in relation to the Mamoré River (Goulding 1979). However, this hypothesis should be tested with detailed ecological studies on the productivity of the systems (e.g. primary productivity). The sizes reported in the Bolivian Amazon (75.0 – 120.5 cm) are similar to the average standard lengths observed by Goulding (1979) for the Madera River, and by Garcia et al. (2009) for the Amazon-Ucayali system in Peru. However, larger individuals (148 cm) reported in the Peruvian Amazon by Garcia et al. (2009), were significantly larger than those of the Bolivian Amazon (105.8 cm Ichilo River – Figure 1.2.6, Beni River 120.5 cm). Similar differences were noted when comparing the maximum standard lengths observed in Brazil (192 cm, Solimões – Amazon River) and Colombia (167 cm, Caquetá River), with sizes from the Bolivian Amazon. These substantial variations in the available data may be influenced by factors related to a latitudinal gradient. 10 Figure 1.2. 6 Frequency distribution of standard lengths for Brachyplatystoma rousseauxii observed in the Mamoré River (Le Guennec 1985) and Ichilo River (2000 - Coronel et al. 2004; 2001 to 2003 - Van Damme unpublished data) in the Bolivian Amazon. F: females, M: male. Figure extracted and modified from Van Damme et al. 2011a. Considering the growth model (von Bertalanffy) proposed by Garcia et al. (2009), a significant proportion of individuals caught in the Ichilo River would be between 2.5 – 3.5 years (females) and 2.0 – 2.5 years of age (males). The fraction of immature individuals that are caught in this area is unknown, but the few existing reports indicate advanced stages of maturity in individuals caught by fishermen. The absence of older and larger individuals might be due to fishing pressures on this species along the Amazon and Madera rivers, although this hypothesis seems unlikely considering the fact that fishing pressure is probably lower in the Madera than in the main axis of the Amazon River. Alternatively, Garcia et al’ growth model may not be suitable for the high Madera because of the existence of several populations with distinct growth characteristics in the Amazon basin. 11 1.2 Questions and hypotheses about the population structure of Plateado (Brachyplatystoma rousseauxii) in relation to its migratory behavior along the Amazon and Madera rivers Animal migration is considered a cyclical process that drives migrants to return to the region from which they migrated (Heape 1931), and implicitly conceives the notion of returning to the place of origin (homing) that promotes the differentiation. However, this is not a mandatory feature of migratory behavior. Even when the migratory behavior of a species is well known, the difficulty in establishing a phenomenon of homing and fidelity to breeding sites may be a consequence of multiple confounding factors (Telles et al. 2011). It has been shown that many animal species (e.g. birds, mammals, and fishes) are faithful to their natal sites or groups for reproduction. In many of them, one sex may be more philopatric than the other. The increase in effective population size through increased access to mating or resources, and avoidance of inbreeding, are important in facilitating gender differences in dispersion. Thus, the philopatry will favor the evolution of certain traits (cooperative) between members of the sedentary sex (Greenwood 1980). Annually, billions of animals move at different geographical scales promoted by reproductive events, foraging, searching for better climatic conditions (Heape 1931) or avoidance of parasites (Altizer et al. 2011). Inland fish can migrate to different geographic scales, between marine- and fresh-waters (diadromous) or within freshwaters only (potadromous) (Flecker et al. 2010). B. rousseauxii is a fish that performs potadromous amphidromic type migrations (returns to the estuary in the early stages of development), on a continental scale (Amazon basin) and synchronizes these movements with the hydrological cycle of the system. The direction and timing of their movements have been partially deduced along the main axis of the Amazon, but it is unknown whether the species is composed of several populations with different life history (e.g. spawning curves in one place, McPherson et al. 2003 ) and / or ethological traits (e.g. learning - Odling-Smee & Braithwaite 2003). In the case of several population units, there is the possibility that each one of them may perform reproductive migrations to different areas within the basin or tributaries. In this way, at least at one time and place, populations with distinct features could be separated from the whole (mixed populations), that form along the main axis of the Amazon and some major tributaries. This reproductive pattern could condition the return and gradual recruitment of adults toward birth places through a recognition (chemical, physical) of the place of origin (home) or homing, as in other fish species (e.g. Salmo salar – Dodson 1988; Oncorhynchus spp. – Dittman & Quinn 1996; Oncorhynchus masou – Shoji et al. 2000; Salmo trutta – Shields et al. 2005; Oncorhynchus tshawytscha – Neville et al. 2006; Oncorhynchus keta and O. nerka –Yamamoto & Ueda 2007; O. nerka – Bandoh et al. 2011). Some molecular studies have tried to understand the population structure of B. rousseauxii in relation with its geographic distribution (Magalhães 2003; Coronel et al. 2004; Batista & Alves-Gomez 2006; Ferreira 2007; Batista 2010). 12 Coronel et al. (2004) evaluated the genetic variability (allozymes and DNAmtRFLP) of B. flavicans (now B. rousseauxii) in two rivers (Beni and Ichilo) from the Bolivian Amazon and found that the diversity of both markers was low. Haplotype diversity (RFLP technique) was higher in the Ichilo River, but the differences were not significantly different (Figure 1.3.1). Supported by the low mitochondrial diversity observed with this technique, they suggested that the species could have suffered a historical population decline. Figure 1.3. 1 Haplotype frequencies (pies) of Brachyplatystoma flavicans (now B. rousseauxii) in the upper portions of the Beni and Ichilo rivers (Bolivian Amazon). A network of haplotypes (RFLP) identified by Coronel et al. (2004) is inserted in the image. Image reconstructed and modified from Coronel et al. (2004). Batista and Alves-Gomez (2006) evaluated the genetic diversity of the species in three localities along the main axis of the Amazon River (Belén, Manaus, and Tabatinga), using a marker of the mitochondrial genome (Control Region - CR) (Figure 1.3.2). They found that haplotype diversity decreased toward the interior of the continent (Belén > Manaus > Tabatinga), and suggested that it could be due to the effect of a homing event. Haplotype diversity decreases as the fish move upstream and enter non-randomly to the tributaries of the Amazon River. Under this assumption, the stock of developing juveniles in the estuary (Belén) may be the result of the contribution of different populations in different tributaries hosted upstream. However, it should be noted that only 15 specimens were analyzed in each location; in 31 haplotypes the authors found just one individual from Belén identical to one of Tabatinga, and the marker used (CR) only provides a partial picture of the population’s integrity (maternal heritance). 13 15, H=1 15, H=0.91 15, H=0.89 H=0. Figure 1.3. 2 Collection sites of Brachypl hyplatystoma rousseauxii analyzed by Batista & Alves-Gomez (2006), (2006 along the main axis of the Amazon River (more e than 2 200 km) in Brazil. White boxes show the number of specime ecimens analyzed by locality and the corresponding haploty aplotype diversity (H). The areas delineated with colored ovals correspond corres to the different areas used by the species throug hroughout its life cycle. Figure extracted and modified from Batista & Alves-Gomez (2006). For the same study area ea (a (axis and several tributaries), Batista (2010) 2010) carried out a more extensive study on the population structure of this species specie using mitochondrial (CR sequence uences) and nuclear markers (microsatellite fragments). frag The author analyzed 652 individuals for the CR and 483 individu dividuals for microsatellites, distributed in 15 locations within an area of approximate imately 4 000 km from Belén (Brazil) to Puc Pucallpa (Peru) (Figure 1.3.3). Based on her analysis, it was concluded that both markers confirmed the migratory behavio havior of the species and that it is com composed of a single genetic unit (stock) ock) of wide distribution in the same e sen sense as Barthem & Goulding (1997). The estimated es migration flows between n reg regions (two markers), showed values greate reater than 4 individuals per generation leading to the assumption of high exchang change rates. However, it is worth noting ting th that CR analyses revealed significant differen ifferentiations between some regionss (e. (e.g. Madera River vs Japurá River, considering con Bonferroni correction). Likewise, Likew comparisons (FST) based on microsa icrosatellites, showed values that could be related to significant differentiation (e.g. (e. 0.05: Juruá vs Santarém, 0.04: Juruá vs Manaus). Batista’s microsatellite ellite a analysis did not show whether there was a significant deviation from panmixia mixia (overall FIS for 483 individuals), nor the significance of FST values between regions. region Ma (2003) for the Japurá River (Brazil) (Bra and Existing CR analyses by Magalhães Ferreira (2007) for the Branco Branc River (Brazil) similarly suggested a single unit or stock. 14 Figure 1.3. 3 Localities in the Amazon Basin collected by Batista (2010), for the genetic analysis (CR and microsatellites) of Brachyplatystoma rousseauxii. The numbers in each locality represent different regions defined by the author. Figure taken from Batista (2010). Numbers in the circles represents different regions defined by Batista (2010). The results presented in the aforementioned works coincide with the migratory behavior that has been proposed and accepted for the species. However, it is surprising that despite the extensive area occupied by the species within the 6 million km2 of the Amazon basin, the existence of differentiated populations could not be evidenced. The Amazon basin contains a high heterogeneity of environments and populations which could be related, at least in a given time, to defined geographical areas or types of habitats. Taking into account the biological, ecological, and demographic characteristics outlined above and the differences that can be noted between the different systems (e.g. Amazon vs. Madera) and tributaries (rivers from the Bolivian Amazon), this study aimed at 1) testing the hypothesis that B. rousseauxii is structured into different genetic populations and 2) exploring whether such a population segregation could be related to a homing behavior. The following hypotheses could account for the existence of different populations within the Amazon basin: a) Hypothesis of a strict homing behavior (salmon-type) within the Upper Madera Basin (Bolivia and Peru) (Figure 1.3.4) If there is a genetic structure of B. rousseauxii within the Upper Madera (Bolivia and Peru) linked to a homing event, then one would expect that the tributaries in the upper parts of this basin contain different panmictic populations during 15 the breeding period. Within the Madera River down to the confluence of all tributaries, a mixture of all the populations should be observed. As each one of these populations advance in their upstream movements, their respective individuals would choose their preferred tributary to find the area where they were born. In this regard, the physicochemical characteristics of each tributary could be determinant in the recognition of the tributary (e.g. imprinting the memory of the neonates). The separation of populations may occur during a short period such as reproduction, but the place and time at which they can occur a priori is unknown. Once the reproduction in the upper parts is completed, fertilized eggs and the resulting larvae would drift downstream to reach the mouth of the Madera River or the estuary of the Amazon as proposed by Barthem & Goulding (1997, 2007). On the other hand, adults, post-spawning, would descend the waters toward the lower parts of the basin to take shelter, feed, and to spend the dry season in deep areas waiting for the next breeding season (Figure 1.3.4). Figure 1.3. 4 Representation of the homing hypothesis (recognition of the place of origin) that Brachyplatystoma rousseauxii would perform during the reproductive period to the headwaters of the Upper Madera (local scale - small basins, Bolivia and Peru). Each geometric figure represents individuals in a panmictic population distinct from the others. The different forms of arrow indicate the direction of each population during ascent to the headwaters close to the Andes. The three arrows indicate the direction and descent of the populations after spawning. b) Hypothesis of a large-scale homing behavior at the level of the major systems of the Amazon (e.g. Amazon vs. Upper Madera) (Figure 1.3.5) If there is a genetic structure of B. rousseauxii related to large systems (subbasins) of the Amazon and episodes of homing on a large scale, then it would 16 be expected that the headwaters of the great tributaries of the basin contain distinct populations at least during the reproductive period. Under this hypothesis, the Amazon estuary receives the larvae and small juveniles of all the populations from the major tributaries of the basin, and therefore constitutes a mix of various populations (repository). As the individuals of each panmictic population begin to grow and mature, they would travel jointly up the main axis and would move selectively to the major tributaries where they were born. It is unknown whether the temporal and spatial separation of the populations occurs only during short time spaces during the reproductive period. This hypothesis is similar in several aspects to those previously mentioned but it differs in its occurrence on a major geographical scale (regional - major subbasins). Additionally, it assumes that all the populations arrive at the estuary traveling downstream during B. rousseauxii’s first development stages (Figure 1.3.5). Figure 1.3. 5 Representation of the homing hypothesis (recognition of the place of origin) that Brachyplatystoma rousseauxii would perform during its reproductive period towards the headwaters of the major tributaries of the Amazon (regional scale – major sub-basins, Amazon basin). Each geometric figure represents individuals in a panmictic population distinct from the others. The different forms of arrow indicate the way each population would travel towards the headwaters of the major tributaries of the Amazon close to the Andes. The two arrows indicate the direction and the descent of the populations after spawning. c) Hypothesis of spatial segregation (homing) within a common distribution area in the major systems of the Amazon (e.g. Western Amazon and Upper Madera) (Figure 1.3.6) 17 In this hypothesis, populations of B. rousseauxii would have the same distribution, but somehow segregate spatially at the moment of reproduction into that same distribution area. This segregation hypothesis could occur to different geographic scales. Within the upper Madera basin for example, different populations could inhabit all of the major tributaries (e.g. Mamoré, Beni, Madre de Dios), but one particular population could reproduce only in one of these major tributaries. Alternatively, different populations could inhabit all of the major tributaries (e.g. Mamoré, Beni, Madre de Dios), but reproduce in different portions (e.g. different altitudes) or habitats of these tributaries. Figure 1.3. 6 Hypothesized representation that allows the existence of several populations of Brachyplatystoma rousseauxii in the same geographical areas independently from the temporality. Every geometric figure represents individuals of a panmictic population differentiated of others. The main axis of the Amazon and its major tributaries in all its extension contain several populations which are located in the same geographical areas but are genetically different. The arrows indicate the different population distribution states during non-reproduction period (left chart) and reproduction period (right chart). d) Hypothesis of temporal segregation in the major systems of the Amazon (e.g. Western Amazon and Upper Madera) without homing. In this hypothesis, populations of B. rousseauxii would have the same distribution, but segregate temporally (phenology) at the moment of reproduction into that same distribution area. In addition, it is possible other pre-zygotic isolation mechanism could exist between populations (e.g. behavior, morphology, breeding period) that allows simultaneous reproductive events in the same distribution area. 1.3 Election of molecular descriptors used in evolutionary genetics and conservation The genetic descriptors are simply heritable characters with multiple states in each of them. Typically, in diploid organisms, each individual can take one or two different states (alleles) per character (locus) (Sunnucks 2000). Molecular descriptors are useful because they can reveal the polymorphism of the animals at the level of their DNA, and therefore have been enormously useful for assessing the genetic status of their populations and their evolution (Godoy 18 2009; Warn 2004). Several techniques have been developed to obtain this information according to the relevant biological implications, and in accordance with differing purposes. The choice of a molecular descriptor depends basically on two aspects. From a biological point of view, the process to obtain the genotypes should be simple and cost-effective, to generate the greatest amount of data required. From a statistical point of view, and in accordance with the type of analysis to develop, the interrelations of dominance, the information content, the neutrality, and the level of genetic independence of the descriptors are important. Regardless of the chosen descriptor, the information must be as trustworthy as possible (Vignal et al. 2009). The molecular descriptors allow us to observe three main types of variation at the DNA level, but individually, none can be referred to as optimal for all applications (Sunnucks 2000). The types of variations are single nucleotide changes, appointed SNPs for single nucleotide polymorphisms, insertions or deletions (indels) of various lengths reaching between one and several hundred base pairs, and variations in the number of tandem repeats (VNTR e.g. microsatellites) (Vignal et al. 2009). All descriptors reflect genetic differences in DNA sequences, usually with a tradeoff between accuracy and convenience. The information in separated loci may allow one to realize independent tests of hypotheses. Thus, using several of them together allows the possibility to achieve extreme sensibility, depending on the goal of the study (Sunnucks 2000). Many Eukaryotic cells contain nuclear DNA inherited from both parents, as well as DNA in organelles (mitochondria, and chloroplasts in plants), which is usually single parent inherited. This difference in transmission and some major differences in patterns of evolution produce genealogies of genes, in the organelle DNA and nuclear DNA, which reflect different aspects of population biology and history. Mitochondrial DNA has a smaller Ne (effective size) than nuclear markers, and consequently, in many demographic scenarios mtDNA variations allow faster diagnostic for taxa. Comparisons of nuclear and mitochondrial genotypes can help to recognize hybrid individuals, asymmetrical mating preferences and stochastic effects on variables for which the ancestral taxa were polymorphic. These phenomena can produce phylogenetic trees (several genes), that do not properly describe the relations of their taxa. Therefore, it is generally preferable to use a series of descriptors that can detect such a phenomenon (Sunnucks 2000). The recent development of the coalescence theory (Hudson 1990) and phylogenetic have fundamentally changed the way of analyzing and interpreting molecular data. With the generalized use of PCR (Polymerase Chain Reaction) and the introduction of sensitive molecular markers at the mitochondrial (mtDNA) and nuclear (nDNA) levels, current research in population genetics and mapping has undergone profound change (Zhang & Hewitt 2003; Mittal & Dubey 2009). In the field of animal phylogeography, most studies have used the mtDNA as molecular maker (e.g. Avise 2004; Arif & Khan 2009; Godoy 2009), although the combined use of both mitochondrial and nuclear markers is currently becoming the rule. Similarly, supported by the demonstration of Mendelian inheritance of multiple alleles due to variations in the number of 19 short repeats (e.g. Litt & Luty 1989; Yazdani et al. 2003; Guichoux et al. 2011), most of populations genetic research involving nDNA markers have used microsatellite DNA. While mtDNA sequences have proven to be very useful for genealogical evolutionary studies in animal populations and microsatellite sequences (nDNA) most relevant to the inference of dynamics and population genetic structure, it should be noted that these markers have some significant and unavoidable limitations (e.g. Angers et al. 2000; Estoup et al. 2002; William et al. 2004; Rubinoff & Holland 2005). The presence of mitochondrial pseudogenes in the nuclear genome (sequences similar to authentic mitochondrial sequences) of various organisms is an unwanted reality for population studies. This has considerably weakened the effectiveness of using mtDNA in population genetic studies, in addition to the low differentiation observed among members of various groups (see Zhang & Hewitt 2009). Besides, mtDNA data have some other important limitations. The mtDNA represents only a single locus, and therefore a single window of evolution. This window represent basically the matrilineal story (however see some examples such as Kondo et al. 1990; Kyriakou et al. 2010), which may differ from that in the population or species, and therefore the resulting inferences may be biased or partial. The effective population size of mtDNA is one fourth of the nuclear autosomal sequences, therefore mtDNA lineages have a much faster selection rate and higher allele extinction rate. Consequently, i) the evolutionary relationships may be oversimplified by mtDNA data, ii) genetic diversity may be underestimated by mtDNA markers, iii) uncertainty in genealogical analysis may increase due to higher likelihood of absent linkages in many mitochondrial haplotypes, iv) remote populations processes might not be detected properly by mtDNA markers (Zhang & Hewitt 2009). On the other hand, the popularity of microsatellites in population studies is not surprising considering their special characteristics and their apparent reliability (see Jarne & Lagoda 1996; Schlotterer 2000; Selkoe & Toonen 2006; Höglund 2009). The microsatellites (simple repetitive sequences of mono-, di-, tri-, tetrarepetitions in tandem) are widely present in the genome of eukaryotic organisms and have high levels of polymorphism (high mutation rate) (Zhang & Hewitt 2009). However, their mode and pattern of molecular evolution as well as their mechanisms of mutation need to be addressed by extensive and systematic analysis (exhaustive) of the allele sequences. Thus the following points require attention in studies of population genetics: i) Differences in sizes (alleles) are not necessarily directly related to divergence. The assumption that all variation is due to changes in the number of copies (repeat unit) requires careful consideration. Differences between alleles can be caused by a variation in the number of repetitions or by punctual mutations (base changes). The latter occurs both within the repeat regions and in flanking regions. In the case of homoplasy, it is not possible to distinguish the variation and therefore alleles with different evolutionary histories are confused. ii) The mutation rate varies considerably between organisms, between varieties and between loci. Substantial mutation rate variation was 20 iii) observed inter- and intra-locus, and the rate and direction of the mutation are affected by the allele’s size; The neutrality of some microsatellite sequences has become questionable (e.g. Kauer et al. 2003). Some authors suggest that these simple sequence repeats may be related to variation in multigenic quantitative traits (e.g. weight, height). The conservation of some microsatellite loci observed through a large evolutionary distance provides evidence against selective neutrality of those loci (e.g. Kashi et al. 1997; Martin et al. 2002). A notable weakness of microsatellite data is that the ancestral information they contain is sometimes ambiguous (multiple states of alleles). Therefore, the genealogical pattern of relationships cannot be deduced with certainty. The data produced by other methods based on the size of fragments, such as RFLP (restriction fragment length polymorphism), RAPD (randomly amplified polymorphic DNA), AFLP (amplified fragment length polymorphism), SSCP (single strand conformation polymorphism) and D / TGGE (denaturing / temperature gradient gel electrophoresis), have similar weaknesses. This means that for allozyme alleles, they are disordered and therefore the genealogies cannot be easily inferred (Zhang & Hewitt 2009). Reasonably, and considering the weaknesses identified in microsatellites, single copies of nuclear DNA polymorphic (single copy nuclear polymorphic, SCNP) are becoming the descriptor of choice and have created a boom for studies of population genetics (Vignal et al. 2009; Zhang & Hewitt 2009). The mutation process involved in creating SCNPs is simple and well understood compared to that of microsatellites, which are primarily due to slippage of the endogenous DNA polymerase during transcription (Dieringer & Schlotterer 2003; Leclercq et al. 2010). It has seen that the SCNPs evolve mainly due to point mutations and / or via insertions and deletions, which occur less frequently (10 exp-6 by generation), compared to microsatellites (10 exp-3 by generation). In this way, the history of any pair of alleles at a single SCNP mutation event can be traced with certainty, which greatly simplifies the theory to understand the patterns of genetic variation in contemporary populations and the tools used to analyze these patterns (Höglund 2009). However, microsatellites are still used for their versatility and low cost applications, and Guichoux et al. (2011) provide a brief summary of their merits with respect to SCNPs. Molecular markers are immensely useful (with their advantages and disadvantages) for evolutionary processes and to assess the genetic status (diversity) of natural populations. One of the central and fundamental goals of conservation genetics has been risk prevention to ensure the persistence of populations and species, and their genetic diversity. However, as mentioned above the application of molecular markers in conservation has not been limited to this, and has also contributed fundamentally to understanding the evolutionary history (phylogeny), demography and ecology of commercial species and other threatened species (e.g. Hrbek et al. 2005; Na-Nakorn et al. 2006). Thus, molecular markers allow us to describe genetic patterns at scales ranging from individuals to species. From these identifiable patterns, and through applying the growing evolutionary and population genetics theories, inferences can be made about demographic and evolutionary processes that 21 have influenced species at different time scales. Thus, knowledge of these processes in combination with ecological models (e.g. May et al. 2011), should guide the delimitation of conservation units, risk assessment and design of conservation strategies (Piorski et al. 2008). Finally, it is important to note that molecular descriptors are efficient tools for species identification (e.g. identification through DNA sequences, Hebert et al. 2003a), assignment (ancestry) of individuals to populations (e.g. Blanchong et al. 2002; Hauser et al. 2006; Paschou et al. 2010), among other applications in conservation practice (Piorski et al. 2008; Arif & Khan 2009; Godoy 2009). 22 Chapter 2 Phylogeny of the family Pimelodidae and phylogenetic position of the Plateado (Brachyplatystoma rousseauxii) as revealed by mitochondrial (RC and CO1) and nuclear (F-reticulon4) sequences 2.1 Introduction Neotropical Siluriformes are an extremely diverse group with respect to their ecological adaptions and behavioural peculiarities (e.g. Barthem & Goulding 1997; Proudlove 2005; Parzefall & Trajano 2010). They are one of the most numerous groups of the Neotropics, along with the Characiformes (Saint-Paul et al. 2000; Reis et al. 2003; Eschmeyer 2011), and include the largest-bodied species, after the osteoglossiform Arapaima (Berra 2003). According to Nelson (2006) there are at least 1727 species of Siluriformes in the Americas, and it is estimated that this figure will grow by at least 2000, as exhaustive revisions of the majority of these families take place (e.g. Callichthyidae, Loricariidae, Pimelodidae, and Trichomycteridae). The Pimelodidae (sensu lato) family has the greatest species richness and morphological diversity of the Siluriformes after the Loricariidae (Berra 2003; Teugels 2006). It is distinguished by a naked, generally elongated body, three pairs of barbels (but missing a nasal barbel), an adipose fin, and, in almost all cases, a dorsal spine (Teugels 1996). The family has undergone a number of recent revisions with the inclusion and description of new genera (e.g. Britsky 1981; Lundberg & Parisi 2002; Lundberg & Akama 2005; Rodiles-Hernández et al. 2005; Parisi & Lundbert 2009), and has a complex evolutionary history, which remain unresolved (Lundberg et al. 1991a, b; Silfvergrip 1996; Shibatta 2003; Diogo 2007). This heterogeneous family includes more than 95 species (including 5 fossil species) in 30 genera that are distributed from the south of Mexico to Argentina (Nelson 2006; Ferraris Jr. 2007; Aguilera et al. 2008; Lundberg & Parisi 2009). Traditionally, since 1988, four subfamilies of the Pimelodidae have been recognized (Calophysinae, Pimelodinae, Luciopimelodinae and Sorubinae), to which other small groups, with peculiar morphological and ecological traits, have been added (Phreatobinae e Hypophthalmini) (Shibatta 2003). After 1988, under the principles of phylogenetical systematic, new phylogenetic arrangements were created in which various species were excluded from groups established based on older classifications. A new classification for the Pimelodidae has been proposed, but lacks an explicit demonstration of monophyly into the subfamilies Heptapteridae (the Rhamdiinae of Lundberg et al. 1991a, b), Pseudopimelodinae and Pimelodinae (de Pinna 1998; Shibatta 2003; Diogo 2007). The Pimelodinae subfamily inhabits the principal rivers of South America, and includes species of medium (15-60 cm) and large (~ 300 cm) sizes, with different ecological adaptations such as predators – Brachyplatystoma, Pseudoplatystoma, omnivores – Phractocephalus, Pimelodus, and planktivores - Hypophthalmus. 23 According to an analysis of both published and unpublished information (de Pinna 1998), this subfamily consists of four relatively well-differentiated groups. The basal group and sister group to all of the other species is Lundberg’s (1991a, b) group A, consisting of Phractocephalus and the sister genera Leiarius and Perrunichthys. The second group (the new group A or Calophysus-Pimelodus clade) consists of two related groups (but with a polytomy) known as the Calophysus group and the Pimelodus group, in addition to the Megalonema, formerly known as the Sorubiminae. The third group, comparable to the Sorubiminae or Sorubinae classification, contains the genera of high commercial and ecological value such as Brachyplastystoma, Pseudoplatystoma, Sorubimichthys, Zungaro, amongst various others, but does not demonstrate good evidence of being a robust monophyletic group (Figure 2.1). Figure 2. 1 Cladogram of morphological relationships between the Pimelodidae genera, combining information from Lundberg et al. (1988; 1991b), Nass (1991), and de Pinna (1993). Figure adapted from de Pinna (1998). Since 2003, the Pimelodidae family contains only species of the former Pimelodinae subfamily proposed by Lundberg et al. (1991a, b) and de Pinna (1998), as well as the Hypophthalmus genus of the former Hypophthalmidae family (Lundberg & Littman 2003). The remaining genera, which had been 24 included in the Pimelodidae family for a long time, were excluded from the group and re-assigned to two distinct taxonomic categories at the family level, namely the Heptapteridae (Bockmann & Guazzelli 2003) and the Pseudopimelodidae (Shibatta 2003). It is important to note than Muriel-Cunha (2008) also proposes a new Phreatobiidae family. Hence, the Pimelodidae family was reduced to a moderately species-rich group to which the species Conorhynchos conirostris no longer pertains (Valenciennes 1840); it is instead in an uncertain taxonomic position at the family level in the Siluriformes (insertae sedis) (Lundberg & Littman 2003). The reason behind the re-organization was the absence of clear synapomorphic characteristics (Diogo 2004; Diogo et al. 2004), though de Pinna (1998) found some morphological characters (none very clear) that relate these three families with other groups of silurids. This phylogenetic hypothesis of three families (Heptapteridae, Pseudopimelodidae and Pimelodidae) instead of one was later confirmed by Sullivan et al. (2006), who developed a phylogeny of the principal catfish groups based on the analysis of nuclear genes (rag1 and rag2). This study also showed that the Pseudopimelodidae family is a sister group to the Pimelodidae, contrary to the proposal by Diogo et al. (2004), and that the Heptapteridae is a sister group to the Conorhynchus. Despite the absence of morphological synapomorphies that support the integrity of this group, the congruent molecular evidence from nuclear genes was sufficient to indicate monophyly and the recommendation was to consider it part of the Pimelodoidea superfamily (Sullivan et al. 2006). Additionally, Monteiro et al. (2008) have shown that the Pseudopimelodidae family can be differentiated from the Pimelodidae and Heptapteridae families by the number of chromosomes, which is 2n = 54 for the Pseudopimelodidae only. After the work by Sullivan et al. (2006), no other study had been carried out on the molecular systematics of the Pimelodidae family, or on its component groups until the recent Lundberg et al. (2011), carried out in parallel to our study and discussed at the end of the results of this chapter – section 2.3.5. An exception is the work by Hardman & Lundberg (2006), who propose a molecular phylogeny and chronology of diversification of the genera in the ‘Phractocephaline’ group, which constitutes one of the few phylogenetic works comparing relationships between genera of the Pimelodidae family (sensu stricto). At the morphological level, sporadic work has continued, with Lundberg & Akama (2005) as the most noteworthy. Other works are also available in thesis form (e.g. Xantos de Abreu 1998; Xantos de Abreu 2002; Apone 2008), but have not yet been published and are difficult to access; these studies have started to develop current hypotheses on the organization of the Pimelodidae and allied families (e.g. Nass 1991; de Pinna 1993). Lundberg & Akama (2005) simultaneously described a new species of Brachyplatystoma (Goliath catfish) for the Amazon basin, and presented a maximum parsimony phylogeny of the genus which identified a set of clear, unambiguous characters that support the monophyly of the group. Based on their analysis, they established a new tribe named Brachyplatystomatini and subgenus Malacobagrus (the name of an old genus proposed by Bleeker). In this tribe, Platynematichthys notatus ends up as a sister taxa of the 25 Brachyplatystoma, which in turn includes the former genera Merodontotus (Brachyplatystoma tigrinum) and Goslinia (Brachyplatystoma platynemum) as new synonymies due to identified synapomorphies. The subgenus Malacobagrus, in turn, is composed of the species B. filamentosum, B. capapretum y B. rousseauxii, and constitutes one monophyletic group supported by five synapomorphies in which B. filamentosum and B. capapretum are sister species. The remaining species (B. tigrinum, B.juruense, B. platynemum) are positioned between the subgenus Malacobagrus and the more basal species (B. vaillantii), without a well-defined relationship (Figura 2.2). Figure 2. 2 Strict consensus of six most parsimonious trees of a phylogenetic analysis of morphological data for the Pimelodidae family, emphasizing relationships and characters of Platynematichthys y and species of Brachyplatystoma. (Figure adapted from Lundberg & Akama, 2005). 26 Genetic trees are fundamental for molecular systematics. The principal use of these trees, based on variations of DNA sequences in individual genetic loci, is to infer the phylogeny of the taxa within these genes. Accordingly, a phylogenetic tree of species can be defined as the basis for the branching of lineages through the speciation process (Madisson 1997). Taking into account these assumptions and the absence of a molecular phylogeny of the Pimelodidae family- including the Brachyplatystoma species the present chapter has these objectives: 1) elaborate a molecular phylogeny of the family using mtDNA and nDNA sequences, which is as complete as possible; 2) define the molecular position of B. rousseauxii in relation to other related species; 3) determine at the molecular level if all species of the Brachyplatystoma genus have a common and exclusive ancestor (monophyly) as established by morphological analysis; and 4) establish the relationship between the Brachyplatystoma group and other genera that make up the family as defined by Lundberg and Littmann (2003). 2.2 Methods 2.2.1. Sample collection The species and specimens used in this study are listed in Table 2.1 according to their geographical origin (Figure 2.3) and the molecular marker with which they were analyzed. In Annex 1 the images of most species used for phylogenetic analyzes are presented. The collection of taxa within the Pimelodidae family and outgroups were chosen according to previous research such as those of Lundberg et al. (1991a, b), de Pinna (1998), Diogo (2005), Lundberg & Akama (2005), Sullivan et al. (2006), and Hardman & Lundberg (2006). Samples were collected in the upper Madera River (Bolivia and Peru), and in the basin of the Ucayalí and Amazon rivers (Peru), which correspond to two different hydrological systems in the Amazon basin (Figure 2.3). In the Upper Madera basin (Bolivian Amazon and Puerto Maldonado-Peru) the specimens were caught using gill nets of different mesh sizes (2.5 – 10 cm between knots), hook and lines, and occasionally cast nets (2.5 mm between knots), between the years 2002, 2005 – 2009. In the Ucayali-Amazon, the specimens were bought in the popular markets from Requena (mouth of the Tapiche River in the Ucayali River), and Belén (Iquitos, Amazon River), and the ornamental fish aquarium S.A. C. (Iquitos, property of Edgard Panduro), between 2007 – 2010. For each specimen collected, a picture was taken whenever possible, and about 1 – ½ cm3 of tissue was removed to be preserved in 95 % ethanol. Specimens and samples collected in the Bolivian Amazon were deposited in the fish collection of the Unidad de Limnología y Recursos Acuáticos (ULRA), belonging to the University Mayor de San Simón (UMSS, Cochabamba-Bolivia). Likewise, specimens and tissues collected in Peru were deposited in the fish collection from the Instituto de Investigaciones de la Amazonía Peruana (IIAP, Iquitos Peru). 27 Figure 2. 3 Geographical representation of the localities in the Bolivian and Peruvian Amazon where samples of Pimelodids and out groups were collected. Black bars represent the series of rapids in the Upper Madera region. 28 Table 2. 1 List of fish species of Siluriformes collected by locality and used to phylogenetically position the Plateado (B. rousseauxii), and build a phylogeny of the Pimelodidae family based on two mitochondrial DNA markers (CR and CO1) and one nuclear marker (RTN4). The black horizontal bars indicate the marker that was amplified for each species. The code column corresponds to the collection code that was assigned to each specimen in the fish collections from the ULRA (Bolivia) and IIAP (Peru). RC: Control Region; CO1: Cytochrome oxidase 1; RTN4: Freticulon-4. F amilia Cet ops d i ae Lo rica riida e Gén ero Ceto psis País Zo n a Lo ca lid ad Fe cha L at itu d L on g itu d Cód ig o RC CO 1 Lor icar ia Planilor icar ia Iqu itos Iqu itos Iqu itos Requ en a Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Requ en a Requ en a Requ en a Requ en a Iqu itos Iqu itos Requ en a Requ en a Requ en a Iqu itos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Me rca do de R equ ena Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Or nam en tal F ish Aq uar ium , Iq uitos 12- abr -1 0 12- abr -1 0 12- abr -1 0 21- jul-0 8 05- ago -0 8 05- ago -0 8 05- ago -0 8 11- ago -0 8 11- ago -0 8 11- ago -0 8 11- ago -0 8 05- ago -0 8 05- ago -0 8 11- ago -0 8 11- ago -0 8 11- ago -0 8 11- ago -0 8 05- ago -0 8 05- ago -0 8 05- ago -0 8 05- ago -0 8 21- jul-0 8 21- jul-0 8 25- jul-0 8 25- jul-0 8 11- ago -0 8 11- ago -0 8 21- jul-0 8 21- jul-0 8 25- jul-0 8 11- ago -0 8 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 5.05 27 09 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 3.77 77 15 - 3.77 77 15 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 3.77 77 15 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.8 514 15 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 951 55 -7 3.2 951 55 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 951 55 801 46 801 47 801 48 126 847 850 851 903 906 908 909 852 855 904 905 902 907 853 854 848 849 127 128 672 674 897 898 129 130 656 899 1 1 1 sp . sp . sp . sp . fila men tos um fila men tos um m acu latus m acu latus cla vipinn a cf. cr ypto do n Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Pseud or inele pis cr ypto do n cr ypto do n g enib arb is Per ú Per ú Per ú Iqu itos Iqu itos Requ en a Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Me rca do de R equ ena 11- ago -0 8 11- ago -0 8 26- jul-0 8 - 3.77 77 15 - 3.77 77 15 - 5.05 27 09 -7 3.2 951 55 -7 3.2 951 55 -7 3.8 514 15 900 901 728 ng i rir ostr um ng i rir ostr um r ann inus Per ú Requ en a Per ú Requ en a Bolivia Chap ar e Me rca do de R equ ena Me rca do de R equ ena Cha par e, Villa Tu nar i 22- jul-0 8 22- jul-0 8 * - 5.05 27 09 - 5.05 27 09 - 16.9 72 308 -7 3.8 514 15 -7 3.8 514 15 -6 5.4 129 84 322 324 A19 e que s e que s e que s sp . Per ú Per ú Per ú Bolivia Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Río Be ni, Ca chu er ñ i a 04- ma r- 10 04- ma r- 10 04- ma r- 10 29- abr -0 8 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 - 10,4 24 455 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 -6 5,4 703 71 801 43 801 14 801 45 GEN30 79 sp . sp . sp . q uele n q uele n to ro sus Bolivia Villa Bella Bolivia Lag o Bay Bolivia Gua yar am erí n Río Mam or é, Villa Bella Río Man ur ipi, L ago Bay Río Mam or é, Gua yara me rín 06- ma y-08 28- nov -02 11- jun- 07 - 10.3 96 734 - 11.9 53 628 - 10.8 13 437 -6 5.3 848 99 -6 8.6 569 11 -6 5.3 428 28 GEN30 89 Pim .sp 374 6 GEN25 215 Per ú Requ en a Per ú Requ en a Bolivia Rur ren aba qu e Me rca do de R equ ena Me rca do de R equ ena Río Be ni, Ru rr ena ba que 23- jul-0 7 26- jul-0 7 02- dic- 07 - 5.05 27 09 - 5.05 27 09 - 14.4 40 752 -7 3.8 514 15 -7 3.8 514 15 -6 7.5 308 97 470 726 GEN30 10 1 ca pap re tum ca pap re tum ca pap re tum fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um fila men tos um Per ú Per ú Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Villa Bella Villa Bella Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Tr inida d Tr inida d Tr inida d Tr inida d Iqu itos Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Río Mam or é, Cach uelita Río Mam or é, Villa Bella Río Be ni, M ota cus al Río Be ni, b oca ar royo Nap ur era Río Be ni, b oca ar royo Nap ur era Río Be ni, b oca ar royo T equ eje Río Be ni, b oca ar royo Nap ur era Río Be ni, b oca ar royo T equ eje Río Be ni, J ri um a Río Be ni, Alta ma ran i Río Be ni, b oca ar royo Ma ije Río Be ni, Pu ert o Salina s Río Be ni, Alta ma ran i Río Ichilo, bo ca r ío Ch imo ré Río Ichilo, re cta Chiqu iño Río Ichilo, re cta Chiqu iño Río Mam or é, Cam iaco Río Mam or é, Cam iaco Río Mam or é, Cam iaco Río Mam or é, Cam iaco Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 05- abr -0 7 07- ago -0 8 07- ago -0 8 24- ma r- 08 26- ma r- 08 15- jul-0 7 11- jul-0 7 11- jul-0 7 08- jul-0 7 05- ago -0 7 09- sep -07 13- oct- 07 13- oct- 07 21- oct- 07 28- oct- 07 04- nov -07 14- ma r- 06 16- ma r- 06 17- ma r- 07 19- ago -0 6 26- ago -0 6 26- ago -0 6 26- ago -0 6 07- ago -0 8 07- ago -0 8 07- ago -0 8 07- ago -0 8 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 10.4 16 721 - 10,4 03 147 - 13.5 80 594 - 13.6 01 385 - 13.6 01 385 - 13.5 14 744 - 13.6 01 385 - 13.5 14 744 - 14.3 44 756 - 14.3 34 447 - 14.2 99 425 - 14.2 62 508 - 14.3 34 447 - 16,7 45 186 - 16.9 83 757 - 16.9 83 757 - 16.7 17 238 - 16.7 17 238 - 16.7 17 238 - 16.7 17 238 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -6 5.3 821 34 -6 5,3 813 55 -6 7.3 634 14 -6 7.3 893 55 -6 7.3 893 55 -6 7.3 890 17 -6 7.3 893 55 -6 7.3 890 17 -6 7.5 571 75 -6 7.5 576 81 -6 7.5 255 81 -6 7.5 049 78 -6 7.5 576 81 -6 4,8 435 33 -6 4.6 994 72 -6 4.6 994 72 -1 5.4 000 89 39 -1 5.4 000 89 39 -1 5.4 000 89 39 -1 5.4 000 89 39 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 061 860 862 GEN30 43 GEN30 55 GEN26 49 GEN26 60 GEN26 61 RU6 RU11 RU14 RU22 RU23 RU26 RU30 RU32 PV1 PV5 PV7 PST 3 PST 6 PST 7 PST 8 861 863 865 868 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 24- ma r- 07 24- ma r- 07 24- ma r- 07 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 00 800 01 800 02 1 1 1 jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 24- ma r- 07 24- ma r- 07 24- ma r- 07 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 03 800 06 800 08 1 1 1 jur ue nse jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Iqu itos Me rca do Me rca do Me rca do Me rca do Iqu itos Iqu itos Iqu itos Iqu itos 24- ma r- 07 24- ma r- 07 24- ma r- 07 24- ma r- 07 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 09 800 10 800 11 800 12 1 1 1 1 jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 26- ma r- 07 26- ma r- 07 30- ma r- 07 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 51 800 53 800 56 1 1 1 jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 30- ma r- 07 02- abr -0 7 02- abr -0 7 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 57 800 58 800 59 1 1 1 jur ue nse jur ue nse jur ue nse Per ú Per ú Per ú Iqu itos Requ en a Requ en a Me rca do Be lén, Iqu itos Me rca do de R equ ena Me rca do de R equ ena 02- abr -0 7 21- jul-0 8 21- jul-0 8 - 3.75 93 40 - 5.05 27 09 - 5.05 27 09 -7 3.2 477 08 -7 3.8 514 15 -7 3.8 514 15 800 60 92 93 1 1 1 jur ue nse jur ue nse pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m Per ú Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Requ en a Iqu itos Villa Bella Villa Bella Villa Bella Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to Villar ro el Rur ren aba qu e Me rca do de R equ ena Me rca do Be lén, Iqu itos Río Be ni, Ca chu er ñ i a Río Mam or é, Villa Bella Río Mam or é, Villa Bella Río Be ni, b oca ar royo Nap ur era Río Be ni, So rayd a Río Be ni, b oca ar royo Nap ur era Río Ichilo, Puer to Villar ro el Río Be ni, L imó n 26- jul-0 8 07- ago -0 8 26- jul-0 7 30- jul-0 7 24- jul-0 7 10- jul-0 7 10- jul-0 7 05- jul-0 7 19- sep -07 03- jul-0 7 - 5.05 27 09 - 3.75 93 40 - 10.4 13 919 - 10.3 99 100 - 10,4 03 147 - 13.6 01 385 - 14.0 75 481 - 13.6 01 385 - 16,8 38 889 - 14.3 00 968 -7 3.8 514 15 -7 3.2 477 08 -6 5.4 274 88 -6 5.3 843 21 -6 5,3 813 55 -6 7.3 893 55 -6 7.5 023 57 -6 7.3 893 55 -6 4,7 916 67 -6 7.5 258 07 716 876 GEN27 52 GEN27 53 GEN28 12 GEN26 63 GEN26 66 GEN26 89 GEN23 07 GEN27 02 1 1 1 1 1 1 1 1 1 1 Ancistr us Fa rlow ella Hypo stom us Lam on ticht hys Lor icar ichth ys Stur si om a Pseu dop ime lodid ae Batr ocho glan is Goe diella Hep tap ter idae Pimelo della Rha mdia Pime lodid ae Agua run ichth ys Brac hypla tysto ma Esp ec ie co ecu tiens co ecu tiens co ecu tiens h oplo gen ys cf. h asem an i cf. h asem an i cf. h asem an i cf. h enr ique i cf. h enr ique i cf. h enr ique i cf. h enr ique i cf. n atte rer i o xyrh ynch a o xyrh ynch a o xyrh ynch a pa l tor hyn cho s pa l tor hyn cho s r ugo sa r ugo sa sm ithi sm ithi Iqu itos Iqu itos Iqu itos Villa Bella Be lén, Be lén, Be lén, Be lén, RTN4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 29 1 1 Calop hys us Hem isor ubim Hypo pht halm us Leia rius pa l tyn emu m Boliva Tr inida d Río Mam or é, Cam iaco 19- ago -0 6 - 16.7 17 238 -1 5.4 000 89 39 PST 4 1 1 pa l tyn emu m pa l tyn emu m pa l tyn emu m Boliva Tr inida d Boliva Tr inida d Per ú Puer to M ald ona do Río Mam or é, Cam iaco Río Mam or é, Cam iaco Río Mad re de Dios, Pu er to M aldo na do 19- ago -0 6 26- ago -0 6 19- ago -0 8 - 16.7 17 238 - 16.7 17 238 - 12.5 93 581 -1 5.4 000 89 39 -1 5.4 000 89 39 -6 7.1 727 19 PST 5 PST 10 900 013 1 1 1 1 1 pa l tyn emu m pa l tyn emu m pa l tyn emu m Per ú Per ú Per ú Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do 19- ago -0 8 19- ago -0 8 20- ago -0 8 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 900 015 900 016 900 036 1 1 1 pa l tyn emu m pa l tyn emu m pa l tyn emu m Per ú Per ú Per ú Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do 20- ago -0 8 22- ago -0 8 22- ago -0 8 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 900 044 900 132 900 152 1 1 1 pa l tyn emu m pa l tyn emu m pa l tyn emu m pa l tyn emu m Per ú Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Iqu itos Me rca do Me rca do Me rca do Me rca do 24- ma r- 07 24- ma r- 07 24- ma r- 07 07- ago -0 8 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 13 800 14 800 15 874 1 1 1 1 1 1 1 1 pa l tyn emu m r ous seau xii r ous seau xii Per ú Iqu itos Bolivia Vil la Bella Bolivia Vil la Bella Me rca do Be lén, Iqu itos Río Mad er a, Ca chu ela M ad er a Río Mad er a, Ca chu ela M ad er a 07- ago -0 8 07- jun- 06 07- jun- 06 - 3.75 93 40 - 10.3 63 381 - 10.3 63 381 -7 3.2 477 08 -6 5.3 788 62 -6 5.3 788 62 875 VB2 VB3 1 1 1 1 1 r ous seau xii r ous seau xii r ous seau xii Bolivia Vil la Bella Bolivia Vil la Bella Bolivia Vil la Bella Río Mad er a, Ca chu ela M ad er a Río Mam or é, Villa Bella Río Mam or é, Cach uela Ma mo ré 15- jul-0 6 09- ma y-07 01- ago -0 7 - 10.3 63 381 - 10,4 03 147 - 10,3 73 000 -6 5.3 788 62 -6 5,3 813 55 -6 5,3 884 45 VB8 VB1 2 GEN28 62 1 1 1 1 1 r ous seau xii r ous seau xii r ous seau xii Bolivia Cach uela Espe ran za Río Be ni, Ca chu ela Es per anza Bolivia Cach uela Espe ran za Río Be ni, Ca chu ela Es per anza Bolivia Cach uela Espe ran za Río Be ni, Ca chu ela Es per anza 04- nov -06 24- ene -0 7 04- feb -07 - 10.5 32 36 - 10.5 32 36 - 10.5 32 36 -6 5.5 856 39 -6 5.5 856 39 -6 5.5 856 39 CE9 CE12 CE15 1 1 1 1 1 r ous seau xii r ous seau xii r ous seau xii r ous seau xii Bolivia Bolivia Bolivia Bolivia 01- ma r- 07 19- ene -0 8 01- abr -0 8 26- oct- 07 - 10.5 32 36 - 10.5 32 36 - 10.5 32 36 - 14.3 44 756 -6 5.5 856 39 -6 5.5 856 39 -6 5.5 856 39 -6 7.5 571 75 CE27 CE45 CE57 RU27 1 1 1 1 r ous seau xii r ous seau xii r ous seau xii Bolivia Rur ren aba qu e Bolivia Rur ren aba qu e Bolivia Rur ren aba qu e Río Be ni, J ri um a Río Be ni, L imó n Río Be ni, Co pa n i a 26- oct- 07 03- jul-0 7 10- ene -0 8 - 14.3 44 756 - 14.3 00 968 - 14.2 41 324 -6 7.5 571 75 -6 7.5 258 07 -6 7.5 143 3 RU29 GEN27 06 GEN27 34 1 1 1 r ous seau xii r ous seau xii r ous seau xii Bolivia Rur ren aba qu e Bolivia Rur ren aba qu e Bolivia Puer to Villar ro el Río Be ni, b oca ar royo T equ eje Río Be ni, Alta ma ran i Río Ichilo, Rect a Ch iquiñ o 21- abr -0 8 29- abr -0 8 16- feb -05 - 13.5 14 744 - 14.3 34 447 - 16.9 83 757 -6 7.3 890 17 -6 7.5 576 81 -6 4.6 994 72 GEN27 37 GEN34 33 BR3 1 1 1 r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii r ous seau xii tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m va illa ntii va illa ntii va illa ntii va illa ntii Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Per ú Per ú Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Vil la Bella Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to M ald ona do Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Iqu itos Río Ichilo, bo ca r ío I sar zam a Río Ichilo, La Pam pita (bo ca I sar zam a) Río Ichilo, bo ca r ío Ch imo ré Río Ichilo, bo ca r ío Ch imo ré Río Ichilo, Sant a Lu cia Río Ichilo, bo ca r ío Ch imo ré Río Ichilo, bo ca r ío Ch imo ré Río Ichilo, Rem an zo d e los Cru cos Río Ichilo, Rect a Ch iquiñ o Río Ichilo, Rect a L arg a Río Ichilo, La Quin ce Río Ichilo, Rect a L arg a Río Ichilo, Rect a d el Don o Río Ichilo, Rect a d e M onica Río Ichilo, Rect a d el Don o Río Be ni, Ca chu er ñ i a Río Be ni, Co cal Río Be ni, So rayd a Río Be ni, So rayd a Río Be ni, b oca ar royo Ma ije Río Be ni, b oca ar royo Ma ije Río Be ni, Co pa n i a Río Be ni, Alta ma ran i Río Mad re de Dios, Pu er to M aldo na do Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 16- feb -05 17- feb -05 17- feb -05 23- feb -05 09- ma r- 05 29- ma r- 05 29- ma r- 05 31- ma r- 05 16- ma r- 06 16- ma r- 06 03- abr -0 6 12- jun- 07 12- ago -0 7 17- nov -06 12- ma y-07 26- jul-0 7 04- ma y-08 16- jul-0 7 11- oct- 07 11- oct- 07 19- oct- 07 04- nov -07 28- ma y-08 22- ago -0 8 24- ma r- 07 26- ma r- 07 24- ma r- 07 24- ma r- 07 24- ma r- 07 24- ma r- 07 - 17.0 20 017 - 17.0 18 824 - 16.7 40 397 - 16.7 40 397 - 16.6 91 538 - 16.7 40 397 - 16.7 40 397 - 16.3 77 134 - 16.9 83 757 - 16.7 30 501 - 16.9 26 598 - 16.7 30 501 - 16.7 30 501 - 16.6 36 611 - 16.7 30 501 - 10,4 24 455 - 13.8 66 000 - 14.0 75 481 - 14.0 75 481 - 14.2 99 425 - 14.2 99 425 - 14.2 41 324 - 14.3 34 447 - 12.5 93 581 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -6 4.6 844 47 -6 4.6 813 67 -6 4.8 447 24 -6 4.8 447 24 -6 4.7 966 15 -6 4.8 447 24 -6 4.8 447 24 -6 4.6 545 2 -6 4.6 994 72 -6 4.8 370 85 -6 4.7 196 10 -6 4.8 370 85 -6 4.8 370 85 -6 4.7 722 22 -6 4.8 370 85 -6 5,4 703 71 -6 7.4 748 63 -6 7.5 023 57 -6 7.5 023 57 -6 7.5 255 81 -6 7.5 255 81 -6 7.5 143 30 -6 7.5 576 81 -6 7.1 727 19 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 BR5 BR10 BR21 BR29 BR33 BR58 BR59 BR65 PV2 PV6 PV2 6 PV2 02 PV2 04 PV9 1 PV1 94 GEN28 40 GEN30 88 RU7 RU15 RU16 RU24 RU31 GEN33 23 900 129 800 07 800 54 800 04 800 05 800 17 800 18 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 va illa ntii va illa ntii va illa ntii Per ú Per ú Per ú Iqu itos Requ en a Requ en a Me rca do Be lén, Iqu itos Me rca do de R equ ena Me rca do de R equ ena 21- abr -0 7 21- jul-0 8 21- jul-0 8 - 3.75 93 40 - 5.05 27 09 - 5.05 27 09 -7 3.2 477 08 -7 3.8 514 15 -7 3.8 514 15 800 71 90 91 1 1 1 m acr opt eru s m acr opt eru s m acr opt eru s Bolivia Vil la Bella Bolivia Vil la Bella Bolivia Vil la Bella Río Be ni, Ca chu er ñ i a Río Be ni, Ca chu er ñ i a Río Be ni, Ca chu er ñ i a 23- jul-0 7 23- jul-0 7 23- jul-0 7 - 10,4 24 455 - 10,4 24 455 - 10,4 24 455 -6 5,4 703 71 -6 5,4 703 71 -6 5,4 703 71 GEN28 06 GEN28 07 GEN28 08 1 1 1 m acr opt eru s m acr opt eru s m acr opt eru s Bolivia Cach uela Espe ran za Río Be ni, Ca chu ela Es per anza Bolivia El Se na Río Man up are , El Sen a Bolivia El Se na Río Man up are , El Sen a 27- ene -0 9 01- nov -07 01- nov -07 - 10.5 32 360 - 11.4 93 352 - 11.4 93 352 -6 5.5 856 39 -6 7.2 559 15 -6 7.2 559 15 CE84 GEN29 81 GEN29 82 1 1 1 m acr opt eru s m acr opt eru s m acr opt eru s m acr opt eru s Bolivia Bolivia Bolivia Bolivia 01- nov -07 19- sep -07 19- sep -07 04- jun- 07 - 11.4 93 352 - 16,8 38 889 - 16,8 38 889 - 14,7 93 333 -6 7.2 559 15 -6 4,7 916 67 -6 4,7 916 67 -6 4,9 722 22 GEN29 83 GEN28 90 GEN29 15 GEN22 83 1 1 1 1 1 m acr opt eru s m acr opt eru s m acr opt eru s Bolivia Tr inida d Bolivia Tr inida d Bolivia Gua yar am erí n Río Ibar e, Pu er to Ba l iviá n Río Ibar e, Pu er to Ba l iviá n Río Mam or é, Gua yara me rín 04- jun- 07 04- jun- 07 10- jun- 07 - 14,7 93 333 - 14,7 93 333 - 10.8 13 437 -6 4,9 722 22 -6 4,9 722 22 -6 5.3 428 28 GEN22 84 GEN22 85 GEN24 82 1 1 1 1 1 1 m acr opt eru s m acr opt eru s m acr opt eru s Bolivia Gua yar am erí n Bolivia Gua yar am erí n Per ú Requ en a Río Mam or é, Gua yara me rín Río Mam or é, Gua yara me rín Me rca do de R equ ena 11- jun- 07 11- jun- 07 21- jul-0 8 - 10.8 13 437 - 10.8 13 437 - 5.05 27 09 -6 5.3 428 28 -6 5.3 428 28 -7 3.8 514 15 GEN25 07 GEN25 29 98 1 1 1 1 1 1 m acr opt eru s m acr opt eru s pa l tyr hync hos pa l tyr hync hos pa l tyr hync hos pa l tyr hync hos pa l tyr hync hos pa l tyr hync hos m ar gina tus m ar gina tus m ar gina tus m ar gina tus m ar gina tus e den tatu s e den tatu s e den tatu s fim br iatus cf. m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s Per ú Per ú Bolivia Bolivia Bolivia Per ú Per ú Per ú Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Per ú Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Me rca do de R equ ena Me rca do de R equ ena Río Ichilo, Puer to Villar ro el Río Ichilo, Puer to Villar ro el Río Ichilo, Puer to Villar ro el Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do de R equ ena Río Mam or é, Los Puen tes Río Mam or é, Los Puen tes Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Río Be ni, Ca chu er ñ i a Río Mam or é, Villa Bella Río Mam or é, Villa Bella Río Ort hon , San Luis Río Mad re de Dios, El Carm en 21- jul-0 8 23- jul-0 8 19- sep -07 19- sep -07 19- sep -07 21- abr -0 7 21- abr -0 7 23- jul-0 8 28- sep -02 28- sep -02 19- abr -0 7 19- abr -0 7 19- abr -0 7 21- jul-0 8 21- jul-0 8 22- jul-0 8 22- jul-0 8 23- jul-0 7 26- jul-0 7 18- oct- 07 05- ago -0 7 07- ago -0 7 - 5.05 27 09 - 5.05 27 09 - 16,8 38 889 - 16,8 38 889 - 16,8 38 889 - 3.75 93 40 - 3.75 93 40 - 5.05 27 09 - 14.8 84 238 - 14.8 84 238 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 10,4 24 455 - 10,4 03 147 - 10,4 03 147 - 10.8 39 682 - 10.1 01 199 -7 3.8 514 15 -7 3.8 514 15 -6 4,7 916 67 -6 4,7 916 67 -6 4,7 916 67 -7 3.2 477 08 -7 3.2 477 08 -7 3.8 514 15 -6 5.0 346 02 -6 5.0 346 02 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -6 5,4 703 71 -6 5,3 813 55 -6 5,3 813 55 -6 5.2 619 16 -6 5.4 298 85 99 474 GEN23 44 GEN23 45 GEN23 46 800 75 800 76 450 273 2 273 3 800 64 800 65 800 66 108 109 162 160 GEN27 87 GEN28 35 GEN29 38 GEN27 56 GEN27 62 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Cach uela Espe ran za Cach uela Espe ran za Cach uela Espe ran za Rur ren aba qu e El Se na Puer to Villar ro el Puer to Villar ro el Tr inida d Requ en a Requ en a Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Iqu itos Iqu itos Requ en a Tr inida d Tr inida d Iqu itos Iqu itos Iqu itos Requ en a Requ en a Requ en a Requ en a Vil la Bella Vil la Bella Vil la Bella Riber alta Riber alta Río Río Río Río Río Río Río Río Be lén, Be lén, Be lén, Be lén, Iqu itos Iqu itos Iqu itos Iqu itos Be ni, Ca chu ela Es per anza Be ni, Ca chu ela Es per anza Be ni, Ca chu ela Es per anza Be ni, J ri um a Man up are , El Sen a Ichilo, Puer to Villar ro el Ichilo, Puer to Villar ro el Ibar e, Pu er to Ba l iviá n 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 30 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 m ar mor atu s Bolivia Riber alta Río Mad re de Dios, El Carm en 07- ago -0 7 - 10.1 01 199 -6 5.4 298 85 GEN27 63 1 m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s m ar mor atu s Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Puer to Villar ro el Puer to Villar ro el Puer to Villar ro el Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Iqu itos Iqu itos Iqu itos Requ en a Requ en a Requ en a Iqu itos Río Ichilo, Puer to Villar ro el Río Ichilo, Puer to Villar ro el Río Ichilo, Puer to Villar ro el Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Or nam en tal F ish Aq uar ium , Iq uitos 19- sep -07 19- sep -07 19- sep -07 19- ago -0 8 19- ago -0 8 19- ago -0 8 24- ma r- 07 24- ma r- 07 24- ma r- 07 22- jul-0 8 22- jul-0 8 24- jul-0 8 11- ago -0 8 - 16,8 38 889 - 16,8 38 889 - 16,8 38 889 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 3.77 77 15 -6 4,7 916 67 -6 4,7 916 67 -6 4,7 916 67 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 951 55 GEN23 26 GEN23 27 GEN23 28 900 010 900 019 900 080 800 46 800 47 800 49 238 326 598 896 1 1 1 1 1 1 1 1 1 1 1 1 1 Me galo nem a pa l tyce pha lum pa l tyce pha lum pa l tyce pha lum Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos 11- ago -0 8 11- ago -0 8 11- ago -0 8 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 885 886 887 Phra ctoc eph alus h emilio pter us h emilio pter us h emilio pter us Bolivia Villa Bella Bolivia Villa Bella Bolivia Puer to Ric o Río Mad er a, Ca chu ela M ad er a Río Mad er a, Ca chu ela M ad er a Río Ort hon , Pue rto Rico 07- jun- 06 13- jun- 06 23- sep -07 - 10.3 63 381 - 10.3 63 381 - 11,1 03 443 -6 5.3 788 62 -6 5.3 788 62 -6 7,5 586 64 h emilio pter us h emilio pter us h emilio pter us Bolivia Puer to Ric o Bolivia Rur ren aba qu e Bolivia Rur ren aba qu e Río Ort hon , Pue rto Rico Río Be ni, M ota cus al Río Be ni, Bib osal 25- sep -07 15- jul-0 7 13- jul-0 7 - 11,1 03 443 - 13.5 80 594 - 13.5 80 594 h emilio pter us h emilio pter us h emilio pter us h emilio pter us Bolivia Per ú Per ú Per ú Río Be ni, Bib osal Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena 13- jul-0 7 21- jul-0 8 21- jul-0 8 22- jul-0 8 bo l chii bo l chii bo l chii Bolivia Villa Bella Bolivia Villa Bella Bolivia Villa Bella Río Mam or é, Villa Bella Río Mam or é, Villa Bella Río Be ni, Ca chu er ñ i a bo l chii bo l chii bo l chii Bolivia Villa Bella Bolivia Rur ren aba qu e Bolivia Villa Bella bo l chii bo l chii bo l chii bo l chii Bolivia Bolivia Bolivia Bolivia bo l chii bo l chii bo l chii Bolivia Puer to Villar ro el Bolivia Gua yar am erí n Per ú Iqu itos bo l chii bo l chii bo l chii Per ú Per ú Per ú o rna tus p ci tus p ci tus Pimelo dus Pimelo dina Pinira mpu s Platysilu rus Platyn ema ticht hys Platysto ma ticht hys Pseud op a l tysto ma 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Ma VB3 Ma VB4 GEN21 11 1 1 1 1 1 -6 7,5 586 64 -6 7.3 634 14 -6 7.3 634 14 GEN21 23 GEN26 47 GEN26 55 1 1 1 1 1 1 1 1 1 - 13.5 80 594 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 -6 7.3 634 14 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 GEN26 56 110 111 320 1 1 1 1 1 1 1 1 1 1 1 1 18- oct- 07 18- oct- 07 23- jul-0 7 - 10.3 96 734 - 10.3 96 734 - 10,4 24 455 -6 5.3 848 99 -6 5.3 848 99 -6 5,4 703 71 GEN29 35 GEN29 36 GEN28 01 1 1 1 1 1 Río Be ni, Ca chu er ñ i a Río Be ni, Co pa n i a Río Be ni, Ca chu er ñ i a 23- jul-0 7 09- dic- 07 23- jul-0 7 - 10,4 24 455 - 14.2 41 324 - 10,4 24 455 -6 5,4 703 71 -6 7.5 143 3 -6 5,4 703 71 GEN28 02 GEN30 22 GEN28 03 1 1 1 1 1 Río Río Río Río 03- nov -02 03- nov -02 24- ma y-07 24- ma y-07 - 14.2 76 861 - 14.2 76 861 - 16,7 72 946 - 16,7 72 946 -6 7.4 755 56 -6 7.4 755 56 -6 4,7 944 33 -6 4,7 944 33 370 0 370 1 GEN22 41 GEN22 42 1 1 1 1 1 1 Río Ichilo, Río Vie jo ( com un d i ad Pallar ) Río Mam or é, playa Lo s Bato s Me rca do Be lén, Iqu itos 24- ma y-07 29- ago -0 6 21- abr -0 7 - 16,7 72 946 - 12.0 00 758 - 3.75 93 40 -6 4,7 944 33 -6 4.0 809 28 -7 3.2 477 08 GEN22 44 GEN16 11 800 88 1 1 1 1 Iqu itos Iqu itos Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos 21- abr -0 7 21- abr -0 7 21- abr -0 7 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 800 89 800 92 800 93 1 1 1 1 1 1 Per ú Per ú Per ú Iqu itos Iqu itos Iqu itos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos 04- ma r- 10 11- ago -0 8 11- ago -0 8 - 3.77 77 15 - 3.77 77 15 - 3.77 77 15 -7 3.2 951 55 -7 3.2 951 55 -7 3.2 951 55 801 42 888 889 1 1 1 1 1 p ci tus sp A sp A sp A Per ú Bolivia Bolivia Bolivia Iqu itos Villa Bella Villa Bella Rur ren aba qu e Or nam en tal F ish Aq uar ium , Iq uitos Río Mam or é, Villa Bella Río Mam or é, Villa Bella Río Be ni, Co pa n i a 11- ago -0 8 18- oct- 07 18- oct- 07 09- dic- 07 - 3.77 77 15 - 10.3 96 734 - 10.3 96 734 - 14.2 41 324 -7 3.2 951 55 -6 5.3 848 99 -6 5.3 848 99 -6 7.5 143 3 890 GEN29 35 GEN29 36 GEN30 22 1 1 1 1 1 1 1 1 sp A sp B sp B fla vipinn is fla vipinn is fla vipinn is Bolivia Puer to Villar ro el Per ú Iqu itos Per ú Iqu itos Río Ichilo, Río Vie jo ( com un d i ad Pallar ) Or nam en tal F ish Aq uar ium , Iq uitos Or nam en tal F ish Aq uar ium , Iq uitos 24- ma y-07 11- ago -0 8 11- ago -0 8 - 16,7 72 946 - 3.77 77 15 - 3.77 77 15 -6 4,7 944 33 -7 3.2 951 55 -7 3.2 951 55 GEN22 44 892 893 1 1 1 1 1 1 1 Per ú Per ú Per ú Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do de R equ ena 19- abr -0 7 19- abr -0 7 07- ago -0 8 - 3.75 93 40 - 3.75 93 40 - 5.05 27 09 -7 3.2 477 08 -7 3.2 477 08 -7 3.8 514 15 800 68 800 69 879 1 1 1 1 1 1 1 fla vipinn is p ri ina mpu p ri ina mpu Per ú Requ en a Bolivia Puer to Ric o Bolivia El Se na Me rca do de R equ ena Río Ta hua ma nu, Puer to R ci o Río Man up are , ap ro x. 7 Km a rr b i a El Sen a 07- ago -0 8 22- ma y-07 04- nov -07 - 5.05 27 09 - 11,1 03 443 - 11.5 33 144 -7 3.8 514 15 -6 7,5 586 64 -6 7.2 923 14 880 GEN21 09 GEN29 93 1 1 1 1 1 p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu p ri ina mpu Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú El Se na Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to Villar ro el Puer to Villar ro el Gua yar am erí n Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Río Río Río Río Río Río Río Río Río 05- nov -07 05- jul-0 7 05- jul-0 7 02- oct- 07 18- sep -07 18- sep -07 09- sep -06 19- ago -0 8 19- ago -0 8 19- ago -0 8 - 11.6 47 319 - 13.6 01 385 - 13.6 01 385 - 14.1 85 022 - 16,8 38 889 - 16,8 38 889 - 12.4 25 081 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.3 188 42 -6 7.3 893 55 -6 7.3 893 55 -6 7.5 365 47 -6 4,7 916 67 -6 4,7 916 67 -6 5.1 599 25 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 GEN29 96 GEN26 80 GEN26 85 GEN27 88 GEN22 93 GEN22 94 GEN16 39 900 018 900 028 900 029 1 1 1 1 1 1 1 1 1 1 p ri ina mpu p ri ina mpu p ri ina mpu Per ú Per ú Per ú Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do 21- ago -0 8 21- ago -0 8 21- ago -0 8 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 900 077 900 094 900 095 1 1 1 p ri ina mpu p ri ina mpu p ri ina mpu m uco sus m uco sus m uco sus m uco sus n otat us n otat us n otat us st urio st urio st urio fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um fa sciat um tig rinu m tig rinu m tig rinu m Per ú Per ú Per ú Bolivia Per ú Per ú Per ú Bolivia Bolivia Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Bolivia Bolivia Bolivia Requ en a Requ en a Requ en a Rur ren aba qu e Iqu itos Iqu itos Iqu itos Villa Bella Villa Bella Puer to M ald ona do Villa Bella Rur ren aba qu e Rur ren aba qu e Villa Bella Villa Bella Villa Bella Villa Bella Puer to Villar ro el Puer to Villar ro el Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Río Be ni, Co pa n i a Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Me rca do Be lén, Iqu itos Río Mad er a, Ca chu ela M ad er a Río Mad er a, Ca chu ela M ad er a Río Mad re de Dios, Pu er to M aldo na do Río Mam or é, Villa Bella Río Be ni, Ru rr ena ba que Río Be ni, L imó n Río Mam or é, cach uela Piedr a G ord a Río Mam or é, Villa Bella Río Mam or é, Villa Bella Río Be ni, la gun a Bico Shato Río Ichilo, Puer to Villar ro el Río Ichilo, Puer to Villar ro el Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Be ni, So rayd a Río Be ni, So rayd a Río Be ni, So rayd a 21- jul-0 8 21- jul-0 8 21- jul-0 8 09- dic- 07 21- abr -0 7 07- ago -0 8 07- ago -0 8 27- jul-0 7 27- jul-0 7 21- ago -0 8 26- ma r- 08 02- dic- 07 03- dic- 07 18- oct- 07 20- oct- 07 20- oct- 07 22- oct- 07 18- sep -07 18- sep -08 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 21- ago -0 8 22- ago -0 8 22- ago -0 8 22- ago -0 8 22- ago -0 8 06- jul-0 7 06- jul-0 7 06- jul-0 7 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 14.2 41 324 - 3.75 93 40 - 3.75 93 40 - 3.75 93 40 - 10,3 73 000 - 10,3 73 000 - 12.5 93 581 - 10.3 96 734 - 14.4 40 752 - 14.1 85 022 - 10.4 43 593 - 10.3 96 734 - 10.3 96 734 - 10.3 94 550 - 16,8 38 889 - 16,8 38 889 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 14.0 75 481 - 14.0 75 481 - 14.0 75 481 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -6 7.5 143 3 -7 3.2 477 08 -7 3.2 477 08 -7 3.2 477 08 -6 5,3 884 45 -6 5,3 884 45 -6 7.1 727 19 -6 5.3 848 99 -6 7.5 308 97 -6 7.5 365 47 -6 5.3 917 97 -6 5.3 848 99 -6 5.3 848 99 -6 5.4 050 47 -6 4,7 916 67 -6 4,7 916 67 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.5 023 57 -6 7.5 023 57 -6 7.5 023 57 95 96 97 GEN30 39 800 74 877 878 GEN28 48 GEN28 49 900 096 GEN30 56 GEN30 11 GEN30 12 GEN29 31 GEN29 47 GEN29 50 GEN29 68 GEN22 97 GEN22 98 900 001 900 007 900 021 900 022 900 026 900 104 900 131 900 134 900 143 900 149 GEN26 68 GEN26 72 GEN26 73 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Rur ren aba qu e Requ en a Requ en a Requ en a Tr inida d Tr inida d Puer to Villar ro el Puer to Villar ro el Iqu itos Iqu itos Requ en a Be ni, la gun a G ring o Be ni, la gun a G ring o Ichilo, Puer to Yu ca Ichilo, Puer to Yu ca Man up are , ap ro x. 3 Km a bajo bo ca r ío M an urim i Be ni, b oca ar royo Nap ur era Be ni, b oca ar royo Nap ur era Be ni, L imó n Ichilo, Puer to Villar ro el Ichilo, Puer to Villar ro el Mam or é, Es tan cia Wa rn es Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 31 1 1 1 1 1 1 1 1 Prop ime o l du s Soru bim Soru bim ci hth ys Zu nga ro tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Per ú Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Río Be ni, b oca ar royo Nap ur era Be ni, L imó n Be ni, Pu ert o Salina s Be ni, Pu ert o Salina s Be ni, Pu ert o Salina s Be ni, L imó n Be ni, L imó n Be ni, L imó n Be ni, L imó n Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do Mad re de Dios, Pu er to M aldo na do 05- jul-0 7 03- jul-0 7 01- dic- 07 01- dic- 07 01- dic- 07 01- dic- 07 01- dic- 07 01- dic- 07 01- dic- 07 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 20- ago -0 8 21- ago -0 8 21- ago -0 8 22- ago -0 8 22- ago -0 8 - 13.6 01 385 - 14.1 85 022 - 14.2 62 508 - 14.2 62 508 - 14.2 62 508 - 14.1 85 022 - 14.1 85 022 - 14.1 85 022 - 14.1 85 022 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.3 893 55 -6 7.5 365 47 -6 7.5 049 78 -6 7.5 049 78 -6 7.5 049 78 -6 7.5 365 47 -6 7.5 365 47 -6 7.5 365 47 -6 7.5 365 47 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 GEN26 75 GEN27 05 GEN31 52 GEN31 58 GEN31 59 GEN31 63 GEN31 65 GEN31 68 GEN31 71 900 003 900 004 900 020 900 024 900 025 900 032 900 047 900 075 900 079 900 130 900 142 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m tig rinu m ca esiu s Per ú Per ú Per ú Per ú Per ú Per ú Per ú Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Iqu itos Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Me rca do Be lén, Iqu itos 22- ago -0 8 22- ago -0 8 22- ago -0 8 22- ago -0 8 22- ago -0 8 22- ago -0 8 07- ago -0 8 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 3.75 93 40 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -7 3.2 477 08 900 144 900 145 900 146 900 147 900 150 900 151 881 1 1 1 1 1 1 1 1 eo l ng atus lim a lim a Per ú Requ en a Bolivia Villa Bella Bolivia Puer to Villar ro el Me rca do de R equ ena Río Mam or é, Villa Bella Río Ichilo, Puer to Villar ro el 22- jul-0 8 28- jul-0 7 19- sep -07 - 5.05 27 09 - 10,4 03 147 - 16,8 38 889 -7 3.8 514 15 -6 5,3 813 55 -6 4,7 916 67 250 GEN28 56 GEN23 47 1 1 1 1 1 1 lim a lim a lim a lim a Bolivia Bolivia Bolivia Bolivia Río Río Río Río Ichilo, Puer to Villar ro el Ichilo, Puer to Villar ro el Mam or é, Gua yara me rín Mam or é, Gua yara me rín 19- sep -07 19- sep -07 10- jun- 07 11- jun- 07 - 16,8 38 889 - 16,8 38 889 - 10.8 13 437 - 10.8 13 437 -6 4,7 916 67 -6 4,7 916 67 -6 5.3 428 28 -6 5.3 428 28 GEN23 48 GEN23 63 GEN24 96 GEN25 01 1 1 1 1 1 1 1 1 1 lim a lim a lim a Bolivia Gua yar am erí n Per ú Iqu itos Per ú Requ en a Río Mam or é, Gua yara me rín Me rca do Be lén, Iqu itos Me rca do de R equ ena 11- jun- 07 21- abr -0 7 21- jul-0 8 - 10.8 13 437 - 3.75 93 40 - 5.05 27 09 -6 5.3 428 28 -7 3.2 477 08 -7 3.8 514 15 GEN25 02 800 77 113 1 1 1 1 1 1 lim a lim a lim a m anir ad i m anir ad i sp . sp . sp . sp . pa l nice ps pa l nice ps pa l nice ps pa l nice ps pa l nice ps pa l nice ps zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro zu nga ro Per ú Per ú Per ú Per ú Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Per ú Per ú Per ú Per ú Per ú Requ en a Requ en a Iqu itos Requ en a Iqu itos Versa lles Versa lles Versa lles Puer to Villar ro el Tr inida d Tr inida d Tr inida d Requ en a Requ en a Requ en a Villa Bella Villa Bella Puer to Ric o Puer to Ric o El Se na El Se na El Se na Rur ren aba qu e Rur ren aba qu e Rur ren aba qu e Puer to Villar ro el Tr inida d Tr inida d Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Me rca do de R equ ena Me rca do de R equ ena Or nam en tal F ish Aq uar ium , Iq uitos Me rca do de R equ ena Me rca do Be lén, Iqu itos Río Itén ez, b ah ía Ne gra Río Itén ez, b ah ía Ne gra Río Itén ez, b ah ía Ne gra Río Ichilo, Puer to Villar ro el Río Mam or é, Car nava lito Río Mam or é, Tr inida d Río Mam or é, Tr inida d Me rca do de R equ ena Me rca do de R equ ena Me rca do de R equ ena Río Be ni, Ca chu er ñ i a Río Mam or é, Villa Bella Río Ta hua ma nu, Puer to R ci o Río Ta hua ma nu, Puer to R ci o Río Mad re de Dios, boca Arr oyo El M at i Río Mad re de Dios, boca Arr oyo El M at i Río Mad re de Dios, boca Arr oyo El M at i Río Be ni, M ota cus al Río Be ni, Bib osal Río Be ni, Bib osal Río Ichilo, bo ca r ío Ch imo ré Río Mam or é, Sa n An tonio de Lo ra Río Mam or é, Sa n An tonio de Lo ra Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do 21- jul-0 8 22- jul-0 8 11- ago -0 8 22- jul-0 8 21- abr -0 7 * * * 19- sep -07 02- jun- 07 04- jun- 07 04- jun- 07 22- jul-0 8 22- jul-0 8 22- jul-0 8 22- jul-0 7 18- oct- 07 19- ma y-07 21- ma y-07 09- nov -07 09- nov -07 09- nov -07 14- jul-0 7 13- jul-0 7 12- jul-0 7 19- sep -07 19- jun- 07 19- jun- 07 19- ago -0 8 19- ago -0 8 19- ago -0 8 19- ago -0 8 20- ago -0 8 - 5.05 27 09 - 5.05 27 09 - 3.77 77 15 - 5.05 27 09 - 3.75 93 40 - 12,6 30 499 - 12,6 30 499 - 12,6 30 499 - 16,8 38 889 - 15.1 30 726 - 14.8 41 347 - 14.8 41 347 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 10,4 24 455 - 10.3 96 734 - 11,1 03 443 - 11,1 03 443 - 11.4 61 600 - 11.4 61 600 - 11.4 61 600 - 13.5 80 594 - 13.5 80 594 - 13.5 80 594 - 16,7 45 186 - 15.2 08 067 - 15.2 08 067 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 951 55 -7 3.8 514 15 -7 3.2 477 08 -6 3,4 106 61 -6 3,4 106 61 -6 3,4 106 61 -6 4,7 916 67 -6 5.0 144 68 -6 4.9 032 14 -6 4.9 032 14 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -6 5,4 703 71 -6 5.3 848 99 -6 7,5 586 64 -6 7,5 586 64 -6 7.2 318 26 -6 7.2 318 26 -6 7.2 318 26 -6 7.3 634 14 -6 7.3 634 14 -6 7.3 634 14 -6 4,8 435 33 -6 4.9 864 32 -6 4.9 864 32 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 115 246 894 242 800 79 GEN22 99 GEN23 00 GEN23 01 GEN23 31 PST 11 PST 30 PST 31 156 157 158 GEN27 50 GEN29 28 GEN21 02 GEN21 05 GEN31 21 GEN31 22 GEN31 23 GEN26 51 GEN26 54 GEN26 57 GEN28 82 PST 49 PST 61 900 006 900 009 900 014 900 017 900 040 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 zu nga ro zu nga ro zu nga ro Per ú Per ú Per ú Puer to M ald ona do Puer to M ald ona do Puer to M ald ona do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do Río Mad re de Dios, Pu er to M aldo na do 20- ago -0 8 21- ago -0 8 21- ago -0 8 - 12.5 93 581 - 12.5 93 581 - 12.5 93 581 -6 7.1 727 19 -6 7.1 727 19 -6 7.1 727 19 900 058 900 090 900 091 1 1 1 Per ú Per ú Per ú Iqu itos Requ en a Requ en a Me rca do Be lén, Iqu itos Me rca do de R equ ena Me rca do de R equ ena 21- abr -0 7 21- jul-0 8 21- jul-0 8 - 3.75 93 40 - 5.05 27 09 - 5.05 27 09 -7 3.2 477 08 -7 3.8 514 15 -7 3.8 514 15 800 73 102 112 1 1 1 1 1 1 1 1 1 1 Puer to Villar ro el Puer to Villar ro el Gua yar am erí n Gua yar am erí n 1 1 1 1 1 1 1 1 1 1 1 1 1 Dor ad idae Hem idor as zu nga ro zu nga ro zu nga ro m or risi cf. Auch enip ter idae Oxyd or as Agen eiosu s m or risi cf. ng i er ine rm is Per ú Per ú Per ú Per ú Requ en a Requ en a Requ en a Iqu itos Me rca do Me rca do Me rca do Me rca do de R equ ena de R equ ena de R equ ena Be lén, Iqu itos 24- jul-0 8 24- jul-0 8 24- jul-0 8 21- abr -0 7 - 5.05 27 09 - 5.05 27 09 - 5.05 27 09 - 3.75 93 40 -7 3.8 514 15 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 477 08 602 604 596 800 80 1 1 1 1 Per ú Per ú Per ú Requ en a Requ en a Iqu itos Me rca do de R equ ena Me rca do de R equ ena Me rca do Be lén, Iqu itos 21- jul-0 8 21- jul-0 8 21- abr -0 7 - 5.05 27 09 - 5.05 27 09 - 3.75 93 40 -7 3.8 514 15 -7 3.8 514 15 -7 3.2 477 08 114 606 800 81 1 1 1 1 1 Tr ach elyop ter us ine rm is ine rm is g alea tus g alea tus Per ú Iqu itos Me rca do Be lén, Iqu itos 21- abr -0 7 - 3.75 93 40 -7 3.2 477 08 800 82 1 1 2.2.2 Laboratory methodology and DNA extraction Total DNA (genomic) was extracted from tissue samples preserved in 95% ethanol using a modification of the CTAB procedure developed by Doyle & Doyle (1987). The procedure began by preheating the extraction solution (5% of hexadecyltrimetil ammonium bromide [CTAB, Sigma], NaCl 5M, EDTA 0.5 M pH8, Tris. Hcl 1 M) to 60 °C in a bain-marie or stove. Then, about 100 mg of crushed dry tissue were introduced into a tube (2 mL) with 1 mL of the CTAB extraction solution (preheated) plus 15 µL of Proteinase K (10 mg/mL) (Sigma). The preparation was incubated at 60 °C (bain-marie or stove) for a period of 8 – 10 hours, with occasional agitation every 2 – 3 h to accelerate and improve the digestion process. Once the pieces of muscle were completely digested, 1 mL of chloroform was added and the content was mixed vigorously (5 min), before 32 submitting it to 8000 rpm centrifugation during 5 min. After that, 750 µL of the supernatant (without interface particles) were transferred to another sterile tube (1.5 mL) to be mixed gently (2 min) with 750 µL of Isopropanol at - 5 °C. The mixture was left to stand at - 20 °C for 2 h to accelerate the precipitation of DNA molecules. Afterwards, the solution was submitted to 13 000 rpm centrifugation during 15 min to separate and concentrate the DNA in a whitish pellet on the walls or bottom of the tube. The surrounding solution was carefully discarded and replaced with 750 µL of ethanol (70%) for a final 15 min wash at 13 000 rpm centrifugation. The ethanol was then discarded from the tube and the residues around the pellet were eliminated by evaporation at room temperature for 5 – 7 h. Finally, the DNA obtained (dry) was re-suspended with sterile water Milli-Q (50 µL) for subsequent dilution in aliquots and use in PCR amplifications. 2.2.3 Molecular markers selection 2.2.3.1 Control Region (RC) - mtDNA The mitochondrial DNA (mtDNA) has been the most studied genome in eukaryotes and has played an important role in the development of evolutionary and population genetics in the last decades (Moritz et al. 1987; Rand 2001; William et al. 2004). This genome, uniparentally inherited and without recombination (clonal pattern) (Ingman et al. 2000) is a circular and monocatenary (single-strand) molecule containing 15 – 20 kilo bases (kb) as a whole. In fish and most vertebrates, it contains 37 genes, which code for proteins (13) that participate in the transport of electrons (or ATP synthesis) and oxidative phosphorylation (Meyer 1993). It does not have interrupted genes, introns are absent from the entire sequence, but it has a non-coding area (neutral) that participates in the regulation and initiation of replication and transcription (Rand 2001). This area, between the RNAt-tre and RNAt-phe (Pereira 2000), is known as the Control Region (CR) and comprises a fragment of 1000 bp, on average (taxa dependent), rich in Adenine (A) and Thymine (T). Structurally, the CR contains a loop or fold displacement (D-loop) involved in the replication, which is unidirectional and highly asymmetric in animals (Rand 2001). It has been shown that the sequence of the CR is the most variable of the mtDNA. In humans, for example, it has been estimated that the substitution rate is 2.8 – 5 times faster than the rest of the mitochondrial genome. This high rate of mutation is useful for detecting recent distinctions between species or populations, but their phylogenetic utility, in cases of deep divergence, may be limited due to saturation and ambiguities in determining homologies (Kocher & Carleton 1997; Ruokonen & Kvist 2002). Globally, the approximate rate of mtDNA mutation is 10-8/site/year (DeSalle et al. 1987) compared to 109 /site/year in nuclear genes. Many differences between the mtDNA sequences are punctual mutations with a strong bias towards transitions over transversions (Brown et al. 1982). The maternal inheritance of CR and its relatively rapid evolution have led to their widespread use as a genetic marker for matrilineal gene flow studies, the history of the species (including hybrid taxa) and the dynamics of hybrid zones (Moritz et al. 1987). In several groups of fish, a significant number of studies 33 have been carried out using the CR as a tool for phylogenetic inferences, especially between close taxa (e.g. Tinti et al. 1999; Sturmbauer & Meyer 1993; Sturmbauer et al. 1994; Zhao et al. 2006). In the Neotropics this marker has been used to reconstruct the phylogeny of several groups of freshwater fish such as some families of characiforms (e.g. Hubert et al. 2007a; Orti et al. 2008; Sivasundar et al. 2001; Pretti et al. 2009), perciforms (e.g. Renno et al. 2006; Willis et al. 2007) and siluriforms (e.g. Torrico et al. 2009). Based on this background, the CR was amplified (~ 900 pb) for 328 individuals belonging to 32 species corresponding to 4 families (Cetopsidae - 1, Pseudopimelodidae - 1, Heptapteridae - 2, Pimelodidae - 28). Cetopsidae, Pseudopimelodidae and Heptapteridae were considered as out groups to the Pimelodidae. The amplification of the corresponding fragment plus a portion of the RNAt-phe was performed with the primers DL20 F (5 'ACCCCTAGCTCCCAAAGCTA 3'), available in Agnese et al. (2006), and DL20 R (5 'TTAGCAAGGCGTCTTGGGCT 3') kindly provided by Agnese (unpublished). 2.3.3.2 Cytochrome c Oxidase 1 (CO1) – mtDNA The Cytochrome c Oxidase (CO) protein is the component of the respiratory chain that catalyzes the reduction of oxygen to water. Its coding gene of ~ 650 bp, is located in the outermost strand (heavy chain) of the mitochondrial genome between the RNAt-tri and RNAt-asp. It is composed by three subunits (1 – 3) that form the functional nucleus of the enzyme complex, and the fraction 1 (CO1) is the catalytic unit of the enzyme. The CO and CO1 proteins interact during the final step of the electron transport system of the mitochondria, which plays a central role in cellular energy production (Avise 2004). It has been proposed that the 5' termination of the mitochondrial gene is a particularly promising descriptor for the identification of species (Ward et al. 2009) and phylogenetic studies (e.g. Burridge 2000; Pereira et al. 2002; Halanych & Janosik 2006; Kitahara et al. 2010). The diversity of nucleotide sequences that are found in this region of the gene regularly allows the discernment of closely related species (e.g. Lepidoptera). Similarly, but on a longer time scale, the resulting amino acid sequences of this gene are sufficient to reliably position species in higher taxonomic categories (from phylum to order) (Hebert et al. 2003a). It is clear that the mitochondrial genome of animals, in general, is a better target for identification and phylogenetic analysis than the nuclear genome due to the lack of introns, their limited exposure to recombination, and their haploid mode of inheritance (Saccone et al. 1999). The availability of a wide range of primers also allows the continuous recovery of CO1 segments of diverse phylum (Folmer et al. 1994). Several phylogenetic works have focused on mitochondrial gene coding for ribosomal DNA (e.g. 12S RNA, 16S rDNA), but their utility in taxonomy, in the broad sense, is limited by the prevalence of insertions and deletions (indels) that significantly complicate the alignment of sequences (Doyle & Gaut 2000). In comparison, the gene encoding proteins (13) in the animal mitochondria are better descriptors because indels rarely occur during the reading of the DNA. A priori, convincing reasons do not exist to focus the analysis on a specific mitochondrial gene, but 34 the CO1 gene has two important advantages. First, the universal primers for this gene are robust and enable to obtain the 5' strain termination for almost all animal phyla. Second, this gene seems to have a greater scope of phylogenetic signal than any other mitochondrial gene (Hebert et al. 2003a). Like other protein encoding genes, the position of the third nucleotide shows a high incidence of base substitutions, leading to rate of molecular evolution nearly three times larger than the 12S or 16S DNAr (e.g. shrimp Alpheus, Knowlton & Weigt 1998). In fact, the evolution of this gene is rapid enough to allow the discrimination of closely related species but also of phylogeographic groups within a single species (Cox & Hebert 2001; Hebert et al. 2003b; Ward et al. 2005). Although the CO1 can be replaced by other mitochondrial descriptors (genes) to resolve cases of recent divergence, the CO1 is more likely to provide a clearer idea or more precise phylogenetic resolution than others such as Cytochrome b because changes in its amino acid sequence occur more slowly than in any other mitochondrial gene (Lynch & Jarrell 1993). As a result, by analyzing the amino acid substitution it is possible to assign any unidentified organism to its higher taxonomic group (e.g. phylum, order), before examining the sequence and nucleotide substitution (DNA) to determine its specific identity (Hebert et al. 2003b). Inspired by the bar code of a supermarket (Stoeckle & Hebert 2008), the CO1 gene sequence is being used as a barcode for DNA (DNA barcoding) to identify and classify the great biodiversity of the planet that remains unknown. Identification via DNA barcoding is based on the observation of intraspecific genetic divergence which is usually smaller than interspecific divergence (Hebert et al. 2003a). In principle, the method used is cost effective and quick to document as many species as possible in the short term before they become extinct. Despite the criticisms and controversies that have emerged from this procedure (e.g. Meyer & Paulay 2005; Wheeler 2005; Packer et al., 2009; Stoeckle & Heber 2008), in addition to some specific cases in which conflicts were observed in the correct assignment of species (e.g. Spooner 2009; Dasmahapatra et al. 2010), the methodology appears to work well for the majority of organisms to which it has been applied (e.g. Hebert et al. 2003a; Ward et al. 2005; Tavares & Baker 2008; Baker et al. 2009; Zemlak et al. 2009; Heger et al. 2010). In the case of fish, studies have shown a great efficiency of the marker (CO1) (e.g. Pegg et al. 2006; Hubert et al. 2008; Zemlak et al. 2009) and have allowed the identifation of conflicting groups that require further studies of morphological taxonomy (traditional), ecology and the application of additional genetic descriptors for resolution. Some examples from the Neotropical region are represented in the work of Toffoli et al. (2008) and Ardura et al. (2010). With those considerations in mind, the termination 5' of CO1 was obtained for 218 individuals of silurids belonging to 61 species, distributed in seven families (Loricariidae - 15, Doradidae - 2, Auchenipteridae - 2, Cetopsidae - 1, Heptapteridae - 4, Pseudopimelodidae - 1 and Pimelodidae - 36), using the primers FishF1-5'TCAACCAACCACAAAGACATTGGCAC3' and FishR15'TAGACTTCTGGGTGGCCAAAGAATCA3' of Hubert et al. (2008). The Loricariidae, Doradidae, Ageneiosidae, Cetopsidae, and Pseudopimelodidae Heptapteridae families were considered as outgroups to the Pimelodidae. A 35 greater number of species and families with this descriptor were analyzed, in comparison to those for the CR and Freticulon-4, due to the broad efficiency demonstrated by the primers used. 2.2.3.3 Introns (Freticulon-4) – nDNA The F-reticulon4, also known as Nogo or RTN4 (fourth member of the family of reticulon genes), is a gene of nuclear DNA (biparental inheritance) that encodes for different isoform proteins with a C-terminal domain highly conserved (reticulon homology domain). This gene belongs to a family of proteins that are predominantly associated with the endoplasmic reticulum present in the nervous system of several eukaryotes (Oertle et al. 2003), mammals (Fergani et al. 2005; Yan et al. 2006), fish (Diekmann et al. 2005) and insects (Wakefield & Tear 2006). Its primary role seems to be regeneration (morphogenesis) and inhibition of axonal growth on the surface of nerve cells (Yang & Strittmatter 2007). This descriptor has been used recently to reconstruct phylogenies and study the phylogeography of some groups of Loricariids (Siluriformes) (Chiachio et al. 2008; Cardoso & Montoya-Burgos 2009; Roxo 2010). These studies revealed new hypotheses of diversification in the Neotropical region (Pseudancistrus) and hypotheses of classification of some subfamilies (e.g. Hypoptopomatinae, Neoplecostominae). The fragment Freticulon-4 (~ 1700 bp) was obtained for 117 individuals belonging to 38 species and four families of Siluriformes (Loricariidae - 1, Auchenipteridae - 2, Heptapteridae - 3 and Pimelodidae - 32). The Loricariidae, Auchenipteridae and Heptapteridae were taken as the outgroups to the Pimelodidae. Its amplification by PCR was performed with the primers Freticul4-D (5'AGGCTAACTCGCTYTSGGCTTTG3') and Freticul4-R (5'GGCAVAGRGCRAARTCCATCTC3'), kindly provided by Montoya-Burgos in 2009 and used in Roxo (2010). 2.2.4 DNA amplification and sequencing The Polymerase Chain Reaction for the three descriptors (DNAmt and DNAn) was carried out in a total volume of 60 µl composed by 12 µL of reaction buffer 5X (Colorless GoTaq Promega, 7.5 mM MgCl2 at pH 8.5); 3.6 µL of MgCl2 (25 mM). 12 (CR and Freticulon -4); 3.6 µl (CO1) of dNTPs (1 mM each dNTP); 1.2 µL of each primer (10 uM each one), 0.3 (CO1 and RC); 1.2 U (Freticulon-4) of Taq polymerase (GoTaq Promega); approximately 150 - 200 ng of genomic DNA extract (2 µL of extraction); and 27.7 (RC), 36.1 (CO1); 27.76 µL (Freticulon-4) of Milli-Q water. The temperature profile started with a denaturation at 95 (CR), 94 °C (CO1 and Freticulon-4) for a period of 2 min (3 min - Freticulon-4), followed by 35 (CR and CO1), 39 cycles (Freticulon -4) composed by denaturation at 95 (RC), 94 °C (CO1 and Freticulon-4) (30 sec), hybridization at 53 °C (30 - CR and Freticulon-4, 40 sec - CO1); elongation at 72 °C (60 sec - CR and CO1, 2 min - Freticulon-4); and a final elongation at 72 °C (5 min) before being refrigerated at 4 °C. Each batch of amplification included a negative control reaction tube, in which all reagents except the DNA template were mixed. All amplifications were carried out in a thermocycler Mastercycler ep (Eppendorf AG 2231Hamburg). The obtained fragments were 36 sequenced with the same primers used during their amplification by commercial enterprises of genomic services Macrogen (Korea, http://www.macrogen.com/) and GenoScreen (France, http://www.genoscreen.fr/) between the years 2008 2010. 2.2.5 Genetic analysis The sequences obtained with the three markers were edited and manipulated with MEGA version 5.01 (Tamura et al. 2011) and BIOEDIT version 7.0.9.0 (Hall 1999). The haplotypes obtained for each species were identified with the program DNASP version 5.10 (Librado & Rozsas 2009) and the multiple alignment was carried out with MAFFT - method E-INS-i (Katoh et al. 2005). Phylogenetic analysis of the individual and combined descriptors (concatenated) was realized using an approach of maximum likelihood (ML) with the software PHYML version 3.0 (Guindon & Gascuel 2003). The search for the most probable trees was carried out using topological movements SPR (Subtree Pruning and Regrafting) (Hordijk & Gascuel 2005) and NNI (Nearest Neighbor Interchange) (Robinson 1971, Moore et al. 1973). The construction of the best ML tree required a model of nucleotide evolution with the highest adjustment (approach) to the data and the lowest number of estimated parameters. This model was chosen from 28 available, based on the Akaike Information Criterion (AIC) (Huelsenbeck & Rannala 1997) with the program APE (Paradis et al. 2004) written in the R statistical environment (R Development Core Team 2009). Under this criterion, the general model more suitable for sequences corresponding to each individual descriptor (CR, CO1, Freticulon-4) and the concatenated of the three, was GTR (General Time Reversible Model) (Tavaré 1986) + I (invariable sites ) + Γ (rate heterogeneity among sites, α). The parameters for each descriptor were fixed in CR [GTR + I (0.145) + Γ (α = 0.754)], CO1 [GTR + I (0.554) + Γ (α = 0.945)], Freticulon-4 [GTR + I (0313) + Γ (α = 1.721)], concatenated [GTR + I (0267) + Γ (α = 0.497)]. The evaluation of the nodes support was carried out with a nonparametric bootstrap analysis (Felsenstein 1985) of 100 random repeats. The data matrices obtained for mitochondrial descriptors (CR and CO1) were supplemented with other taxa sequences available in GenBank. Thus, for the CR, partial sequences deposited by Matoso et al. (unpublished, submission to Genbank July 29, 2008) (Sorubim lima - EU930047.1, Steindachneridion scriptum - EU930029.1 - UE930044, Zungaro zungaro - EU930046.1), Boni et al. (unpublished, submission to GenBank June 9, 2009) (Zungaro zungaro FJ797695 - FJ797697, Zungaro jahu - FJ797691 - FJ797694, GQ254526 GQ254529), and Torrico et al. (2009) (Pseudoplatystoma corruscans FJ889873 - FJ889877, Pseudoplatytoma magdaleniatum - FJ889878 FJ889882, Pseudoplatystoma reticulatum - FJ889869 - FJ889872) were included. Other usable sequences in GenBank, corresponding to the species Trichomycterus areolatus (Quezada-Romegialli et al., 2010, GQ178147 GQ178151) and Corydoras rabauti (Saitoh et al., 2003, AB054128 and NC_004698) were not included in the analyzes due to the high existing 37 divergence with the sequences of other taxa and the difficulty in achieving a balanced alignment. The data matrix of CO1, was supplemented with the sequences obtained by Ardura et al. (2010) (Ageneiosus inermis - FJ418755.1, Brachyplatystoma filamentosum - FJ418760.1, B. rousseauxii - FJ418759.1, Cetopsis candiru FJ418756.1, Phractocephalus hemioliopterus - FJ418764.1, Pseudoplatystoma fasciatum - FJ418766.1, P. tigrinum - FJ978041.1, wrongly labeled as B. filamentosum in GenBank), Cramer et al. (2007) (Astroblepus spp. EU359404.1 - EU359407.1, Callichthys Callichthys - EU359408.1, Nematogenys inermis - EU359428.1, Scoloplax distolothrix - EU359463.1), Martinez et al. (Unpublished submission to GenBank 26 Sep 2006) (Batrochoglanis ranninus - EU179809.1, B. villosus - EU179808.1, Cephalosilurus apurensis - EU179818.1, Lophiosilurus alexandri - EU179802.1, Diplomystes mesembrinus - EU179801.1, Henonemus punctatus EU179799.1, Microglanis aff. cottoides - EU179805.1 and EU179806.1 (approaching of Rhamdia quelen) Microglanis garavelloi - EU179807.1, Microglanis leptostriatus - EU179803.1, Pseudopimelodus bufonius EU179813.1 and EU179814.1 , P. charus - EU179815.1, P. mangurus EU179816.1, P. pulcher - EU179812.1, Pseudopimelodus sp. - EU179817.1, Rhamdia quelen - EU179804.1, Zungaro zungaro - EU179810.1), Ng (Unpublished submission to GenBank 18 Sep 2006) (Diplomystes nahuelbutaensis - EF014945.1), Lundberg & Parisi (2009) (Pimelabditus mill GU181205.1 - GU181207.1), Saitoh et al. (2003) (Corydoras rabauti NC_004698.1), Sullivan et al. (Unpublished submission to GenBank February 11, 2008) (Acanthodoras cataphractus - EU490847.1, Ageneiosus ucayalensis - EU490849.1, Bunocephalus verrucosus - EU490846.1, Hoplomyzon sexpapilostoma - EU490843.1, Micromyzon akamai - EU490844.1, Pterobunocephalus sp. - EU490845.1, Trachelyopterus galeatus EU490848.1), Valdez-Moreno et al. (2009) (Rhamdia guatemalensis EU751953.1 - EU751962.1, Rhamdia sapo - EU074579.1, Rhamdia sp. 1 EU751963.1) and Ferraris & Vari (2009) (Cetopsidium soniae - GQ141710.1 and GQ141711.1). For the general analysis (concatenated) of the mitochondrial descriptors (CR and CO1) and the nuclear descriptor (F-reticulon4), 116 individuals of 37 species in four families (Loricariidae - 1, Achenipteridae - 2, Heptapteridae - 3, Pimelodidae – 31) were analyzed. Families Loricariidae (Hypostomus sp.), Auchenipteridae (Tracheliopterus galeatus and Ageneiosus inermis) and Heptapteridae (Goediella eques, Pimelodella sp., Rhamdia quelen) were used as external groups to the Pimelodidae family. In the data, nine taxa were included for which it was not possible to amplify one of the three fragments or the obtained sequence was unreadable (e.g. individual heterozygous for the nuclear descriptor). These taxa were Sorubimichthys planiceps (CR), Hemisorubim platyrhynchos (RC), Hypophthalmus marginatus (CR), H. edentatus (CR), Pimelodella sp. (CR), Rhamdia quelen (RC), Ageneiosus inermis (CR), Trachelyopterus galeatus (CR), Hypostomus sp. (CR). Missing data in the matrix were encoded with the symbol '?'. 38 2.2.6 Molecular clock test and estimation of evolutionary distance The molecular clock test for each descriptor was carried out by comparing the values of the maximum likelihood (ML) for given topologies with and without the restrictions under the GTR model. The differences in evolutionary rates between sites were modeled using a discrete distribution of Gamma (Γ) (shape parameter) and invariant (I), which were estimated from the invariable portion of the sites. The null hypothesis of uniform evolutionary rate through the tree was rejected at a significance level of 5%. The analysis of CR included 266 nucleotide sequences and there were a total of 1 251 positions in the final database. For the analysis of CO1 were used 180 nucleotide sequences and 685 positions in the total matrix. The treatment of the RTN4 included 117 nucleotide sequences with 2 266 positions in the final database. The test on concatenated descriptors was composed of 112 sequences and 4 136 positions in the final matrix. All analyzes were conducted in MEGA 5.01 (Tamura et al. 2011). The evolutionary distance (d) average between pairs of sequences for taxa, was obtained taking into account the nucleotide substitution model of TamuraNei (Tamura & Nei 1993), rate of change between sites with the gamma parameter (α = 0.7), the proportion of sites with transitional and transversional nucleotide differences (d: transitions + transversions) and heterogeneous pattern among lineages (Tamura and Kumar 2002). Spaces and absent data between pairs of sequences were not considered (pairwise delete), and the variance of the distance was estimated from 500 pseudo-repeats randomly generated (bootstrap). Both the estimated distance and its respective standard the deviation were obtained in MEGA 5.01 (Tamura et al. 2011). 2.3 Results 2.3.1 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on CR – mt DNA sequences The 17 nominal genera of Pimelodidae included in this study for analysis of CR, conformed coherent monophyletic groups (except Brachyplatystoma) supported by high bootstrap values between 90 and 100% (Figure 2.4). The species identified at the morphological level corresponded well with the groupings (clades) obtained with the ML analysis. Paraphyletic groups were not observed at the genus level, but there were some particular cases with the Zungaro genus. A sequence of Brazil, identified as Z. zungaro in GenBank (EU930046.1), stayed in the middle of the sequences of Z. Jahu and not within the group of slightly variable sequences from Bolivia and Peru. Phractocephalus and Steindachneriodon formed the most basal group, sister of a larger group that contained the remaining genera of the family Pimelodidae, including Leiarius. Within this larger group were two groups, with Leiarius as the most basal species to all of them. The first group (bootstrap 88%) included the genera Megalonema, Pimelodina, Pimelodus, Propimelodus, Aguarunichthys, Pinirampus and Calophysus, but without a clear internal resolution of their relationships. The group formed by Aguarunichthys, Pinirampus and 39 Calophysus was supported by a bootstrap of 57%, and the group formed by Pimelodus and Propimelodus by one of 89%. The second group without significant support contained a branch formed by Sorubim and Pseudoplatystoma, supported by a bootstrap of 58%, and another branch without significant support (bootstrap < 50%) that included species of the Zungaro, Brachyplatystoma, Platynematichthys, Platystomatichthys and Platysilurus genera. This last branch was composed of two groups with bootstrap support greater than 50%. One of the groups (bootstrap 73%), was composed by the species Brachyplatystoma vaillantii B. rousseauxii, B. capapretum and B. filamentosum. In this group, the set of species B. rousseauxii + (B filamentosum + B capapretum) with bootstrap of 100%, was positioned as a sister group of B. vaillantii. The other established group (bootstrap 53%) was constituted by Platynematichthys notatus, Brachyplatystoma tigrinum, B. juruense and B. platynemum. The species B. juruense and B. platynemum together formed the sister group of B. tigrinum (bootstrap 69%), and these three species conformed the sister group of P. notatus (Figure 2.4). Pairwise species comparison within genera showed both low (1.4% Pseudoplatystoma fasciatum vs P. reticulatum) and high (24.9%, Brachyplatystoma tigrinum vs B. capapretum) divergence between species. However, according to the analyzed sequences and an external morphologic inspection of the individuals of Sorubim, there seems to be an undescribed species in Bolivia with several affinities to S. elongatus. A similar case was observed for a Pimelodus species in Bolivia, which morphologically is very similar to P. blochii. The null hypothesis of uniform evolutionary rate across the tree, constructed with the sequences of the CR, was rejected at a significance level of 5% (P < 4.2897 exp - 114). According to the ML method, the clock model had a lnL = 23 204.956 (G = 4.72, I = 0.04) with 275 parameters and the model without clock a lnL = - 22 620.002 (G = 0.75, I = 0.14) with 539 parameters. The values of the distance p were superior to one between several taxa of the ingroup and the outgroup (e.g. Cetopsis candiru vs Steindachneriodon scriptum), which reflects the type of calculation and denotes a high divergence (Table 2.2). In the ingroup the distances ranged from 0.014 (Pseudoplatystoma fasciatum vs P. reticulatum) to 0.666 (Steindachneridion scriptum vs Zungaro jahu). The values superior to one indicate that the alignment between those taxa had few homologous areas (high differentiation) (Table 2.2). Between the species of Brachyplatystoma the distance ranged from 0.06 (B. juruense vs B. platynemum) to 0.249 (B. capapretum vs B. tigrinum). 40 Figure 2. 4 Maximum likelihood (ML) tree built with PHYML for CR sequences of 33 species of Pimelodidae (lnL = 22620.051) considering the evolution model GTR + I (0.146) + Γ (α = 0.758). The families Cetopsidae (Cetopsis coecutiens) Heptapteridae (Goediella eques and Rhamdia quelen), Pseudopimelodidae (Batrochoglanis raninus) were used as outgroups. The numbers near the nodes, some before the species names, represent the bootstrap values and the numbers in brackets [ ] the number of haplotypes per species. The branch in blue color corresponds to the group that contains the Brachyplatystoma and highlighted branch in red belongs to B rousseauxii. The names with a star indicate that the taxa could represent undescribed species. The arrows pointing to left denote the position of Zungaro jahu with respect to Z. zungaro. The codes that begin with EU (Sorubim lima), FJ and GQ (Zungaro) correspond to sequences deposited in GenBank. The image of Steindachneridion scriptum was extracted from Garavello (2005), those of Pseudoplatystoma magdaleniatum, P. corruscans and P. reticulatum of Buitrago-Suarez & Burr (2009), and that of Brachyplatystoma capapretum of Lundberg & Akama (2006). 41 Table 2. 2 Average number of substitutions per site of all pairs of sequences (CR) between the taxa of Pimelodidae and its outgroups (upper diagonal). The estimated standard error for each comparison is shown in the lower diagonal. The analyses were conducted using the nucleotide substitution model of Tamura-Nei and the rate of variation between sites was modeled with the gamma distribution (shape parameter, α = 0.7). The differences in the composition biases between sequences were considered in evolutionary comparisons. The analysis considered 266 nucleotide sequences and all ambiguous positions were removed for each pair of sequences (pairwise deletion). The final matrix was composed by 1251 positions. 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 Aguarunichtys_torosus Brachyplatystoma_capapretum Brachyplatystoma_filamentosum Brachyplatystoma_juruense Brachyplatystoma_platynemum Brachyplatystoma_rousseauxii Brachyplatystoma_tigrinum Brachyplatystoma_vaillantii Calophysus_macropterus Leiarius_marmoratus Megalonema_platycephalum Phractocephalus_hemiliopterus Pimelodus_spA Pimelodus_spB Pimelodus_blochii Pimelodus_pictus Pimelodina_flavipinnis Pinirampus_pirinampu Platysilurus_mucosus Platynematichthys_notatus Platystomatichthys_sturio Propimelodus_caesius Pseudoplatystoma_corruscans Pseudoplatystoma_fasciatum Pseudoplatystoma_magdaleniatum Pseudoplatystoma_reticulatum Pseudoplatystoma_tigrinum Sorubim_elongatus Sorubim_lima Sorubim_maniradii Sorubim_sp. Zungaro_jahu Zungaro_zungaro Steindachneridion_scriptum Batrochoglanis_raninus Goediella_eques Rhamdia_quelen Cetopsis_candiru 0.033 0.041 0.041 0.040 0.039 0.041 0.034 0.032 0.035 0.046 0.046 0.028 0.029 0.025 0.034 0.030 0.025 0.039 0.038 0.041 0.030 0.037 0.035 0.048 0.035 0.029 0.032 0.033 0.030 0.032 0.522 0.048 0.057 0.100 0.079 0.063 0.092 2 3 0.334 0.347 0.097 0.016 0.023 0.017 0.024 0.016 0.015 0.010 0.033 0.020 0.018 0.022 0.041 0.032 0.029 0.036 0.046 0.039 0.036 0.038 0.031 0.034 0.030 0.033 0.029 0.032 0.040 0.035 0.029 0.029 0.029 0.040 0.025 0.019 0.022 0.016 0.029 0.020 0.031 0.035 0.026 0.033 0.027 0.020 0.038 0.023 0.026 0.033 0.021 0.028 0.020 0.027 0.021 0.029 0.021 0.027 0.021 0.026 0.179 0.038 0.027 0.017 0.046 0.040 0.074 0.114 0.066 0.077 0.054 0.064 0.083 0.147 4 0.334 0.172 0.182 0.008 0.014 0.018 0.022 0.033 0.035 0.035 0.036 0.032 0.031 0.027 0.031 0.030 0.035 0.018 0.015 0.017 0.032 0.032 0.020 0.024 0.038 0.028 0.023 0.024 0.022 0.025 0.033 0.016 0.053 0.117 0.065 0.055 0.112 5 0.335 0.178 0.173 0.060 0.015 0.018 0.024 0.035 0.036 0.033 0.038 0.031 0.031 0.029 0.031 0.031 0.036 0.019 0.013 0.018 0.033 0.037 0.021 0.028 0.041 0.031 0.023 0.024 0.021 0.025 0.029 0.016 0.050 0.112 0.071 0.054 0.122 6 0.347 0.091 0.087 0.151 0.158 0.021 0.019 0.031 0.033 0.034 0.036 0.030 0.031 0.028 0.034 0.028 0.035 0.018 0.015 0.020 0.030 0.029 0.018 0.024 0.028 0.024 0.023 0.024 0.023 0.023 0.034 0.016 0.042 0.087 0.064 0.055 0.099 7 0.345 0.249 0.220 0.173 0.185 0.227 0.029 0.031 0.037 0.040 0.041 0.035 0.034 0.033 0.036 0.032 0.036 0.019 0.019 0.020 0.033 0.044 0.027 0.032 0.058 0.035 0.030 0.030 0.027 0.029 0.041 0.020 0.053 0.088 0.072 0.053 0.104 8 0.346 0.174 0.174 0.169 0.181 0.153 0.224 0.038 0.028 0.047 0.037 0.033 0.029 0.030 0.043 0.028 0.027 0.025 0.022 0.025 0.030 0.025 0.028 0.038 0.029 0.023 0.024 0.024 0.022 0.023 0.176 0.027 0.053 0.086 0.072 0.055 0.087 9 0.251 0.353 0.358 0.345 0.368 0.343 0.354 0.336 0.048 0.041 0.045 0.031 0.033 0.025 0.028 0.027 0.027 0.027 0.030 0.029 0.031 0.047 0.029 0.039 0.051 0.036 0.038 0.039 0.035 0.040 0.095 0.031 0.063 0.110 0.074 0.064 0.115 10 0.418 0.316 0.306 0.321 0.306 0.295 0.343 0.321 0.390 0.058 0.041 0.037 0.046 0.038 0.047 0.040 0.033 0.039 0.030 0.039 0.043 0.038 0.036 0.052 0.040 0.032 0.029 0.029 0.030 0.031 0.352 0.043 0.063 0.092 0.075 0.053 0.112 11 0.392 0.409 0.454 0.396 0.390 0.383 0.456 0.447 0.442 0.483 0.053 0.035 0.041 0.032 0.035 0.036 0.044 0.037 0.034 0.039 0.037 0.070 0.037 0.051 0.082 0.046 0.042 0.042 0.038 0.046 0.121 0.040 0.063 0.112 0.082 0.068 0.132 12 0.506 0.399 0.423 0.405 0.427 0.404 0.463 0.405 0.487 0.461 0.571 0.056 0.048 0.049 0.049 0.048 0.041 0.039 0.039 0.043 0.052 0.055 0.039 0.057 0.055 0.039 0.040 0.037 0.037 0.038 0.107 0.035 0.048 0.096 0.131 0.059 0.100 13 0.272 0.323 0.341 0.318 0.324 0.321 0.346 0.328 0.296 0.411 0.377 0.503 0.021 0.007 0.026 0.024 0.026 0.031 0.033 0.030 0.020 0.036 0.024 0.036 0.031 0.026 0.032 0.030 0.031 0.032 0.085 0.030 0.053 0.076 0.071 0.058 0.092 14 0.299 0.312 0.338 0.330 0.332 0.315 0.365 0.310 0.333 0.468 0.442 0.441 0.244 0.018 0.031 0.027 0.031 0.030 0.032 0.030 0.015 0.037 0.028 0.038 0.036 0.027 0.032 0.033 0.032 0.033 0.080 0.029 0.053 0.080 0.076 0.061 0.092 15 0.249 0.310 0.324 0.282 0.312 0.307 0.326 0.310 0.254 0.428 0.359 0.464 0.057 0.225 0.021 0.019 0.023 0.028 0.029 0.028 0.018 0.032 0.023 0.033 0.029 0.023 0.028 0.028 0.028 0.030 0.083 0.028 0.053 0.077 0.067 0.053 0.088 16 0.312 0.369 0.414 0.346 0.354 0.385 0.395 0.381 0.303 0.413 0.390 0.528 0.221 0.300 0.196 0.035 0.030 0.032 0.032 0.030 0.031 0.047 0.027 0.037 0.046 0.031 0.033 0.036 0.034 0.037 0.066 0.030 0.062 0.123 0.082 0.061 0.116 17 0.290 0.292 0.297 0.306 0.316 0.278 0.337 0.283 0.264 0.416 0.372 0.418 0.257 0.303 0.226 0.350 0.026 0.029 0.031 0.029 0.027 0.036 0.026 0.038 0.034 0.026 0.030 0.028 0.028 0.029 0.078 0.026 0.055 0.093 0.072 0.058 0.087 18 0.257 0.327 0.336 0.316 0.335 0.330 0.319 0.307 0.201 0.378 0.421 0.463 0.254 0.324 0.232 0.278 0.270 0.031 0.037 0.036 0.032 0.035 0.031 0.052 0.033 0.026 0.027 0.024 0.024 0.025 0.215 0.040 0.064 0.086 0.090 0.060 0.101 19 0.342 0.202 0.206 0.180 0.196 0.199 0.200 0.213 0.315 0.337 0.415 0.442 0.320 0.328 0.298 0.383 0.291 0.305 0.021 0.013 0.030 0.031 0.022 0.025 0.038 0.028 0.027 0.029 0.027 0.028 0.039 0.018 0.053 0.100 0.069 0.054 0.120 20 0.331 0.164 0.157 0.143 0.129 0.144 0.192 0.171 0.340 0.260 0.381 0.417 0.318 0.350 0.301 0.360 0.327 0.316 0.202 0.020 0.034 0.034 0.022 0.027 0.034 0.026 0.025 0.027 0.024 0.025 0.036 0.018 0.047 0.099 0.072 0.055 0.122 21 0.339 0.215 0.205 0.174 0.182 0.206 0.234 0.213 0.325 0.351 0.441 0.460 0.306 0.312 0.286 0.370 0.297 0.327 0.121 0.204 0.031 0.030 0.020 0.023 0.037 0.026 0.027 0.027 0.028 0.029 0.036 0.017 0.055 0.108 0.070 0.048 0.138 22 0.311 0.296 0.338 0.336 0.340 0.308 0.360 0.307 0.321 0.463 0.407 0.491 0.227 0.153 0.209 0.309 0.294 0.326 0.318 0.352 0.329 0.037 0.027 0.040 0.036 0.029 0.031 0.033 0.030 0.031 0.108 0.032 0.050 0.076 0.074 0.062 0.103 23 0.391 0.254 0.238 0.208 0.253 0.234 0.307 0.236 0.394 0.380 0.529 0.530 0.323 0.379 0.306 0.406 0.350 0.366 0.235 0.239 0.239 0.381 0.016 0.016 0.010 0.010 0.023 0.022 0.024 0.024 0.113 0.026 0.052 0.137 0.099 0.084 0.149 24 0.329 0.208 0.208 0.193 0.218 0.184 0.260 0.225 0.333 0.326 0.412 0.421 0.240 0.318 0.231 0.323 0.267 0.294 0.224 0.203 0.221 0.294 0.073 0.011 0.009 0.010 0.024 0.023 0.023 0.024 0.033 0.016 0.047 0.094 0.065 0.051 0.114 25 0.399 0.254 0.225 0.230 0.262 0.232 0.308 0.251 0.400 0.405 0.519 0.534 0.310 0.375 0.299 0.392 0.351 0.396 0.247 0.249 0.240 0.388 0.069 0.077 0.018 0.018 0.035 0.032 0.033 0.039 0.031 0.021 0.048 0.248 0.089 0.066 0.225 26 0.371 0.238 0.244 0.235 0.266 0.219 0.338 0.264 0.423 0.396 0.511 0.519 0.286 0.384 0.276 0.407 0.325 0.347 0.266 0.238 0.267 0.358 0.068 0.014 0.079 0.008 0.024 0.024 0.025 0.023 0.124 0.028 0.053 0.129 0.106 0.079 0.147 27 0.336 0.226 0.225 0.197 0.223 0.198 0.269 0.226 0.340 0.349 0.418 0.422 0.259 0.292 0.243 0.310 0.286 0.299 0.230 0.204 0.217 0.313 0.072 0.043 0.088 0.051 0.018 0.019 0.019 0.019 0.100 0.021 0.050 0.074 0.064 0.050 0.090 28 0.325 0.204 0.225 0.188 0.189 0.206 0.249 0.234 0.328 0.310 0.399 0.437 0.312 0.343 0.286 0.304 0.308 0.297 0.227 0.216 0.211 0.333 0.218 0.187 0.236 0.226 0.193 0.008 0.009 0.009 0.147 0.029 0.055 0.090 0.068 0.056 0.093 29 0.349 0.220 0.233 0.201 0.193 0.223 0.248 0.241 0.344 0.313 0.415 0.437 0.314 0.366 0.299 0.332 0.307 0.289 0.235 0.223 0.225 0.348 0.220 0.192 0.229 0.232 0.206 0.070 0.009 0.009 0.196 0.032 0.058 0.085 0.074 0.054 0.100 30 0.308 0.208 0.225 0.185 0.172 0.206 0.241 0.221 0.311 0.304 0.384 0.415 0.304 0.353 0.282 0.306 0.294 0.277 0.220 0.203 0.232 0.315 0.226 0.188 0.235 0.229 0.204 0.068 0.072 0.010 0.125 0.026 0.057 0.078 0.073 0.056 0.091 31 0.335 0.210 0.206 0.197 0.188 0.203 0.236 0.218 0.347 0.315 0.435 0.425 0.322 0.358 0.303 0.330 0.305 0.291 0.224 0.210 0.222 0.331 0.214 0.187 0.240 0.217 0.198 0.071 0.072 0.073 0.172 0.028 0.050 0.085 0.078 0.053 0.099 32 0.425 0.246 0.240 0.188 0.178 0.209 0.254 0.198 0.524 0.456 0.643 0.549 0.384 0.430 0.388 0.427 0.403 0.388 0.242 0.202 0.204 0.522 0.196 0.198 0.183 0.222 0.194 0.266 0.266 0.249 0.264 0.008 0.118 0.975 7.107 2.503 0.370 33 0.316 0.201 0.192 0.167 0.170 0.175 0.205 0.178 0.343 0.335 0.445 0.374 0.302 0.311 0.288 0.345 0.272 0.329 0.183 0.182 0.179 0.329 0.196 0.173 0.206 0.215 0.174 0.222 0.223 0.211 0.217 0.024 0.048 0.126 0.192 0.072 0.114 34 0.561 0.399 0.436 0.507 0.500 0.421 0.561 0.459 0.600 0.542 0.648 0.478 0.545 0.521 0.538 0.607 0.530 0.566 0.501 0.489 0.515 0.520 0.477 0.456 0.462 0.468 0.458 0.511 0.543 0.522 0.476 0.666 0.481 35 0.904 0.738 0.806 0.894 0.858 0.719 0.787 0.832 0.864 0.915 0.884 0.902 0.744 0.756 0.778 0.863 0.879 0.835 0.853 0.800 0.819 0.733 1.140 0.756 1.145 1.094 0.761 0.831 0.819 0.759 0.779 1.450 0.853 1.183 36 0.743 0.636 0.683 0.622 0.647 0.608 0.678 0.670 0.699 0.672 0.749 0.732 0.690 0.739 0.692 0.749 0.699 0.791 0.645 0.659 0.661 0.745 0.810 0.601 0.744 0.822 0.608 0.661 0.708 0.687 0.710 2.488 0.752 1.005 0.995 37 0.651 0.585 0.640 0.589 0.602 0.589 0.596 0.583 0.671 0.570 0.694 0.658 0.632 0.645 0.593 0.638 0.585 0.628 0.576 0.598 0.553 0.670 0.738 0.536 0.618 0.710 0.516 0.618 0.624 0.607 0.588 1.245 0.666 0.786 0.981 0.372 0.182 0.147 0.125 0.080 0.117 0.037 0.235 0.115 0.091 0.085 38 0.915 0.822 0.857 0.823 0.853 0.770 0.860 0.844 0.914 0.980 0.977 0.956 0.886 0.892 0.878 0.895 0.879 0.991 0.885 0.807 0.942 0.977 1.128 0.856 1.143 1.141 0.856 0.927 0.966 0.902 0.944 1.344 0.925 1.357 1.084 0.871 0.824 42 2.3.2 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on CO1 – mtDNA sequences The living nominal genera (19) of Pimelodidae obtained and included in the analysis of CO1 sequences, conformed coherent monophyletic groups (except Pimelodus) supported by high bootstrap values between 98 and 100% (Figure 2.5). The morphologically identified species conformed differentiated groups or clades according to the ML analysis. The species of the Pimelodidae family conformed a monophyletic group supported by a bootstrap value of 56%. Other families of silurids, with a smaller number of species, conformed monophyletic groups with major bootstrap values: 80% (Aspredinidae), 83% (Auchenipteridae and Heptapteridae), 85% (Doradidae) and 91% (Pseudopimelodidae). Within the Pimelodidae family, the relations between genera were poorly supported (bootstrap < 50%). The Phractocephalus genus appeared as the most basal taxa but without relevant support. The only groups with bootstrap values superior to 50% were those formed by Calophysus, Pinirmapus, Pimelodina (51%), Propimelodus, Pimelodus spB (99%), Sorubimichthys, Zungaro (65%), Platysilurus, Platystomatichthys (100%) and B. trigrinum, Sorubim (60%). The species of the Brachyplatystoma genus did not fit into a monophyletic group with a significantly high bootstrap value; the node containing all the species was lower than 50%. Five species of this genus were distributed in two groups with notable bootstrap support. A group supported by a bootstrap of 98%, comprised the species B. juruense and B. platynemum. The other, containing the species B. filamentosum, B. rousseauxii and B. capapretum, had a bootstrap value of 96%. Within this group the relationship between species was not resolved. The remaining species of the Brachyplatystomatini tribe, Platynematichthys and B. vaillantii, were not significantly related to any species or groups that conformed the same genus. Taking into account the information obtained from the analysis of CO1 sequences and external morphologic observations, in Bolivia there seems to be two undescribed species of Sorubim and Pimelodus with affinity to the species S. elongatus and P. blochii, respectively. The null hypothesis of a uniform evolutionary rate throughout the tree, constructed with CO1 sequences, was rejected at a significance level of 5% (P < 6.648 exp - 22). According to the ML method the clock model had a lnL = - 17 839.902 (G = 0.961, I = 0.56) with 189 parameters, and the model without clock a lnL = - 17 628.738 (G = 0.94, I = 0.55) with 367 parameters. The average distance p between taxa of the ingroup (Table 2.3) ranged from 0.131 (Zungaro jahu vs Pseudopimelodus sp.) to 0.362 (Pimelabditus moli vs Farlowella hasemani; P moli vs Farlowella nattereri), and from 0.019 (Pimelodus blochii vs Pimelodus spA) to 0.269 (Pimelabditus moli vs Platystomatichthys sturio) between taxa of the ingroup. Between Zungaro jahu and the taxa of the outgroup distances lower than 0.165 were observed, but it may be due to the sequence used, available in GenBank, which consisted only in a partial fragment of the CO1. 43 Figure 2. 5 Maximum likelihood tree (ML) constructed with PHYML for CO1 sequences of 37 species of Pimelodidae (lnL = 17628.728), under the evolution model GTR + I (0.554) + Γ (α = 0.945). The tree was rooted with species of the family Pseudopimelodidae (12 species), Heptapteridae (7 species), Cetopsidae (2 species), Auchenipteridae (3 species), Doradidae (3 species), Callichthyidae (2 species), Trichomycterdiae (1 species), Nematogenyidae (1 species), Aspredinidae (4 species), Scoloplacidae (1 species), Loricariidae (7 species), Astroblepidae (1 species), Diplomystidae (2 species). The numbers near the nodes represent bootstrap values, and the number between [ ] the number of haplotypes per species. The branch in blue color corresponds to the group that contains the Brachyplatystoma, the branch highlighted in red represents the Plateado (B. rousseauxii). The names with a star indicate that the taxa could represent undescribed species. The names followed by surname (e.g. Cramer, Saitoh, Martin), correspond to sequences obtained from GenBank described in the methods. The image of A. torosus was courtesy of Rey G. (Faunagua). The image of B. capapretum was extracted from Lundberg & Akama (2006), and the image of P. moli from Lundberg & Parisi (2009). 44 Table 2. 3 Average number of substitutions per site (distance p) of all pairs of sequences (CO1) between taxa of Pimelodidae and its outgroups (upper diagonal). The estimated standard error for each comparison is shown in the lower diagonal. The analyses were conducted using the nucleotide substitution model of Tamura-Nei and the rate of variation between sites was modeled with the gamma distribution (shape parameter, α = 0.9). The differences in the composition bias between sequences were considered in the evolutionary comparisons. The analysis considered 180 nucleotide sequences and all the ambiguous positions were removed for each pair of sequences (pairwise deletion). The final matrix consisted of 685 positions. 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 Aguarunichthys_torosus Brachyplatystoma_capapretum Brachyplatystoma_filamentosum Brachyplatystoma_juruense Brachyplatystoma_platynemum Brachyplatystoma_rousseauxii Brachyplatystoma_tigrinum Brachyplatystoma_vaillantii Calophysus_macropterus Hemisorubim_platyrhynchos Hypophthalmus_edentatus Hypophthalmus_marginatus Hypophthalmus_cf._fimbriatus Leiarius_marmoratus Megalonema_platycephalum Phractocephalus_hemiliopterus Pimelabditus_moli Pimelodus_blochii Pimelodina_flavipinnis Pimelodus_ornatus Pimelodus_pictus Pimelodus_spA Pimelodus_spB Pinirampus_pirinampu Platysilurus_mucosus Platynematichthys_notatus Platystomatichthys_sturio Propimelodus_caesius Pseudoplatystoma_fasciatum Pseudoplatystoma_tigrinum Sorubimichthys_planiceps Sorumbim_elongatus Sorubim_lima Sorubim_maniradii Sorubim_sp. Zungaro_jahu Zungaro_zungaro Batrochoglanis_raninus Batrochoglanis_villosus Cephalosilurus_apurensis Lophiosilurus_alexandri Microglanis_cottoides Microglanis_garavelloi Microglanis_leptostriatus Pseudopimelodus_bufonius Pseudopimelodus_charus Pseudopimelodus_mangurus Pseudopimelodus_pulcher Pseudopimelodus_sp. Goediella_eques Pimelodella_sp. Rhamdia_quelen Rhamdia_guatemalensis Rhamdia_sapo Rhamdia_sp._bolivia Rhamdia_sp._brasil Cetopsis_candiru Cetopsidium_soniae Acanthodoras_cataphractus Hemidoras_cf._morrisi Oxydoras_niger Ageneiosus_inermis Ageneiosus_ucayalensis Trachelyopterus_galeatus Callichthys_callichthys Corydoras_rabauti Bunocephalus_verrucosus Hoplomyzon_sexpapilostoma Micromyzon_akamai Pterobunocephalus_sp. Nematogenys_inermis Henonemus_punctatus Scoloplax_distolothrix Astroblepus_sp. Ancistrus_sp. Farlowella_hasemani Farlowella_henriquei Farlowella_nattereri Farlowella_oxyrhyncha Farlowella_platorynchus Farlowella_rugosa Farlowella_smithi Hypostomus_sp. Lamontichthys_filamentosum Loricarichthys_maculatus Loricaria_cf._clavipinna Sturisoma_nigrirostrum Planiloricaria_cryptodon Pseudorinelepis_genibarbis Diplomystes_mesembrinus Diplomystes_nahuelbutaensis 0.020 0.017 0.022 0.021 0.017 0.019 0.018 0.025 0.022 0.026 0.024 0.028 0.021 0.023 0.020 0.025 0.017 0.018 0.026 0.017 0.019 0.017 0.024 0.023 0.020 0.023 0.019 0.021 0.021 0.019 0.021 0.020 0.019 0.020 0.023 0.020 0.027 0.025 0.032 0.033 0.021 0.026 0.023 0.022 0.024 0.024 0.027 0.022 0.024 0.023 0.021 0.027 0.024 0.021 0.028 0.025 0.027 0.027 0.029 0.027 0.029 0.028 0.024 0.029 0.028 0.034 0.037 0.026 0.028 0.030 0.028 0.036 0.028 0.030 0.029 0.029 0.029 0.024 0.029 0.029 0.024 0.029 0.026 0.027 0.026 0.028 0.028 0.030 0.027 0.031 2 3 0.155 0.134 0.029 0.007 0.015 0.016 0.015 0.014 0.007 0.006 0.016 0.016 0.014 0.013 0.021 0.023 0.019 0.019 0.025 0.022 0.020 0.021 0.023 0.022 0.024 0.023 0.023 0.021 0.019 0.018 0.023 0.023 0.018 0.018 0.020 0.018 0.022 0.023 0.018 0.019 0.019 0.018 0.022 0.020 0.024 0.025 0.019 0.018 0.015 0.015 0.019 0.020 0.021 0.020 0.015 0.016 0.016 0.016 0.018 0.017 0.015 0.015 0.014 0.013 0.015 0.015 0.014 0.015 0.020 0.020 0.017 0.015 0.023 0.022 0.027 0.027 0.031 0.033 0.031 0.030 0.023 0.022 0.027 0.029 0.027 0.027 0.025 0.025 0.027 0.025 0.028 0.028 0.022 0.023 0.024 0.025 0.026 0.023 0.026 0.025 0.022 0.022 0.028 0.026 0.026 0.026 0.024 0.025 0.029 0.030 0.026 0.023 0.026 0.026 0.027 0.025 0.024 0.025 0.028 0.027 0.025 0.024 0.026 0.025 0.024 0.023 0.030 0.028 0.025 0.027 0.032 0.033 0.030 0.031 0.028 0.028 0.036 0.035 0.035 0.032 0.031 0.028 0.031 0.031 0.028 0.026 0.031 0.027 0.029 0.030 0.027 0.028 0.029 0.030 0.024 0.025 0.027 0.028 0.027 0.028 0.024 0.025 0.026 0.026 0.025 0.026 0.025 0.026 0.024 0.024 0.026 0.029 0.025 0.027 0.028 0.030 0.030 0.029 0.035 0.033 4 0.168 0.104 0.110 0.010 0.016 0.019 0.014 0.023 0.019 0.023 0.021 0.021 0.023 0.026 0.023 0.027 0.020 0.019 0.020 0.023 0.021 0.021 0.025 0.022 0.020 0.021 0.020 0.016 0.017 0.016 0.018 0.018 0.017 0.017 0.023 0.017 0.025 0.031 0.029 0.029 0.026 0.028 0.032 0.025 0.025 0.027 0.025 0.025 0.028 0.029 0.025 0.030 0.030 0.025 0.033 0.024 0.026 0.028 0.025 0.026 0.027 0.028 0.025 0.030 0.025 0.033 0.034 0.028 0.036 0.035 0.035 0.036 0.029 0.030 0.029 0.030 0.029 0.028 0.030 0.030 0.029 0.026 0.023 0.024 0.026 0.026 0.028 0.029 0.027 0.031 5 0.167 0.101 0.095 0.057 0.015 0.019 0.014 0.025 0.019 0.021 0.020 0.020 0.022 0.024 0.020 0.024 0.020 0.019 0.022 0.022 0.021 0.019 0.023 0.023 0.019 0.020 0.021 0.017 0.017 0.017 0.017 0.018 0.017 0.018 0.024 0.018 0.024 0.029 0.027 0.025 0.023 0.027 0.031 0.024 0.023 0.026 0.023 0.024 0.024 0.026 0.024 0.026 0.028 0.025 0.032 0.023 0.025 0.026 0.023 0.024 0.025 0.028 0.025 0.029 0.024 0.034 0.033 0.027 0.035 0.032 0.031 0.033 0.028 0.028 0.027 0.030 0.027 0.028 0.030 0.030 0.028 0.025 0.024 0.024 0.026 0.027 0.029 0.029 0.029 0.032 6 0.129 0.031 0.023 0.115 0.106 0.015 0.012 0.023 0.019 0.023 0.020 0.022 0.022 0.023 0.017 0.024 0.018 0.019 0.024 0.016 0.018 0.021 0.026 0.017 0.015 0.019 0.020 0.015 0.015 0.016 0.016 0.014 0.016 0.015 0.020 0.015 0.023 0.027 0.032 0.031 0.022 0.027 0.026 0.024 0.026 0.027 0.023 0.024 0.025 0.025 0.022 0.026 0.025 0.024 0.031 0.025 0.026 0.024 0.025 0.028 0.027 0.027 0.023 0.028 0.027 0.034 0.030 0.027 0.034 0.035 0.029 0.032 0.026 0.029 0.028 0.027 0.028 0.025 0.027 0.026 0.025 0.028 0.026 0.027 0.025 0.028 0.026 0.029 0.028 0.031 7 0.152 0.112 0.110 0.135 0.132 0.106 0.017 0.024 0.021 0.022 0.021 0.021 0.022 0.023 0.022 0.026 0.019 0.020 0.023 0.020 0.020 0.022 0.023 0.022 0.019 0.023 0.023 0.018 0.019 0.019 0.015 0.016 0.014 0.016 0.021 0.018 0.026 0.028 0.027 0.029 0.021 0.025 0.026 0.024 0.025 0.027 0.023 0.024 0.024 0.027 0.021 0.027 0.026 0.023 0.027 0.026 0.024 0.026 0.026 0.027 0.028 0.028 0.025 0.029 0.024 0.031 0.032 0.026 0.035 0.037 0.027 0.038 0.027 0.025 0.026 0.030 0.026 0.025 0.030 0.030 0.025 0.023 0.027 0.031 0.030 0.028 0.028 0.025 0.025 0.026 8 0.135 0.090 0.082 0.098 0.097 0.083 0.125 0.023 0.018 0.022 0.019 0.021 0.020 0.023 0.019 0.028 0.018 0.017 0.021 0.020 0.018 0.020 0.024 0.018 0.017 0.019 0.019 0.015 0.016 0.015 0.017 0.015 0.016 0.017 0.019 0.015 0.023 0.024 0.029 0.027 0.019 0.025 0.025 0.025 0.027 0.028 0.028 0.026 0.024 0.024 0.020 0.026 0.023 0.021 0.030 0.026 0.023 0.025 0.024 0.028 0.024 0.028 0.025 0.030 0.025 0.037 0.034 0.029 0.040 0.035 0.029 0.035 0.030 0.029 0.026 0.029 0.026 0.024 0.028 0.028 0.024 0.025 0.023 0.027 0.026 0.023 0.027 0.026 0.026 0.029 9 0.203 0.176 0.189 0.191 0.211 0.191 0.205 0.193 0.026 0.028 0.024 0.023 0.028 0.027 0.026 0.027 0.019 0.019 0.025 0.022 0.020 0.024 0.018 0.026 0.023 0.025 0.026 0.023 0.025 0.025 0.022 0.022 0.022 0.024 0.030 0.024 0.025 0.031 0.026 0.030 0.026 0.028 0.027 0.027 0.031 0.029 0.028 0.028 0.027 0.025 0.023 0.029 0.025 0.024 0.029 0.030 0.024 0.028 0.032 0.029 0.028 0.030 0.026 0.032 0.030 0.032 0.030 0.035 0.036 0.037 0.037 0.034 0.031 0.036 0.030 0.032 0.030 0.029 0.032 0.032 0.029 0.025 0.026 0.028 0.025 0.029 0.027 0.029 0.031 0.034 10 0.190 0.155 0.163 0.151 0.156 0.160 0.162 0.140 0.222 0.020 0.019 0.020 0.024 0.024 0.022 0.025 0.020 0.020 0.024 0.022 0.021 0.023 0.023 0.021 0.020 0.024 0.022 0.020 0.020 0.020 0.022 0.020 0.020 0.021 0.023 0.022 0.025 0.025 0.028 0.029 0.023 0.024 0.028 0.024 0.027 0.024 0.026 0.024 0.029 0.027 0.023 0.030 0.028 0.025 0.030 0.026 0.025 0.032 0.024 0.029 0.026 0.032 0.025 0.031 0.026 0.030 0.030 0.027 0.033 0.031 0.030 0.035 0.027 0.029 0.027 0.031 0.027 0.025 0.031 0.031 0.025 0.028 0.027 0.024 0.024 0.026 0.024 0.027 0.027 0.030 11 0.198 0.177 0.164 0.167 0.157 0.170 0.157 0.162 0.237 0.158 0.013 0.014 0.021 0.023 0.023 0.028 0.022 0.021 0.024 0.024 0.023 0.020 0.023 0.024 0.025 0.029 0.022 0.023 0.024 0.025 0.025 0.024 0.023 0.025 0.025 0.025 0.027 0.027 0.028 0.027 0.026 0.031 0.031 0.021 0.024 0.023 0.026 0.021 0.025 0.028 0.025 0.030 0.029 0.026 0.031 0.028 0.029 0.026 0.025 0.026 0.029 0.035 0.025 0.032 0.026 0.028 0.036 0.031 0.034 0.034 0.028 0.034 0.027 0.027 0.026 0.034 0.026 0.027 0.034 0.033 0.027 0.027 0.030 0.026 0.028 0.026 0.026 0.030 0.028 0.030 12 0.184 0.147 0.152 0.159 0.143 0.146 0.150 0.138 0.203 0.151 0.094 0.014 0.020 0.024 0.022 0.026 0.018 0.020 0.022 0.022 0.019 0.019 0.021 0.021 0.021 0.024 0.018 0.018 0.019 0.020 0.021 0.021 0.020 0.023 0.023 0.020 0.026 0.027 0.024 0.027 0.023 0.028 0.028 0.024 0.025 0.025 0.024 0.024 0.023 0.026 0.024 0.030 0.025 0.025 0.027 0.022 0.025 0.028 0.022 0.024 0.026 0.030 0.023 0.029 0.025 0.030 0.032 0.026 0.031 0.033 0.028 0.030 0.029 0.024 0.023 0.029 0.023 0.025 0.029 0.028 0.025 0.024 0.024 0.023 0.026 0.025 0.027 0.027 0.029 0.031 13 0.214 0.167 0.161 0.154 0.152 0.155 0.167 0.152 0.209 0.156 0.092 0.101 0.019 0.023 0.024 0.029 0.022 0.021 0.023 0.024 0.024 0.023 0.022 0.024 0.024 0.025 0.021 0.020 0.022 0.025 0.023 0.023 0.022 0.024 0.025 0.023 0.026 0.029 0.025 0.026 0.026 0.029 0.035 0.025 0.027 0.027 0.025 0.025 0.024 0.026 0.025 0.028 0.029 0.026 0.031 0.025 0.028 0.028 0.022 0.024 0.026 0.031 0.026 0.028 0.027 0.032 0.033 0.030 0.032 0.037 0.032 0.033 0.030 0.026 0.025 0.029 0.025 0.024 0.029 0.029 0.024 0.026 0.024 0.026 0.026 0.026 0.025 0.027 0.030 0.030 14 0.167 0.188 0.180 0.188 0.179 0.177 0.183 0.155 0.234 0.194 0.169 0.163 0.155 0.025 0.020 0.027 0.023 0.022 0.023 0.023 0.024 0.022 0.028 0.026 0.025 0.027 0.024 0.020 0.022 0.022 0.024 0.025 0.023 0.026 0.023 0.022 0.026 0.031 0.029 0.030 0.025 0.029 0.030 0.029 0.032 0.029 0.030 0.030 0.028 0.026 0.025 0.035 0.031 0.027 0.030 0.026 0.030 0.033 0.025 0.026 0.028 0.033 0.028 0.031 0.028 0.031 0.037 0.030 0.037 0.034 0.031 0.041 0.028 0.028 0.030 0.030 0.030 0.026 0.029 0.029 0.026 0.026 0.030 0.025 0.028 0.026 0.030 0.031 0.028 0.031 15 0.194 0.185 0.165 0.207 0.197 0.183 0.174 0.188 0.228 0.209 0.198 0.200 0.199 0.214 0.022 0.026 0.019 0.020 0.022 0.024 0.019 0.022 0.022 0.023 0.023 0.024 0.023 0.022 0.022 0.022 0.025 0.024 0.022 0.023 0.027 0.025 0.028 0.028 0.036 0.033 0.022 0.027 0.030 0.026 0.028 0.027 0.026 0.026 0.026 0.026 0.023 0.031 0.026 0.025 0.028 0.023 0.028 0.030 0.026 0.026 0.026 0.031 0.027 0.030 0.028 0.035 0.038 0.035 0.037 0.034 0.029 0.033 0.029 0.028 0.031 0.026 0.031 0.029 0.026 0.026 0.029 0.028 0.028 0.028 0.027 0.027 0.030 0.025 0.030 0.033 16 0.159 0.148 0.142 0.172 0.166 0.138 0.179 0.145 0.222 0.180 0.197 0.185 0.197 0.169 0.189 0.027 0.017 0.018 0.024 0.022 0.018 0.022 0.024 0.021 0.022 0.021 0.021 0.020 0.020 0.020 0.023 0.021 0.022 0.022 0.024 0.022 0.022 0.028 0.029 0.027 0.021 0.028 0.025 0.022 0.025 0.024 0.027 0.023 0.023 0.024 0.022 0.027 0.025 0.023 0.033 0.023 0.027 0.028 0.029 0.024 0.028 0.030 0.024 0.030 0.029 0.033 0.033 0.029 0.030 0.036 0.030 0.032 0.025 0.029 0.025 0.029 0.025 0.025 0.029 0.029 0.025 0.027 0.026 0.027 0.026 0.021 0.033 0.026 0.030 0.034 17 0.203 0.202 0.206 0.224 0.201 0.209 0.227 0.233 0.230 0.222 0.245 0.246 0.240 0.234 0.235 0.232 0.023 0.025 0.027 0.026 0.024 0.024 0.027 0.027 0.027 0.031 0.027 0.027 0.026 0.028 0.024 0.024 0.024 0.025 0.027 0.027 0.028 0.030 0.033 0.033 0.025 0.028 0.027 0.024 0.026 0.025 0.027 0.024 0.026 0.029 0.026 0.033 0.030 0.028 0.032 0.032 0.029 0.037 0.031 0.032 0.029 0.033 0.027 0.033 0.031 0.033 0.031 0.031 0.039 0.034 0.029 0.034 0.027 0.032 0.040 0.039 0.040 0.033 0.038 0.038 0.033 0.030 0.030 0.030 0.030 0.035 0.032 0.032 0.033 0.036 18 0.144 0.141 0.134 0.154 0.150 0.133 0.152 0.138 0.162 0.172 0.177 0.143 0.182 0.189 0.158 0.138 0.204 0.015 0.022 0.015 0.005 0.017 0.019 0.021 0.020 0.021 0.019 0.017 0.017 0.020 0.019 0.019 0.018 0.018 0.024 0.019 0.026 0.027 0.028 0.026 0.021 0.025 0.026 0.022 0.024 0.024 0.024 0.023 0.022 0.023 0.021 0.029 0.024 0.023 0.031 0.023 0.022 0.025 0.025 0.023 0.025 0.025 0.022 0.025 0.027 0.034 0.030 0.031 0.032 0.034 0.031 0.033 0.027 0.025 0.024 0.027 0.024 0.025 0.027 0.027 0.025 0.026 0.023 0.027 0.027 0.023 0.028 0.027 0.028 0.034 19 0.135 0.156 0.140 0.148 0.144 0.148 0.160 0.131 0.159 0.170 0.173 0.157 0.170 0.174 0.157 0.143 0.211 0.111 0.022 0.018 0.017 0.019 0.016 0.022 0.020 0.023 0.021 0.018 0.018 0.019 0.020 0.020 0.018 0.019 0.027 0.021 0.021 0.023 0.026 0.025 0.020 0.024 0.028 0.022 0.025 0.024 0.025 0.023 0.025 0.022 0.021 0.027 0.026 0.023 0.029 0.022 0.022 0.025 0.027 0.023 0.025 0.029 0.023 0.030 0.023 0.028 0.028 0.028 0.030 0.031 0.031 0.036 0.027 0.027 0.028 0.031 0.028 0.027 0.031 0.031 0.027 0.022 0.025 0.026 0.026 0.024 0.030 0.027 0.026 0.029 20 0.215 0.183 0.190 0.181 0.194 0.190 0.181 0.181 0.220 0.208 0.214 0.187 0.191 0.184 0.188 0.208 0.228 0.187 0.184 0.020 0.021 0.023 0.026 0.025 0.022 0.028 0.025 0.021 0.022 0.020 0.022 0.022 0.021 0.022 0.026 0.023 0.028 0.032 0.032 0.034 0.025 0.028 0.028 0.027 0.029 0.029 0.029 0.029 0.029 0.029 0.026 0.034 0.029 0.027 0.029 0.027 0.027 0.027 0.026 0.022 0.031 0.031 0.029 0.031 0.031 0.028 0.031 0.037 0.042 0.034 0.031 0.032 0.029 0.031 0.029 0.031 0.029 0.026 0.031 0.031 0.026 0.028 0.026 0.026 0.025 0.026 0.026 0.028 0.036 0.040 21 0.128 0.140 0.139 0.183 0.179 0.118 0.153 0.161 0.178 0.195 0.204 0.177 0.193 0.197 0.204 0.188 0.228 0.107 0.146 0.169 0.016 0.021 0.022 0.025 0.023 0.026 0.021 0.021 0.020 0.020 0.020 0.018 0.017 0.018 0.023 0.020 0.028 0.025 0.031 0.030 0.021 0.025 0.026 0.025 0.028 0.028 0.024 0.025 0.025 0.025 0.021 0.031 0.026 0.023 0.030 0.026 0.026 0.024 0.025 0.024 0.029 0.028 0.025 0.029 0.028 0.033 0.030 0.027 0.034 0.041 0.035 0.033 0.028 0.028 0.030 0.029 0.030 0.026 0.029 0.029 0.025 0.026 0.023 0.030 0.030 0.026 0.027 0.030 0.030 0.031 22 0.155 0.142 0.141 0.163 0.159 0.138 0.159 0.146 0.164 0.180 0.189 0.149 0.200 0.201 0.159 0.155 0.216 0.019 0.127 0.182 0.108 0.018 0.021 0.021 0.020 0.021 0.019 0.018 0.019 0.020 0.020 0.020 0.019 0.019 0.025 0.020 0.025 0.026 0.030 0.028 0.020 0.025 0.024 0.023 0.025 0.026 0.025 0.024 0.023 0.024 0.020 0.030 0.023 0.022 0.030 0.025 0.021 0.027 0.025 0.024 0.026 0.025 0.023 0.025 0.028 0.035 0.029 0.031 0.034 0.035 0.032 0.033 0.028 0.026 0.026 0.028 0.026 0.026 0.028 0.028 0.026 0.027 0.023 0.028 0.027 0.024 0.028 0.026 0.029 0.035 23 0.138 0.174 0.159 0.167 0.146 0.163 0.180 0.151 0.187 0.192 0.165 0.153 0.184 0.175 0.184 0.182 0.216 0.125 0.144 0.205 0.173 0.134 0.025 0.024 0.023 0.023 0.011 0.020 0.021 0.021 0.020 0.020 0.020 0.022 0.025 0.020 0.027 0.029 0.032 0.027 0.024 0.032 0.031 0.022 0.025 0.023 0.026 0.023 0.026 0.026 0.024 0.029 0.026 0.025 0.029 0.026 0.027 0.025 0.028 0.024 0.028 0.026 0.026 0.031 0.027 0.035 0.038 0.028 0.033 0.029 0.028 0.034 0.028 0.030 0.031 0.033 0.031 0.030 0.033 0.033 0.030 0.027 0.027 0.030 0.027 0.028 0.031 0.030 0.029 0.032 24 0.196 0.188 0.195 0.197 0.193 0.204 0.188 0.193 0.124 0.181 0.191 0.176 0.187 0.231 0.191 0.196 0.229 0.169 0.127 0.211 0.185 0.176 0.202 0.026 0.024 0.027 0.023 0.021 0.022 0.026 0.023 0.024 0.024 0.024 0.033 0.025 0.027 0.029 0.025 0.029 0.022 0.027 0.026 0.031 0.032 0.031 0.028 0.031 0.026 0.023 0.023 0.027 0.026 0.025 0.028 0.028 0.028 0.031 0.031 0.031 0.028 0.033 0.025 0.033 0.028 0.027 0.031 0.034 0.034 0.032 0.035 0.038 0.028 0.029 0.029 0.031 0.029 0.027 0.030 0.030 0.027 0.027 0.025 0.028 0.028 0.029 0.029 0.027 0.030 0.031 25 0.181 0.144 0.137 0.175 0.180 0.139 0.168 0.150 0.228 0.180 0.182 0.166 0.185 0.207 0.196 0.176 0.238 0.167 0.182 0.216 0.205 0.173 0.200 0.221 0.019 0.017 0.022 0.020 0.021 0.022 0.021 0.020 0.021 0.020 0.025 0.019 0.027 0.027 0.033 0.034 0.024 0.030 0.028 0.029 0.033 0.031 0.029 0.030 0.022 0.025 0.022 0.026 0.026 0.022 0.028 0.025 0.024 0.029 0.026 0.031 0.026 0.030 0.024 0.033 0.026 0.028 0.028 0.034 0.033 0.033 0.030 0.030 0.027 0.032 0.029 0.030 0.029 0.027 0.030 0.030 0.027 0.027 0.026 0.026 0.021 0.029 0.023 0.026 0.024 0.026 26 0.159 0.108 0.108 0.151 0.139 0.112 0.134 0.125 0.199 0.175 0.197 0.162 0.190 0.199 0.188 0.178 0.232 0.162 0.167 0.191 0.183 0.162 0.197 0.204 0.146 0.022 0.022 0.020 0.021 0.018 0.019 0.019 0.018 0.019 0.023 0.018 0.029 0.031 0.027 0.028 0.024 0.031 0.029 0.028 0.029 0.029 0.029 0.028 0.023 0.028 0.023 0.030 0.027 0.024 0.026 0.026 0.029 0.026 0.029 0.027 0.027 0.029 0.028 0.031 0.029 0.033 0.033 0.033 0.036 0.032 0.030 0.038 0.029 0.029 0.032 0.031 0.032 0.029 0.031 0.031 0.029 0.029 0.027 0.025 0.026 0.029 0.027 0.030 0.028 0.032 27 0.204 0.172 0.174 0.175 0.167 0.169 0.191 0.162 0.224 0.213 0.230 0.200 0.215 0.240 0.217 0.180 0.269 0.178 0.199 0.252 0.221 0.187 0.211 0.232 0.121 0.177 0.022 0.019 0.020 0.020 0.020 0.021 0.021 0.020 0.025 0.020 0.028 0.028 0.033 0.029 0.025 0.032 0.028 0.028 0.031 0.030 0.027 0.029 0.028 0.026 0.023 0.027 0.026 0.023 0.032 0.026 0.025 0.032 0.028 0.029 0.030 0.034 0.029 0.032 0.028 0.034 0.033 0.034 0.037 0.037 0.032 0.030 0.027 0.032 0.029 0.028 0.029 0.025 0.027 0.027 0.025 0.033 0.022 0.026 0.024 0.027 0.026 0.031 0.029 0.033 28 0.160 0.170 0.167 0.157 0.157 0.165 0.192 0.157 0.197 0.193 0.183 0.147 0.176 0.203 0.186 0.178 0.242 0.145 0.165 0.219 0.179 0.145 0.072 0.191 0.196 0.188 0.203 0.020 0.022 0.021 0.022 0.020 0.022 0.022 0.023 0.019 0.026 0.028 0.029 0.026 0.024 0.032 0.028 0.026 0.028 0.028 0.028 0.027 0.024 0.027 0.023 0.029 0.026 0.024 0.027 0.025 0.029 0.029 0.029 0.028 0.028 0.029 0.024 0.032 0.024 0.033 0.041 0.030 0.031 0.032 0.028 0.036 0.029 0.031 0.029 0.032 0.029 0.027 0.032 0.032 0.027 0.027 0.026 0.029 0.028 0.026 0.028 0.028 0.027 0.030 29 0.167 0.111 0.118 0.116 0.124 0.112 0.144 0.110 0.191 0.161 0.169 0.135 0.153 0.160 0.177 0.157 0.238 0.135 0.144 0.187 0.177 0.149 0.159 0.178 0.155 0.164 0.162 0.170 0.006 0.016 0.017 0.015 0.016 0.016 0.021 0.016 0.027 0.027 0.027 0.026 0.023 0.026 0.028 0.025 0.026 0.028 0.024 0.025 0.029 0.024 0.024 0.028 0.027 0.024 0.028 0.023 0.027 0.033 0.023 0.023 0.025 0.029 0.026 0.028 0.027 0.030 0.033 0.031 0.038 0.034 0.034 0.037 0.029 0.030 0.028 0.027 0.028 0.024 0.027 0.026 0.024 0.025 0.025 0.025 0.025 0.023 0.029 0.028 0.027 0.031 30 0.166 0.115 0.120 0.124 0.125 0.113 0.149 0.112 0.207 0.161 0.178 0.140 0.167 0.166 0.175 0.159 0.234 0.135 0.144 0.185 0.172 0.154 0.164 0.188 0.168 0.167 0.174 0.180 0.023 0.017 0.019 0.017 0.016 0.018 0.022 0.016 0.026 0.026 0.028 0.026 0.023 0.026 0.029 0.025 0.026 0.029 0.023 0.026 0.026 0.024 0.023 0.027 0.026 0.024 0.030 0.024 0.028 0.030 0.025 0.023 0.026 0.030 0.026 0.029 0.027 0.031 0.033 0.032 0.039 0.033 0.032 0.034 0.030 0.031 0.030 0.029 0.030 0.026 0.028 0.028 0.026 0.026 0.025 0.026 0.026 0.023 0.032 0.029 0.029 0.032 31 0.144 0.136 0.129 0.124 0.123 0.119 0.141 0.104 0.209 0.166 0.197 0.152 0.192 0.187 0.191 0.173 0.246 0.169 0.152 0.190 0.168 0.169 0.172 0.221 0.183 0.134 0.168 0.164 0.119 0.122 0.017 0.016 0.015 0.018 0.018 0.014 0.026 0.026 0.028 0.024 0.021 0.024 0.023 0.022 0.022 0.023 0.024 0.022 0.028 0.027 0.022 0.030 0.025 0.024 0.029 0.022 0.025 0.027 0.028 0.022 0.025 0.030 0.026 0.032 0.028 0.034 0.031 0.031 0.033 0.032 0.033 0.038 0.026 0.031 0.027 0.030 0.027 0.025 0.030 0.030 0.025 0.027 0.027 0.024 0.027 0.026 0.030 0.029 0.026 0.031 32 0.176 0.110 0.110 0.133 0.129 0.116 0.113 0.130 0.194 0.181 0.187 0.163 0.183 0.189 0.208 0.186 0.222 0.160 0.162 0.195 0.165 0.165 0.166 0.186 0.172 0.148 0.176 0.184 0.131 0.145 0.133 0.009 0.009 0.009 0.021 0.017 0.025 0.028 0.029 0.028 0.022 0.027 0.026 0.023 0.024 0.026 0.021 0.024 0.026 0.025 0.022 0.025 0.027 0.024 0.027 0.023 0.025 0.029 0.028 0.026 0.026 0.030 0.023 0.031 0.026 0.033 0.032 0.026 0.037 0.034 0.032 0.035 0.027 0.030 0.030 0.031 0.030 0.028 0.030 0.030 0.028 0.029 0.025 0.028 0.027 0.027 0.028 0.031 0.026 0.030 33 0.173 0.103 0.104 0.136 0.134 0.108 0.122 0.120 0.200 0.179 0.178 0.164 0.177 0.200 0.204 0.188 0.224 0.157 0.168 0.198 0.152 0.160 0.161 0.202 0.168 0.153 0.196 0.178 0.123 0.139 0.135 0.049 0.007 0.009 0.021 0.017 0.026 0.029 0.028 0.026 0.022 0.027 0.026 0.025 0.026 0.029 0.023 0.025 0.025 0.025 0.022 0.025 0.026 0.023 0.029 0.023 0.027 0.030 0.030 0.027 0.027 0.029 0.025 0.031 0.027 0.035 0.033 0.027 0.040 0.039 0.033 0.033 0.029 0.031 0.030 0.028 0.030 0.026 0.027 0.027 0.026 0.027 0.024 0.028 0.027 0.026 0.029 0.031 0.027 0.030 34 0.157 0.110 0.109 0.127 0.124 0.114 0.101 0.123 0.206 0.173 0.173 0.150 0.177 0.181 0.188 0.186 0.228 0.146 0.141 0.184 0.136 0.151 0.164 0.194 0.167 0.144 0.180 0.186 0.120 0.125 0.122 0.048 0.038 0.008 0.021 0.017 0.025 0.025 0.028 0.025 0.021 0.024 0.027 0.023 0.025 0.027 0.022 0.024 0.026 0.024 0.021 0.026 0.026 0.022 0.026 0.022 0.025 0.027 0.029 0.024 0.027 0.031 0.024 0.029 0.027 0.033 0.032 0.025 0.037 0.036 0.032 0.034 0.026 0.029 0.030 0.027 0.030 0.026 0.027 0.027 0.026 0.026 0.024 0.026 0.028 0.025 0.028 0.031 0.025 0.029 35 0.161 0.108 0.110 0.130 0.138 0.109 0.113 0.128 0.213 0.184 0.184 0.176 0.198 0.202 0.198 0.183 0.241 0.150 0.156 0.193 0.150 0.157 0.187 0.205 0.164 0.144 0.181 0.193 0.128 0.142 0.140 0.055 0.052 0.045 0.023 0.016 0.027 0.029 0.028 0.028 0.022 0.027 0.026 0.025 0.028 0.029 0.023 0.025 0.027 0.026 0.021 0.026 0.025 0.023 0.028 0.023 0.025 0.030 0.029 0.028 0.028 0.029 0.024 0.032 0.027 0.031 0.034 0.028 0.038 0.035 0.034 0.034 0.027 0.032 0.030 0.027 0.030 0.026 0.027 0.027 0.026 0.027 0.025 0.029 0.028 0.028 0.027 0.030 0.027 0.030 36 0.194 0.155 0.158 0.178 0.191 0.155 0.170 0.153 0.255 0.191 0.198 0.183 0.195 0.195 0.230 0.200 0.243 0.203 0.212 0.224 0.183 0.209 0.199 0.258 0.211 0.181 0.214 0.197 0.167 0.176 0.133 0.171 0.173 0.163 0.189 0.013 0.026 0.029 0.026 0.027 0.019 0.024 0.021 0.017 0.019 0.019 0.022 0.017 0.028 0.027 0.023 0.028 0.028 0.027 0.029 0.028 0.030 0.029 0.031 0.031 0.031 0.033 0.026 0.036 0.030 0.033 0.030 0.029 0.041 0.038 0.031 0.042 0.031 0.031 0.029 0.031 0.029 0.028 0.031 0.031 0.028 0.034 0.031 0.030 0.029 0.029 0.027 0.033 0.034 0.035 37 0.167 0.122 0.118 0.126 0.140 0.115 0.140 0.109 0.208 0.182 0.192 0.161 0.184 0.187 0.202 0.174 0.236 0.157 0.172 0.205 0.158 0.168 0.168 0.216 0.151 0.138 0.174 0.160 0.115 0.118 0.105 0.135 0.134 0.129 0.133 0.088 0.028 0.028 0.028 0.029 0.024 0.033 0.027 0.025 0.027 0.028 0.027 0.026 0.026 0.026 0.023 0.028 0.027 0.025 0.031 0.026 0.028 0.027 0.025 0.026 0.028 0.033 0.025 0.033 0.028 0.034 0.032 0.033 0.041 0.036 0.035 0.034 0.031 0.030 0.030 0.029 0.030 0.027 0.029 0.029 0.027 0.030 0.025 0.029 0.026 0.026 0.027 0.028 0.028 0.034 38 0.237 0.207 0.203 0.218 0.217 0.212 0.226 0.210 0.236 0.226 0.241 0.233 0.238 0.240 0.255 0.192 0.272 0.239 0.200 0.252 0.250 0.228 0.248 0.246 0.237 0.241 0.251 0.233 0.227 0.229 0.220 0.221 0.240 0.225 0.241 0.220 0.249 0.018 0.033 0.030 0.017 0.020 0.019 0.023 0.022 0.023 0.021 0.023 0.023 0.024 0.020 0.025 0.022 0.022 0.025 0.029 0.023 0.027 0.024 0.030 0.025 0.025 0.023 0.030 0.029 0.032 0.029 0.028 0.029 0.032 0.027 0.036 0.028 0.031 0.026 0.031 0.026 0.026 0.032 0.032 0.026 0.028 0.028 0.026 0.027 0.028 0.029 0.026 0.030 0.030 39 0.212 0.237 0.245 0.236 0.238 0.241 0.227 0.215 0.261 0.207 0.240 0.229 0.251 0.266 0.259 0.236 0.282 0.234 0.204 0.279 0.218 0.226 0.252 0.248 0.242 0.272 0.245 0.231 0.215 0.219 0.214 0.233 0.240 0.209 0.240 0.248 0.251 0.146 0.031 0.029 0.019 0.022 0.022 0.025 0.027 0.027 0.025 0.026 0.028 0.025 0.021 0.026 0.023 0.023 0.025 0.030 0.026 0.029 0.027 0.030 0.025 0.030 0.025 0.031 0.031 0.029 0.033 0.033 0.031 0.032 0.030 0.035 0.029 0.031 0.034 0.039 0.034 0.032 0.039 0.039 0.032 0.032 0.033 0.033 0.028 0.032 0.032 0.031 0.028 0.029 40 0.266 0.257 0.270 0.231 0.226 0.259 0.210 0.234 0.226 0.232 0.232 0.202 0.209 0.246 0.287 0.245 0.293 0.239 0.211 0.269 0.270 0.257 0.261 0.219 0.260 0.223 0.263 0.261 0.225 0.231 0.227 0.231 0.231 0.226 0.234 0.218 0.245 0.250 0.231 0.019 0.027 0.024 0.025 0.023 0.023 0.024 0.024 0.024 0.026 0.031 0.031 0.032 0.031 0.033 0.035 0.028 0.031 0.033 0.036 0.030 0.028 0.033 0.029 0.039 0.030 0.034 0.034 0.033 0.035 0.035 0.035 0.047 0.030 0.032 0.033 0.033 0.033 0.032 0.033 0.033 0.032 0.031 0.036 0.026 0.031 0.033 0.032 0.037 0.036 0.039 41 0.266 0.241 0.246 0.223 0.206 0.254 0.223 0.228 0.255 0.230 0.219 0.218 0.215 0.252 0.280 0.226 0.278 0.216 0.205 0.270 0.248 0.228 0.228 0.249 0.275 0.224 0.255 0.233 0.224 0.221 0.193 0.230 0.230 0.211 0.241 0.209 0.237 0.230 0.208 0.126 0.028 0.030 0.029 0.020 0.020 0.021 0.020 0.021 0.029 0.034 0.034 0.037 0.034 0.035 0.038 0.027 0.032 0.033 0.038 0.030 0.027 0.034 0.028 0.040 0.036 0.036 0.036 0.035 0.037 0.036 0.033 0.043 0.030 0.040 0.038 0.044 0.038 0.043 0.044 0.044 0.043 0.033 0.039 0.028 0.037 0.034 0.037 0.042 0.041 0.043 42 0.204 0.219 0.220 0.239 0.224 0.222 0.200 0.197 0.265 0.225 0.238 0.224 0.234 0.232 0.225 0.208 0.254 0.212 0.203 0.241 0.203 0.209 0.233 0.221 0.225 0.222 0.247 0.231 0.224 0.220 0.202 0.219 0.220 0.214 0.221 0.183 0.243 0.174 0.177 0.227 0.218 0.013 0.012 0.018 0.021 0.020 0.021 0.019 0.020 0.017 0.012 0.018 0.015 0.015 0.020 0.024 0.024 0.024 0.023 0.024 0.024 0.024 0.022 0.029 0.026 0.026 0.025 0.026 0.030 0.031 0.024 0.034 0.025 0.027 0.027 0.031 0.027 0.026 0.032 0.032 0.026 0.025 0.026 0.028 0.024 0.027 0.026 0.027 0.026 0.026 43 0.221 0.224 0.241 0.242 0.232 0.224 0.213 0.213 0.262 0.210 0.259 0.236 0.241 0.249 0.245 0.225 0.256 0.212 0.205 0.248 0.210 0.210 0.266 0.233 0.264 0.249 0.283 0.264 0.222 0.218 0.211 0.233 0.243 0.219 0.241 0.206 0.289 0.179 0.180 0.196 0.223 0.108 0.014 0.021 0.025 0.024 0.021 0.023 0.030 0.024 0.021 0.026 0.025 0.024 0.026 0.028 0.027 0.031 0.026 0.028 0.029 0.028 0.025 0.031 0.031 0.029 0.028 0.028 0.032 0.036 0.029 0.039 0.027 0.033 0.031 0.037 0.031 0.029 0.037 0.037 0.029 0.027 0.032 0.031 0.031 0.036 0.031 0.030 0.031 0.032 44 0.190 0.223 0.229 0.257 0.252 0.221 0.203 0.217 0.247 0.238 0.254 0.223 0.261 0.247 0.250 0.201 0.261 0.216 0.221 0.244 0.218 0.208 0.250 0.220 0.229 0.232 0.252 0.236 0.222 0.238 0.195 0.228 0.231 0.222 0.225 0.162 0.240 0.159 0.176 0.187 0.211 0.113 0.090 0.021 0.023 0.021 0.019 0.022 0.025 0.026 0.019 0.026 0.022 0.022 0.025 0.036 0.026 0.032 0.028 0.029 0.027 0.025 0.025 0.034 0.030 0.030 0.026 0.028 0.031 0.033 0.030 0.044 0.027 0.031 0.030 0.033 0.030 0.027 0.033 0.033 0.028 0.030 0.031 0.031 0.027 0.030 0.027 0.032 0.034 0.033 45 0.195 0.197 0.210 0.200 0.196 0.206 0.199 0.213 0.240 0.212 0.186 0.200 0.207 0.242 0.235 0.194 0.213 0.189 0.196 0.242 0.212 0.197 0.193 0.255 0.242 0.230 0.240 0.214 0.201 0.210 0.185 0.193 0.209 0.198 0.216 0.141 0.225 0.190 0.192 0.173 0.138 0.161 0.158 0.157 0.007 0.006 0.014 0.003 0.024 0.026 0.023 0.030 0.027 0.025 0.030 0.027 0.026 0.026 0.028 0.029 0.025 0.029 0.026 0.035 0.029 0.032 0.027 0.028 0.033 0.031 0.030 0.036 0.027 0.036 0.034 0.040 0.034 0.031 0.040 0.039 0.031 0.031 0.033 0.026 0.025 0.030 0.029 0.035 0.031 0.032 46 0.204 0.216 0.210 0.197 0.193 0.217 0.209 0.223 0.266 0.234 0.201 0.208 0.216 0.262 0.243 0.213 0.233 0.205 0.212 0.248 0.235 0.208 0.213 0.260 0.266 0.240 0.261 0.225 0.214 0.221 0.191 0.204 0.223 0.218 0.239 0.159 0.243 0.190 0.204 0.174 0.143 0.184 0.190 0.175 0.038 0.008 0.016 0.007 0.024 0.028 0.028 0.033 0.030 0.031 0.030 0.028 0.028 0.027 0.031 0.029 0.026 0.030 0.028 0.034 0.030 0.037 0.030 0.029 0.031 0.033 0.031 0.036 0.031 0.033 0.034 0.041 0.034 0.034 0.041 0.041 0.034 0.035 0.035 0.026 0.029 0.032 0.037 0.037 0.034 0.035 47 0.212 0.220 0.231 0.206 0.212 0.229 0.220 0.229 0.249 0.214 0.196 0.212 0.218 0.248 0.236 0.205 0.229 0.206 0.207 0.247 0.236 0.213 0.201 0.257 0.253 0.229 0.253 0.230 0.226 0.236 0.189 0.210 0.235 0.223 0.244 0.147 0.243 0.188 0.205 0.174 0.141 0.175 0.172 0.154 0.030 0.041 0.015 0.006 0.028 0.029 0.026 0.034 0.028 0.029 0.033 0.029 0.028 0.029 0.030 0.030 0.027 0.030 0.026 0.038 0.030 0.035 0.028 0.030 0.035 0.030 0.030 0.040 0.028 0.036 0.033 0.043 0.033 0.033 0.042 0.042 0.033 0.034 0.033 0.027 0.027 0.032 0.033 0.033 0.032 0.034 48 0.221 0.190 0.195 0.209 0.193 0.192 0.179 0.223 0.237 0.217 0.213 0.181 0.198 0.247 0.224 0.221 0.243 0.200 0.206 0.238 0.205 0.204 0.216 0.239 0.229 0.225 0.228 0.236 0.196 0.187 0.193 0.165 0.194 0.181 0.197 0.178 0.237 0.172 0.178 0.164 0.142 0.180 0.152 0.146 0.097 0.106 0.102 0.015 0.025 0.029 0.026 0.033 0.029 0.028 0.030 0.025 0.027 0.028 0.028 0.028 0.025 0.026 0.025 0.031 0.029 0.032 0.026 0.028 0.032 0.036 0.029 0.030 0.028 0.031 0.035 0.037 0.035 0.034 0.037 0.037 0.034 0.028 0.030 0.023 0.029 0.032 0.031 0.035 0.032 0.033 49 0.194 0.188 0.202 0.190 0.190 0.196 0.198 0.214 0.237 0.205 0.179 0.195 0.203 0.246 0.231 0.194 0.217 0.187 0.196 0.244 0.215 0.198 0.199 0.251 0.240 0.228 0.235 0.211 0.199 0.208 0.182 0.193 0.207 0.195 0.214 0.131 0.220 0.194 0.196 0.173 0.141 0.166 0.166 0.159 0.014 0.033 0.023 0.098 0.025 0.028 0.024 0.030 0.028 0.026 0.031 0.027 0.026 0.027 0.029 0.030 0.026 0.031 0.026 0.036 0.028 0.034 0.028 0.028 0.034 0.031 0.031 0.037 0.028 0.036 0.033 0.040 0.033 0.032 0.039 0.039 0.032 0.033 0.033 0.026 0.025 0.030 0.030 0.036 0.031 0.032 50 0.200 0.208 0.196 0.237 0.205 0.205 0.189 0.194 0.225 0.247 0.208 0.192 0.203 0.229 0.233 0.191 0.233 0.187 0.210 0.244 0.209 0.195 0.225 0.225 0.177 0.178 0.245 0.217 0.240 0.219 0.225 0.217 0.210 0.210 0.228 0.247 0.218 0.204 0.228 0.213 0.229 0.198 0.253 0.211 0.210 0.210 0.231 0.202 0.212 0.019 0.020 0.024 0.022 0.021 0.023 0.026 0.026 0.025 0.026 0.026 0.022 0.027 0.025 0.035 0.031 0.033 0.031 0.033 0.031 0.033 0.025 0.033 0.029 0.031 0.028 0.032 0.028 0.029 0.032 0.032 0.030 0.026 0.025 0.028 0.026 0.026 0.029 0.029 0.028 0.029 51 0.193 0.218 0.218 0.242 0.226 0.215 0.227 0.202 0.231 0.235 0.230 0.223 0.219 0.216 0.236 0.199 0.260 0.209 0.184 0.255 0.218 0.217 0.226 0.200 0.211 0.231 0.230 0.233 0.214 0.212 0.231 0.215 0.222 0.209 0.226 0.241 0.240 0.225 0.217 0.255 0.269 0.169 0.199 0.208 0.226 0.236 0.243 0.223 0.235 0.155 0.016 0.019 0.019 0.018 0.020 0.027 0.025 0.028 0.027 0.028 0.024 0.026 0.024 0.034 0.035 0.032 0.033 0.033 0.032 0.032 0.029 0.032 0.029 0.030 0.028 0.030 0.028 0.027 0.030 0.030 0.027 0.026 0.025 0.030 0.026 0.027 0.028 0.029 0.028 0.030 52 0.192 0.200 0.202 0.223 0.213 0.206 0.191 0.177 0.225 0.206 0.222 0.212 0.225 0.222 0.217 0.206 0.258 0.206 0.196 0.238 0.211 0.202 0.222 0.212 0.196 0.203 0.215 0.216 0.213 0.205 0.205 0.205 0.213 0.198 0.196 0.216 0.221 0.187 0.192 0.251 0.270 0.121 0.190 0.179 0.211 0.229 0.225 0.220 0.212 0.176 0.141 0.014 0.009 0.006 0.015 0.027 0.023 0.025 0.024 0.026 0.025 0.026 0.022 0.030 0.027 0.030 0.030 0.029 0.033 0.034 0.027 0.032 0.029 0.027 0.027 0.032 0.027 0.027 0.032 0.032 0.026 0.026 0.023 0.028 0.025 0.026 0.025 0.028 0.026 0.029 53 0.231 0.233 0.225 0.256 0.225 0.232 0.239 0.232 0.264 0.265 0.248 0.253 0.226 0.286 0.287 0.242 0.309 0.260 0.237 0.290 0.269 0.265 0.260 0.252 0.212 0.263 0.250 0.258 0.247 0.239 0.260 0.227 0.230 0.231 0.228 0.257 0.260 0.242 0.227 0.272 0.286 0.173 0.228 0.227 0.250 0.265 0.283 0.256 0.250 0.208 0.152 0.111 0.014 0.013 0.014 0.034 0.028 0.028 0.033 0.032 0.029 0.032 0.025 0.033 0.033 0.031 0.030 0.033 0.033 0.037 0.032 0.032 0.031 0.035 0.032 0.036 0.032 0.034 0.036 0.036 0.034 0.030 0.027 0.035 0.027 0.036 0.028 0.032 0.030 0.030 54 0.197 0.217 0.218 0.254 0.231 0.215 0.219 0.187 0.225 0.236 0.255 0.204 0.256 0.252 0.240 0.231 0.278 0.218 0.224 0.251 0.231 0.206 0.221 0.236 0.216 0.227 0.236 0.226 0.227 0.214 0.213 0.219 0.231 0.218 0.212 0.250 0.246 0.200 0.194 0.246 0.271 0.141 0.210 0.198 0.230 0.247 0.235 0.232 0.233 0.180 0.145 0.058 0.106 0.010 0.016 0.030 0.024 0.027 0.028 0.031 0.025 0.026 0.023 0.030 0.031 0.029 0.028 0.028 0.031 0.031 0.027 0.033 0.029 0.031 0.030 0.032 0.030 0.031 0.032 0.032 0.031 0.029 0.026 0.031 0.027 0.029 0.028 0.029 0.031 0.032 55 0.182 0.201 0.207 0.215 0.212 0.211 0.194 0.178 0.219 0.206 0.218 0.214 0.223 0.230 0.227 0.211 0.262 0.209 0.205 0.238 0.213 0.200 0.211 0.217 0.187 0.197 0.213 0.198 0.210 0.207 0.211 0.207 0.207 0.195 0.195 0.237 0.225 0.199 0.198 0.271 0.275 0.140 0.207 0.198 0.224 0.257 0.238 0.229 0.226 0.171 0.146 0.041 0.097 0.058 0.016 0.028 0.024 0.027 0.028 0.028 0.026 0.028 0.022 0.031 0.029 0.029 0.032 0.031 0.035 0.034 0.029 0.031 0.029 0.029 0.028 0.033 0.028 0.028 0.033 0.033 0.028 0.026 0.023 0.030 0.025 0.027 0.025 0.028 0.026 0.029 56 0.231 0.244 0.233 0.266 0.256 0.248 0.235 0.246 0.256 0.258 0.265 0.243 0.260 0.266 0.252 0.260 0.295 0.259 0.234 0.258 0.263 0.249 0.244 0.246 0.235 0.224 0.277 0.227 0.241 0.250 0.251 0.223 0.248 0.223 0.227 0.264 0.276 0.225 0.212 0.283 0.282 0.180 0.222 0.209 0.243 0.241 0.265 0.233 0.250 0.193 0.160 0.112 0.092 0.101 0.104 0.030 0.028 0.033 0.030 0.030 0.027 0.028 0.025 0.029 0.035 0.030 0.032 0.031 0.030 0.035 0.032 0.033 0.029 0.032 0.036 0.041 0.036 0.035 0.041 0.041 0.035 0.028 0.026 0.034 0.030 0.037 0.030 0.034 0.029 0.030 57 0.204 0.204 0.189 0.200 0.194 0.199 0.213 0.215 0.246 0.217 0.237 0.175 0.208 0.231 0.201 0.208 0.282 0.212 0.186 0.216 0.220 0.220 0.208 0.223 0.227 0.229 0.249 0.216 0.182 0.196 0.185 0.188 0.198 0.182 0.192 0.241 0.225 0.243 0.247 0.238 0.236 0.233 0.236 0.271 0.226 0.231 0.248 0.203 0.227 0.230 0.240 0.235 0.292 0.249 0.241 0.252 0.022 0.033 0.030 0.025 0.030 0.030 0.022 0.032 0.029 0.034 0.029 0.031 0.036 0.033 0.033 0.034 0.030 0.031 0.028 0.029 0.028 0.028 0.029 0.029 0.028 0.028 0.025 0.027 0.026 0.028 0.030 0.027 0.029 0.033 58 0.238 0.220 0.225 0.231 0.220 0.230 0.213 0.199 0.213 0.220 0.236 0.210 0.237 0.252 0.249 0.242 0.258 0.195 0.201 0.243 0.238 0.195 0.231 0.248 0.222 0.245 0.224 0.257 0.238 0.249 0.225 0.233 0.244 0.225 0.233 0.260 0.262 0.225 0.234 0.253 0.269 0.242 0.247 0.223 0.229 0.236 0.240 0.230 0.225 0.213 0.223 0.229 0.256 0.219 0.224 0.243 0.190 0.033 0.028 0.028 0.025 0.027 0.025 0.031 0.031 0.029 0.028 0.029 0.031 0.034 0.028 0.029 0.029 0.028 0.029 0.027 0.029 0.026 0.027 0.027 0.026 0.024 0.028 0.025 0.025 0.028 0.027 0.024 0.025 0.028 59 0.232 0.224 0.217 0.240 0.231 0.207 0.217 0.224 0.245 0.293 0.225 0.230 0.232 0.268 0.261 0.244 0.311 0.211 0.225 0.245 0.207 0.226 0.212 0.274 0.247 0.219 0.297 0.241 0.279 0.263 0.230 0.247 0.244 0.228 0.251 0.249 0.223 0.245 0.261 0.287 0.261 0.232 0.269 0.266 0.227 0.241 0.242 0.243 0.231 0.211 0.245 0.230 0.250 0.230 0.238 0.266 0.288 0.287 0.029 0.022 0.034 0.031 0.033 0.032 0.034 0.032 0.032 0.033 0.034 0.040 0.033 0.036 0.033 0.035 0.031 0.033 0.031 0.031 0.033 0.033 0.031 0.033 0.032 0.035 0.032 0.033 0.029 0.035 0.032 0.032 60 0.247 0.202 0.207 0.224 0.198 0.205 0.219 0.209 0.293 0.218 0.230 0.197 0.211 0.241 0.242 0.233 0.293 0.216 0.222 0.234 0.227 0.216 0.247 0.269 0.235 0.246 0.267 0.248 0.201 0.215 0.228 0.240 0.257 0.245 0.261 0.258 0.222 0.222 0.235 0.287 0.305 0.229 0.222 0.237 0.256 0.266 0.270 0.235 0.256 0.230 0.243 0.226 0.294 0.252 0.255 0.257 0.256 0.263 0.237 0.021 0.022 0.024 0.031 0.031 0.026 0.033 0.034 0.030 0.034 0.039 0.029 0.036 0.030 0.030 0.029 0.031 0.029 0.030 0.031 0.031 0.030 0.029 0.028 0.026 0.027 0.034 0.031 0.027 0.033 0.036 61 0.240 0.243 0.238 0.228 0.214 0.239 0.234 0.244 0.261 0.276 0.238 0.204 0.223 0.228 0.231 0.216 0.290 0.203 0.203 0.203 0.211 0.210 0.217 0.274 0.287 0.246 0.274 0.240 0.187 0.195 0.202 0.232 0.240 0.206 0.231 0.267 0.237 0.268 0.262 0.253 0.264 0.241 0.243 0.250 0.248 0.245 0.258 0.239 0.258 0.236 0.251 0.249 0.276 0.266 0.252 0.258 0.218 0.259 0.174 0.167 0.025 0.030 0.031 0.030 0.031 0.033 0.036 0.031 0.034 0.037 0.033 0.033 0.030 0.028 0.030 0.033 0.030 0.029 0.034 0.034 0.029 0.032 0.027 0.027 0.030 0.030 0.036 0.031 0.032 0.035 62 0.241 0.215 0.200 0.224 0.218 0.226 0.230 0.212 0.268 0.228 0.247 0.216 0.227 0.241 0.234 0.234 0.256 0.229 0.229 0.264 0.247 0.228 0.235 0.249 0.226 0.234 0.265 0.249 0.212 0.216 0.220 0.231 0.232 0.244 0.251 0.259 0.253 0.234 0.226 0.226 0.215 0.221 0.231 0.220 0.211 0.210 0.222 0.206 0.215 0.199 0.212 0.223 0.241 0.214 0.230 0.220 0.244 0.224 0.257 0.188 0.215 0.014 0.023 0.036 0.035 0.030 0.035 0.031 0.032 0.033 0.031 0.038 0.029 0.029 0.034 0.031 0.034 0.032 0.032 0.031 0.032 0.027 0.028 0.025 0.028 0.029 0.034 0.035 0.028 0.030 63 0.238 0.231 0.211 0.240 0.243 0.221 0.232 0.235 0.277 0.275 0.301 0.258 0.265 0.272 0.270 0.253 0.304 0.223 0.247 0.281 0.236 0.219 0.221 0.292 0.262 0.254 0.303 0.247 0.241 0.249 0.245 0.251 0.243 0.264 0.248 0.287 0.293 0.247 0.260 0.279 0.281 0.239 0.232 0.212 0.248 0.249 0.252 0.226 0.260 0.237 0.239 0.247 0.281 0.233 0.253 0.241 0.253 0.243 0.246 0.211 0.252 0.092 0.027 0.034 0.034 0.033 0.033 0.032 0.035 0.037 0.034 0.042 0.034 0.035 0.034 0.035 0.034 0.033 0.035 0.035 0.034 0.032 0.034 0.031 0.032 0.036 0.038 0.039 0.036 0.036 64 0.217 0.213 0.206 0.227 0.236 0.212 0.219 0.227 0.251 0.238 0.221 0.213 0.241 0.242 0.256 0.220 0.262 0.204 0.211 0.275 0.228 0.209 0.229 0.226 0.231 0.247 0.269 0.220 0.234 0.229 0.232 0.210 0.228 0.224 0.223 0.242 0.236 0.231 0.231 0.262 0.250 0.233 0.237 0.227 0.236 0.245 0.231 0.226 0.232 0.235 0.222 0.219 0.235 0.212 0.211 0.240 0.222 0.241 0.284 0.281 0.287 0.188 0.229 0.033 0.033 0.028 0.030 0.027 0.031 0.027 0.030 0.032 0.026 0.030 0.031 0.031 0.031 0.029 0.032 0.032 0.029 0.027 0.029 0.031 0.029 0.029 0.028 0.033 0.028 0.029 65 0.264 0.283 0.270 0.286 0.290 0.270 0.279 0.280 0.301 0.308 0.293 0.284 0.274 0.299 0.281 0.282 0.311 0.244 0.282 0.299 0.279 0.242 0.295 0.301 0.298 0.292 0.302 0.296 0.259 0.265 0.300 0.306 0.297 0.282 0.297 0.350 0.308 0.298 0.304 0.346 0.363 0.309 0.292 0.311 0.324 0.317 0.335 0.294 0.319 0.318 0.320 0.305 0.331 0.299 0.307 0.304 0.290 0.310 0.291 0.290 0.287 0.335 0.320 0.321 0.029 0.035 0.034 0.033 0.033 0.035 0.032 0.033 0.033 0.030 0.033 0.033 0.033 0.031 0.034 0.034 0.031 0.032 0.031 0.031 0.036 0.034 0.036 0.030 0.034 0.034 66 0.257 0.232 0.240 0.230 0.215 0.242 0.225 0.216 0.266 0.236 0.232 0.216 0.244 0.265 0.267 0.267 0.285 0.238 0.214 0.299 0.248 0.251 0.244 0.248 0.242 0.267 0.272 0.227 0.242 0.246 0.245 0.253 0.263 0.256 0.256 0.281 0.251 0.280 0.288 0.260 0.298 0.261 0.269 0.258 0.257 0.270 0.269 0.257 0.248 0.270 0.296 0.254 0.294 0.279 0.261 0.300 0.259 0.261 0.309 0.257 0.302 0.310 0.304 0.280 0.269 0.032 0.033 0.029 0.037 0.032 0.032 0.039 0.030 0.033 0.031 0.035 0.031 0.034 0.034 0.034 0.034 0.028 0.030 0.027 0.031 0.033 0.029 0.029 0.033 0.035 67 0.280 0.268 0.275 0.274 0.278 0.276 0.251 0.306 0.279 0.271 0.248 0.264 0.283 0.282 0.294 0.260 0.276 0.282 0.241 0.256 0.292 0.292 0.295 0.247 0.244 0.279 0.305 0.276 0.243 0.255 0.289 0.265 0.286 0.269 0.252 0.287 0.277 0.274 0.239 0.271 0.294 0.244 0.254 0.247 0.265 0.294 0.281 0.263 0.270 0.267 0.255 0.252 0.266 0.242 0.235 0.246 0.269 0.248 0.270 0.268 0.267 0.253 0.281 0.240 0.300 0.279 0.029 0.029 0.026 0.035 0.033 0.032 0.029 0.033 0.038 0.035 0.038 0.031 0.034 0.034 0.031 0.032 0.038 0.030 0.028 0.034 0.026 0.035 0.029 0.030 68 0.298 0.255 0.268 0.299 0.289 0.259 0.284 0.295 0.259 0.278 0.309 0.276 0.283 0.319 0.351 0.292 0.273 0.272 0.259 0.275 0.245 0.266 0.321 0.269 0.260 0.289 0.306 0.343 0.280 0.282 0.277 0.272 0.289 0.284 0.296 0.266 0.286 0.268 0.301 0.298 0.297 0.260 0.245 0.237 0.254 0.280 0.260 0.240 0.258 0.280 0.290 0.286 0.278 0.262 0.289 0.273 0.247 0.244 0.302 0.288 0.326 0.293 0.295 0.259 0.319 0.291 0.252 0.024 0.034 0.038 0.035 0.034 0.033 0.037 0.031 0.037 0.031 0.034 0.038 0.038 0.034 0.032 0.033 0.033 0.029 0.038 0.028 0.033 0.031 0.032 69 0.216 0.235 0.233 0.245 0.240 0.225 0.233 0.246 0.292 0.251 0.258 0.222 0.259 0.256 0.305 0.232 0.263 0.253 0.241 0.319 0.232 0.257 0.246 0.298 0.289 0.269 0.298 0.258 0.261 0.271 0.263 0.231 0.246 0.225 0.245 0.258 0.290 0.238 0.292 0.284 0.286 0.257 0.241 0.229 0.244 0.255 0.261 0.240 0.243 0.283 0.275 0.274 0.290 0.259 0.280 0.274 0.260 0.237 0.290 0.263 0.273 0.266 0.277 0.246 0.312 0.261 0.258 0.197 0.027 0.039 0.035 0.034 0.033 0.032 0.033 0.036 0.033 0.034 0.036 0.036 0.034 0.028 0.030 0.030 0.033 0.034 0.037 0.033 0.032 0.032 70 0.247 0.304 0.296 0.304 0.312 0.300 0.298 0.340 0.321 0.299 0.296 0.270 0.288 0.321 0.330 0.245 0.329 0.287 0.271 0.346 0.290 0.303 0.298 0.311 0.291 0.307 0.317 0.280 0.320 0.330 0.282 0.318 0.340 0.316 0.316 0.333 0.339 0.246 0.263 0.297 0.307 0.287 0.289 0.256 0.274 0.274 0.281 0.263 0.276 0.267 0.280 0.299 0.305 0.277 0.298 0.265 0.299 0.262 0.295 0.285 0.315 0.269 0.302 0.275 0.305 0.324 0.206 0.279 0.225 0.036 0.033 0.035 0.029 0.035 0.033 0.037 0.033 0.033 0.037 0.038 0.033 0.036 0.035 0.035 0.036 0.037 0.036 0.038 0.031 0.032 71 0.278 0.324 0.310 0.316 0.307 0.326 0.329 0.314 0.343 0.300 0.300 0.282 0.329 0.320 0.311 0.327 0.322 0.326 0.291 0.309 0.360 0.319 0.268 0.306 0.302 0.292 0.331 0.297 0.314 0.306 0.294 0.320 0.357 0.325 0.325 0.330 0.326 0.297 0.299 0.334 0.335 0.301 0.322 0.284 0.289 0.303 0.281 0.326 0.287 0.302 0.303 0.318 0.345 0.292 0.321 0.316 0.314 0.311 0.363 0.341 0.342 0.291 0.308 0.276 0.314 0.291 0.332 0.361 0.349 0.337 0.035 0.042 0.029 0.039 0.035 0.038 0.035 0.036 0.038 0.038 0.036 0.034 0.036 0.028 0.033 0.034 0.038 0.035 0.034 0.037 72 0.253 0.277 0.262 0.318 0.295 0.259 0.234 0.264 0.334 0.277 0.248 0.250 0.296 0.284 0.278 0.273 0.288 0.276 0.274 0.292 0.311 0.287 0.267 0.311 0.266 0.273 0.283 0.267 0.292 0.277 0.286 0.297 0.307 0.295 0.305 0.288 0.326 0.255 0.274 0.301 0.291 0.253 0.274 0.265 0.270 0.283 0.271 0.253 0.271 0.240 0.260 0.256 0.289 0.241 0.264 0.288 0.283 0.263 0.298 0.266 0.307 0.291 0.293 0.289 0.301 0.291 0.292 0.317 0.325 0.300 0.313 0.038 0.030 0.031 0.032 0.038 0.032 0.034 0.039 0.039 0.034 0.032 0.036 0.033 0.030 0.035 0.032 0.031 0.033 0.034 73 0.325 0.289 0.292 0.340 0.322 0.295 0.338 0.322 0.327 0.319 0.311 0.283 0.310 0.348 0.319 0.296 0.309 0.316 0.338 0.305 0.319 0.323 0.325 0.335 0.282 0.342 0.281 0.331 0.317 0.304 0.339 0.322 0.307 0.319 0.327 0.359 0.315 0.314 0.327 0.384 0.358 0.329 0.330 0.349 0.319 0.330 0.340 0.286 0.326 0.298 0.301 0.320 0.311 0.325 0.298 0.321 0.313 0.269 0.343 0.328 0.316 0.343 0.391 0.328 0.305 0.344 0.287 0.293 0.295 0.313 0.367 0.339 0.035 0.035 0.043 0.038 0.043 0.039 0.038 0.038 0.039 0.029 0.037 0.032 0.033 0.042 0.034 0.035 0.033 0.033 74 0.271 0.259 0.253 0.288 0.279 0.259 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0.336 0.340 0.337 0.336 0.304 0.314 0.263 0.218 0.115 0.016 0.015 0.001 0.001 0.015 0.026 0.018 0.026 0.028 0.016 0.027 0.030 0.033 0.035 78 0.276 0.244 0.256 0.255 0.235 0.248 0.230 0.239 0.280 0.247 0.230 0.212 0.224 0.280 0.293 0.234 0.362 0.231 0.244 0.265 0.274 0.243 0.276 0.265 0.259 0.278 0.255 0.271 0.246 0.262 0.248 0.257 0.256 0.253 0.263 0.272 0.265 0.250 0.289 0.291 0.328 0.270 0.285 0.262 0.294 0.312 0.296 0.294 0.285 0.241 0.258 0.266 0.293 0.266 0.262 0.303 0.247 0.264 0.279 0.263 0.280 0.295 0.305 0.305 0.313 0.270 0.303 0.305 0.311 0.298 0.303 0.272 0.361 0.259 0.226 0.000 0.115 0.012 0.016 0.016 0.012 0.028 0.018 0.027 0.024 0.018 0.026 0.025 0.031 0.035 79 0.227 0.201 0.217 0.247 0.235 0.211 0.212 0.206 0.261 0.218 0.221 0.203 0.207 0.238 0.268 0.225 0.305 0.232 0.228 0.234 0.231 0.240 0.267 0.244 0.232 0.257 0.218 0.253 0.213 0.228 0.227 0.251 0.238 0.229 0.241 0.249 0.243 0.245 0.272 0.272 0.341 0.259 0.260 0.239 0.262 0.290 0.279 0.284 0.262 0.245 0.240 0.255 0.294 0.277 0.259 0.299 0.242 0.231 0.279 0.265 0.267 0.273 0.291 0.297 0.301 0.279 0.264 0.320 0.300 0.294 0.309 0.274 0.314 0.252 0.227 0.080 0.106 0.080 0.015 0.015 0.001 0.027 0.017 0.029 0.022 0.016 0.022 0.030 0.028 0.031 80 0.266 0.231 0.245 0.263 0.265 0.235 0.240 0.242 0.281 0.267 0.271 0.241 0.258 0.263 0.248 0.252 0.343 0.251 0.266 0.276 0.269 0.263 0.282 0.270 0.257 0.264 0.243 0.280 0.221 0.242 0.260 0.258 0.238 0.241 0.244 0.281 0.253 0.291 0.317 0.279 0.334 0.297 0.316 0.277 0.321 0.345 0.337 0.302 0.313 0.270 0.270 0.295 0.319 0.290 0.287 0.341 0.258 0.247 0.300 0.288 0.314 0.281 0.297 0.315 0.320 0.291 0.278 0.339 0.342 0.340 0.338 0.307 0.312 0.265 0.220 0.116 0.001 0.116 0.108 0.001 0.015 0.027 0.018 0.026 0.028 0.016 0.027 0.030 0.034 0.036 81 0.265 0.230 0.244 0.264 0.264 0.234 0.238 0.241 0.283 0.268 0.270 0.240 0.256 0.264 0.247 0.253 0.342 0.250 0.264 0.274 0.268 0.262 0.281 0.271 0.256 0.265 0.244 0.281 0.220 0.241 0.261 0.257 0.237 0.240 0.243 0.282 0.255 0.292 0.319 0.280 0.335 0.297 0.314 0.278 0.319 0.344 0.338 0.301 0.312 0.269 0.269 0.295 0.317 0.288 0.288 0.340 0.256 0.246 0.298 0.286 0.312 0.280 0.295 0.317 0.319 0.289 0.276 0.337 0.341 0.341 0.339 0.305 0.313 0.264 0.221 0.115 0.001 0.115 0.107 0.001 0.015 0.027 0.018 0.026 0.028 0.016 0.027 0.030 0.034 0.036 82 0.230 0.202 0.218 0.249 0.237 0.214 0.215 0.208 0.259 0.219 0.223 0.204 0.208 0.241 0.270 0.225 0.309 0.233 0.230 0.235 0.230 0.239 0.268 0.242 0.234 0.258 0.220 0.252 0.214 0.231 0.229 0.253 0.239 0.232 0.243 0.251 0.245 0.246 0.273 0.274 0.344 0.260 0.262 0.241 0.264 0.292 0.281 0.284 0.263 0.245 0.241 0.254 0.295 0.278 0.257 0.300 0.242 0.233 0.280 0.264 0.269 0.276 0.292 0.298 0.303 0.280 0.266 0.321 0.302 0.292 0.311 0.276 0.317 0.252 0.229 0.079 0.108 0.079 0.003 0.109 0.108 0.027 0.017 0.029 0.023 0.016 0.022 0.030 0.028 0.031 83 0.256 0.228 0.230 0.243 0.227 0.239 0.189 0.221 0.233 0.247 0.236 0.223 0.231 0.237 0.258 0.241 0.263 0.225 0.197 0.266 0.234 0.233 0.230 0.241 0.235 0.249 0.289 0.240 0.236 0.257 0.244 0.260 0.242 0.237 0.244 0.301 0.255 0.265 0.278 0.268 0.274 0.247 0.237 0.271 0.263 0.290 0.282 0.245 0.271 0.229 0.244 0.258 0.288 0.265 0.250 0.262 0.253 0.209 0.292 0.250 0.287 0.258 0.301 0.269 0.309 0.239 0.280 0.297 0.271 0.321 0.310 0.287 0.268 0.249 0.164 0.230 0.215 0.230 0.213 0.217 0.216 0.214 0.024 0.021 0.029 0.027 0.029 0.028 0.028 0.030 84 0.243 0.216 0.230 0.205 0.209 0.229 0.229 0.208 0.234 0.248 0.247 0.202 0.214 0.271 0.254 0.232 0.277 0.209 0.221 0.234 0.209 0.204 0.239 0.221 0.232 0.235 0.200 0.245 0.219 0.230 0.251 0.219 0.217 0.216 0.239 0.283 0.231 0.258 0.289 0.303 0.310 0.253 0.271 0.275 0.282 0.301 0.292 0.253 0.281 0.218 0.224 0.230 0.251 0.230 0.220 0.226 0.219 0.254 0.273 0.242 0.250 0.243 0.294 0.289 0.290 0.252 0.324 0.307 0.294 0.319 0.309 0.298 0.335 0.257 0.239 0.138 0.147 0.138 0.131 0.149 0.148 0.130 0.195 0.024 0.022 0.015 0.023 0.028 0.027 0.030 45 85 0.240 0.212 0.217 0.217 0.208 0.229 0.252 0.226 0.240 0.215 0.223 0.191 0.211 0.215 0.251 0.240 0.270 0.244 0.233 0.249 0.270 0.247 0.262 0.252 0.221 0.217 0.239 0.257 0.209 0.220 0.220 0.260 0.260 0.249 0.279 0.264 0.264 0.228 0.279 0.222 0.240 0.257 0.262 0.253 0.228 0.229 0.238 0.204 0.220 0.240 0.256 0.241 0.291 0.257 0.250 0.278 0.230 0.212 0.315 0.239 0.249 0.221 0.277 0.279 0.294 0.216 0.269 0.302 0.268 0.311 0.262 0.279 0.285 0.239 0.209 0.210 0.199 0.210 0.205 0.197 0.196 0.208 0.179 0.186 0.021 0.024 0.027 0.033 0.032 0.036 86 0.230 0.201 0.195 0.231 0.223 0.206 0.246 0.216 0.227 0.238 0.239 0.220 0.221 0.248 0.244 0.242 0.278 0.237 0.239 0.229 0.263 0.241 0.240 0.262 0.188 0.216 0.214 0.248 0.224 0.230 0.227 0.243 0.251 0.246 0.259 0.261 0.249 0.252 0.253 0.266 0.298 0.252 0.270 0.248 0.226 0.261 0.248 0.244 0.220 0.230 0.238 0.245 0.254 0.245 0.234 0.258 0.226 0.222 0.290 0.253 0.291 0.250 0.272 0.295 0.330 0.260 0.253 0.271 0.295 0.317 0.312 0.263 0.294 0.256 0.239 0.190 0.202 0.190 0.166 0.201 0.200 0.167 0.230 0.170 0.154 87 0.241 0.213 0.238 0.231 0.229 0.230 0.225 0.196 0.256 0.235 0.223 0.203 0.229 0.232 0.247 0.204 0.310 0.208 0.212 0.232 0.218 0.214 0.246 0.258 0.244 0.238 0.238 0.236 0.202 0.200 0.221 0.241 0.234 0.224 0.245 0.251 0.227 0.246 0.266 0.288 0.271 0.252 0.293 0.248 0.255 0.280 0.273 0.268 0.256 0.227 0.243 0.249 0.306 0.262 0.240 0.297 0.238 0.254 0.295 0.288 0.273 0.248 0.302 0.283 0.311 0.266 0.280 0.333 0.305 0.318 0.292 0.285 0.346 0.268 0.207 0.124 0.110 0.124 0.115 0.109 0.108 0.117 0.217 0.106 0.171 0.183 88 0.246 0.217 0.235 0.245 0.255 0.222 0.240 0.235 0.244 0.237 0.227 0.234 0.226 0.270 0.272 0.269 0.288 0.242 0.265 0.240 0.244 0.243 0.271 0.249 0.197 0.236 0.236 0.255 0.244 0.263 0.268 0.251 0.262 0.244 0.235 0.261 0.243 0.282 0.283 0.293 0.322 0.258 0.272 0.241 0.263 0.314 0.286 0.264 0.261 0.243 0.237 0.239 0.256 0.255 0.227 0.257 0.256 0.245 0.267 0.279 0.316 0.296 0.325 0.279 0.352 0.254 0.228 0.260 0.315 0.325 0.345 0.290 0.302 0.258 0.290 0.205 0.206 0.205 0.171 0.204 0.203 0.172 0.229 0.185 0.189 0.110 0.222 89 0.266 0.240 0.260 0.261 0.269 0.250 0.218 0.246 0.266 0.240 0.260 0.236 0.238 0.276 0.240 0.231 0.283 0.248 0.249 0.252 0.279 0.249 0.269 0.235 0.250 0.259 0.276 0.257 0.251 0.261 0.261 0.273 0.275 0.279 0.266 0.289 0.262 0.256 0.268 0.310 0.342 0.269 0.276 0.276 0.298 0.320 0.283 0.306 0.300 0.267 0.259 0.268 0.287 0.271 0.259 0.309 0.247 0.222 0.324 0.274 0.293 0.310 0.340 0.295 0.289 0.277 0.308 0.300 0.283 0.315 0.304 0.272 0.318 0.296 0.259 0.219 0.243 0.219 0.242 0.245 0.246 0.244 0.230 0.244 0.264 0.232 0.238 0.241 90 0.251 0.262 0.257 0.241 0.249 0.246 0.226 0.228 0.293 0.229 0.240 0.254 0.264 0.265 0.284 0.268 0.300 0.269 0.250 0.303 0.267 0.269 0.266 0.274 0.234 0.263 0.280 0.245 0.230 0.239 0.240 0.245 0.246 0.232 0.243 0.300 0.248 0.279 0.245 0.313 0.338 0.274 0.283 0.288 0.275 0.293 0.282 0.276 0.267 0.250 0.251 0.267 0.287 0.284 0.251 0.266 0.251 0.234 0.298 0.288 0.305 0.261 0.320 0.267 0.296 0.290 0.250 0.291 0.286 0.277 0.303 0.305 0.287 0.280 0.306 0.264 0.263 0.264 0.228 0.265 0.263 0.230 0.248 0.228 0.268 0.234 0.215 0.222 0.250 0.025 0.015 0.028 0.028 0.029 0.029 0.027 0.026 0.025 0.027 0.027 0.028 0.026 0.029 0.005 91 0.272 0.282 0.276 0.275 0.274 0.264 0.238 0.253 0.312 0.244 0.250 0.270 0.264 0.288 0.297 0.293 0.319 0.311 0.277 0.323 0.278 0.312 0.287 0.289 0.255 0.278 0.301 0.265 0.257 0.263 0.266 0.270 0.262 0.254 0.260 0.307 0.290 0.276 0.259 0.327 0.348 0.279 0.300 0.288 0.286 0.302 0.294 0.283 0.277 0.263 0.264 0.279 0.289 0.291 0.264 0.275 0.279 0.257 0.289 0.306 0.321 0.274 0.313 0.273 0.300 0.307 0.258 0.292 0.285 0.286 0.322 0.311 0.284 0.296 0.314 0.287 0.275 0.287 0.242 0.277 0.276 0.243 0.263 0.252 0.292 0.233 0.235 0.227 0.262 0.018 The distances between Z. zungaro, sister species of Z. jahu, and the outgroup taxa were superior to 0.21. The species of the Brachyplatystoma genus had distances ranging from 0.023 (B. filamentosum vs B rousseauxii) to 0.135 (B. juruense vs B. rousseauxii) (Table 2.3). 2.3.3 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on Freticulon-4 – nDNA squences The 18 living nominal genera of the Pimelodidae family included in the analysis of the sequences of Freticulon-4, conformed coherent monophyletic groups supported by high bootstrap values ranging from 94 to 100% (Figure 2.6). The morphologically identified species coincided with groups or clades obtained with the ML analysis. The Pimelodidae family conformed a monophyletic group supported by a high bootstrap value (90%). Heptapteridae and Auchenipteridae families also formed monophyletic groups with supports of 100%. Leiarius was the most basal taxa (bootstrap 86%) to the remaining group of genera within the Pimelodidae family, which itself had Phractocephalus as the most basal species (bootstrap 78%). This group in turn was divided into two clades. One of the clades (bootstrap 94%) was formed by species of the genera Megalonema, Pimelodus, Aguarunichthys, Pimelodina, Pinirampus and Calophysus. The position of Megalonema was not resolved, and the Pimelodina + (Pinirampus + Calophysus) group (bootstrap 97%) appeared as sister group of Aguarunichthys (bootstrap 59%). The other clade (bootstrap 79%) had Zungaro near the base with an uncertain position of the Sorubim (bootstrap 50%). The remaining group of genera was supported by a branch with a bootstrap value of 61% and comprised two small groups: Sorubimichthys + Pseudoplatystoma (bootstrap 88%), and Platysilurus + Platystomatichthys (bootstrap 100%). The species of the Platynematichthys and Brachyplatystoma genera were associated in small groups with high supports (bootstrap 100%), but collectively did not conform a robust monophyletic group. The groups were conformed by B. juruense + B. platynemum, B. vaillantii + Platynematichthys, and by B. rousseauxii + (B filamentosum + B capapretum). B. tigrinum had an uncertain position in relation to the other groups of species of the genus (Figure 2.6). The null hypothesis of uniform evolutionary rate through the tree, constructed with the Freticulon-4 sequences, was rejected at a significance level of 5% (P < 4.644 exp - 21). According to the ML method the clock model had a lnL = -13 716.58 (G = 1667, I = 0.31) with 126 parameters and the model without clock a lnL = -13 557.158 (G = 1.66, I = 0.31) with 241 parameters. The average values of distance p between the pairwise sequences ranged from 0.169 (Sorubimichthys planiceps vs Goediella eques) to 0.353 (Zungaro zungaro vs Hypostomus sp.), between in- and outgroup taxa, and from 0.005 (B. juruense vs B. platynemum) to 0.11 (Hypophthalmus edentatus vs Megalonema platycephalum) between the taxa of ingroup. Within the Brachyplatystoma genus, the greatest distance (0.04) was observed between B. platynemum vs B. tigrinum (Table 2.4). 46 Figure 2. 6 Maximum likelihood tree (ML) constructed with PHYML for the Freticulon-4 sequences of 32 species of Pimelodidae (lnL = - 13 557.170), considering the evolution model GTR + I (0.313) + Γ (α = 1.721). The families Heptapteridae (Goediella eques, Rhamdia cf. Quelen, Pimelodella sp.), Auchenipteridae (Ageneiosus inermis, Trachelyopterus galeatus) Loricariidae (Hypostomus sp.) were used like outgroups. The numbers near the nodes represent the bootstrap values and numbers between [ ] the number of haplotypes per species. The branch in blue color corresponds to the group that contains the Brachyplatystoma, the branch highlighted in red to Plateado (B. rousseauxii). The names followed by a star indicate that the taxa might represent undescribed species. The image of A. torosus was provided by Rey G. (Faunagua), and the image of B. capapretum was extracted from Lundberg & Akama (2006). 47 Table 2. 4 Average number of substitutions per site (distance p) of all pairwise comparisons of sequences (Freticulon-4) between the taxa of Pimelodidae and the outgroups (upper diagonal). The estimated standard error for each comparison is shown in the lower diagonal. The analyses were conducted using the nucleotide substitution model of Tamura-Nei and the rate of variation between sites was modeled with the gamma distribution (shape parameter, α = 1.7). The differences in the composition bias between sequences were considered in the evolutionary comparisons. The analysis took into account 117 nucleotide sequences and all the ambiguous positions were removed for each pair of sequences (pairwise deletion). The final matrix consisted of 2266 positions. 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 Aguarunichthys_torosus Brachyplatystoma_filamentosum Brachyplatystoma_capapretum Brachyplatystoma_juruense Brachyplatystoma_platynemum Brachyplatystoma_rousseauxii Brachyplatystoma_tigrinum Brachyplatystoma_vaillantii Calophysus_macropterus Hemisorubim_platyrhynchos Hypophthalmus_edentatus Hypophthalmus_marginatus Hypophthalmus_cf._fimbriatus Leiarius_marmoratus Megalonema_platycephalum Phractocephalus_hemiliopterus Pimelodina_flavipinnis Pimelodus_blochii Pimelodus_pictus Pimelodus_spA Pinirampus_pirinampu Platynematichthys_notatus Platysilurus_mucosus Platystomatichthys_sturio Pseudoplatystoma_fasciatum Pseudoplatystoma_tigrinum Sorubimichthys_planiceps Sorubim_lima Sorubim_maniradii Sorubim_sp. Zungaro_zungaro Goediella_eques Pimelodella_sp. Rhamdia_quelen Ageneiosus_inermis Trachelyopterus_galeatus Hypostomus_sp. 0.006 0.007 0.007 0.007 0.006 0.007 0.006 0.006 0.007 0.008 0.008 0.008 0.007 0.009 0.007 0.006 0.006 0.007 0.007 0.006 0.006 0.007 0.007 0.006 0.006 0.006 0.007 0.007 0.007 0.006 0.015 0.016 0.017 0.014 0.015 0.024 2 3 0.060 0.061 0.006 0.002 0.005 0.005 0.005 0.005 0.002 0.002 0.004 0.004 0.003 0.004 0.006 0.006 0.005 0.005 0.005 0.005 0.006 0.006 0.005 0.005 0.006 0.006 0.008 0.008 0.006 0.006 0.006 0.006 0.005 0.005 0.007 0.007 0.007 0.007 0.006 0.006 0.004 0.004 0.005 0.005 0.006 0.005 0.005 0.005 0.004 0.005 0.004 0.004 0.005 0.005 0.005 0.005 0.005 0.005 0.004 0.004 0.013 0.013 0.015 0.015 0.016 0.016 0.013 0.014 0.014 0.014 0.021 0.021 4 0.064 0.030 0.032 0.002 0.005 0.005 0.005 0.007 0.006 0.006 0.006 0.006 0.006 0.009 0.006 0.006 0.006 0.007 0.007 0.007 0.005 0.005 0.006 0.005 0.005 0.004 0.006 0.006 0.006 0.006 0.013 0.014 0.015 0.013 0.014 0.022 5 0.065 0.032 0.035 0.005 0.005 0.005 0.005 0.007 0.006 0.006 0.006 0.006 0.006 0.009 0.006 0.006 0.006 0.007 0.007 0.007 0.005 0.006 0.006 0.006 0.005 0.005 0.006 0.006 0.006 0.006 0.013 0.015 0.015 0.013 0.014 0.022 6 0.060 0.006 0.009 0.031 0.033 0.004 0.004 0.006 0.005 0.005 0.006 0.005 0.006 0.008 0.006 0.006 0.005 0.007 0.007 0.006 0.004 0.005 0.006 0.005 0.004 0.004 0.005 0.005 0.005 0.004 0.013 0.016 0.016 0.014 0.014 0.021 7 0.072 0.027 0.028 0.035 0.040 0.027 0.005 0.006 0.006 0.006 0.006 0.006 0.006 0.009 0.006 0.006 0.006 0.007 0.007 0.006 0.004 0.006 0.006 0.006 0.005 0.005 0.006 0.006 0.006 0.005 0.014 0.016 0.016 0.013 0.013 0.020 8 0.061 0.019 0.021 0.032 0.035 0.020 0.030 0.006 0.005 0.005 0.006 0.005 0.006 0.008 0.006 0.006 0.006 0.007 0.007 0.006 0.003 0.005 0.005 0.005 0.005 0.004 0.005 0.005 0.005 0.004 0.013 0.016 0.016 0.013 0.013 0.022 9 0.062 0.055 0.058 0.060 0.063 0.056 0.064 0.057 0.006 0.007 0.007 0.007 0.007 0.008 0.007 0.005 0.005 0.007 0.007 0.003 0.006 0.007 0.007 0.006 0.006 0.006 0.007 0.006 0.006 0.006 0.014 0.015 0.017 0.014 0.015 0.022 10 0.064 0.038 0.040 0.040 0.042 0.036 0.046 0.039 0.066 0.006 0.006 0.006 0.007 0.008 0.006 0.006 0.006 0.007 0.007 0.007 0.005 0.006 0.006 0.006 0.005 0.005 0.006 0.006 0.006 0.005 0.014 0.016 0.015 0.013 0.013 0.022 11 0.081 0.040 0.042 0.052 0.054 0.042 0.053 0.043 0.076 0.053 0.003 0.002 0.007 0.008 0.007 0.007 0.007 0.007 0.008 0.007 0.006 0.006 0.007 0.006 0.006 0.005 0.006 0.006 0.006 0.006 0.013 0.015 0.016 0.013 0.014 0.022 12 0.082 0.041 0.043 0.053 0.055 0.043 0.054 0.045 0.077 0.054 0.015 0.003 0.007 0.009 0.007 0.007 0.007 0.008 0.008 0.008 0.006 0.007 0.007 0.007 0.006 0.006 0.007 0.006 0.007 0.006 0.014 0.016 0.016 0.014 0.013 0.022 13 0.081 0.040 0.042 0.052 0.055 0.041 0.053 0.043 0.076 0.052 0.010 0.017 0.007 0.008 0.007 0.007 0.007 0.007 0.008 0.007 0.006 0.006 0.007 0.006 0.006 0.005 0.006 0.006 0.006 0.006 0.014 0.015 0.016 0.013 0.014 0.022 14 0.067 0.048 0.050 0.054 0.057 0.050 0.056 0.051 0.066 0.057 0.066 0.065 0.065 0.008 0.006 0.006 0.006 0.007 0.008 0.007 0.006 0.007 0.007 0.006 0.006 0.006 0.007 0.006 0.006 0.006 0.013 0.015 0.016 0.012 0.013 0.022 15 0.101 0.086 0.090 0.093 0.097 0.087 0.092 0.093 0.091 0.096 0.108 0.110 0.107 0.097 0.009 0.008 0.008 0.009 0.009 0.008 0.008 0.009 0.009 0.008 0.008 0.008 0.009 0.008 0.008 0.009 0.015 0.017 0.017 0.014 0.015 0.023 16 0.070 0.042 0.047 0.048 0.051 0.046 0.055 0.046 0.059 0.056 0.063 0.062 0.062 0.048 0.094 0.006 0.006 0.007 0.007 0.007 0.006 0.006 0.007 0.006 0.006 0.005 0.006 0.006 0.006 0.006 0.013 0.015 0.016 0.013 0.013 0.022 17 0.067 0.054 0.055 0.059 0.062 0.054 0.062 0.054 0.043 0.061 0.070 0.070 0.071 0.065 0.081 0.060 0.005 0.007 0.007 0.005 0.006 0.007 0.007 0.005 0.005 0.005 0.006 0.005 0.006 0.006 0.014 0.016 0.016 0.014 0.014 0.023 18 0.071 0.055 0.057 0.063 0.066 0.055 0.064 0.060 0.063 0.062 0.076 0.077 0.076 0.068 0.091 0.064 0.062 0.005 0.003 0.006 0.006 0.006 0.006 0.006 0.006 0.005 0.006 0.006 0.006 0.006 0.013 0.015 0.015 0.012 0.013 0.020 19 0.075 0.059 0.062 0.066 0.070 0.060 0.070 0.063 0.066 0.067 0.078 0.079 0.076 0.067 0.086 0.065 0.068 0.050 0.006 0.007 0.007 0.007 0.008 0.007 0.007 0.007 0.007 0.007 0.008 0.007 0.013 0.016 0.016 0.013 0.014 0.021 20 0.079 0.059 0.062 0.068 0.072 0.059 0.068 0.064 0.067 0.068 0.082 0.081 0.081 0.072 0.096 0.067 0.065 0.033 0.044 0.007 0.007 0.008 0.008 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.015 0.016 0.017 0.013 0.014 0.020 21 0.063 0.056 0.058 0.062 0.065 0.057 0.063 0.056 0.015 0.065 0.075 0.076 0.075 0.065 0.090 0.061 0.044 0.063 0.065 0.066 0.007 0.007 0.007 0.006 0.006 0.006 0.007 0.006 0.006 0.006 0.014 0.015 0.017 0.014 0.015 0.021 22 0.062 0.020 0.023 0.035 0.037 0.021 0.032 0.015 0.061 0.040 0.045 0.045 0.046 0.053 0.094 0.047 0.058 0.062 0.066 0.063 0.061 0.005 0.005 0.005 0.004 0.004 0.005 0.005 0.005 0.004 0.013 0.015 0.015 0.013 0.013 0.021 23 0.070 0.038 0.041 0.044 0.046 0.038 0.049 0.040 0.069 0.046 0.058 0.058 0.058 0.063 0.095 0.054 0.064 0.069 0.071 0.071 0.067 0.040 0.004 0.006 0.005 0.005 0.006 0.006 0.006 0.006 0.014 0.016 0.016 0.014 0.014 0.021 24 0.078 0.043 0.044 0.050 0.053 0.043 0.053 0.043 0.075 0.054 0.064 0.066 0.063 0.067 0.103 0.060 0.072 0.072 0.078 0.075 0.075 0.043 0.025 0.006 0.006 0.006 0.006 0.006 0.007 0.006 0.014 0.016 0.017 0.014 0.014 0.021 25 0.068 0.034 0.035 0.043 0.045 0.035 0.045 0.037 0.064 0.050 0.056 0.055 0.056 0.058 0.095 0.052 0.058 0.068 0.072 0.070 0.063 0.038 0.048 0.055 0.002 0.004 0.006 0.006 0.006 0.006 0.014 0.015 0.016 0.013 0.013 0.022 26 0.066 0.030 0.032 0.041 0.043 0.032 0.042 0.034 0.061 0.047 0.051 0.050 0.051 0.055 0.089 0.052 0.052 0.064 0.069 0.067 0.060 0.035 0.046 0.054 0.009 0.004 0.006 0.005 0.005 0.005 0.014 0.015 0.016 0.013 0.013 0.022 27 0.056 0.022 0.024 0.030 0.033 0.023 0.033 0.024 0.051 0.035 0.041 0.042 0.041 0.048 0.082 0.042 0.047 0.053 0.057 0.057 0.049 0.025 0.037 0.043 0.029 0.027 0.005 0.005 0.005 0.004 0.012 0.015 0.015 0.012 0.013 0.021 28 0.074 0.040 0.044 0.049 0.052 0.043 0.052 0.043 0.069 0.051 0.060 0.061 0.061 0.063 0.099 0.052 0.064 0.073 0.075 0.076 0.068 0.045 0.054 0.058 0.050 0.048 0.038 0.002 0.003 0.006 0.014 0.016 0.016 0.013 0.014 0.021 29 0.069 0.036 0.039 0.047 0.049 0.038 0.048 0.039 0.064 0.050 0.056 0.057 0.055 0.059 0.096 0.049 0.060 0.068 0.072 0.071 0.064 0.040 0.053 0.057 0.046 0.044 0.034 0.009 0.003 0.005 0.014 0.016 0.016 0.013 0.014 0.020 30 0.072 0.036 0.038 0.044 0.047 0.039 0.047 0.039 0.065 0.049 0.056 0.058 0.056 0.057 0.095 0.049 0.059 0.069 0.072 0.069 0.064 0.040 0.052 0.057 0.046 0.044 0.034 0.015 0.012 0.005 0.013 0.015 0.016 0.013 0.013 0.021 31 0.058 0.027 0.029 0.035 0.037 0.028 0.036 0.028 0.055 0.041 0.046 0.050 0.045 0.050 0.091 0.039 0.055 0.061 0.066 0.066 0.054 0.029 0.043 0.049 0.038 0.034 0.025 0.038 0.036 0.035 0.015 0.016 0.017 0.015 0.015 0.027 32 0.212 0.182 0.186 0.179 0.184 0.184 0.187 0.184 0.197 0.177 0.189 0.192 0.193 0.185 0.198 0.179 0.200 0.195 0.187 0.207 0.197 0.185 0.188 0.193 0.193 0.188 0.169 0.191 0.188 0.187 0.190 0.009 0.010 0.014 0.015 0.023 33 0.226 0.204 0.204 0.194 0.198 0.203 0.206 0.207 0.219 0.197 0.214 0.212 0.213 0.200 0.214 0.201 0.211 0.207 0.204 0.213 0.218 0.202 0.210 0.214 0.209 0.205 0.187 0.210 0.207 0.208 0.206 0.100 34 0.220 0.197 0.199 0.189 0.194 0.193 0.195 0.196 0.212 0.187 0.205 0.201 0.204 0.195 0.218 0.200 0.204 0.198 0.201 0.206 0.217 0.195 0.201 0.204 0.201 0.196 0.180 0.197 0.195 0.197 0.197 0.094 0.068 35 0.198 0.183 0.184 0.182 0.182 0.183 0.189 0.182 0.194 0.183 0.194 0.193 0.195 0.171 0.198 0.174 0.187 0.194 0.185 0.206 0.191 0.185 0.183 0.189 0.184 0.181 0.172 0.193 0.191 0.192 0.192 0.206 0.222 0.214 36 0.208 0.190 0.192 0.185 0.186 0.190 0.189 0.188 0.206 0.192 0.199 0.198 0.201 0.179 0.204 0.184 0.194 0.205 0.194 0.210 0.201 0.186 0.187 0.194 0.191 0.185 0.183 0.202 0.198 0.195 0.198 0.222 0.238 0.235 0.075 0.007 0.015 0.015 0.016 0.016 0.007 0.025 0.024 0.023 0.023 37 0.346 0.316 0.323 0.310 0.318 0.318 0.323 0.324 0.326 0.332 0.329 0.328 0.330 0.323 0.331 0.315 0.326 0.326 0.305 0.324 0.321 0.324 0.328 0.329 0.338 0.331 0.305 0.323 0.318 0.323 0.353 0.367 0.387 0.369 0.346 0.344 48 2.3.4 Phylogeny of the Pimelodidae and phylogenetic position of B. rousseauxii based on concatenated mtDNA and nDNA sequences (CR, CO1, Freticulon-4) The 18 nominal genus of the family Pimelodidae included in the analysis of concatenated sequences (CR, CO1, Freticulon-4), formed coherent monophyletic groups supported by high levels of bootstrap (100%) (Figure 2.6). The morphologically identified species conformed groups or discrete clades obtained through ML analysis. The species of the Pimelodidae family formed a monophyletic group supported by a bootstrap of 89%. Phractocephalus hemioliopterus was the basal species of a clade (bootstrap 51) that contained the other genera of the family. In turn, Leiarius was presented as the sister taxa of a group (bootstrap 84%) constituted by several branches with undetermined relationships. Within this group, one clade was composed of species of the genera Pimelodus, Megalonema, Aguarunichthys, Pimelodina, Pinirampus and Calophysus, with a bootstrap of 100%. The Pimelodus species conformed a single branch (bootstrap 100%), differentiated from other species and supported by a bootstrap value of 79%. In this clade, Pinirampus + Calophysus were the sister group of Pimelodina, and together were in turn sister group of Aguarunichthys. Two other small groups were comprised of Hemisorubim + Hypophthalmus (bootstrap 66%) and Platysilurus + Platystomatichthys (bootstrap 100%). The species of the Brachyplatystomatini tribe (Brachyplatystoma + Platynematichthys) conformed a monophyletic group with a support of 77%. Within this were two groups: one with B. juruense + B. platynemum as sister group of B. tigrinum (bootstrap 53%), and the other (bootstrap 77%) conformed by two minor groups which included Platynematichthys + B. vaillantii (bootstrap 79%) and B. capapretum + B. filamentosum, as sister group of B. rousseauxii (bootstrap 100%). The genera Sorubimichthys, Zungaro, Sorubim and Pseudoplatystoma had uncertain relationships with the other groups. The null hypothesis of a uniform evolutionary rate throughout the tree, constructed with the concatenated sequences of the three descriptors, was rejected at a significance level of 5% (P < 7.099 exp - 76). According to the ML method the model with clock had a lnL = - 38 447.469 (G = 0.489, I = 0.23) with 121 parameters and the model without a clock a lnL = - 38 127.001 (G = 0.50, I = 0.27) with 231 parameters. The values of the distance (p) between each pair of taxa of the outgroup and the ingroup ranged from 0.219 (Sorubimichthys planiceps vs Goediella eques) to 0.445 (Aguarunichthys torosus vs Hypostomus sp.). Between taxa of the ingroup the distance ranged from 0.022 (Pseudoplatystoma fasciatum vs P. tigrinum) to 0.252 (Megalonema platycephalum vs Phractocephalus hemioliopterus). Distances for the pecies of the Brachyplatystoma genus ranged from 0.032 (B. juruense vs B. platynemum) to 0.11 (B. tigrinum vs B. vaillantii) (Table 2.5). 49 Figure 2. 7 Maximum likelihood tree (ML) constructed with PHYML for concatenated sequences of the CR + CO1 + Freticulon-4 for 31 species of Pimelodidae (lnL = - 38 127.061) under the evolution model GTR + I (0267) + Γ (α = 0.497). The tree was rooted with the families Heptapteridae (Goediella eques, Rhamdia quelen, Pimelodella sp.), Auchenipteridae (Ageneiosus inermis, Trachelyopterus galeatus) and Loricariidae (Hypostomus sp.). The numbers close to the nodes represent bootstrap values and the numbers between [ ] the number of haplotypes per species. The branch in blue color corresponds to the group that contains the Brachyplatystoma, the branch highlighted in red correspond to Plateado (B rousseauxii). The stars indicate that the taxa might represent undescribed species. The image of A. torosus was gently provided by Rey G.(Faunagua), and image of B. capapretum was extracted from Lundberg & Akama (2006). 50 Table 2. 5 Average number of substitutions per site (distance p) of all pairs of sequences (concatenated CR + CO1+ Freticulon-4) between the taxa of Pimelodidae and its outgroups (upper diagonal). The estimated standard error for each comparison is shown in the lower diagonal. The analyses were conducted using the nucleotide substitution model of TamuraNei and the rate of variation between sites was modeled with the gamma distribution (shape parameter, α = 0.497). The differences in the composition biases between sequences were considered in the evolutionary comparisons. The analysis considered 112 nucleotide sequences and all the ambiguous positions were removed for each pair of sequences (pairwise deletion). The final matrix consisted of 4136 positions. 1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 Aguarunichthys_torosus Brachyplatystoma_capapretum Brachyplatystoma_filamentosum Brachyplatystoma_juruense Brachyplatystoma_platynemum Brachyplatystoma_rousseauxii Brachyplatystoma_tigrinum Brachyplatystoma_vaillantii Calophysus_macropterus Hemisorubim_platyrhynchos Hypophthalmus_edentatus Hypophthalmus_marginatus Hypophthalmus_cf._fimbriatus Leiarius_marmoratus Megalonema_platycephalum Phractocephalus_hemiliopterus Pimelodina_flavipinnis Pimelodus_pictus Pimelodus_blochii Pimelodus_spA Pinirampus_pirinampu Platynematichthys_notatus Platysilurus_mucosus Platystomatichthys_sturio Pseudoplatystoma_fasciatum Pseudoplatystoma_tigrinum Sorubimichthys_planiceps Sorubim_lima Sorubim_maniradii Sorubim_sp. Zungaro_zungaro Goediella_eques Pimelodella_sp. Rhamdia_quelen Ageneiosus_inermis Trachelyopterus_galeatus Hypostomus_sp. 0.010 0.010 0.010 0.010 0.010 0.010 0.009 0.010 0.008 0.010 0.011 0.010 0.011 0.013 0.012 0.010 0.010 0.008 0.010 0.011 0.010 0.012 0.011 0.011 0.011 0.007 0.009 0.009 0.010 0.010 0.023 0.018 0.018 0.018 0.017 0.032 2 3 0.162 0.151 0.034 0.003 0.007 0.007 0.006 0.006 0.003 0.003 0.006 0.006 0.006 0.005 0.010 0.010 0.006 0.006 0.006 0.006 0.008 0.007 0.007 0.007 0.010 0.009 0.013 0.012 0.010 0.009 0.009 0.009 0.010 0.010 0.009 0.009 0.010 0.010 0.011 0.011 0.006 0.006 0.008 0.008 0.008 0.008 0.007 0.007 0.007 0.007 0.005 0.005 0.007 0.007 0.007 0.007 0.006 0.006 0.008 0.007 0.021 0.020 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.018 0.028 0.027 4 0.168 0.089 0.088 0.003 0.007 0.007 0.006 0.011 0.006 0.007 0.008 0.008 0.010 0.013 0.010 0.009 0.011 0.009 0.011 0.011 0.006 0.007 0.008 0.007 0.007 0.006 0.007 0.008 0.008 0.007 0.022 0.021 0.019 0.021 0.019 0.029 5 0.169 0.092 0.083 0.032 0.006 0.007 0.006 0.011 0.006 0.007 0.008 0.007 0.010 0.013 0.010 0.009 0.011 0.009 0.010 0.011 0.006 0.008 0.008 0.007 0.007 0.006 0.007 0.007 0.008 0.007 0.022 0.019 0.018 0.020 0.018 0.028 6 0.158 0.037 0.032 0.085 0.085 0.006 0.005 0.010 0.006 0.006 0.007 0.007 0.009 0.012 0.009 0.008 0.010 0.008 0.010 0.011 0.006 0.007 0.007 0.007 0.006 0.005 0.007 0.007 0.006 0.007 0.019 0.018 0.017 0.018 0.018 0.028 7 0.169 0.107 0.094 0.101 0.105 0.099 0.007 0.011 0.007 0.007 0.008 0.008 0.010 0.012 0.011 0.010 0.010 0.009 0.010 0.011 0.006 0.007 0.008 0.007 0.007 0.006 0.007 0.007 0.008 0.009 0.020 0.020 0.018 0.019 0.018 0.028 8 0.158 0.083 0.075 0.087 0.094 0.076 0.110 0.010 0.006 0.007 0.009 0.008 0.009 0.015 0.009 0.009 0.011 0.009 0.011 0.010 0.006 0.007 0.008 0.006 0.006 0.005 0.007 0.007 0.007 0.007 0.021 0.017 0.016 0.019 0.018 0.027 9 0.160 0.172 0.164 0.172 0.184 0.168 0.181 0.171 0.009 0.009 0.010 0.010 0.013 0.013 0.012 0.008 0.010 0.009 0.012 0.006 0.010 0.010 0.010 0.010 0.010 0.008 0.010 0.011 0.011 0.011 0.024 0.019 0.019 0.021 0.019 0.030 10 0.103 0.073 0.072 0.073 0.076 0.070 0.080 0.069 0.115 0.006 0.007 0.007 0.007 0.011 0.007 0.008 0.008 0.007 0.008 0.009 0.006 0.007 0.008 0.007 0.006 0.006 0.008 0.008 0.008 0.008 0.019 0.019 0.018 0.018 0.019 0.028 11 0.120 0.075 0.072 0.084 0.083 0.072 0.086 0.074 0.120 0.084 0.004 0.003 0.008 0.011 0.009 0.008 0.008 0.008 0.009 0.009 0.007 0.008 0.009 0.008 0.007 0.007 0.008 0.007 0.008 0.008 0.019 0.020 0.018 0.020 0.019 0.026 12 0.122 0.081 0.075 0.088 0.088 0.078 0.087 0.079 0.129 0.087 0.037 0.005 0.009 0.013 0.010 0.009 0.010 0.009 0.010 0.010 0.008 0.009 0.010 0.009 0.009 0.008 0.010 0.009 0.010 0.010 0.017 0.021 0.019 0.022 0.018 0.025 13 0.118 0.073 0.071 0.086 0.083 0.071 0.083 0.072 0.120 0.083 0.022 0.039 0.009 0.012 0.009 0.009 0.009 0.009 0.009 0.010 0.008 0.009 0.009 0.008 0.008 0.007 0.009 0.007 0.008 0.009 0.019 0.021 0.019 0.019 0.019 0.028 14 0.190 0.156 0.144 0.163 0.157 0.148 0.170 0.151 0.202 0.098 0.097 0.100 0.098 0.015 0.010 0.012 0.011 0.010 0.012 0.011 0.010 0.011 0.011 0.009 0.009 0.007 0.009 0.009 0.009 0.010 0.023 0.018 0.017 0.017 0.016 0.028 15 0.216 0.217 0.207 0.219 0.217 0.205 0.214 0.224 0.235 0.139 0.148 0.149 0.148 0.238 0.014 0.011 0.012 0.011 0.012 0.013 0.012 0.013 0.014 0.013 0.012 0.010 0.013 0.013 0.014 0.015 0.026 0.021 0.019 0.019 0.019 0.026 16 0.206 0.165 0.159 0.171 0.175 0.162 0.190 0.166 0.216 0.094 0.104 0.104 0.102 0.185 0.252 0.010 0.013 0.009 0.011 0.012 0.010 0.010 0.010 0.010 0.011 0.008 0.010 0.011 0.010 0.010 0.024 0.018 0.017 0.019 0.017 0.026 17 0.158 0.151 0.140 0.154 0.155 0.145 0.161 0.146 0.136 0.096 0.103 0.105 0.102 0.192 0.192 0.183 0.011 0.008 0.010 0.008 0.010 0.010 0.011 0.008 0.008 0.007 0.008 0.008 0.009 0.010 0.022 0.019 0.019 0.019 0.018 0.026 18 0.170 0.168 0.161 0.176 0.178 0.156 0.174 0.177 0.168 0.108 0.115 0.120 0.111 0.194 0.221 0.213 0.179 0.007 0.007 0.011 0.010 0.010 0.011 0.011 0.010 0.009 0.010 0.010 0.010 0.010 0.023 0.018 0.019 0.019 0.019 0.025 19 0.160 0.152 0.141 0.153 0.157 0.142 0.163 0.154 0.161 0.100 0.108 0.111 0.103 0.197 0.205 0.187 0.141 0.122 0.004 0.011 0.009 0.009 0.009 0.008 0.008 0.007 0.009 0.009 0.010 0.009 0.020 0.016 0.016 0.018 0.018 0.027 20 0.169 0.156 0.147 0.165 0.166 0.146 0.168 0.161 0.168 0.105 0.113 0.119 0.106 0.201 0.209 0.196 0.153 0.108 0.065 0.012 0.010 0.010 0.011 0.010 0.010 0.008 0.010 0.010 0.010 0.011 0.022 0.018 0.017 0.019 0.020 0.030 21 0.154 0.173 0.164 0.171 0.176 0.170 0.169 0.163 0.094 0.103 0.113 0.117 0.112 0.194 0.216 0.201 0.134 0.165 0.158 0.161 0.011 0.011 0.011 0.011 0.011 0.009 0.011 0.011 0.011 0.012 0.027 0.019 0.019 0.020 0.019 0.026 22 0.164 0.084 0.077 0.095 0.092 0.078 0.099 0.083 0.174 0.078 0.082 0.088 0.080 0.157 0.212 0.179 0.159 0.176 0.161 0.158 0.174 0.007 0.008 0.007 0.007 0.005 0.007 0.008 0.007 0.007 0.019 0.019 0.017 0.018 0.019 0.028 23 0.182 0.120 0.110 0.120 0.125 0.111 0.124 0.121 0.180 0.085 0.093 0.095 0.091 0.174 0.225 0.189 0.160 0.188 0.166 0.169 0.179 0.115 0.006 0.008 0.008 0.007 0.009 0.009 0.009 0.008 0.018 0.019 0.019 0.018 0.020 0.026 24 0.192 0.128 0.119 0.121 0.122 0.122 0.139 0.125 0.185 0.100 0.108 0.115 0.105 0.190 0.240 0.196 0.172 0.202 0.173 0.176 0.193 0.123 0.077 0.009 0.008 0.007 0.009 0.009 0.010 0.009 0.020 0.018 0.017 0.020 0.020 0.031 25 0.169 0.102 0.100 0.102 0.112 0.095 0.125 0.111 0.172 0.083 0.084 0.088 0.082 0.160 0.217 0.177 0.144 0.171 0.146 0.147 0.159 0.116 0.128 0.133 0.003 0.005 0.006 0.007 0.007 0.006 0.022 0.019 0.018 0.018 0.017 0.028 26 0.169 0.105 0.101 0.104 0.111 0.097 0.128 0.111 0.172 0.078 0.081 0.085 0.078 0.164 0.210 0.176 0.142 0.167 0.143 0.149 0.161 0.114 0.131 0.134 0.022 0.005 0.007 0.007 0.007 0.006 0.021 0.019 0.017 0.017 0.018 0.029 27 0.085 0.056 0.051 0.058 0.060 0.050 0.064 0.047 0.099 0.073 0.080 0.086 0.075 0.089 0.121 0.080 0.080 0.092 0.089 0.091 0.100 0.055 0.078 0.080 0.054 0.053 0.006 0.007 0.007 0.005 0.019 0.018 0.017 0.016 0.018 0.026 28 0.178 0.110 0.105 0.115 0.113 0.110 0.123 0.120 0.181 0.089 0.095 0.097 0.094 0.168 0.221 0.183 0.161 0.168 0.166 0.167 0.165 0.121 0.139 0.142 0.107 0.110 0.066 0.003 0.003 0.006 0.023 0.021 0.019 0.020 0.019 0.027 29 0.166 0.109 0.104 0.113 0.108 0.105 0.115 0.115 0.170 0.087 0.089 0.092 0.085 0.162 0.210 0.179 0.152 0.158 0.159 0.159 0.161 0.112 0.135 0.142 0.106 0.107 0.060 0.033 0.004 0.007 0.023 0.019 0.018 0.020 0.018 0.026 30 0.173 0.106 0.101 0.111 0.110 0.101 0.115 0.113 0.179 0.088 0.094 0.095 0.091 0.164 0.223 0.178 0.152 0.163 0.166 0.165 0.165 0.113 0.135 0.141 0.110 0.111 0.065 0.034 0.036 0.007 0.023 0.020 0.018 0.019 0.018 0.027 31 0.169 0.109 0.098 0.100 0.104 0.097 0.117 0.097 0.184 0.087 0.089 0.097 0.085 0.167 0.234 0.173 0.161 0.180 0.162 0.170 0.182 0.107 0.121 0.126 0.105 0.102 0.052 0.121 0.119 0.120 0.023 0.020 0.020 0.021 0.020 0.032 32 0.391 0.350 0.345 0.356 0.353 0.344 0.352 0.354 0.384 0.235 0.230 0.235 0.231 0.367 0.391 0.365 0.383 0.376 0.369 0.371 0.407 0.348 0.346 0.384 0.362 0.354 0.219 0.371 0.369 0.376 0.375 0.010 0.009 0.019 0.021 0.032 33 0.261 0.252 0.249 0.252 0.250 0.248 0.261 0.249 0.271 0.252 0.264 0.266 0.263 0.248 0.267 0.241 0.245 0.252 0.253 0.260 0.259 0.255 0.255 0.266 0.252 0.247 0.241 0.260 0.252 0.260 0.265 0.127 34 0.253 0.238 0.234 0.237 0.238 0.231 0.233 0.225 0.259 0.229 0.252 0.251 0.248 0.243 0.265 0.238 0.240 0.246 0.241 0.243 0.261 0.237 0.235 0.246 0.239 0.234 0.223 0.242 0.235 0.235 0.244 0.126 0.093 35 0.255 0.233 0.225 0.233 0.231 0.234 0.243 0.233 0.259 0.234 0.245 0.254 0.243 0.229 0.252 0.226 0.241 0.244 0.245 0.255 0.250 0.242 0.234 0.255 0.228 0.227 0.221 0.244 0.247 0.250 0.257 0.249 0.267 0.265 36 0.246 0.236 0.230 0.230 0.236 0.231 0.234 0.238 0.255 0.250 0.252 0.242 0.251 0.229 0.261 0.227 0.234 0.244 0.244 0.250 0.247 0.239 0.237 0.257 0.237 0.234 0.235 0.256 0.246 0.244 0.247 0.268 0.278 0.272 0.113 0.009 0.020 0.018 0.020 0.019 0.010 0.034 0.036 0.029 0.031 37 0.445 0.391 0.382 0.382 0.383 0.392 0.370 0.387 0.402 0.403 0.390 0.396 0.394 0.393 0.399 0.383 0.378 0.386 0.399 0.406 0.408 0.404 0.401 0.432 0.413 0.414 0.380 0.399 0.392 0.403 0.416 0.434 0.487 0.467 0.434 0.425 51 2.3.5 Comparison of our results on the molecular phylogeny of the Pimelodidae family with Lundberg et al.’ study, carried out in parallel Recently, Lundberg et al. (2011) showed that the South American catfish Pimelodidae family conforms a monophyletic group using molecular data. Below is a summary of the results extracted from their work, and the most remarkable comparative results and conclusions of the present study. Lundberg et al. (2011)' study analyzed more than seven kilobases of aligned nucleotide sequences from the rag1 and rag2 nuclear genes, and the 12S, 16S and cytochrome b mitochondrial genes for 52 nominal and five undescribed pimelodid species representing 27 of 31 extant genera. Results of Bayesian likelihood and maximum parsimony analyses of the combined sequence data consistently recover 40 monophyletic pimelodid clades above the species level. The basal lineages of Pimelodidae are Steindachneridion and Phractocephalus that are serially, or together as a small clade, sister to all the other members of the family. Leiarius and the nominal Perrunichthys perruno are sister to the neopimelodines, a clade comprised of the remaining pimelodids divided into two major lineages: the sorubimines and the Pimelodus ornatus-Calophysus-Pimelodus (OCP) Clade. Sorubimines include seven well-supported units whose interrelationships are poorly resolved: Sorubim, Pseudoplatystoma-Sorubimichthys Clade, tribe Brachyplatystomatini, Platysilurus-Platystomatichthys Clade, Hypophthalmus, Zungaro and Hemisorubim. In conflict with morphological evidence, the molecular data do not support monophyly of the genus Brachyplatystoma. However, the subgenus Malacobagrus (B. rousseauxii, B. capapretum, B. filamentosum) and the sister species pair B. juruense and B. platynemum are each recovered as monophyletic. The OCP Clade comprises nominal Pimelodus ornatus that is sister to the Calophysus-Pimelodus Clade in turn split into the calophysines and pimelodines. Calophysines include a monophyletic Calophysus Group (Calophysus, Aguarunichthys, Luciopimelodus, Pinirampus, Pimelodina) and the MegalonemaCheirocerus Group. Intrarelationships of the Calophysus Group recovered with molecular data are congruent with relationships based on morphology. Placement of Cheirocerus sister to Megalonema is unexpected but well supported by molecular data. Pimelodines include the Exallodontus-Pimelodus altissimus Group and Pimelodus Group. The former correspond to the “long-finned” pimelodids including Exallodontus sister to an undescribed miniature species from the Amazon, and those sister to undescribed species of Propimelodus. An undescribed species related to nominal Pimelodus altissimus is the sister to nominal Duopalatinus peruanus. Nominal Pimelodus pictus is sister to remaining members of the Pimelodus Group that in turn contains three subclades: Iheringichthys plus Parapimelodus, Pimelodus maculatus plus P. albicans, and P. blochii including P. argenteus. Pimelodus coprophagus is unresolved among the P. maculatus and P. blochii groups. A generic reclassification of the species now assigned to polyphyletic Pimelodus is needed based on more complete taxon sampling and character evidence. 52 A modest sampling of multiple specimens from thirteen pimelodid species permitted a first examination of their genetic diversity within and across the major South American river basins. The rag and mitochondrial genes examined here show little divergence between distant allopatric populations of Pinirampus pirinampu, Brachyplatystoma vaillantii, B. rousseauxii, B. filamentosum and B. juruense. However, specimens representing allopatric populations of five nominal species are as divergent as distinct congeneric species: Pimelodus blochii, P. ornatus, P. pictus, Platysilurus mucosus and Megalonema platycephalum. In the present study, the molecular monophyly of the Pimelodidae family was demonstrated using a maximum likelihood analysis of 4136 aligned bp from two mitochondrial (CR and CO1) and one nuclear (Freticulon-4) genetic markers. Similar to Lundberg et al. (2011), who used different mitochondrial and nuclear genes, the concatenated sequence analysis recovered the 18 genera (33 species, two potentially new) considered in the analysis as monophyletic groups. Overall, the monophyletic clades of the Pimelodidae family described by Lundberg et al. (2011) were obtained but with some relationships variations. One of the most outstanding results of both the present work and that of Lundberg et al. (2011), was the non-monophyletic molecular definition of the Brachyplatystoma genus sensu Lundberg & Akama (2006). Current nominal species of the genus Brachyplatystoma were positioned in three groups: the subgenus Malacobagrus group (well supported), the B. juruense + B. platynemum group (well supported), and the Platynematichthys notatus + B. vaillantii group (no well supported). The position of B. tigrinum remains uncertain inside de Brachyplatystoma genera, which needs a review and systematic reclassification based on the molecular informations. 2.4 Discussion The analysis conducted in the present work shows the first molecular phylogeny for 18 genera, of 29 nominal (Ferraris Jr 2007), that currently exist in the Pimelodidae family, based on the information contained in two mitochondrial fragments (CR and CO1) and one nuclear fragment (Freticulon-4). The Pimelodidae family possesses a moderate species richness and several of them attain considerable sizes, supporting an important portion of the continental fisheries in South America (Barthem & Goulding 1997; Barthem & Goulding 2007; Van Damme et al. 2011). The evolutionary history of these species remains enigmatic considering their heterogeneity of forms and biological traits. Most efforts to understand and define the relationships between their genus and species have been carried out in the last 20 years using morphological and anatomical characters (de Pinna 1998; Diogo 2005). The few studies conducted on the molecular systematics of certain genera (Hardman & Lundberg 2006) or species (e.g. Torrico et al. 2009) have generated interesting hypotheses on the diversification processes followed by the Neotropical ichthyofauna. According to the synthesized analysis submitted by de Pinna (1998), and the latter complementary works of Lundberg & Akama (2005) and Diogo (2004, 2007), the Pimelodidae family has several internal groups with undetermined level of relationships between them. These sets of species basically correspond to a basal group composed of Phractocephalus, Perrunichthys and Leiarius 53 (Phractocephaline), the Pimelodus-Calophysus group (18 genera including Megalonema), and the Sorubiminae group (9 genera, assuming the new classification of Brachyplatystoma according to Lundberg & Akama 2005). Every group is defined by a synapomorphy, but, with the exception of Phractocephaline, the relationships within every group (principally in the Sorubiminae) are not well defined. The Phractocephaline group has a synapomorphy that consists of seven or more pectoral rays. The Pimelodus- Calophysus-group has the following characteristics in common with synapomorphy: the posteroventral part of mesoetmoid with parallel sides, abruptly rounded in the corners almost at right angles; cornua of the mesoetmoid abruptly deflected centrally, with a middle crack reduced or absent; coronoid process of lower jaw very deep; cleithral ring formed by the process of the lateral and medial of the supracleitrum and the fourth transverse process, together surrounding the branch of the cleitrum. In turn, the Calophysusgroup differs by having a thin pectoral spine which is not sharply-pointed; high number of pectoral rays and an absent posterior cleithral process, and the Pimelodus-group for a transversal process of the fourth and fifth vertebrae completely sutured to its lateral edges. The members of the Sorubiminae group do not have a synapomorphy but it is possible to distinguish two internal groups, the Brachyplatystomatini of Lundberg & Akama (2005), and a subset of 5 species (Hemisorubim, Zungaro, Sorubim, Pseudoplatystoma and Sorubimichthys) presented by de Pinna (1998). The Brachyplatystomatini are defined by two clear synapomorphies. The first one consists of a swim bladder divided into two cameras, with the large and triangular posterior camera connected to the anterior one by a pair of lateral tubes. Both cameras have thick, but translucent walls, and numerous internal septa that give them a spongy appearance. The second one is the elevated ventral margin of cleitrum as thin low ridge between the pit of the articulation of the pectoral spine and the base of posterior process of the cleitrum. The subgroup of these five genera can be distinguished by the presence of the posterolateral corner of the premaxilla in a sharp, pointed form. Inside the tribe Brachyplatystomatini, it is proposed that the Brachyplatystoma genus conforms the sister group of the basal species of the tribe Platynematichthys notatus (Lundberg & Akama 2005). The Brachyplatystoma taxa is defined by two clear morphological synapomorphies consisting of: 1) large expansion of the suspensorium midleback to form a massive plate closer of the parasfenoid. The hyomandibula and metapterigoide union have a long suture with their middle back margins partially or entirely convex and thick in the insertion of the adductor muscle arcus palatin. 2) caudal fin of young and sub-adults provided with remarkably elongated filaments on the lobes, which originate from a simple and unbranched principal ray. According to the latest definition of the genus (Lundberg & Akama 2005), consisting of seven species including the monotypic genera, Morodontotus and Goslinia, B. vaillantii is the most basal species of the group and a subgenus known as Malacobagrus is formed by the larger species B. filamentosum + B. capapretum, sister group of B. rousseauxii. The analysis of the CR sequence for the Pimelodidae species considered in the present study, showed that Phractocephalus + Steindachneridion conform a differentiated group from the main group where Leiarius is positioned as the basal taxa. Within the major group, the relationships between genera are not very clear but a relatively high support (88%) may be noted for most of the species that conform the Pimelodus-Calophysus group, excluding Platysilurus which is closer to Platystomatichthys, defined with morphological characters. The Calophysus and 54 Pimelodus groups, according to the information from this molecular marker, do not seem to be natural as well as the genera of Sorubiminae group. As for the species of the tribe Brachyplatystomatini, they did not fit into a well-supported monophyletic group. The specific interrelations observed were not concordant with those defined by Lundberg & Akama (2005). Alternatively, the ML analysis suggests that the genus is conformed of two groups without established relationships. One group constituted by the species of the subgenus Malacobagrus + B. vaillantii as sister group, and another one formed by B. juruense + B. platynemum as sister group of B. tigrinum. P. notatus, basal species according to the morphological phylogeny of the genus, was located at the root of the latter group but with a quite low support (53%), indicating that its position is uncertain in relation to the Brachyplatystoma. The CO1 showed a less informative image than the CR for the relationships between genera within the Pimelodidae family, which was supported by a low value of bootstrap (56%). This molecular marker had a clear correspondence with the morphological identification of the species, as it has been shown in other studies with fish (e.g. Hubert et al. 2008; Lara et al. 2010; Zhang & Hanner 2011 in press), but provided no relevant information comparable to the organization of genera defined by the morphology. However, it proved useful to catalog species of Neotropical silurids (DNA barcoding) and identify those groups whose taxonomy deserve future attention (e.g. Sorubim, Pimelodus). As with the CR, the Brachyplatytoma genus did not conformed a monophyletic group and its species were distributed in two branches without defined relationships. The first group was made up of (B. rousseauxii + B. filamentosum) + B. capapretum, species of the Malacobagrus subgenus, and the second one by B. juruense + B. platynemum. B. vaillanti and P. notatus which had an uncertain position in relation to the species grouped in the genus, and B. tigrinum was placed at the base (60%) of the species of the Sorubim, a genus that apparently does not have a close relationship at morphological level with Brachyplatystoma. The Freticulon-4 showed that the Pimelodidae family conforms a monophyletic group (90%) differentiated from the Pseudopimelodidae and Heptapteridae families, and a major resolution between genera in comparison to the previous descriptors (RC and CO1). Several relations that were established coincided with the information obtained by CR sequences. In the ML Freticulon-4 tree, Leiarius was located at the base of a major group that enclosed the remaining genera and species of the family, in which Phractocephalus was the most basal. Inside the major group there were two clades, one constituted by the species of Pimelodus-Calophysus group, and another by the remaining species that were closer to the Sorubiminae group, including Hypophthalmus. Platysilurus was excluded from the Pimelodus-Calophysus group, and grouped with Platystomatichthys (similar to what was observed with the CR), in a branch with uncertain relationships inside the second group. The relationships inside this group were not resolved but it was noteworthy that Zungaro and Sorubim were excluded from a group (61%) where Sorubimichthys and Pseudoplatystoma were closely related. Similar to the results of the CR and CO1, the Brachyplatystomatini tribe did not conform a monophyletic group and their species were separated into three groups instead of two. The first group was composed by species of the Malacobagrus subgenus where B. filamentosum + B. capapretum were the sister group of B. rousseauxii. The second group consisted of B. juruense + B. platynemum, and the third one the B. vaillantii with P. notatus. The interrelations 55 between these groups were not defined and nor was the position of B. tigrinum. It is important to note that in relation to the morphology, the only coincidences were at the level of the composition of the Malacobagrus group, and the relationship between B. juruense and B. platynemum. B. vaillantii is nearest to P. notatus, the basal taxa of the tribe morphologically, but the relationships between B. tigrinum and the other groups are undetermined. Figure 2. 8 Comparison of the phylogenetic tree topologies obtained by molecular methods (maximum likelihood - ML) with three genetic markers concatenated (CR + CO1 + RTN4) and morphological methods (maximum parsimony of characters) for the members of the Brachyplatystomatini Tribe defined by Lundberg & Akama (2006 .) In the molecular phylogeny the numbers close to nodes represent bootstrap values, and bars in the morphological phylogeny the number of synapomorphies that characterize the groups. CR: Control Region; CO1: Cytochrome Oxidase 1; RTN4: F-reticulon4, ML: maximum likelihood. The analysis of all the sequences together (concatenated), which simultaneously included all the information contained in the sequences, established a better image on the internal relationships of the Pimelodidae family and the species of Brachyplatystoma. The Pimelodidae family conformed a monophyletic group (89 %), differentiated from Heptapteridae, in which Phractocephalus was positioned as the basal taxa. In turn, Leiarius was established at the base of a group that contained the remaining genera (51 %), where the Pimelodus-Calophysus group was separated from the Sorubiminae. Inside the Pimelodus-Calophysus, the Calophysus group was partially resolved and Megalonema was close to ((Pinirampus + Calphysus) + Pimelodina) + Aguarunichtys. The Sorubiminae group did not show a consistent internal structure of relationships and only exhibited the associations between Platysilurus + Platystomatichthys and the species of Brachyplatystomatini. The Brachyplatystoma together with Platynematichthys conformed a monophyletic group with a support of 77 %, but the arrangement was incongruent with the morphological hypothesis. The branch of this genus was structured into two groups. The first one (77% support) included the species of the Malacobagrus subgenus, (B. filamentosum & B. capapretum) + B. rousseauxii, as the sister group of P. notatus + B. vaillantii, and the second one (53% of support) associated B. juruense + B. platynemum, as the sister group of B. tigrinum. Although the nodes support defining the relationships between the groups and Brachyplatystoma species is not very robust, these results showed clear tendencies. Species classified inside the Brachyplatystomatini tribe possessed major affinity between them than with those of other genera or groups. Platynematichthys, together with B. vaillantii, are positioned at the base of the species of the Malacobagrus subgenus and not at the base of all 56 the Brachyplatystoma. Internally, the tribe contains two well defined clades that correspond to the Malacobagrus subgenus and to the B. juruense + B. platynemum group. The relationships between these two clades are not completely resolved and neither are those of B. tigrinum, which is closer to the last group but with a low support (53%). The Figure 2.8 presents a comparison of molecular (present study) and morphological (Lundberg & Akama 2005) phylogenetic topologies, which summarizes the discrepancies and concordances between both results, and the position of B. rousseauxii with respect to the species assigned morphologically to Malacobagrus subgenus, the Brachyplatystoma genus and the Brachyplatystomatini tribe. Comparing the morphological and molecular phylogenies within the genus, it can be concluded, assuming that the bootstraps are sufficently high to be significant, that Brachyplatystoma genus includes Platynematichthys notatus, or only the species that were assigned to the Malacobagrus subgenus (Figure 2.8). Under the last configuration, B. vaillantii + Platynematichthys would be the sister group of the genus and all together would conform the Brachyplatystomatini tribe. The other nominal species inside Brachyplatystoma but grouped in a differentiated clade according to the molecular analyzes, would correspond to different genera that conform the sister group of the redefined Brachyplatystomatini tribe. Using this hypothesis, it is possible that after an exhaustive morphological reexamination of the genus, a resurrection of the Merodontotus genus (possibly the basal taxa) and Goslinia genus may occur, and that the species identified as B. juruense be classified under a new taxonomic generic category or reassigned to one of the genus in which it was previously positioned (e.g. Ginesia Fernandez-Yepez 1951). 57 Chapter 3 POPULATION GENETIC STRUCTURE OF PLATEADO (BRACHYPLATYSTOMA ROUSSEAUXII) IN THE UPPER MADERA (BOLIVIA) AND UPPER AMAZON RIVERS (PERU) AS SHOWN BY MICROSATELLITE (NUCLEAR DNA) ALLELIC VARIATION ANALYSIS AND CONTROL REGION (MITOCHONDRIAL DNA) SEQUENCES 3.1 Introduction Fish species of the family Pimelodidae represent between 1.5 and 2 % of the total number of species estimated for the Neotropical ichthyofauna and approximately 5 % of the Siluriforms of this zone (Reis et al. 2003). This family of catfish consists of medium- to large-sized species that can exceed 2.5 m in length and 150 Kg (Berra 2003). Within the pimelodids, the genera Brachyplatystoma, Zungaro, Pseudoplatystoma and Sorubimichthys have the largest species (Barthem & Goulding 1997; Barthem & Goulding 2007). Of all of these, Brachyplatystoma is one of the most diverse genera (seven species) and is known for having the most outstanding migratory species known to freshwaters (Barthem & Goulding 1997; Alonso 2002; Araujo-Lima & Ruffino 2003). Species of the genus Brachyplatystoma primarily inhabit the Amazon River basin but many of them can also be found in the Orinoco River basin (Lasso et al. 2004; Maldonado-Ocampo et al. 2006; MaldonadoOcampo et al. 2008; Lasso et al. 2009) and the rivers of the Guianas (Le Bail et al. 2000). The largest species of this group are emblematic of the Amazon basin for their commercial importance (Barthem & Goulding 1997; Barthem 1999; Batista & Petrere 2003; Petrere et al. 2004; Van Damme et al. 2011) and their particular life history traits (Barthem et al. 1991; Barthem & Goulding 1997; Alonso et al. 2002; Barthem & Goulding 2007; García et al. 2009). As seen in the previous chapter, the molecular phylogeny of the genus is, in turn, concordant and discordant in several aspects with the morphological phylogeny of Lundberg & Akama (2006), and in most cases with the molecular phylogeny of Lundberg et al. (2011). In general, species of the genus are well differentiated at the molecular level (monophyletic species) but do not form a monophyletic group. The molecular pattern is concordant with the morphological proposal in the conformation of the subgenus Malacobagrus Brachyplatystoma rousseauxii + (B. filamentosum + B. capapretum), and the proximity of B. juruense and B. platynemum, but is discordant with the configuration of the tribe Brachyplatystomatini established by these authors. The molecular results suggest that the genus may be made up of a number of inferior species (including B. rousseauxii), and the excluded taxa would correspond to different genera requiring a new, more detailed, morphological re-evaluation (e.g. Merodontotus, Goslinia). Brachyplastystoma rousseauxii (Castelnau 1855), is one of the most peculiar species of the Amazon basin due to its large size and its complex life cycle, still only partially understood (Barthem & Goulding 1997; Alonso 2002; García et al. 2009). Commonly known as “Dourada” (Brazil), “Dorado” (Colombia, Bolivia), “Zungaro Dorado” (Peru) and “Plateado“(Bolivia and Colombia) (Araujo-Lima & Ruffino 2003; Carvajal-Vallejos et al. 2011), this species is widely distributed throughout the 58 Amazon River’s main channels of white water tributaries (Araujo-Lima & Ruffino 2003; Barthem & Goulding 2007). However, the species can be observed sporadically in clear water and black water rivers (e.g. Negro, Tocantins) (Goulding 1980). There are few studies on this species to date, despite the interest that arose among ichthyologists as a result of Barthem & Goulding’s (1997) work. These authors followed the presence and size of fish caught for this species (and others) in the main fishing ports along the Amazon and Madera river channels, from its mouth (Belem) to the vicinity of the headwaters of one of its tributaries in Peru (Pucallpa, 4 500 Km from the estuary). Fishery statistics and experimental fishing data collected over several years, supplemented by information in the literature, showed that Plateado juveniles were not present in the flood plains, and that pre-adults and adults were rarely found in those habitats. Juveniles and pre-adults were common in the Amazon estuary, but adults were rare or absent. In the upper Amazon, adults were of the size class most exploited by fisheries but juveniles were rarely observed. Clearly, a size distribution was noted dependent on the geographic position within the system in which they were caught by commercial operations. The average size caught in the estuary was 70 cm, in Central Amazon, near Manaus and in the upper reaches of the Madera River (Porto Velho), 80 - 90 cm, and in the Upper Amazon 90 – 110 cm. According to reports by fishermen, estuarine pre-adults moved annually (August - October) upstream and the sizes fished near Leticia (Colombia) were relatively the same throughout the year. In the upper part of the Madera River the catches and movement of Plateado were noticeable by the presence of rapids (Teotônio) and turbulent areas that the fish needed to pass through during their migration upstream. Such movements were not evident in other comparable systems that lack rapids in the upper reaches. These movements occurred annually between December and February, when the river rose rapidly. The fish that arrived at the Madera River rapids were on average considerably larger than the size classes caught in the lower Amazon River and estuary. In theory, these fish would had to travel at least 15 - 19 Km/day for four to five months if they originated in the estuary, at 3 100 Km from the Teotônio rapids. This maximum speed assumed that the fish would only travel and not feed during their migration, but it was observed that they fed intensively in the Central Amazon. Thus, it was hypothesized that the migratory schools of pre-adult Plateado had to leave the estuary to reach and spread throughout the Central Amazon, where they spent one or two years feeding. At the beginning of the annual floods, the fish that remained as residents of Central Amazon for at least one year, would group into schools and travel upstream. This stage, which could be considered as a second migratory phase, would not have reproduction as the immediate objective as the fish caught at the Teotônio rapid, for example, did not have developed gonads. Instead, reproduction appears to be delayed by at least one more year. This second migration stage also occurred on the Amazon River, but it would not be possible to detect it by the fishery (apparently limited) until the fish reach the border zone between Brazil, Colombia, and Peru, in the western basin. Adult and fully mature fish were observed only in the upper reaches of the Amazon River, with an average size of 112 cm for females; but it was not possible to establish an exact reproductive season. However, the absence of sexually mature fish in Central Amazon and estuary firmly suggested that Plateado would spawn on the west of the Amazon and in the upper reaches of its tributaries. Based on this model, the eggs and larvae resulting from these reproductive events would be taken downstream for 13 - 20 days until reaching the Amazon estuary. Juveniles would remain there, feeding and taking refuge for a few years, until they 59 reached a size large enough ugh to allow them to start their necessary displac isplacements to complete their lifecycle. The e evidence of the downstream migration n of llarvae was evident by the catch of small mall in individuals (6 – 15 cm) in the Amazon n estu estuary and in other locations in the lowerr and mid reaches of the basin. Figure 3.1. 1 Schematic representation n of Barthem & Goulding’s (1997, 2007) hypothesis on the migratory migra movements (upstream, downstream) of Brachyplatystoma oma rousseauxii in the Amazon basin and the areas it uses througho roughout its lifecycle in this basin. Red circle: Nursery area; Yellow ellow area: Food area of adults and pre-adults; White oval: Hypothetical Hypot region of spawning grounds proposed by Barthem & Go Goulding (1997). The white area delineated shows the hypothetical etical area adjusted of spawning grounds proposed by Barthem & Go Goulding (2007). Diagram extracted and modified from Barthem em & Goulding (1997; 2007). Later, Alonso (2002) and d Ga Garcia et al. (2009)’ results confirmed several seve of the observations that led to Barthe arthem and Goulding’s hypothesis. More specific pecific data was presented in these research rch re regarding size, age, and dependence of stocks sto on the fluvial dynamics along the e Am Amazon main stem between Belen (Brazil) azil) a and Iquitos (Peru). Alonso (2002) noted oted tthat juveniles in the estuary were the he sm smallest and started migrating at 1-2 years ears when they reached 60-80 cm in size.. The schools of fish that arrived in Central tral A Amazon would remain in this area unti until reaching approximately 100 cm (3 3 year years). Once they reached this size, they ey wo would move towards the western Amazon azon (Leticia and Iquitos) where stocks are made m up of individuals 80 - 140 cm, and nd 2. 2.5 - 10 years old. In this latter zone (Iquitos) uitos), Garcia et al. (2009) showed that Platea Plateado reproduced during receding waters ters ((not during floods) and at an age greater reater than 3 years old. The first sexually lly mature ma sizes identified were at 91 cm (femal females) and 83 cm (males), and females were ere o on average 60 larger than males. This research provided new information on the knowledge of the species and generated various interesting facts (e.g. reproductive season and estimated location) in relation to previous published findings (e.g. Barthem & Goulding 1997, 2007) confirming the existence of a complex life cycle that occurs between the Amazon estuary and its headwaters. The Amazon basin covers a large extension (over 6 000 000 Km2) and the main tributaries have different hydrological and geological characteristics (e.g. Madera, Ucuyali). Little is known on the biology of B. rousseauxii in the Madera basin, but it would be expected that its migratory dynamics be similar to that described for the Amazon main channel. Given the life cycle of B. rousseauxii and the extremely large extension of the basin, however, it has been suggested that the species could be made up of several populations. These populations could be related to specific geographic zones or to different basins, to which the fish could return to and breed in the same place where they were born (homing, Figure 3.1.2). Batista & AlvesGomez (2006) suggested that the Plateado displays a spatial genetic variability along the Amazon’s main stem that could be explained by a homing phenomenon. These authors found that the genetic variability decreases from the estuary westwards and that this could be due to preferential recruitment by fish to certain tributaries or stocks as they move upstream. Although this was an interesting hypothesis, the variability observed in this study could have alternative explanations (e.g. high differential mortality in the first years of life related to the tributaries, epistatic effects, counter-selection, differential viability, among others), and the sampling design, in addition to the molecular descriptor used (the maternallyinherited Control Region – CR, mtDNA), do not provide sufficient information or consistent evidence of a philopatric migration model. In recent years Batista (2010) demonstrated through the use of nuclear descriptors (microsatellites) that individuals from different tributaries of the Amazon basin (including the Madera River) form part of a single panmitic unit. The possibility of a homing phenomenon was not totally discarded, as a mitochondrial (CR) descriptor was used at the same time and a partial structure was observed among large tributaries. The results of this research have and important impact for the conservation of the species given that the countries sharing the Amazon basin would be exploiting the same stock. This means that the uncontrolled fishery along the Amazon’s main channel in Brazil (e.g. Petrere et al. 2004), would have a general effect in the upper basin in Colombia, Ecuador, Peru, and Bolivia by reducing the number of young fish reaching the upper parts to reproduce. Reciprocally, an uncontrolled fishery of adults with mature gonads that reach the upper reaches of the basin to reproduce will have a negative effect on the recruitment of juveniles in the lower areas of the watershed (estuary). In both cases and considering other threats (e.g. deforestation - Angelini et al. 2006; hydropower dams – Junk et al. 2007; Van Damme et al. 2011c), the negative effects on the conservation status of the species are high, and conservation strategies become difficult with the involvement of five governments with different fishing rules and customs. 61 Figure 3.1. 2 Schematic representation of a possible homing episode occurring at the scale of the Upper Madera by the fish species Plateado (Brachyplatystoma rousseauxii). A similar behaviour could occur in other large turbid water tributaries within the western section of the Amazon River. The geometric figures represent individuals from the same panmitic population that recognize their place of birth during the reproductive period. Considering that the Plateado is a resource with a complex lifecycle that takes place on a continental scale and that it is subject to different fishing pressures (on juveniles in central Amazonia and on adults in western Amazonia), it is important to continue generating information to get a better understanding of its biology and to properly guide its conservation and management. The Madera is one of the largest river basins of the Amazon, and among those that contribute most in terms of water and sediment volumes (Goulding & Barthem 2007; Molina & Vauchel 2011). Most of the Madera upper watershed is in Bolivian territory and is fed by several tributaries with distinct physiochemical characteristics, depending on their geological origin and on climate they are subjected to (Navarro & Maldonado 2002). All of them converge into to the same channel (proper Madera River) that is separated from the lower Madera by a series of rapids spread over 300 Km (Molina 2011). The history of the basin and the rapids seem to have had an important influence on the structure of the aquatic communities (Carvajal-Vallejos & Zeballos 2011), and very likely also on populations or species of migratory fishes such as the Plateado. As such, this study aimed to generate new findings on the geographic populations of Plateado in the interior (tributaries) of the upper basin of the Madera River (Bolivian and Peruvian Amazon), and compare them with information obtained for the Ucayali-Amazon (Peru) system. The molecular markers used (nuclear and mitochondrial) and sample collection were designed to determine the existence of local and/or regional genetic populations, and clarify if there is a homing phenomenon towards the tributaries of the Upper Madera basin (Figure 3.1.2). 62 3.2 Material and Methods Study Area Figure 3.2. 1 Representation of the sub-basins that make up the Bolivian Amazon Basin. Figure extracted and modified from Crespo & Van Damme (2011). 63 The study area included the upper basin of the Madera River in Bolivia (mainly) and Peru (Puerto Maldonado), and the basin of the Ucayali-Amazon System (Peru). The Ucayali-Amazon system in Peru accounts for 22% of the total water volume and represents almost 10% of the total watershed area (Goulding et al. 2003). Its current conformation (flow) has been controlled by the rising of the Fitzcarraldo Arch (Espurt et al. 2010) and its lower reaches have characteristics similar to those seen in Central Amazonia. In terms of flow and sediment, the Madera River is one of the four major rivers of the Amazon basin, next to the Solimões (Amazon in Peru), Japura, and Negro rivers. It contributes to over 45% of all suspended solids of the Amazon basin, which are mostly transported from the Andes (Wilkinson et al. 2010; Molina & Vauchel 2011), and covers an area of 1 380 000 Km2 (20.1% of the Amazon Basin) (Goulding et at. 2003). The Upper Madera River basin or Upper Madera in Bolivia, has an area of 713 867.41 Km2, excluding the Acre River basin (2 038.64 Km2), which drains into the upper basin of the Purus River (Crespo et al. 2008). The total area of the Bolivian Amazon is found on these two basins. In the Upper Madera basin, an area of up to 714 577 Km2 (Llanos de Moxos, or Moxos Plains) can be flooded annually (Crespo & Van Damme 2011), which represents approximately one fourth of the Amazon Basin wetlands (Melack & Hess 2010). Below 600 m.a.s.l. there is a precipitation gradient that ranges from 1000 mm (in the southern area) to 6000 mm (in the western central area, close to the Andes) (Molina & Vauchel 2011). The Upper Madera is divided into nine sub-basins referred to as Abuná (23 253 Km2), Madera (972 Km2), Orthon (18 420 Km2), Yata (20 367 Km2), Madre de Dios (28 855 Km2), Beni (123 285 Km2), Mamoré (242 782 Km2), Itonama-Parapetí (63 518 Km2) and Iténez (131 288 Km2). Owing to their extension, the sub-basins Beni and Mamoré could be divided into another three units referred to as Lower (< 300 m.a.s.l.), Sub-Andean (300 – 3 000 m.a.s.l.), and Upper-Andean (> 3 000 m.a.s.l.) (Crespo & Van Damme 2011) (Figure 3.2.2). All these sub-basins, below 300 m.a.s.l, are aquatic floodplain systems (Junk et al. 1989). Figure 3.2. 2 Volume (A) and sediment transport (B) by the main tributaries of the Madera River in Bolivia. Figure extracted from Molina & Vauchel (2011). 64 Water from the Abuna and Yata sub-basins originates from the flat lowlands (pampas) of the Bolivian Amazon (alluvial and lateritic deposits), and are characterized by a relatively low content of suspended solids. Both sub-basins receive important contributions from several small tributaries originating from the same plain. The sub-basins Itonama-Parapetí and Iténez are characterized by draining for the major part over a plain of Precambrian rock (Brazilian Shield). Riverbed erosion is limited, and as a result, the amount of suspended solids is reduced. For this reason, and for their physiochemical characteristics (hypo-mineralisation; sodic-potassic bicarbonates) they have been considered as clear-water systems (Navarro & Maldonado 2002). a) b) c) d) Figure 3.2. 3 Photos a and b are images of the Beni River at Cachuela Esperanza rapids during the low water season (August 24, 2006). Photos c and d are images of the Mamoré River at one of the rapids that crosses it. Both photographs were taken at the Cachuela Piedra Gorda rapids height just a few kilometers from where it meets the Beni River (Villa Bella community), during the low water season (May 25, 2006). The sub-basins Madre de Dios, Beni and Mamoré, below 300 m.a.s.l., have a large alluvial plain with abundant lakes of meandric and tectonic origins. Their headwaters originate in the Andes rocky mountain chain and they carry large amounts of solids (suspended and dissolved solids) that turn them cloudy and of a milky appearance 65 (McClain & Naiman 2008). Due to their color and physiochemical characteristics (hypominerilization: bicarbonates calcic-sodic, calcic-magnesic, calcic-potassic) these basins are considered of white-waters (Navarro & Maldonado 2002). The sub-basin Orthon originates in the lowlands of the northern Bolivian Amazon (including a part in the south-east of the Peruvian Amazon) and it runs over lateritic deposits (upper area) and alluvial deposits (lower part). The system is considered as a mixed-water system due to the changes in its appearance between the dry season (clear water) and the rainy season (white water). During the dry season, the rivers reach their lowest levels and transports few suspended solids (minimized erosion), and several streams feed the main channels with tea-coloured water. On the contrary, during the rainy season the river levels rise and suspended solids transport increases (increased erosion) (Navarro & Maldonado 2002). In general, the Madre de Dios – Beni system, fed by the Orthon River, provides most of the water volume (50%) and sediment transport (77%) of the Madera River basin (Molina & Vauchel 2011) (Figure 3.2.2). Figure 3.2. 4 Location of rapids along the trans-boundary rivers Mamoré and Madera in the stretch between the cities of Porto Velho (Brazil) and Guayaramerín (Bolivia). Figure extracted and modified from Molina (2011). 66 In addition to the physiochemical differences observed between waters of the Upper Madera system, there is another element that influences the hydrological dynamics, and apparently also the differentiation and structure of strictly aquatic fauna. Before the confluence of the Beni – Madre de Dios and Mamoré – Iténez systems that form the Madera River proper from the community of Villa Bella, stands an uneven rocky bed (Precambrian outcrops) locally known as “cachuelas”. These rapids generate a drop in the water that passes over them and accelerate the flow, turning them turbulent (Molina 2011). On the Beni River, near its mouth on the Madera River, is the most important rapid of the Bolivian lowlands (in terms drop and size) called “Cachuela Esperanza” or Cachuela Esperanza rapids (Figure 3.2.3 a, b). On the Mamoré River, there are five rapids of various sizes that cross the river bed at different levels (Figure 3.2.3 c, d) between the city of Guayaramerín, and its mouth on the Madera River. These rapids are the last ones to the south of a series along the main stretch of the Madera River’s most upper reaches that belong to the countries of Brazil and Bolivia. This area, known as the upper portion of the Madera River, is characterized by a stretch that runs between steep banks (limited flood zone with stable and defined riverbed), and having 18 rapids of various sizes over a stretch of 360 Km (estimated drop of 60 m), between the cities of Porto Velho (Brazil) and the twin cities of Guyaramerín (Bolivia) and Guajaramerim (Brazil) (Molina 2011). There are four rapids in the Bolivian side on the Madera River, and of the 14 remaining in Brazil, two are the most important (Jirau and Teotônio), with an average drop of four metres almost year round (Figure 3.2.4). Sample collection design In biological terms, it has been suggested that the rapids in Bolivia and Brazil may have played a determining role as effective or partial barriers in the isolation and differentiation of species and communities of aquatic organisms in the upper portion of the Madera River and more properly in the Bolivian Amazon (e.g. Torrente-Vilara 2009; Carvajal-Vallejos & Zeballos 2011; Tavera et al. 2011). It has been demonstrated that there are several groups of fish of central Amazon that are also found in the lower Madera basin, but absent in its upper areas, and several species that appear to be restricted only to its upper reaches (Torrente-Vilara 2009; CarvajalVallejos & Zeballos 2011). Of the series of rapids in the upper portion of the Madera River, the Teotônio rapids (Porto Velho) seem to represent the dividing boundary for the communities of fish that are found on both sides (Torrente-Vilara 2009; TorrenteVilara et al. 2011), and possibly for aquatic mammals. There are several groups of fishes, mainly Siluriforms and Characiforms, known for their feeding and breeding longitudinal and lateral migratory movements in Amazon systems that can get through these rapids (Goulding 1980; Barthem & Goulding 1997; Araujo-Lima & Goulding 1997). Of these, migratory fish species of the family Pimelodidae are known for their outstanding movements and are caught annually during their passage through the rapid stretches. Considering the information on the biology of B. rousseauxii and the variability of aquatic systems in the Upper Madera basin (mainly Bolivian Amazon) the collection of Plateado samples was designed in two geographic scales: one local (main tributaries of the Upper Madera River portion) and another regional (main tributaries of the Amazon). 67 To define the collection points at the local level, the hydrological network layout and the information gathered through personal interviews with fishermen between 2005 2006 were the main considerations. Additionally, the information available in the literature on the biology and distribution of large pimelodids in the Madera basin were considered as reference (e.g. Goulding 1979; Goulding 1980; Barthem et al. 1991; Barthem & Goulding 1997; Lauzanne et al. 1999; Barthem et al. 2003; Barthem & Goulding 2007). Following this procedure, it was noted that the fish Plateado was caught by the commercial fishery in a relatively predictable manner during the rainy season and in rivers with turbid waters. The specimens caught had gonads in advanced stages of maturity and consequently it could be presumed they were within their reproductive season. This implied that its catch in Bolivia occurred more frequently in the rivers of Madera, Madre de Dios, Beni and Mamoré, and that they displaced themselves towards the headwaters during the high water season between the months of January to March. The presence of the Plateado in other systems such as Abuná, Orthon, Yata and Iténez, with less suspended solids, seemed sporadic and unpredictable; hence, sampling was not conducted in these water bodies. Therefore, considering the convergence of drainage, each turbid-water tributary was sampled in its upper and the lower areas. This allowed the comparison of the genetic variability in the upper and lower portions of the tributaries. Theoretically, if the species swim up river in a selective manner and each tributary has a panmitic unit distinct from the others, the signals of each unit could be identifiable below the confluence of the tributaries, as fractions of an entire group in which they are mixed (Figure 3.1.2). These same samples (Upper Madera) were used in the regional analysis and were completed with samples obtained from the market in Belen (Iquitos, Peru), as a reference point for the Ucayalí-Amazonas system. In total, 473 individuals of B. rousseauxii (Plateado) were collected between January 2005 and March 2009. Four hundred and eight Plateados were caught using gillnets of 20 - 24 mm mesh size in the principal channels of the rivers Madera (22, Villa Bella), Upper Beni (85, Rurrenabaque), Lower Beni (92, Cachuela Esperanza), Madre de Dios (58, Puerto Maldonado), Mamoré (5, Trinidad; 2, Guayaramerín) and Ichilo or Upper Mamoré (144, Puerto Villarroel), and 64 were purchased from the central market in the city of Iquitos (Belen market, Peru), where individuals from the Amazon systems Ucayalí and Marañon are unloaded and marketed (Figure 3.2.5). Additionally, one individual was purchased from the Requena market at the mouth of the Tapiche River on the Ucayali River (Figure 3.2.5; Table 3.2.1). For each individual caught or bought, approximately 1 cm3 of skeletal tissue (muscle) was extracted, deposited and preserved in a 15 or 10 mL plastic tube in 98% alcohol (ethanol). For most specimens caught in the areas of Cachuela Esperanza (Lower Beni) and Puerto Villarroel (Upper Mamoré), sex was determined and recorded by direct observation of the gonads (ovaries or testes). The tissue samples were kept in darkness at room temperature and passed through two changes of alcohol at 24 h and 5 days after collection, respectively. 68 Figure 3.2. 5 Map of sampling locations of Plateado (Brachyplatystoma rousseauxii) in the Madera River basin and western Amazon (Bolivia and Peru), and locations with available information in the Central Amazon (Brazil). Red circles represent locations sampled between 2005 – 2009, and blue circles represent locations in Brazil that have sequences deposited in GenBank by Batista & Alves-Gomez 2006 that were included in the CR analysis. Numbers next to the localities’ names represent the individuals collected in those points. Oblique black bars represent the rapids series in the Upper Madera basin, between Bolivia and Brazil. 69 Table 3.2.1 List of Brachyplatystoma rousseauxii (Plateado) individuals collected by area and location in the Upper Madera River basin and western Amazon. Dark bars in the CR (Control Region) and MS (microsatelite) columns show the individuals that were analyzed for each molecular marker. Especie Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii 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Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Localidad Río Madera, Cachuela Madera Río Madera, Cachuela Madera Río Madera, Cachuela Madera Río Madera, Cachuela Madera Río Beni, Capitanía de Puerto Río Beni, Capitanía de Puerto Río Madera, Cachuela Madera Río Madera, Cachuela Madera Río Beni, comunidad Villa Bella Río Mamoré, Capitania de Puerto Río Mamoré, Cachuela Mamoré Río Mamoré, Cachuela Mamoré Río Mamoré, comunidad de Villa Bella Río Mamoré, comunidad de Villa Bella Río Madera, Cachuela Madera Río Madera, Cachuela Madera Río Beni, comunidad Villa Bella Río Beni, comunidad Villa Bella Río Beni, comunidad Villa Bella Río Beni, comunidad Villa Bella Río Beni, comunidad Villa Bella Río Beni, comunidad Villa Bella Río Beni, comunidad Cachuela Esperanza Río Beni, 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Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Fecha 07-jun-07 07-jun-07 13-jun-06 13-jun-06 07-jul-06 13-jul-06 15-jul-06 28-jul-06 09-may-07 24-abr-07 01-ago-07 01-ago-07 07-may-08 20-abr-08 01-ago-07 16-jun-08 19-sep-07 16-jul-08 03-ago-08 03-ago-08 04-ago-08 04-ago-08 05-mar-06 10-mar-06 16-mar-06 17-abr-06 09-jun-06 01-ago-06 08-sep-06 04-nov-06 05-nov-06 19-ene-07 24-ene-07 03-feb-07 04-feb-07 07-feb-07 14-feb-07 14-feb-07 15-feb-07 16-feb-07 16-feb-07 21-feb-07 23-feb-07 28-feb-07 01-mar-07 08-mar-07 10-mar-08 11-mar-08 14-mar-07 15-mar-07 24-mar-07 01-abr-07 26-abr-07 27-abr-07 15-may-07 25-jun-07 26-jul-07 04-jul-07 05-jul-07 20-ago-07 04-ene-08 19-ene-08 25-ene-08 02-feb-08 03-feb-08 08-feb-08 12-feb-08 13-feb-08 17-feb-08 28-mar-08 28-mar-08 29-mar-08 29-mar-08 01-abr-08 01-abr-08 02-abr-08 04-abr-08 04-abr-08 05-abr-08 13-abr-08 15-abr-08 16-abr-08 21-abr-08 22-abr-08 23-abr-08 23-abr-08 06-may-08 08-may-08 24-jul-08 01-ago-08 01-ago-08 10-oct-08 13-oct-08 23-oct-08 13-nov-08 15-nov-08 Latitud -10.363381 -10.363381 -10.363381 -10.363381 -10.388307 -10.388307 -10.363381 -10.363381 -10.394738 -10.388143 -10,373000 -10,373000 -10.396738 -10.396738 -10.363381 -10.363381 -10.394738 -10.394738 -10.394738 -10.394738 -10.394738 -10.394738 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 Longitud -65.378862 -65.378862 -65.378862 -65.378862 -65.392287 -65.392287 -65.378862 -65.378862 -65.394756 -65.390386 -65,388445 -65,388445 -65.384879 -65.384879 -65.378862 -65.378862 -65.394756 -65.394756 -65.394756 -65.394756 -65.394756 -65.394756 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 Código VB2 VB3 VB4 VB5 VB6 VB7 VB8 VB9 VB12 VB22 GEN2862 GEN2863 GEN3098 GEN3428 MaVB1 MaVB8 RoVB1 RoVB41 RoVB42 RoVB43 RoVB44 RoVB45 CE1 CE2 CE3 CE4 CE5 CE7 CE8 CE9 CE10 CE11 CE12 CE14 CE15 CE17 CE18 CE19 CE20 CE21 CE22 CE23 CE24 CE26 CE27 CE28 CE29 CE30 CE31 CE32 CE33 CE34 CE35 CE36 CE37 CE39 CE40 CE41 CE42 CE43 CE44 CE45 CE46 CE47 CE48 CE49 CE50 CE51 CE52 CE53 CE54 CE55 CE56 CE57 CE58 CE59 CE60 CE61 CE62 CE63 CE64 CE65 CE66 CE67 CE68 CE69 CE70 CE71 CE72 CE73 CE74 CE75 CE76 CE77 CE78 CE79 RC MS x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x 70 Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Cachuela Esperanza Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Puerto Maldonado Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Beni, comunidad Cachuela Esperanza Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios,comunidad Puerto Maldonado Río Madre de Dios, El Carmen Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Rurrenabaque Río Beni, Boca arroyo Tequeje Río Beni, Cachichira Río Beni, Soraida Río Beni, Boca arroyo Enapurera Río Beni, Boca arroyo Enapurera Río Beni, Boca arroyo Enapurera Río Beni, Boca río Negro Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Altamarani Río Beni, Sorayda Río Beni, Altamarani Río Beni, Jiruma Río Beni, Jiruma 15-ene-09 19-ene-09 20-ene-09 27-ene-09 28-ene-09 29-ene-09 01-feb-09 01-feb-09 02-feb-09 04-feb-09 14-feb-09 17-feb-09 07-mar-09 12-mar-09 12-mar-09 15-mar-09 17-mar-09 17-mar-09 19-ago-08 19-ago-08 20-ago-08 21-ago-08 21-ago-08 21-ago-08 22-ago-08 23-ago-08 23-ago-08 23-ago-08 23-ago-08 27-ago-08 27-ago-08 27-ago-08 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 07-may-09 08-may-09 08-may-09 08-may-09 10-may-09 10-may-09 10-may-09 10-may-09 10-may-09 10-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 15-may-09 21-may-09 21-may-09 21-may-09 21-may-09 21-may-09 06-may-09 06-may-09 06-may-09 06-may-09 07-may-09 07-may-09 07-may-09 26-mar-09 06-may-05 06-may-05 06-may-05 06-may-05 06-may-05 06-may-05 * 08-jul-07 08-jul-07 22-jul-07 04-ago-07 05-ago-07 05-ago-07 01-sep-07 12-oct-07 12-oct-07 12-oct-07 13-oct-07 13-oct-07 21-oct-07 26-oct-07 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -10.532360 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -12.593581 -11.346031 -14.299425 -14.299425 -14.299425 -14.299425 -14.299425 -14.299425 -14.440484 -13.514744 -13.978886 -14.075481 -13.601385 -13.601385 -13.601385 -13.032039 -14.299425 -14.299425 -14.334447 -14.075481 -14.334447 -14.344756 -14.344756 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -65.585639 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.172719 -67.151002 -67.525581 -67.525581 -67.525581 -67.525581 -67.525581 -67.525581 -67.533113 -67.389017 -64.477419 -67.502357 -67.389355 -67.389355 -67.389355 -67.030386 -67.525581 -67.525581 -67.557681 -67.502357 -67.557681 -67.557175 -67.557175 CE80 CE81 CE82 CE83 CE85 CE86 CE87 CE88 CE89 CE91 CE96 CE98 CE106 CE108 CE109 CE110 CE111 CE112 900002 900023 900060 900073 900099 900127 900133 900160 900165 900166 900167 900171 900172 900173 900178 900179 900180 900181 900182 900183 900184 900185 900186 900187 900188 900189 900190 900191 900192 900193 900194 900195 900196 900197 900198 900199 900200 900201 900202 900203 900204 900205 900206 900207 900208 900209 900210 900211 900212 900213 900214 900215 900216 900217 900218 900219 900220 NGRI14 BF7185 BF7186 BF7189 BF7190 BF7191 BF7192 D1 RU4 RU5 RU8 RU9 RU10 RU12 RU13 RU17 RU18 RU19 RU20 RU21 RU25 RU27 x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x 71 Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Rurrenabaque Guayaramerín Guayaramerín Guayaramerín Trinidad Trinidad Trinidad Trinidad Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Río Beni, Jiruma Río Beni, Jiruma Río Beni, Rurrenabaque Río Beni, Rurrenabaque Río Beni, Licatawa Río Beni, Limón Río Beni, Boca río Negro Río Beni, Boca río Negro Río Beni, Boca río Negro Río Beni, Boca río Negro Río Beni, Limón Río Beni, Limón Río Beni, Limón Río Beni, Limón Río Beni, Limón Río Beni, Salinas Río Beni, Salinas Río Beni, Jiruma Río Beni, Copaina Río Beni, Copaina Río Beni, Copaina Río Beni, Boca arroyo Tequeje Río Beni, Boca arroyo Tequeje Río Beni, Tarene (arriba boca Tequeje) Río Beni, Boca arroyo Tequeje Río Beni, Jiruma Río Beni, comunidad Eyiyoquibo Río Beni, Buena Vista (arriba de Jiruma) Río Beni, Boca arroyo Maije Río Beni, Limón Río Beni, Jiruma Río Beni, Jiruma Río Beni, Jiruma Río Beni, Copaina Río Beni, Jiruma Río Beni, Copaina Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Motacusal Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Jiruma Río Beni, Jiruma Río Beni, Jiruma Río Beni, Altamarani Río Beni, Altamarani Río Beni, Altamarani Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Boca arroyo Maije Río Beni, Altamarani Río Beni, Boca arroyo Tequeje Río Beni, Boca arroyo Napurera Río Mamoré, Boca del río Iténez Río Mamoré, Estancia Warnes Río Mamoré, Camiaco Río Mamoré, San Antonio de Lora Río Mamoré, San Antonio de Lora Río Mamoré Río Mamoré Río Ichilo, Boca río Isarzama (segundo corte) Río Ichilo, Chiquiño Río Ichilo, Chiquiño Río Ichilo, Boca río Isarzama (segundo corte) Río Ichilo, Remanso Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, La Pampita Río Ichilo, La Pampita Río Ichilo, Recta Larga Río Ichilo, Corte Tapado Río Ichilo, Corte Tapado Río Ichilo, La Pampita Río Ichilo, Recta Larga Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré 26-oct-07 26-oct-07 16-dic-06 18-jul-07 15-jul-07 03-jul-07 10-ago-07 10-ago-07 22-ago-07 22-ago-07 15-sep-07 02-oct-07 02-oct-07 02-oct-07 26-dic-07 03-ene-08 03-ene-08 03-ene-08 10-ene-08 10-ene-08 10-ene-08 11-abr-08 21-abr-08 21-abr-08 21-abr-08 02-dic-07 02-dic-07 02-dic-07 02-dic-07 03-dic-07 07-dic-07 07-dic-07 07-dic-07 07-dic-07 07-dic-07 14-ene-08 25-abr-08 25-abr-08 29-abr-08 29-abr-08 10-may-08 10-may-08 10-may-08 12-may-08 17-may-08 17-may-08 17-may-08 17-may-08 17-may-08 02-dic-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 23-may-08 28-may-08 28-may-08 30-jun-08 22-ago-08 06-sep-06 26-ago-06 11-jul-06 11-jul-06 28-jul-06 16-sep-06 16-feb-05 16-feb-05 16-feb-05 16-feb-05 16-feb-05 17-feb-05 17-feb-05 17-feb-05 17-feb-05 17-feb-05 18-feb-05 19-feb-05 19-feb-05 19-feb-05 20-feb-05 17-feb-05 17-feb-05 17-feb-05 17-feb-05 17-feb-05 17-feb-05 22-feb-05 22-feb-05 22-feb-05 22-feb-05 23-feb-05 -14.344756 -14.344756 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RU29 PPT3 PPT119 GEN2648 GEN2706 GEN2714 GEN2716 GEN2719 GEN2721 GEN2723 GEN2726 GEN2727 GEN2728 GEN2729 GEN2730 GEN2731 GEN2732 GEN2733 GEN2734 GEN2735 GEN2736 GEN2737 GEN2738 GEN2739 GEN3189 GEN3196 GEN3199 GEN3200 GEN3231 GEN3310 GEN3311 GEN3313 GEN3314 GEN3318 GEN3369 GEN3430 GEN3431 GEN3432 GEN3433 GEN2741 GEN2742 GEN2743 GEN2744 GEN2745 GEN2746 GEN2747 GEN2748 GEN2749 GEN3187 GEN3264 GEN3265 GEN3266 GEN3267 GEN3268 GEN3300 GEN3301 GEN3302 GEN3303 GEN3304 GEN3305 GEN3322 GEN3324 GEN3327 GU1 GU8 PST9 TR1 TR2 TR3 TR4 BR1 BR2 BR3 BR4 BR5 BR6 BR7 BR8 BR9 BR10 BR11 BR12 BR13 BR14 BR15 BR16 BR17 BR19 BR20 BR21 BR22 BR23 BR25 BR26 BR27 BR28 x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x 72 Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Santa Lucia Río Ichilo, Corte del Dono Río Ichilo, Recta de Capernaun Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Corte del Dono Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Puerto Pallar Río Ichilo, Boca río Chimoré Río Ichilo, Santa Lucia Río Ichilo, Santa Lucia Río Ichilo, Boca río Chimoré Río Ichilo, Puerto Pallar Río Ichilo, Puerto Pallar Río Ichilo, Recta Chiquiño Río Ichilo, La Pampita Río Ichilo, Recta Larga Río Ichilo, La Pampita Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, comunidad Mónica Río Ichilo, comunidad Mónica Río Ichilo, comunidad Mónica Río Ichilo, Remanzo de los Crucos Río Ichilo, Remanzo de los Crucos Río Ichilo, Recta del Mapajo Río Ichilo, Recta del Mapajo Río Ichilo, Recta del Mapajo Río Ichilo, Recta Chiquiño Río Ichilo, Recta Chiquiño Río Ichilo, Recta Chiquiño Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Recta Larga Río Ichilo, Arroyo del Callapo Río Ichilo, Arroyo del Callapo Río Ichilo, La Quince Río Ichilo, Recta El Remanso Río Ichilo, Recta Chiquiño Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Encanopo Río Ichilo, Recta Larga Río Ichilo, La Quince Río Ichilo, La Quince Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, El Peligro Río Ichilo, El Peligro Río Ichilo, El Peligro Río Ichilo, El Peligro Río Ichilo, comunidad Mónica Río Ichilo, comunidad Mónica Río Ichilo, Boca río Ibabo Río Ichilo, comunidad Las Flores Vieja Río Ichilo, comunidad Mónica Río Ichilo, Boca río Chimoré Río Ichilo, Cruce de Yacarena Río Ichilo, Corte Hondo, Papi Camacho Río Ichilo, Corte del Dono Río Ichilo, Boca río Chimoré Río Ichilo, Boca río Chimoré Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta de Mónica Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta del Dono Río Ichilo, Recta Chiquiño Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Recta Larga 23-feb-05 23-feb-05 23-feb-05 23-feb-05 09-mar-05 11-mar-05 11-mar-05 11-mar-05 11-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 12-mar-05 13-mar-05 13-mar-05 18-mar-05 18-mar-05 18-mar-05 29-mar-05 29-mar-05 29-mar-05 29-mar-05 29-mar-05 29-mar-05 29-mar-05 30-mar-05 31-mar-05 31-mar-05 03-abr-05 03-abr-05 03-abr-05 16-mar-06 16-mar-06 16-mar-06 16-mar-06 17-mar-06 17-mar-06 17-mar-06 18-mar-06 18-mar-06 18-mar-06 18-mar-06 18-mar-06 18-mar-06 21-mar-06 22-mar-06 22-mar-06 23-mar-06 23-mar-06 03-abr-06 03-abr-06 04-abr-06 04-abr-06 04-abr-06 04-abr-06 04-abr-06 05-abr-06 05-abr-06 08-abr-06 08-abr-06 08-abr-06 08-abr-06 12-abr-06 12-abr-06 12-abr-06 12-abr-06 20-abr-06 20-abr-06 24-abr-06 24-abr-06 17-nov-06 22-abr-06 22-abr-06 23-nov-06 23-nov-06 29-ene-07 29-ene-07 12-mar-07 12-mar-07 12-mar-07 12-mar-07 12-abr-07 12-may-07 12-may-07 12-jun-07 12-ago-07 22-dic-07 24-dic-07 24-dic-07 24-dic-07 -16.740558 -16.740558 -16.740558 -16.740558 -16.691532 -16.732619 -16.614109 -16.740558 -16.740558 -16.740558 -16.740558 -16.732619 -16.740558 -16.740558 -16.740558 -16.764319 -16.740558 -16.691532 -16.691532 -16.740558 -16.764319 -16.764319 -16.987445 * -16.962148 * -16.740558 -16.740558 -16.740558 -16.740558 -16.720245 -16.720245 -16.720245 -16.376931 -16.376931 -16.304392 -16.304392 -16.304392 -16.987445 -16.987445 -16.987445 -16.962148 -16.962148 -16.019447 -16.019447 -16.962148 -16.941457 -16.941457 -16.925686 -16.939276 -16.987445 -16.962148 -16.962148 -16.962148 * -16.962148 -16.925686 -16.925686 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.740558 -16.586256 -16.586256 -16.586256 -16.586256 -16.720245 -16.720245 -16.436903 -16.471259 -16.720245 -16.740558 * -16.663034 -16.732619 -16.740558 -16.740558 -16.732619 -16.732619 -16.732619 -16.732619 -16.720245 -16.732619 -16.732619 -16.732619 -16.732619 -16.987445 -16.962148 -16.962148 -16.962148 -64.844170 -64.844170 -64.844170 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BR29 BR30 BR31 BR32 BR33 BR35 BR36 BR37 BR38 BR40 BR41 BR42 BR43 BR44 BR45 BR46 BR47 BR48 BR49 BR50 BR52 BR53 BR54 BR55 BR56 BR57 BR58 BR59 BR60 BR61 BR62 BR63 BR64 BR65 BR66 BR67 BR68 BR69 PV2 PV3 PV4 PV6 PV8 PV9 PV10 PV13 PV14 PV15 PV16 PV17 PV18 PV19 PV20 PV21 PV24 PV25 PV26 PV27 PV28 PV29 PV30 PV31 PV32 PV33 PV34 PV35 PV36 PV37 PV38 PV39 PV40 PV41 PV42 PV48 PV49 PV57 PV58 PV91 PV96 PV98 PV99 PV100 PV168 PV169 PV172 PV173 PV174 PV175 PV186 PV194 PV195 PV202 PV204 PV209 PV212 PV213 PV214 x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x 73 Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Brachyplatystoma rousseauxii Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Bolivia Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Perú Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Puerto Villarroel Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Iquitos Río Ichilo, La Pampita Río Ichilo, La Pampita Río Ichilo, La Pampita Río Ichilo, La Pampita Río Ichilo, Boca río Isarzama Río Ichilo, Corte Tapado Río Ichilo, La Pampita Río Ichilo, La Pampita Río Ichilo, colonia Majusal Río Ichilo, Río Viejo Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Recta Larga Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Boca río Isarzama Río Ichilo, Corte Tapado Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado de Requena, comunidad de Requena Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos Mercado Belén, ciudad de Iquitos 24-dic-07 24-dic-07 24-dic-07 26-dic-07 26-dic-07 26-dic-07 27-dic-07 27-dic-07 06-ene-08 07-ene-08 07-ene-08 08-ene-08 15-feb-08 05-mar-08 07-mar-08 07-mar-08 09-mar-08 13-mar-08 13-mar-08 13-mar-08 14-mar-08 18-jul-08 07-ago-08 07-ago-08 07-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 12-ago-08 09-ago-08 09-ago-08 09-ago-08 09-ago-08 26-mar-07 21-abr-07 25-sep-08 25-sep-08 16-sep-08 02-oct-08 02-oct-08 03-oct-08 03-oct-08 03-oct-08 07-oct-08 07-oct-08 07-oct-08 07-oct-08 07-oct-08 07-oct-08 09-oct-08 09-oct-08 09-oct-08 09-oct-08 09-oct-08 09-oct-08 09-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 10-oct-08 13-oct-08 13-oct-08 13-oct-08 13-oct-08 13-oct-08 13-oct-08 13-oct-08 13-oct-08 * * * * -16.019447 -16.997113 * * -17.029740 -17.007101 -16.962148 -16.962148 -16.962148 -16.019447 -16.019447 -16.019447 -16.019447 -16.019447 -16.019447 -16.019447 -16.997113 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -5.052709 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 -3.759340 * * * * -64.684470 -64.671628 * * -64.641806 -64.626664 -64.687696 -64.687696 -64.687696 -64.684470 -64.684470 -64.684470 -64.684470 -64.684470 -64.684470 -64.684470 -64.671628 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.851415 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 -73.295155 PV215 PV216 PV217 PV220 PV221 PV222 PV225 PV226 PV227 PV229 PV234 PV235 PV241 PV244 PV245 PV247 PV248 PV249 PV250 PV251 PV253 859 864 866 867 911 912 913 914 915 916 917 918 919 921 922 923 924 925 926 927 931 932 933 934 80055 80072 80094 80095 80103 80104 80105 80106 80107 80108 80109 80110 80111 80112 80113 80114 80116 80117 80118 80120 80121 80122 80123 80124 80125 80126 80127 80128 80129 80130 80131 80132 80133 80134 80135 80136 80137 80138 80139 80140 80141 x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x x Laboratory Methodology and DNA Extraction Genomic DNA was extracted from muscle samples preserved in alcohol (ethanol) following a modification in the CTAB procedure developed by Doyle & Doyle (1987). Extraction consisted of preheating the extraction solution (5 % hexadecyltrimethyl ammonium bromide [CTAB, Sigma], NaCl 5M, EDTA 0.5 M pH 8, 1 M Tris-Hcl) at 60 ºC in a bain-marie or stove. Subsequently, approximately 100 mg of ground muscle tissue was placed in a tube (2mL) with 1 mL of preheated CTAB extraction solution plus 15 µL of Proteinase K (10 mg/mL) (Sigma). This tube was incubated at 60 ºC 74 (bain-marie or stove) for 8 - 10 hours, with occasional agitation every 2 - 3 hours to accelerate and improve digestion. Once the solution looked homogenous and the muscle pieces were digested, 1 mL of chloroform was added and the content was mixed vigorously (5 min) prior to submitting to 8 000 rpm for 5 minutes. After centrifugation, 750 µL of supernatant were transferred to a sterile tube (1.5 mL) to be stirred gently (2 min) with 750 µL of Isopropanol at – 5 ºC. This mixture was allowed to stand at - 20 ºC for 2 hours to precipitate the DNA. After the resting period, the solution was placed in a centrifuge at 13 000 rpm for 15 minutes to separate and concentrate the DNA in the form of a white pellet on the sides and bottom of the tube. The solution surrounding the pellet was carefully discarded and replaced with 750 µL of 70% Ethanol for a final 15 minute wash at 13 000 rpm. After the wash, the ethanol was removed from the tube and the pellet was allowed to dry at room temperature for 5 - 7 hours to allow residual Ethanol to evaporate. Finally, the resulting DNA was suspended in 50 µL Milli-Q water for its subsequent dilution and use in the amplification reactions. Genetic Analysis Nuclear (microsatellite) DNA Analysis Microsatellites are co-dominant molecular descriptors made up of tandems (up to 100 times) consisting of 1 to 5 base pairs. They are widely distributed in the genome of many taxa and are highly variable in length (many alleles). They are also known as single sequence repeats (SSR). This property has made them useful descriptors to assess the genetic structure of populations in molecular ecological studies (Jarne & Lagoda 1996). As a result of its widespread use, understanding of its mutational behaviour, function, evolution and distribution in taxa genomes, is increasing rapidly (Ellegren 2004). Microsatelites have also been successfully used to study the evolutionary relationships among groups that have evolved independently for millions of years (e.g. Bowcock et al. 1994; Goldstein et al. 1995). However, these descriptors have attributes that limit their usefulness in this area due to the fact that they have a high mutation rate and the size variation can be small. The mutation could be a homogenizing factor due to the homoplasy at the size level (e.g. lead to the appearance of alleles already in existence), that can surpass the diversifying effect of genetic drift, especially in large populations where drift is more limited (Richard & Thorpe 2001). Therefore, the genetic divergence measures using microsatellite data can be stabilized quickly over time (e.g. Paetkau et al. 1997). Microsatellites have emerged as one of the most popular options for population studies, in part because they have the potential to provide contemporary migration estimates, allow linkage analysis, distinguish relatively high migration rates (panmixia), and estimate the degree of relatedness between individuals (Selkoe & Toonen 2006). Dinucleotide, trinucleotide, and tetranucleotide repetitions are the most common choices for molecular genetic studies. Of these, dinucleotide repetitions occur for most microsatellites in many species. The DNA surrounding a microsatellite locus is known as the flanking region. Since the sequences in the flanking region are generally conserved (identical) among individuals of the same species, and sometimes in different species, a particular microsatellite locus can be identified by its flanking sequence. Unlike the flanking regions, the repetition of microsatellite sequence mutates frequently by slippage (Schlötterer 2000) and 75 proofreading errors during DNA replication that mainly change the number of repetitions and therefore the repetition chain length (Eisen 1999). Chains with and without a functional recombination system have been shown to have a similar mutation rate, suggesting that recombination is not the predominant mechanism that generates the variability in microsatellites (Schlötterer 2000). Since alleles differ in length, they can be distinguished by electrophoresis with high resolution gels (e.g. sequencer) (Selkoe & Toonen 2006). Many microsatellites have high mutation rates (between 10-2 and 10-6 mutations per locus per generation, and an average of 5 x 104 ) (Schlötterer 2000), which generates the high levels of allelic diversity necessary for population genetic studies of processes acting on ecological time scales. The microsatellite polymorphism analysis was performed on 10 loci using fluorescently labeled primers (FAM, HEX, NED). The primers used were designed for Pseudoplatystoma corruscans, by Revaldaves et al. (2005) (Pcor1, Pcor2, Pcor7, Pcor8; primers Pcor), and B. rousseauxii, by Batista et al. (2009) (BR37, BR38, BR44, BR45, BR47, BR49; primers BR). The four primers by Revaldaves et al. (2005) were selected from eight available by the same authors, based on a prior assessment of fragment polymorphism, the quality of their amplification, and the fragment size. Thirty individuals from three locations (Villa Bella, Puerto Maldonado and Puerto Villarroel) were analyzed for the eight loci with the primers Pcor1, Pcor2, Pcor5, Pcor6, Pcor7, Pcor8, Pcor10 and Pcor21. The Pcor5 primer amplified different sized fragments (seen in 8% polyacrylamide gels stained with silver nitrate) but it was not possible to visualize and quantify its size by capillary gel electrophoresis as sizes exceeded the reference limit of the standard marker (GeneScanTM -500 ROXTM) and the sequencer’s reading extent (500 pb). In turn, amplification with the primer Pcor6 produced a single reading profile for all the individuals, which was made up of a series of multiple peaks of confusing interpretation of a two base pair difference. Furthermore, the primers Pcor10 and Pcor21 produced monomorphic fragments (86 and 104 bp each one) in the 30 individuals considered. Microsatellite amplification by polymerase chain reaction (PCR) was carried out on a Mastercycler thermocycler ep (Eppendorff AG 2231 Hamburg). Fragments amplified with Pcor1, Pcor2, Pcor7 and Pcor8 primers were obtained in a total volume of 10 µL consisting of 2.0 µL of 5X reaction buffer (Colorless GoTaq Promega, 7.5 mM MgCl2 at pH 8.5), 0.6 µl of MgCl2 (25 mM), 1.0 µL of dNTPs (1 mM each dNTP), 0.4 µL of each primer (forward and backward,10 µM), 0.4 U of polymerase Taq (GoTaq Promega), approximately 50 ng DNA extract and 4.02 µL Milli-Q water. The temperature profile to which the mixture was subjected consisted of an initial denaturation at 94 ºC (2 min); followed by 35 denaturation cycles at 94ºC (30 s), annealing at 57 ºC (Pcor1), 58 ºC (Pcor2), 62 ºC (Pcor7), 61ºC (Pcor8) (30 s), elongation at 72 ºC (40 s); and one final elongation at 72 ºC (30 min) to finish at 4 ºC and refrigerate the products. Amplifications with the remaining primers (BR) were designed and made by duplex 1 (BR37-BR38), duplex 2 (BR44-BR45), and duplex 3 (BR47-BR49). Compatibility and grouping of the primers for the formation of the duplexes was evaluated with the program MULTIPLX version 1.2 (Kaplinski et al. 2004). All duplex reactions were carried out in a final volume of 10 µL which was composed of 2 µL de 5X reaction buffer (Colorless GoTaq Promega, 7.5 mM MgCl2 at pH 8.5), 0.6 µL of MgCl2 (25 76 mM), 2.0 µL of dNTPs (10 mM each dNTP), 0.2 µL of each primer for duplex 1, 0.07 µL (BR44) and 0.12 µL (BR45) for duplex 2, 0.08 µL (BR47) and 0.1 µL (BR49) for duplex 3 (all primers at 10 µM), 0.5 U of Taq polymerase (GoTaq Promega), approximately 50 ng of DNA extract, and the corresponding difference with Milli-Q water for each duplex. The temperature profile to which the mixture was subjected consisted of an initial denaturation at 94 ºC (2 min), followed by 32 denaturation cycles at 94 ºC (30 s), annealing at 62 ºC (duplex 1 and 2) or 60 ºC (duplex 3) (35 s), elongation at 72 ºC (40 s); and a final elongation at 72 ºC (30 min) prior to dropping to 4 ºC for cooling. Every PCR reaction performed included a negative control reaction tube, which included all the reagents except for the DNA template. The PCR products were electrophoretically visualized and separated in an automated sequencer ABI 3130 (Applied Biosystems). Allele sizes were defined in relation to the standard size marker GeneScanTM -500 ROXTM (Applied Biosystems) (primers Pcor) and GeneScan -500(-250) ROXTM (Applied Biosystems) (primers BR) using analyses from the program PEAKSCANNERTM version 1.0 (Applied Biosystems). The size or name of alleles was determined based on the values (to one decimal place) obtained with the program PEAKSCANNER version 1.0 (Applied Biosystems 2006) and grouping of individuals into sets with internal close continuous differences (0.1-0.2 bp variation). Thus, one set of values was assigned to one size (allele) when the differences between them showed a continuous variation pattern (0.1-0.2 bp), and they differentiated globally from another set with at least one pair of bases. The locus obtained with the Pcor7 primer was tentatively made up of 15 alleles with a repeat motif of two pairs of bases. Of this total number of alleles or sets, six of them, known as 230, 232, 234, 236, 238 and 240, showed no significance difference between their limits. Intervals between sets (alleles) were inferior to a base pair and the allocation of various individuals was ambiguous. Due to this incongruous pattern, all alleles that were assigned within these sets (230.8 – 240.9 bp) were designated as allele 236 in the analyses. In the population analyses performed the information obtained with the locus Pcor8, which was composed of eight alleles, was not considered. This locus showed a significant deviation from HWE at different composition levels (e.g. global and by sampling locality) and generated relatively inconsistent data in relation to the information obtained with the other loci. In several situations Pcor8 showed disequilibrium (non panmixia) as opposed to the remaining loci that approached panmixia. An analysis with the program MICRO-CHEKER version 2.2.3 (Van Oosterhout et al. 2004) (data not shown), revealed that this locus may contain null alleles and its significant deviation from HWE could be due to this factor. On this hypothesis, Castro (2010) recently showed that the locus Pcor8 cannot amplify all existing alleles in a fish of the same family Pimelodidae (Pseudoplatystoma fasciatum (Linnaeus, 1766)). However, this fish belongs to another species or lineage with a different history to that of Plateado, and an alternative explanation for the deviation from HWE could be the existence of a strong selection pressure that determines the frequency and combination of this locus’s alleles in natural populations. 77 Identification of panmitic units (cluster analysis) and population structure Based on the knowledge available on B. rousseauxii, which generally indicates that the species undergoes great migrations throughout its life cycle, there were no major reasons to make a comparison between a priori defined sets following geographic (e.g. geographic origin of samples) or ecological (e.g. habitat type, basin) criteria. In dealing with a species of large displacements there is a high probability that geographic samples may be constituted of individuals belonging to different uncertain units (if such units exist). Therefore, we first evaluated the Hardy-Weinberg Equilibrium (HWE) for all the individuals together (284 specimens spread over six locations, see Table 3.2.1) to determine if they formed a single panmitic unit. For this purpose, the estimator f of the index of endogamy FIS was used as a measure of the deviation from HWE with the program GENETIX version 4.05.2 (Belkhir et al. 2004). When a deviation from HWE was observed, the population genetic structure was then investigated, including gene flow between intrinsic units collected in the region using a Bayesian approximation, which consisted of a cluster analysis on various levels of hierarchy. For this purpose, the Bayesian Analysis of Population Structure (BAPS) version 5.2 (Corander et al. 2003; 2004) was used since its performance at correctly identifying subpopulations with FST values as low as 0.02 – 0.03 was recently demonstrated (e.g. Latch et al. 2006). The programme STRUCTURE also showed similar performance (Pritchar et al. 2000; Falush et al. 2003), whereas other programs, such as PARTITION (Dawson & Belkhir 2001), can only perform a good subpopulation identification with FST values ≥ 0.09 (Rodríguez-Ramilo et al. 2009). BAPS allows for a grouping of individuals (forming of source panmitic groups) independent of the location where they were captured, and generate a cluster of individuals in relation to a mixing model that takes into account and maintains the known origin of each individual (Corander et al. 2006; 2008), among other functions. The algorithm it uses treats allelic frequencies of a molecular descriptor (or nucleotide frequencies for DNA sequence data), and the number of genetically divergent groups in the population as random variables (Corander et al. 2009). At the same time, it assumes the source populations are in HWE, in linkage equilibrium, and have a relatively low mutation rate (Corander et al. 2003). BAPS considers each stock as a unit rather than as individuals separately, and it can use previous information on the geographic layout of the samples to conduct the analysis if this information is included. The procedure is based on the estimation of allelic frequencies and in determining which of the populations have different allele frequencies, rather than assigning individuals in populations with HWE based on their multilocus genotypes. This information is then used to recalculate allele frequencies in populations redefined most possibly as panmitic. Thus, the method represents a sophisticated estimator of basic allelic differentiation among populations and the time required for calculations is extremely short compared to other programs. The procedure for estimating the optimal number of subpopulations (K, grouping of individuals) with the highest probability, consisted of executing 10 independent runs of the program with a vector made up of 10 repetitions of each K = 2 – 8 value, assuming correlated allele frequencies and a mixture model. The subsequent probability was then calculated for each K value, using the logarithm of estimated marginal probability of K (log-likelihood of partitions that were visited during the 78 treatment), in order to choose the optimal K value. The subsequent probability for the different K values in each run represents only an approximate estimation. It is not generally very informative as the parameter space of maximum likelihood is very broad and therefore, there are many possible solutions (Corander et al. 2006). To obtain the best probability of the number of groups or clusters, the program must be run several times, giving a vector of values for K as indicated above. The probability was computed on the basis of the best partitions that were visited during all runs and the number of clusters inferred (K) was evaluated by the mode value on the replicas. Once the most probable numbers of inferred clusters were identified, separate runs consisting of 100 and 1000 repetitions were executed. This procedure helped choose the best partition and assignation according to the logarithm of the highest marginal probability (log(mp)) value, and to counterbalance the uncertainty regarding the number of groups obtained. The next step in the analysis involved the assignation of individuals to each of the K cluster. Samples were placed in their respective cluster based on the Bayes Factor logarithm value, in such a way that the exp(‘absolute change value’) indicates how many times the optimal partition is better. When the individual is in an optimal solution the value is zero. Very small absolute change values (< 2.3, the program manual recommends to see Kass & Raftery 1995), indicate that the individual could also be possibly assigned to the alternative cluster (Corander et al. 2008). This is one reason why some individuals were assigned to different clusters when several runs were carried out independently. It is important to mention that sometimes the size of clusters obtained can provide additional information for choosing the most optimal partition. Often when the population structure is weak, small groups of individuals (e.g. 1-8 individuals) can be generated with little apparent biological significance and that can lead to an overestimation in the number of populations. In these cases, one could choose to assume the existence of a smaller K that facilities the interpretation of the information’s tendency and prevent the overestimation of the number of populations. Lastly, the relative distance among the clusters inferred by BAPS was visualized, according to the most optimal partition, in a tree generated with the same program according to the criteria of the nearest neighbour (Neighbour Joining) and using the Kullback-Leibler divergence matrix provided at its output. To determine the difference among clusters, the variance of allelic identity (Fstatistics, FST; Weir & Cockerham 1984) and of allelic size (R-statistics, RST; Slatkin 1995) were compared. However, it was decided to work according to the FST values rather that the RST values due to the better estimate performance of FST when divergence among units is expected to be low (Balloux & Goudet 2002). FST values (estimated by θ) and RST (estimated by ρ) between pairs, were calculated using the programs GENETIX version 4.05.2 (Belkhir et al. 2004) and RST CALC version 2.2 (Goodman 1997), respectively, and their significance was assessed starting at 1000 permutations. 79 Intrapopulational genetic diversity, Hardy-Weinberg equilibrium and linkage disequilibrium The genetic variability for each identified cluster was quantified and evaluated with standard descriptive statistics (alleles by locus (A), observed heterozygocity (HO) and expected (HE) heterozygocity, and with analysis to verify deviation of genotypic frequencies from the Hardy-Weinberg equilibrium (HWE) (considering all loci in each population and each locus) using GENETIX version 4.05.2 (Belkhir et al. 2004). Additionally, the program GENALEX version 6.4 (Peakall & Smouse 2006) was used to obtain the plot of allelic frequency per locus and the distribution of exclusive alleles for each identified cluster. Tests for genotype disequilibrium among all loci pairs, according to Black & Krafsur (1985)’ algorithm, were also carried out with GENETIX. In theory, the linkage disequilibrium in a subdivided population can result from a natural epistatic selection within subpopulations (Lewontin 1974) and random drift among subpopulations (Ohta & Kimura 1969). Ohta (1982a) established that the linkage disequilibrium was often attributed to a natural epistatic selection. On the other hand, when migration among subpopulations is limited, random drift can generate different allele combinations and create disequilibrium. To differentiate between random and selective equilibrium causes, Ohta (1982a, b) devised a method to divide the variance of coefficient inferred from dilocus in disequilibrium, into components that occur within and among subpopulations. Otha’s theory is based on the hypothesis that when selection produces specific combinations of alleles, they should appear consistently among the subpopulations. Variability in the observed frequency of allele combinations must therefore be small, in comparison to the expected variance on the allelic drift hypothesis (Black & Krafsur 1985). Five ‘D’ statistics describe the variance in observed and expected frequencies of allelic combinations, and statistics are calculated for pairs of loci. The presentation of the results follow Ohta’s notation and the statistics were indicated with the subscripts I (individuals), S (subpopulations), and T (total population). DIT2, disequilibrium variance in the total population, indicates when the alleles i and j appear together in individuals more frequently than predicted by their independent frequencies in the population in general. DIS2 measures the disequilibrium variance in subpopulations, and is calculated as the squared disequilibrium’ averaged value. DST2 is the disequilibrium variance predictor expected under the genetic drift hypothesis. If populations are distinct, the combination of alleles will have been established independently among subpopulations and DST2 will be greater than DIS2. Furthermore, a uniform epistatic selection among subpopulations will cause a convergence in the frequency of allele combinations such that DST2 deflates and is inferior to DIS2. Conversely, D’IS2 is a disequilibrium index in the total population; it is a measure of the variance in the observed frequency that i and j appear together in individuals within subpopulations. Meanwhile, D’ST2 is the disequilibrium variance in the total population (Ohta 1982a). If random drift caused the variance in the frequency of allele combination, D’IS2 exceeds D’ST2. Uniform selection among subpopulations will increase D’ST2 and deflate the D’IS2 variance. Ohta (1982a) has shown that DIT2 = D’IS2 + D’ST2. This equation and the ‘D’ statistics allow us to assess relative random contributions, processes and selection patterns at disequilibrium. Three linkage disequilibrium patterns may exist in a subdivided population. According to Ohta (1982a), these are non-systematic disequilibrium, systematic equilibrium, and unequal systematic 80 disequilibrium. The disequilibrium is non-systematic when it is caused by random drift. Under these conditions, DIS2 < DST2, and D’IS2 > D’ST2. If disequilibrium arises from a systematic epistatic selection for specific pairs of alleles in subpopulations, DIS2 > DST2, and D’IS2 < D’ST2. Unequal systematic disequilibrium arises if selection for specific allele pairs occurs only in a few subpopulations. Thus, DIS2 is larger than DST2 because disequilibrium in the subpopulations is larger than that expected by random drift. But, D’IS2 is larger than D’ST2, because the variance in frequencies in which alleles show up together in individuals will be greater that the disequilibrium in the total population. Indirect estimation of migrants Indirect genetic estimates of migration rate represent an average of the current successful migration rate among populations (e.g. migrations that lead to reproduction). The genetic estimator used, and which is most commonly used for migration rate, is derived from the FST value. This estimator represents the average migration level within a group of populations, under the assumption of an island model, by way of the theoretical connexion given by the formula: FST = 1/(4Nm + 1) (Wright 1931); where N represents the population size and m the number of migrants per generation. Despite the inaccuracy of this relationship in the sense of biological configurations (and additional considerations of equality, constant population size and symmetric migration), this estimator continues to be used both for historical reasons as for its claim of a direct binding between genetic diversity and the calculated migration rate (Slatkin & Barton 1989; Gaggiotti et al. 1999; Whitlock & McCauley 1999; Neigel 2002; Pearse & Crandall, 2004). Mitochondrial DNA analysis (Control Region - CR) The Control Region’s (CR) haplotype sequence was chosen and assessed in virtue of its rapid rate of evolution (neutral, but see William et al. 2004) and its maternal heredity, making it in an extremely suitable descriptor for studying phenomena at the population level (Avise et al. 1987; Ballard & Whitlock 2004). The CR has been one of the mitochondrial genome fragments most frequently used for genetic studies of fish stocks, based on sequence (Lee et al. 1995). Distribution patterns on the number of differences between haplotypes have been used to define evolutionary processes in populations (Excoffier 2004; Rogers 1995; Rogers & Harpending 1992). Thus, several methods have been applied to estimate population parameters and to test biological hypotheses (e.g. Fu 1997; Tajima 1989a). One thousand and seventy one base pairs (bp) from the control region (CR) were amplified and selected for the analyses in addition to a small fraction of encoding phenylalanine (from three bp after the start of the CR to 45 additional ones on phenylalanine tRNA) for 461 Plateado individuals, using polymerase chain reaction (PCR) with primers DL20 F (Forward) (ACCCCTAGCTCCCAAAGCTA) by Agnèse et al. (2006), and DL20 R (Reverse) (TTAGCAAGGCGTCTTGGGCT) kindly provided by Agnèse J-F. Amplification was performed in 60 µL of reagent volume containing 12 uL of 5X reaction buffer (Colorless GoTaq Promega, 7.5 mM MgCl2 at pH 8.5), 3.6 µl MgCl2 (25 mM), 12 µL dNTPs (1 mM each dNTP), 1.2 µL of each primer (DL20 81 F and DL 20 R, 10 µM), 1.5 U of Taq polymerase (GoTaq Promega), approximately 100-120 ng total genomic DNA extract (1.2 µL reagent) and 28.5 µL Milli-Q water. The temperature cycle regime consisted of an initial denaturation at 95ºC for 2 minutes, followed by 30 cycles of denaturation at 95ºC (1 min), annealing at 53ºC (1 min), extension at 72ºC (1.5 min), and one final extension at 72ºC for 5 min to finish refrigerated at 4ºC. Each PCR reaction included a negative reagent tube control, which included all reagents except for the DNA template. All PCR reactions were done on a Mastercycler thermocycler ep (Eppendorff AG 2231 Hamburg). The products obtained were sequenced with the same primers used for amplification by the commercial genomic services companies Macrogen (Korea, http://www.macrogen.com/) and GenoScreen (Francia, http://www.genoscreen.fr/), between 2008 and 2010. In addition to the sequences obtained during this research another 45 from Central Amazon (Solimões-Amazon main stem, Brazil) deposited in GenBank (DQ779016 DQ779046) by Batista & Alves-Gomez (2006), were included in the phylogeographic and population structure analyses. For analyses that included sequences from Brazil, only one homologous fragment, with 952 bp of the 1041 obtained from fish from Bolivia and Peru, was considered. Phylogeographic analysis of the Control Region - CR The resulting DNA sequences were aligned using the CLUSTAL W (Thompson et al. 1994) program, and edited manually using the BIOEDIT (Hall 1999) and MEGA version 5.01 (Tamura et al. 2011) programs. Identification of the total number of haplotypes distributed in the 506 individuals analyzed (461 sequences obtained in this study plus 45 available in GenBank) was performed with the program DNASP version 5.10 (Librado & Rozsas 2009). Phylogenetic relationships among the different haplotypes were built and evaluated with the maximum likelihood (ML) algorithm implemented in PHYML version 3.0 (Guindon & Gascuel 2003). The evolutionary nucleotide model considered was that of Felsenstein 1984 [F84 + I (invariant) + Г (gamma distribution with α shape parameter); invariant proportion = 0.51; α = 0.62; transition/transversion (Ts/Ts) = 10.65], which is a synthesis of the K80 (Kimura 1980) and F81 (Felsenstein 1981) models. This model of nucleotide (DNA) substitution, with the best fit to the CR sequences, was chosen from 28 available models based on the Akaike Information Criterion (AIC) with the program APE (Paradis et al. 2004), which is developed in R language (R Development Core Team 2009). The parameter of invariable sites (I) specifies that in the model there are sites that have no evolutionary change and that the rest evolve at the same rate. Inclusion of the gamma variable (Г) allows consideration of the substitution rate variation among sites within the sequences. This means that the rate of substitution varies so that some sites evolved rapidly and others slowly. The alpha parameter (α) of the gamma distribution specifies the variation of the rate of variation among sites. A small alpha value (<1) results in an Lshaped distribution with an extreme variation rate in which there are many invariable sites but few with high substitution rates. High alpha values result in a bell-shaped curve, showing that there is little variation rate from site to site. 82 Consistency in tree branch nodes was assessed with a bootstrap analysis (Felsenstein 1985) of 100 allelic repetitions. Three individuals of each species of the external group defined in the previous chapter (Brachyplatystoma vaillantii (Valenciennes, 1840), Brachyplatystoma platynemum (Boulenger, 1898) and Platynematichthys notatus (Jardine, 1841)) were used to root the tree and verify that all of the Plateado sequences formed a monophyletic group. The best tree topology was chosen by a search in the spaces generated by NNI (quick and approximate) and SPR (slow and precise) operations. Tree diagrams were made using ITOL, available at http://itol.embl.de/index.shtml (Letunic & Bork 2006). Genealogic relationships were also examined using a median-network approximation of haplotypes built with the program NETWORK version 4.515 (Fluxus Technology Ltd.; Bandelt et al. 1999) available at http://www.fluxus-engineering.com/. This method begins by combining minimum spanning trees within a minimum spanning network. Then the medium vectors (representing missing intermediate haplotypes) are added to the network using the parsimony criterion. Analysis of population structure according to the Control Region - CR Units or groups of haplotypes were divided beforehand (a priori) according to the information previously obtained with microsatellites (BAPS cluster analysis). Thus the 267 individuals, for which genotypes (microsatellites) and haplotypes (CR) were obtained, were sorted into three groups corresponding to the three panmitic units or populations identified by BAPS. Molecular diversity Indices, such as population haplotype diversity (h), nucleotide diversity (π), the average number of differences among pairs (k), and their corresponding standard deviations were calculated according to Nei (1987) implemented in ARLEQUIN version 3.5 (Excoffier & Lischer 2010). Homogeneity of the distribution of mtDNA haplotypes among populations (population genetic structure), was measured using the estimator θ (FST) values computerized over the genetic distances of haplotype frequencies and using the distance estimator HKY [HKY85 (Hasegawa-Kishino-Yano)] plus α = 0.81 [Г (gamma distribution with α shape parameter)] (Hasegawa et al. 1985). The levels of statistical significance of estimated distances were determined by 10,000 haplotype permutations, as implemented in the program ARLEQUIN. Demographic history of the clusters defined by BAPS mtDNA sequence data was also used to infer the demographic history of each population. Demographic patterns of Plateado populations were examined by two approaches. First, the CR sequences were assessed to determine if they followed a neutral evolution pattern through the statistics FS by Fu (1997) and D by Tajima (1983) in the program ARLEQUIN. Fu (1997) observed that FS is sensitive to demographic population expansions, which generally result in fairly large negative FS values. Similarly, significantly negative D values may be due to factors such as selection, population expansions, or bottle necks (Tajima 1989b). The statistical significance of neutrality was tested by generating random samples (1000) under the hypothesis of neutral selection and population equilibrium, using a coalescence simulation algorithm adapted from Hudson (1990). The P value of the FS statistic was equal to the proportion of values of the statistic (FS) less than or equal to the observed value. Secondly, historical demographic expansion was investigated, by 83 examining the shape of the resulting difference frequency distribution (bp) among sequence pairs, known as mismatch distribution (Rogers & Harpending 1992). According to Rogers & Harpending (1992), this distribution of differences can be used to test hypotheses on the demographic history of the population and the selection it could have been subjected to. The pattern of differences between pairs of haplotypes usually forms a unimodal wave in population samples under expansion, while samples obtained from populations in demographic equilibrium produce a multimodal pattern of many sharp peaks (Rogers & Harpending 1992; Slatkin & Hudson 1991). The parameters of demographic expansion τ (tau), θ0 (theta), θ1 were estimated by a generalized linear approximation of least squares and their confidence intervals by a bootstrap parametric analysis (1000) (Scheneider & Excoffier 1999). The estimator tau, which represents the distribution of differences mode, or mismatch distribution, is an index of time since expansion, expressed in mutational time units (Rogers & Harpending 1992). T values were transformed to estimate the actual time since the expansion, according to the expression T = 2ut, where u is the mutation rate for the sequences under study by generation and t is the time (in generations) since expansion. θ0 y θ1 represent the mutation parameters before and after population growth, respectively. The model’s deviation was evaluated using the Harpending’s raggedness index, Hri (Harpending (1994). Coalescence While a population expansion can be inferred from a histogram or mismatch distribution and statistics D by Tajima (1989) and FS by Fu (1997), it can be difficult to relate this to a particular depth in time. Clear signs of expansion are difficult to distinguish in complex phylogenies, and expansions can have many causes (Finland et al. 2007). The Bayesian Skyline Plot is a recent genetic methodology developed to infer past changes in population size from its current genetic diversity. Under the coalescence theory (ancestral relationships model), the probability that two lineages join or fuse (coalescing) during one generation is inversely proportional to the population size at the time (Pybus et al. 2000). Coalescence describes interrelationships between the form of an intrapopulational genealogy (representing the ancestry of sequences collected at random, non-recombinant and evolutionarily neutral) and the demographic history of the sampled population (Kingman 1982). The coalescence methods for inferring demographic histories require a demographic model, which is simply a mathematical function used to describe the change in effective population size over time. Each demographic model has one or more demographic parameters. The basic demographic models commonly used are constant size (one parameter), exponential growth (constant rate of growth over time; two parameters), logistic growth (decreasing rate of growth over time; three parameters), and expansion growth (increasing rate of growth over time; three parameters) (Drummond et al. 2005). Skyline Plots estimate the effective population sizes during intervals between coalescence events based on interval lengths (Pybus et al. 2000). Bayesian Skyline Plot use Markov chain Monte Carlo (MCMC) sampling to create millions of genealogies, and estimate the posterior distribution of population size at various points in time (Drummond et al. 2005). This method therefore completely parameterizes the mutation model (including relaxed clock models) and the genealogical process. The average, median and the 95% highest posterior density of distributions can be traced in time; representing a measure of the uncertainty in both the coalescence as in the phylogenetic errors. As for other 84 methods of estimating demographic histories, one should not make a priori assumptions regarding the histories of populations. Thus, the Bayesian Skyline Plots (BSP) for Plateado sequences were generated using the BEAST version 1.6.1 (Drummond & Rambaut 2007) program. The BSP model generates a posterior distribution where the parameter m, representing the number of grouped intervals, was set at 10 for clusters 1 and 2, and 5 for cluster 3. The MCMC analysis was run 30 x 106 generations for cluster 1 and 2, and 10 x 106 the cluster 3 (sampled every 1000 iterations), of which the first 10% of each run was discarded as burn-in. The nucleotide substitution model used was HKY85 + I + Г and the median plus the credibility intervals for rendering the BSP were depicted using the program TRACER version 1.5 (Rambaut & Drummond 2007). A constant molecular substitution rate (strict molecular clock) was used of 0.0062 ± 0.0061 per million years per site, obtained on average for Pseudoplatystoma (Pimelodidae) by Torrico et al. (2009). 3.3 Results 3.3.1 Nuclear DNA (microsatellites) The evaluation of the estimator ƒ (FIS) values calculated for the 284 individuals (six locations, Villa Bella – 20; Cachuela Esperanza – 50, Puerto Maldonado – 50; Rurrenabaque – 49, Puerto Villarroel – 50; Iquitos – 65) grouped as a single set, indicates that globally (nine loci, 129 alleles) there is a significant difference between the actual value and the random values generated under the assumed conditions of HWE (panmixia). Thus, this first analysis indicates that the distribution of alleles together as a group, deviates significantly from the hypothetical expectations of the HWE (Table 3.3.1.1). It is important to note that BR45 is the only locus that showed a significant deviation from panmixia. However, the observed deviation was maintained even when a new global analysis was performed on eight loci (excluding BR45): ƒ = 0.023; p = 0.021. Therefore, the overall deviation from HWE depends on the multiple loci combination and not only on the information contained in this locus. In view of the observed deviation as a whole, an analysis similar to the first was carried out on two geographic units defined a priori, the two large systems - the western Amazon (66 individuals) and the Upper Madera (220 individuals). This analysis showed that the hypothesis of panmixia could not be rejected (ƒ = -0.01092; p = 0.724) in the group of individuals from the western Amazon, whereas a significant deviation from panmixia remained for the group of individuals from Upper Madera (ƒ = 0.03325, p = 0.000). 85 Table 3.3.1. 1 Values of the estimator ƒ of the endogamy index FIS for the nine loci (global) analyzed for each of them (locus), considering the total of individuals of Plateado as a single group. The significance of values was determined by the percentage of values dissimilar to the actual value obtained from 1000 random interior allele permutations under conditions assumed by HWE (panmixia). Values are considered significant (different from zero) if the proportion of dissimilar permutation values is equal to or greater than 97.5% (two-tailed or bilateral test); these values are highlighted with gray background. % val. >: percent values above the actual value; % val. <: percent values less than the actual value; % val. =: percent values equal to the actual value. Alleles ƒ (real value) 0.031 % val. > 0.0 % val. < 100.0 % val. = 0.0 32 17 9 12 20 9 12 8 10 0.007 0.017 0.039 0.027 0.016 0.036 0.082 0.079 -0.007 36.2 25.5 8.0 19.4 15.5 9.5 0.0 2.4 56.2 55.8 68.9 83.9 76.8 79.4 88.3 100.0 96.2 38.6 8.0 5.6 8.1 3.8 5.1 2.2 0.0 1.4 5.2 Global Pcor1 Pcor2 Pcor7 BR37 BR38 BR44 BR45 BR47 BR49 Given the overall significant deviation from HWE (p < 0.001) and significant deviation from panmixia of a major geographical unit (Upper Madera, p < 0.000), a Bayesian approach was taken to identify the most likely panmictic units (clusters). The BAPS analysis showed that the higher log values (marginal probability) for the most optimal partitions visited occurred six times when K = 5 (-9214.76 to -9226.41), three when K = 4 (-9236.89 to -9229.40) and one when K = 3 (-9231.4119). The posterior probabilities for the optimal partitions visited reached 1 - 0.96 (K = 5), 1 - 0.94 (K = 4), and 0.97 (K = 3). In general, the partitions with K = 5 were made up of three large and two small groups. One of these small groups was formed only by one individual, in five of the six best visited partitions. Following this result, which approached K = 5 to a partition of four groups, and the other optimal partitions visited by BAPS (K = 3 and K = 4), 100 independent groupings were carried out with fixed values of K = 3 and K = 4. Thus, the cluster analysis to estimate the most correct number of clusters showed that the optimal log(pm) values were -9233.82 to -9255.33 for K = 4 and K = 3. Based on these parameters the most correct partition visited would correspond to K = 4. However, similarly to what was observed with the partition K = 5, one of the clusters belonging to partition K = 4 was formed by only one individual. Thus, approximation to the most correct partition, of the data analyzed, had a tendency for the formation of three groups, and the results generated with K = 3 were chosen for further analysis. This partition of three units consisted of two large clusters or groups of 184 (cluster 2) and 83 (cluster 1) individuals, and a smaller one of 17 individuals (cluster 3) (Table 3.3.1.2). 86 Table 3.3.1. 2 Summary of the optimal partition obtained with BAPS (K = 3, 100 repetitions) on 284 individuals of Plateado from Upper Madera and western Amazonia (Bolivian and Peruvian Amazon). The optimal partition log(mp) was -9240.92. log (pm): marginal probability logarithm a) Assignment of individuals by group in the best partition visited by BAPS. cluster 1 1 3 40 41 87 88 139 144 212 214 4 44 91 146 216 5 45 93 147 7 46 94 150 8 47 96 152 9 48 98 155 11 49 103 162 15 58 104 164 16 60 105 170 18 61 106 181 20 62 109 184 23 63 111 186 25 65 112 188 28 76 113 190 29 79 116 197 32 81 117 198 35 82 120 199 36 83 122 200 37 85 138 206 cluster 2 2 6 52 53 86 89 130 131 160 161 192 193 220 221 241 242 261 262 281 282 10 54 90 132 165 194 222 243 263 283 13 56 92 133 166 195 223 244 264 284 14 57 95 136 167 196 224 245 265 17 59 97 137 168 201 226 246 266 19 64 100 140 169 202 227 247 267 21 67 101 141 171 203 228 248 268 22 68 102 142 173 204 229 249 269 24 69 107 143 174 205 230 250 270 26 70 108 145 176 207 231 251 271 27 71 110 148 177 208 232 252 272 30 72 115 149 178 209 233 253 273 31 73 119 151 179 210 234 254 274 34 74 123 153 180 211 235 255 275 38 75 125 154 183 213 236 256 276 39 77 126 156 185 215 237 257 277 42 78 127 157 187 217 238 258 278 43 80 128 158 189 218 239 259 279 50 84 129 159 191 219 240 260 280 cluster 3 12 33 51 55 66 99 114 118 121 124 134 135 163 172 175 182 225 b) Changes in the log(pm) obtained by BAPS if individual i is moved to group j. Ind 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 cluster 1 0.0 -1.8 0.0 0.0 0.0 -2.8 0.0 0.0 0.0 -2.6 0.0 -9.5 -8.5 -0.2 0.0 0.0 -3.7 0.0 -11.8 0.0 -6.9 -2.2 0.0 -2.4 0.0 -11.7 -2.6 0.0 0.0 -5.3 -11.0 0.0 -13.2 -3.3 0.0 0.0 0.0 -5.0 -3.6 0.0 0.0 -6.0 -3.7 0.0 0.0 0.0 0.0 0.0 0.0 -0.8 -5.7 -2.4 -13.7 -1.9 -16.3 -10.5 -3.0 0.0 -2.2 0.0 0.0 0.0 0.0 -0.7 0.0 -2.1 -0.5 -0.4 -0.1 -14.9 -14.1 -5.6 -3.7 -6.2 -7.6 0.0 -5.2 -0.1 0.0 -7.8 0.0 0.0 0.0 -7.5 0.0 -10.1 0.0 0.0 -6.0 -1.4 0.0 -4.1 0.0 0.0 -7.7 cluster 2 -7.1 0.0 -5.3 -5.4 -5.0 0.0 -7.7 -0.5 -3.4 0.0 -4.3 -5.7 0.0 0.0 -4.6 -5.5 0.0 -2.1 0.0 -4.1 0.0 0.0 -5.5 0.0 -1.2 0.0 0.0 -4.3 -2.7 0.0 0.0 -1.8 -8.7 0.0 -2.3 -0.8 -1.0 0.0 0.0 -4.0 -11.7 0.0 0.0 -10.6 -2.1 -4.3 -9.0 -4.8 -2.2 0.0 -12.9 0.0 0.0 0.0 -11.7 0.0 0.0 -7.0 0.0 -7.2 -9.4 -1.0 -3.8 0.0 -3.0 -5.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -1.1 0.0 0.0 -1.0 0.0 -2.2 -3.0 -2.7 0.0 -4.7 0.0 -2.0 -7.7 0.0 0.0 -10.8 0.0 -0.5 -2.1 0.0 cluster 3 -14.8 -17.1 -26.6 -17.0 -17.2 -16.5 -23.1 -9.2 -25.1 -13.0 -9.0 0.0 -12.6 -21.9 -13.1 -19.0 -3.2 -6.1 -9.5 -18.9 -25.0 -12.5 -23.4 -15.2 -15.2 -9.4 -19.3 -22.1 -6.3 -8.4 -9.6 -15.2 0.0 -16.4 -14.7 -15.8 -21.8 -16.9 -18.9 -20.9 -31.8 -12.3 -16.7 -2.6 -13.5 -27.5 -23.8 -23.6 -9.7 -10.6 0.0 -11.2 -14.7 -20.4 0.0 -9.7 -13.7 -18.6 -19.4 -34.4 -20.1 -9.3 -18.0 -8.0 -12.3 0.0 -20.6 -7.2 -11.2 -15.4 -14.2 -6.9 -18.2 -10.8 -21.7 -22.8 -15.0 -20.9 -17.1 -15.7 -11.4 -12.0 -22.3 -8.3 -12.6 -10.8 -17.3 -30.2 -10.0 -18.3 -25.4 -2.6 -7.6 -10.2 -18.2 Ind 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 cluster 1 0.0 -7.4 0.0 -4.0 -7.0 -4.3 -9.9 0.0 0.0 0.0 0.0 -2.5 -7.4 0.0 -6.9 0.0 0.0 0.0 -12.9 -2.3 0.0 0.0 -7.2 -10.9 0.0 -17.3 0.0 -10.2 -8.3 -7.3 -6.9 -10.9 -6.4 -6.5 -1.7 -5.6 -2.4 -11.2 -14.0 -9.3 -5.7 -2.9 0.0 0.0 -3.1 -5.6 -1.8 -0.3 0.0 -4.0 0.0 0.0 -12.5 -4.4 0.0 -10.4 0.0 -11.9 -6.4 0.0 -3.7 -1.6 -4.1 -4.5 -4.0 -5.6 0.0 -15.1 0.0 -2.0 -6.8 -0.9 -8.7 -1.1 0.0 -5.6 -4.2 -2.7 -2.1 -7.1 -0.3 -5.2 -1.6 -1.9 -9.0 0.0 -6.3 -2.2 0.0 -10.4 0.0 -11.4 0.0 -3.2 0.0 cluster 2 -3.2 0.0 -1.5 -5.0 0.0 0.0 0.0 -2.4 -2.8 -2.8 -2.0 0.0 0.0 -5.6 0.0 -7.5 -5.1 -2.6 -5.7 0.0 -0.9 -2.3 -4.0 0.0 -2.2 -2.9 -1.6 0.0 -8.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -6.6 -2.2 0.0 0.0 -3.8 -5.9 0.0 0.0 0.0 0.0 -0.9 0.0 -1.2 -4.8 0.0 0.0 -2.6 0.0 -0.8 0.0 0.0 -3.4 0.0 0.0 0.0 0.0 0.0 0.0 -7.1 -9.6 -4.5 0.0 0.0 0.0 0.0 0.0 -1.4 0.0 -0.8 0.0 0.0 -4.1 0.0 0.0 0.0 0.0 0.0 -3.3 -4.7 0.0 -2.8 0.0 -1.2 0.0 -5.2 0.0 -3.3 cluster 3 -21.5 -16.4 -4.6 0.0 -28.8 -17.8 -9.7 -22.0 -10.5 -9.9 -21.1 -9.0 -12.6 -20.9 -9.0 -9.7 -20.4 -21.2 0.0 -21.7 -19.7 -22.2 0.0 -17.9 -13.1 0.0 -19.6 -22.3 0.0 -28.3 -7.5 -20.1 -15.0 -16.8 -16.7 -16.9 -17.5 -15.5 0.0 0.0 -11.2 -13.0 -9.5 -10.5 -9.8 -22.4 -11.7 -17.5 -22.6 -11.3 -9.7 -15.6 -8.5 -15.2 -27.2 -7.5 -8.7 -1.5 -27.9 -17.1 -10.2 -24.2 -12.0 -8.6 -6.7 -24.2 -28.8 0.0 -21.1 -13.3 -17.3 -21.9 -15.0 -11.5 -7.1 -10.0 0.0 -10.2 -12.5 0.0 -21.4 -18.4 -15.0 -25.0 -18.4 -17.8 0.0 -14.0 -16.3 -18.3 -8.4 -16.4 -14.4 -14.5 -23.4 Ind 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 cluster 1 -9.2 -6.4 -6.7 -5.2 -3.7 -2.6 0.0 0.0 0.0 0.0 -5.0 -5.3 -1.3 -9.7 -6.1 0.0 -1.5 -6.1 -4.7 -9.1 -4.0 0.0 -4.5 0.0 -9.7 0.0 -10.5 -5.0 -8.4 -10.4 -6.9 -4.4 -21.4 -4.5 -8.3 -8.2 -17.6 -6.7 -8.7 -0.6 -9.7 -3.4 -8.1 -22.3 -10.1 -7.0 -7.4 -14.8 -3.7 -3.0 -0.8 -10.9 -18.6 -8.3 -2.2 -17.5 -7.3 -9.6 -11.1 -13.3 -15.0 -9.9 -17.5 -9.7 -7.6 -10.1 -10.5 -3.9 -5.7 -12.1 -4.4 -6.0 -11.2 -19.4 -7.2 -6.0 -8.7 -14.6 -10.8 -8.7 -3.6 -1.4 -9.1 -8.6 -13.1 -10.7 -13.7 -8.4 -3.5 -12.1 -5.5 -5.2 -3.0 -4.6 cluster 2 0.0 0.0 0.0 0.0 0.0 0.0 -0.3 -7.4 -3.7 -0.8 0.0 0.0 0.0 0.0 0.0 -5.2 0.0 0.0 0.0 0.0 0.0 -8.2 0.0 -5.2 0.0 -2.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -6.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 cluster 3 -20.0 -11.4 -21.0 -11.4 -8.9 -3.4 -16.3 -22.9 -25.8 -7.8 -13.7 -8.6 -30.6 -5.3 -8.4 -7.7 -25.1 -8.6 -4.2 -10.9 -9.2 -12.7 -10.2 -17.8 -2.5 -19.6 -13.1 -25.1 -22.2 -20.5 -12.4 -12.3 -17.6 -21.2 0.0 -18.4 -7.5 -17.1 -10.3 -13.8 -9.3 -22.2 -14.4 -2.5 -2.1 -9.8 -9.1 -7.3 -19.9 -15.6 -10.4 -8.8 -21.2 -18.5 -20.8 -27.0 -16.8 -7.4 -13.3 -12.6 -14.8 -7.5 -6.4 -28.0 -20.0 -8.2 -31.3 -13.0 -18.3 -20.9 -4.5 -12.7 -20.3 -10.9 -7.4 -20.4 -12.3 -14.1 -19.2 -20.0 -5.9 -27.2 -8.9 -22.3 -17.7 -13.4 -17.4 -19.0 -22.4 -1.4 -20.1 -19.5 -19.8 -11.1 87 c) List of the size of the 10 best partitions obtained with BAPS and their corresponding log (pm) values. K 3 3 3 3 3 log(pm) -9240.92 -9240.94 -9241.04 -9241.33 -9241.62 K 3 3 3 3 3 log(pm) -9242.22 -9244.93 -9245.06 -9247.51 -9249.67 Additionally, to compare and verify the consistency of internal conformation of the three clusters generated with 100 repetitions, an analysis was performed with K = 3 and 1000 repetitions. The resulting conformation showed that the two larger clusters were modified by the migration of individuals among them, but the smaller group was essentially the same as that identified with 100 replicates (Table 3.3.1.3). Table 3.3.1. 3 Composition of grouping of individuals in the optimal partition obtained with BAPS (K = 3, 1000 repetitions) for 284 individuals of Plateado from the Upper Madera and western Amazon (Bolivian and Peruvian Amazon). The optimal partition log(mp) was -9240.92. cluster 1 1 2 44 45 91 94 143 144 212 219 cluster 2 6 8 43 50 82 84 126 127 160 161 193 194 218 220 240 242 261 262 284 cluster 3 12 33 3 46 95 146 241 4 47 96 150 271 5 48 101 152 272 7 49 104 155 279 9 58 106 157 11 59 109 162 13 60 111 164 15 61 112 168 16 63 113 169 18 65 115 176 20 69 117 177 30 76 120 178 32 78 129 179 35 81 131 186 36 83 132 190 39 85 139 198 40 87 141 199 41 88 142 206 10 52 86 128 165 195 221 243 263 14 53 89 130 166 196 222 244 264 17 54 90 133 167 197 223 245 265 19 56 93 135 170 200 224 246 266 21 57 97 136 171 201 226 247 267 22 62 98 137 172 202 227 248 268 23 64 100 138 173 203 228 249 269 24 67 102 140 174 204 229 250 270 25 68 103 145 180 205 230 251 273 26 70 105 147 181 207 231 252 274 27 71 107 148 183 208 232 253 275 28 72 108 149 184 209 233 254 276 29 73 110 151 185 210 234 255 277 31 74 116 153 187 211 235 256 278 34 75 119 154 188 213 236 257 280 37 77 122 156 189 214 237 258 281 38 79 123 158 191 216 238 259 282 42 80 125 159 192 217 239 260 283 51 55 66 92 99 114 118 121 124 134 163 175 182 215 225 The integrity and internal homogeneity of the clusters obtained with BAPS, as assessed by their deviation from HWE with the estimator ƒ (FIS), showed that the identified clusters form units without significant global deviation from HWE. The value of ƒ per locus was significant in two particular loci (BR37 and BR45), but its deviation could be explained by chance or by the small sample size (BR37, cluster 3) rather than by a real disequilibrium in opposite direction to that of the other loci (Table 3.3.1.4). 88 Table 3.3.1. 4 Values of the estimator ƒ of the endogamy index FIS calculated globally with data from nine loci (a) and with each one (b) for three Plateado clusters as defined by BAPS. The significance of values was determined by the percentage of values dissimilar to the actual value that were obtained from 1000 random interior allele permutations of groups under conditions assumed by HWE (panmixia). Significant values are highlighted with a gray background. n: number of individuals; % val. >: percent values above the actual value ; % val. <: percent values less than the actual value; % val. =: percent values equal to the actual value. n ƒ (valor real) % val. > % val. < % val. = 83 184 17 0.027 0.005 0.054 7.39 32.53 9.69 91.08 64.9 86.26 1.53 2.57 4.05 Pcor1 cluster 1 cluster 2 cluster 3 83 184 17 -0.032 -0.005 0.011 66.59 51.98 28.37 23.09 38.32 40.82 10.32 9.7 30.81 Pcor2 cluster 1 cluster 2 cluster 3 83 184 17 0.053 -0.005 0.008 16.01 51.48 35.96 77.02 40.54 42.03 6.97 7.98 22.01 Pcor7 cluster 1 cluster 2 cluster 3 83 184 17 0.073 -0.029 0.009 13.33 63.06 22.29 78.40 19.61 33.92 8.27 17.33 43.79 BR37 cluster 1 cluster 2 cluster 3 83 184 17 0.017 -0.018 0.480 35.47 62.50 0.15 54.12 30.39 99.44 10.41 7.11 0.41 BR38 cluster 1 cluster 2 cluster 3 83 184 17 0.044 -0.007 0.037 8.46 56.77 22.9 84.64 32.53 53.26 6.90 10.70 23.84 BR44 cluster 1 cluster 2 cluster 3 83 184 17 0.040 0.007 0.177 19.44 37.9 5.28 72.32 54.31 84.75 8.24 7.79 9.97 BR45 cluster 1 cluster 2 cluster 3 83 184 17 0.049 0.085 0.050 11.24 0.39 21.63 81.53 99.43 57.23 7.23 0.18 21.14 BR47 cluster 1 cluster 2 cluster 3 83 184 17 0.050 0.057 -0.169 24.99 11.01 77.36 67.08 84.65 9 7.93 4.34 13.64 BR49 cluster 1 cluster 2 cluster 3 83 184 17 -0.026 -0.051 -0.143 63.84 91.57 72.64 24.58 5.52 11.27 11.58 2.91 16.09 a) cluster 1 cluster 2 cluster 3 b) In turn, differentiation between clusters, as assessed by the estimator θ (FST), showed that there are significant differences among all combinations of pairs of groups, but the estimate ρ (RST) did not show the same results. According to the estimate ρ, averaged over the variance components and the loci, there are no significant differences among any of the three clusters when one also considers the allelic identity and a step by step mutation model between alleles as independent variables. At this juncture, the information provided by θ was primarily taken into account because it is a more sensitive and appropriate estimator when there are weak differentiations between units (Table 3.3.1.5). 89 Table 3.3.1. 5 Estimators of differentiation between pairs of the three clusters obtained with BAPS for Plateado from the Bolivian and Peruvian Amazon. a) Values of the estimator θ of the fixation index FST. Nm represents the number of migrants between clusters. The significance of values was determined by the percentage of values dissimilar to the actual value that were obtained from 1000 permutations of individuals between groups under assumption of a single unit (not structure of various units). Values are considered significant (different to zero) if the percentage of dissimilar permutations values is equal to or greater than 95%, these values are highlighted with a gray background. % val. >: percent values above the actual value; % val. <: percent values less than the actual value. b) Values of the estimator ρ of the RST index, averaged over the variance components and the loci. The significance of values was determined from 1000 permutations. The negative value of ρ and Nm, represent zero and large proportions of migrants among the groups, respectively. a) θ (valor real) 0.028 0.043 0.038 Comparación de clusters cluster 1 x cluster 2 cluster 1 x cluster 3 cluster 2 x cluster 3 Nm (θ) 8.760 5.510 6.310 % val. > 0.0 0.0 0.0 % val. < 100.0 100.0 100.0 b) Comparación de clusters cluster 1 x cluster 2 cluster 1 x cluster 3 cluster 2 x cluster 3 ρ (comp var) 0.000 0.006 0.010 Nm (ρ) -1090.110 40.905 23.917 P 0.389 0.274 0.150 Additionally, Figure 3.3.1.1 shows that the clusters identified by BAPS have a similar allelic distribution by size classes (p > 0.05) between them. Therefore, one can assume that there is not a determining influence of allele size distribution between clusters. 1400 1200 1000 clus1 (83 ind) 800 clus2 (184 ind) 600 clus3 (17 ind) 400 200 0 98-150 151-200 201-250 251-300 301-340 Figure 3.3.1. 1 Distribution of the total number of alleles in five size classes for each of the three clusters identified by BAPS in samples of Plateado (Brachyplatystoma rousseauxii) from Upper Madera and western Amazon (Amazonian Bolivian and Peruvian Amazon). The table at the top right, contains the probability values (p) for the independent chi2 test (95%) between clusters identified by BAPS. clus1: cluster 1; clus2: cluster 2; clus3: cluster 3. Considering these results, it can be assumed that the clusters obtained by BAPS represent panmictic Plateado units distributed in different geographical areas of the Upper Madera and western Amazon (Bolivian and Peruvian Amazon) (Figure 3.3.1.2). 90 a) b) c) Figure 3.3.1. 2 Geographical distribution (presence) of the three clusters identified by BAPS for 284 individuals of Plateado from six locations in the Upper Madera basin and western Amazon (Bolivian and Peruvian Amazon) based on data from nine microsatellite loci. a) Cluster 1 distribution, 83 individuals; b) cluster 2 distribution, 184 individuals; c) Cluster 3 distribution, 17 individuals. Numbers next to the localities’ names represent the individuals collected in those points. Oblique black bars represent the rapids series in the Upper Madera basin, between Bolivia and Brazil. The genetic diversity of each cluster was moderate, with an average observed heterozygosity (H obs) ranging from 66% (cluster 3) to 71% (cluster 2), and 6.67 (cluster 3) to 13.11 (cluster 2) alleles per locus (Table 3.3.6 and 3.3.1.7, Figure 3.3.1.3). Locus polymorphism was significant both at a confidence limit of 95 and 99% (Table 3.3.1.6) Table 3.3.1. 6 Average heterozygosity on nine loci for the three clusters of Plateado in the Bolivian and Peruvian Amazon as identified by BAPS. H exp: expected heterozygosity, H nb: heterozygosity calculated without deviation (Nei 1978), H obs: observed heterozygosity, P (0.95): polymorphism at 95% threshold, P (0.99): polymorphism at 99% threshold. N H exp. H n.b. H obs. P (0.95) P (0.99) Mean allele/locus cluster 1 standar error 183 0.710 0.141 0.714 0.146 0.695 1.0 1.00 8.33 cluster 2 standar error 184 0.711 0.210 0.713 0.211 0.710 1.0 1.00 13.11 cluster 3 standar error 17 0.676 0.132 0.696 0.176 0.660 1.0 1.00 6.67 91 Table 3.3.1. 7 Allelic frequencies for three plateado clusters identified by BAPS for Upper Madera and western Amazon (Bolivian and Peruvian Amazon). N: number of individuals, H exp: expected heterozygosity, H nb: heterozygosity calculated without bias (Nei 1978), H obs: observed heterozygosity. Locus cluster 1 2 3 Pcor1 N 120 122 124 126 128 132 134 136 138 140 142 144 146 148 150 152 154 158 160 162 164 166 168 172 178 180 182 184 186 188 212 274 83 0.000 0.006 0.042 0.012 0.000 0.000 0.012 0.000 0.175 0.000 0.000 0.030 0.000 0.000 0.157 0.012 0.000 0.000 0.000 0.000 0.078 0.452 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024 184 0.003 0.022 0.011 0.000 0.005 0.000 0.030 0.000 0.128 0.027 0.003 0.063 0.030 0.008 0.117 0.003 0.005 0.025 0.005 0.003 0.079 0.285 0.008 0.000 0.008 0.011 0.027 0.000 0.005 0.073 0.016 0.000 17 0.000 0.000 0.000 0.088 0.000 0.029 0.000 0.059 0.000 0.029 0.000 0.088 0.059 0.000 0.382 0.000 0.000 0.000 0.000 0.000 0.000 0.059 0.000 0.029 0.000 0.000 0.000 0.059 0.000 0.118 0.000 0.000 H exp H nb H obs 0.731 0.735 0.759 0.868 0.870 0.875 0.808 0.832 0.824 Pcor2 N 257 259 277 279 281 283 285 287 289 291 293 295 303 309 311 329 333 83 0.030 0.006 0.000 0.205 0.048 0.048 0.000 0.175 0.476 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.012 184 0.038 0.000 0.016 0.147 0.030 0.022 0.046 0.226 0.394 0.011 0.025 0.011 0.005 0.011 0.016 0.000 0.003 17 0.000 0.000 0.000 0.000 0.059 0.088 0.000 0.324 0.500 0.000 0.000 0.000 0.000 0.000 0.000 0.029 0.000 H exp H nb H obs 0.6953 0.6995 0.6627 0.7659 0.768 0.7717 0.6332 0.6524 0.6471 Locus cluster 1 2 3 Locus cluster 1 2 3 83 0.000 0.006 0.289 0.006 0.139 0.000 0.211 0.229 0.121 184 0.065 0.019 0.302 0.022 0.060 0.022 0.258 0.174 0.079 17 0.088 0.000 0.265 0.000 0.088 0.029 0.029 0.471 0.029 Pcor7 N 204 218 224 236 242 244 260 278 296 83 0.000 0.127 0.000 0.729 0.000 0.115 0.024 0.000 0.006 184 0.035 0.005 0.005 0.859 0.041 0.038 0.005 0.003 0.008 17 0.000 0.029 0.029 0.765 0.088 0.029 0.029 0.000 0.029 BR44 N 190 192 194 196 198 200 202 204 206 H exp H nb H obs 0.439 0.442 0.410 0.258 0.259 0.266 0.403 0.415 0.412 H exp H nb H obs 0.786 0.791 0.759 0.797 0.799 0.794 0.690 0.711 0.588 BR37 N 304 308 310 312 316 318 320 330 334 336 338 340 83 0.000 0.518 0.006 0.265 0.163 0.000 0.024 0.024 0.000 0.000 0.000 0.000 184 0.005 0.465 0.019 0.275 0.125 0.003 0.000 0.071 0.003 0.022 0.011 0.003 17 0.000 0.441 0.000 0.353 0.177 0.000 0.000 0.000 0.000 0.000 0.029 0.000 BR45 N 194 198 202 204 206 208 210 212 214 216 218 220 83 0.000 0.036 0.036 0.084 0.000 0.331 0.090 0.108 0.169 0.115 0.030 0.000 184 0.005 0.033 0.033 0.060 0.003 0.212 0.185 0.201 0.171 0.060 0.030 0.008 17 0.000 0.000 0.000 0.088 0.000 0.324 0.147 0.000 0.206 0.206 0.029 0.000 H exp H nb H obs 0.634 0.638 0.627 0.687 0.689 0.701 0.649 0.668 0.353 H exp H nb H obs 0.818 0.823 0.783 0.841 0.843 0.772 0.780 0.804 0.765 BR38 N 208 210 212 214 216 218 220 222 224 226 228 230 232 234 236 238 240 242 244 252 83 0.000 0.006 0.012 0.066 0.193 0.139 0.054 0.108 0.000 0.042 0.042 0.042 0.018 0.151 0.072 0.018 0.000 0.036 0.000 0.000 184 0.008 0.035 0.065 0.111 0.144 0.114 0.044 0.022 0.019 0.076 0.049 0.052 0.027 0.128 0.038 0.027 0.011 0.025 0.003 0.003 17 0.000 0.088 0.000 0.000 0.235 0.029 0.000 0.000 0.029 0.265 0.000 0.118 0.000 0.118 0.000 0.029 0.000 0.088 0.000 0.000 BR47 N 98 102 104 106 108 110 112 114 83 0.060 0.000 0.000 0.488 0.422 0.030 0.000 0.000 184 0.025 0.030 0.008 0.679 0.198 0.057 0.000 0.003 17 0.118 0.000 0.000 0.471 0.353 0.029 0.029 0.000 H exp H nb H obs 0.580 0.583 0.554 0.494 0.496 0.467 0.638 0.658 0.765 H exp H nb H obs 0.889 0.895 0.855 0.915 0.917 0.924 0.829 0.854 0.824 BR49 N 290 292 294 296 298 300 302 304 306 308 83 0.012 0.319 0.018 0.054 0.145 0.072 0.181 0.072 0.115 0.012 184 0.005 0.171 0.000 0.111 0.068 0.402 0.098 0.060 0.068 0.016 17 0.000 0.412 0.000 0.029 0.000 0.412 0.059 0.059 0.029 0.000 H exp H nb H obs 0.817 0.822 0.843 0.774 0.776 0.815 0.652 0.672 0.765 92 93 clus cluster 1 cluster 2 cluster 3 Figure 3.3.1. 3 Representation and visual ual co comparison of allele frequencies by locus for each of the three hree Plateado clusters identified by BAPS in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon). The y-axis corresponds co to the frequency and the x-axis to the alleles in each locus. alleles showed that cluster 2 was composed ed of the highest The distribution of private allele number of unique alleles (39) (39), while cluster 1 had the lowest (4). Generally, Gen the frequency of these alleles was low (< 6%). The locus with the highest hest number of unique alleles per cluster was Pcor1, with 14 alleles in cluster 2 (Table 3.3.1.8). 3.3. 94 Table 3.3.1. 8 Summary of private alleles for each of the three clusters identified by BAPS for Plateado from Upper Madera and western Amazon (Bolivian and Peruvian Amazon). N: number of individuals. cluster 1 (N=83) Nº Locus Allele Frequency 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 Pcor1 Pcor2 BR37 BR49 274 259 320 294 0.024 0.006 0.024 0.018 cluster 2 (N=184) Locus Allele Frequency cluster 3 (N=17) Locus Allele Frequency Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor1 Pcor2 Pcor2 Pcor2 Pcor2 Pcor2 Pcor2 Pcor2 Pcor2 Pcor7 Pcor7 BR37 BR37 BR37 BR37 BR37 BR38 BR38 BR38 BR38 BR45 BR45 BR45 BR47 BR47 BR47 Pcor1 Pcor1 Pcor1 Pcor1 Pcor2 BR47 120 128 142 148 154 158 160 162 168 178 180 182 186 212 277 285 291 293 295 303 309 311 204 278 304 318 334 336 340 208 240 244 252 194 206 220 102 104 114 0.003 0.005 0.003 0.008 0.005 0.024 0.005 0.003 0.008 0.008 0.011 0.027 0.005 0.016 0.016 0.046 0.011 0.024 0.011 0.005 0.011 0.016 0.035 0.003 0.005 0.003 0.003 0.022 0.003 0.008 0.011 0.003 0.003 0.005 0.003 0.008 0.030 0.008 0.003 132 136 172 184 329 112 0.029 0.059 0.029 0.059 0.029 0.029 The linkage disequilibrium analysis, measured by the values of 'D' for the different comparisons between pairs of clusters identified by BAPS, showed a non-systematic pattern (random drift) where DST2 > DIS2, y D’IS2 > D’ST2 (Table 3.3.1.9). These results demonstrate that the disequilibrium observed between the different cluster loci depends more on differentiation and genetic drift than on selection. The graphical representation of the relative divergence among the three clusters obtained with BAPS, showed that there is greater closeness between the numerically larger clusters 1 and 2, relative to the smaller cluster 3, which was the most distant (Figure 3.3.1.4). 95 Table 3.3.1. 9 Linkage disequilibrium variance components according to Ohta (1982 a, b) for the nine loci studied in the three clusters of Plateado defined in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon) according to BAPS. Comparación de locus DIS2 D'IS2 DST2 D'ST2 DIT2 Pcor1 - Pcor2 Pcor1 - Pcor7 Pcor1 - BR37 Pcor1 - BR38 Pcor1 - BR44 Pcor1 - BR45 Pcor1 - BR47 Pcor1 - BR49 Pcor2 - Pcor7 Pcor2 - BR37 Pcor2 - BR38 Pcor2 - BR44 Pcor2 - BR45 Pcor2 - BR47 Pcor2 - BR49 Pcor7 - BR37 Pcor7 - BR38 Pcor7 - BR44 Pcor7 - BR45 Pcor7 - BR47 Pcor7 - BR49 BR37 - BR38 BR37 - BR44 BR37 - BR45 BR37 - BR47 BR37 - BR49 BR38 - BR44 BR38 - BR45 BR38 - BR47 BR38 - BR49 BR44 - BR45 BR44 - BR47 BR44 - BR49 BR45 - BR47 BR45 - BR49 BR47 - BR49 0.009 0.003 0.006 0.007 0.007 0.008 0.005 0.006 0.002 0.004 0.007 0.009 0.008 0.004 0.008 0.005 0.003 0.002 0.003 0.002 0.003 0.006 0.006 0.008 0.005 0.008 0.009 0.009 0.005 0.006 0.007 0.004 0.005 0.004 0.005 0.008 0.034 0.051 0.039 0.019 0.031 0.025 0.045 0.043 0.021 0.017 0.018 0.027 0.023 0.032 0.051 0.019 0.027 0.037 0.031 0.078 0.095 0.019 0.024 0.020 0.040 0.053 0.018 0.016 0.027 0.026 0.022 0.038 0.040 0.029 0.032 0.079 0.024 0.041 0.024 0.012 0.022 0.016 0.030 0.025 0.013 0.009 0.013 0.019 0.011 0.014 0.022 0.006 0.019 0.027 0.015 0.024 0.032 0.011 0.016 0.009 0.011 0.019 0.013 0.009 0.014 0.015 0.014 0.021 0.024 0.013 0.015 0.024 0.004 0.001 0.002 0.004 0.003 0.004 0.001 0.003 0.001 0.002 0.004 0.002 0.002 0.001 0.003 0.003 0.001 0.001 0.001 0.001 0.001 0.002 0.001 0.003 0.001 0.002 0.004 0.003 0.002 0.003 0.002 0.002 0.003 0.003 0.004 0.001 0.038 0.052 0.041 0.022 0.034 0.029 0.047 0.046 0.022 0.018 0.022 0.029 0.026 0.033 0.054 0.021 0.028 0.038 0.032 0.079 0.096 0.021 0.025 0.023 0.042 0.055 0.021 0.019 0.029 0.028 0.023 0.040 0.043 0.032 0.036 0.080 Figure 3.3.1. 4 Squared representation of the relative distance between the three clusters of Plateado from Upper Madera and western Amazon (Bolivian and Peruvian Amazon) inferred by BAPS from nine microsatellite loci, according to the most optimal partition visited (K = 3 and 100 repetitions). Relationships were built using the nearest neighbor criterion (NJ) and using the Leibler-Kullbak divergence matrix- generated by the same BAPS program. All comparisons between pairs of clusters are significant as per the estimator θ of the fixation index FST. 96 a) b) Figure 3.3.1. 5 a) Mixture analysis graph ph pr produced by BAPS on 284 Plateado individuals from five localities localit in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon) for K = 3 (cluster) and 100 repetitions. titions. Individuals are represented by vertical bars of a single color depending on the cluster assigned by BAPS. The width of the vertical ve bars varies according to the number of contiguous individuals individ belonging to the same cluster. Locations correspond to VB: VB Villa Bella; CE: Cachuela Esperanza; PM: Puerto Maldonad donado; RU: Rurrenabaque; PV: Puerto Villarroel; IQ: Iquitos,, and b) Composition representation (number of individuals) of the clusters identified by BAPS for each geographic location studied stud in the Upper Madera and western Amazon (Bolivian and P Peruvian Amazon). Numbers next to the name’s localities refer to the number of individuals of Plateado that were considered dered for each location. Oblique black bars represent the rapids series ser in the Upper Madera basin, between Bolivia and Brazil. In b both figures (a and b) cluster 1 is represented in red, cluster 2 in green g and cluster 3 in blue. The geographical distribution tion of the three clusters determined by the he best be partition with BAPS, revealed that a uniform spatial arrangement does nott exis exist between them. Cluster 1 was identified tified in the five localities studied from the Upp Upper Madera (Bolivian Amazon + Puerto Ma Maldonado) but not in the western Amazon zon (Iquitos). In 97 turn, individuals attributed to the largest group (cluster 2) were distributed both in the Upper Madera and in the western Amazon, but were predominant in the latter. A single individual in the sample from Iquitos in the western Amazon was part of cluster 3, which was the smallest in size but was present in all geographic locations sampled (Figure 3.3.1.5). Genetic distance tree (Rousset 1997) established by microsatellites polymorphism for the geographical locations in each of the two main clusters A neighbor joining tree was built according to the distance from Rousset (1997) considering the allelic variation of the microsatellites (Figure 3.3.1.6). Each geographic sample was divided into the two major clusters (1 and 2) forming several subsamples. Within both clusters, a similar tendency was observed where geographical subsamples were organised following a downstream - upstream pattern: Villa Bella (VB), Puerto Maldonado (PM), Rurrenabaque (RU), Puerto Villarroel (PV). Only Cachuela Esperanza (CE) did not follow the same order within the two clusters. In addition, it is important to note that the subsample from Iquitos was closer to a subsample (c2VB) originating from the lowest portion of the Bolivian Amazon (Villa Bella) (Figure 3.3.1.6). In general, there is a structuring tendency from downstream to upstream, and it is likely that the individuals from Brazil (for which we have no microsatellite information) are closer to the individuals originating from Iquitos. Figure 3.3.1.6 Representation (tree with no root) of the distance, inferred from microsatellite allelic variation among geographic subsamples within the clusters defined by BAPS, built with the Neighbor-Joining criterion and the distance by Rousset (1997). c1: cluster 1; c2: cluster 2; VB: Villa Bella; CE: Cachuela Esperanza; PM: Puerto Maldonado; RU: Rurrenabaque; PV: Puerto Villarroel; IQ: Iquitos. Cluster 3 is not represented in the figure due to the small number of individuals. The group enclosed by the dotted line and green color corresponds to cluster 1, and the group with the barred line and red color to cluster 2. The difference between cluster 1 and cluster 2 is significant according to the estimator θ of FST. 98 3.3.2 Mitochondrial DNA (Control Region - CR) We identified 170 haplotypes defined by 116 polymorphic sites (120 total mutations, 5 gaps) in the 506 (461 in this study plus 45 from Brazil’s GenBank) Plateado individuals analyzed from the Upper Madera, Central and Western Amazon (Bolivian, Peruvian and Brazilian Amazon) (Table 3.3.2.1). Overall, haplotype diversity (H) was 0.9685 ± 0.0029, and nucleotide diversity (π) 0.00817 ± 0.00014. The total number of insertions / deletions (InDel) was three, and the number of sites with gaps was two in three individuals. Table 3.3.2. 1 Haplotype frequency for Plateado found in 461 samples obtained in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon), plus 45 sequences of Central Amazon (Brazil) available at GenBank. VB: Villa Bella, CE: Cachuela Esperanza; PM: Puerto Maldonado; RU: Rurrenabaque; PV: Puerto Villarroel, IQ: Iquitos; BR: Brazil. Figures in parentheses represent the number of individuals analyzed per respective location. Haplotipo VB (22) CE (91) PM (51) RU (86) PV (143) IQ (61) BR (45) Total Hap 1 Hap 2 Hap 3 Hap 4 Hap 5 Hap 6 Hap 7 Hap 8 Hap 9 Hap 10 Hap 11 Hap 12 Hap 13 Hap 14 Hap 15 Hap 16 Hap 17 Hap 18 Hap 19 Hap 20 Hap 21 Hap 22 Hap 23 Hap 24 Hap 25 Hap 26 Hap 27 Hap 28 Hap 29 Hap 30 Hap 31 Hap 32 Hap 33 Hap 34 Hap 35 Hap 36 Hap 37 Hap 38 Hap 39 Hap 40 Hap 41 Hap 42 Hap 43 Hap 44 Hap 45 Hap 46 Hap 47 Hap 48 Hap 49 Hap 50 3 3 1 6 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 15 9 12 0 0 4 0 4 0 0 0 1 1 1 1 7 1 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 9 7 8 0 0 2 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 1 0 1 0 2 0 0 0 1 1 1 1 1 4 0 0 4 6 1 0 0 0 0 4 0 0 0 0 0 1 11 0 0 9 0 3 0 0 0 0 0 0 2 0 0 0 1 0 4 0 0 0 3 0 0 0 0 0 0 0 0 0 0 5 0 1 3 15 3 0 0 0 0 0 0 0 0 0 0 0 12 0 2 12 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 0 8 0 0 0 0 1 0 0 0 0 0 0 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 6 0 0 0 0 0 0 0 0 0 0 0 0 0 1 17 5 26 33 47 5 1 7 1 7 6 1 1 1 1 1 2 35 1 4 28 3 4 1 1 1 1 1 2 3 1 1 1 2 1 25 2 2 1 13 1 3 1 1 2 3 1 1 1 4 0 0 0 2 4 0 0 0 0 2 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 1 0 0 0 0 0 0 0 0 1 0 0 0 2 99 Haplotipo VB (22) CE (91) PM (51) RU (86) PV (143) IQ (61) BR (45) Total Hap 51 Hap 52 Hap 53 Hap 54 Hap 55 Hap 56 Hap 57 Hap 58 Hap 59 Hap 60 Hap 61 Hap 62 Hap 63 Hap 64 Hap 65 Hap 66 Hap 67 Hap 68 Hap 69 Hap 70 Hap 71 Hap 72 Hap 73 Hap 74 Hap 75 Hap 76 Hap 77 Hap 78 Hap 79 Hap 80 Hap 81 Hap 82 Hap 83 Hap 84 Hap 85 Hap 86 Hap 87 Hap 88 Hap 89 Hap 90 Hap 91 Hap 92 Hap 93 Hap 94 Hap 95 Hap 96 Hap 97 Hap 98 Hap 99 Hap 100 Hap 101 Hap 102 Hap 103 Hap 104 Hap 105 Hap 106 Hap 107 Hap 108 Hap 109 Hap 110 Hap 111 Hap 112 Hap 113 Hap 114 Hap 115 Hap 116 Hap 117 Hap 118 Hap 119 Hap 120 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 3 1 1 1 1 2 1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 1 0 0 2 0 0 0 4 0 0 0 0 0 0 0 0 0 1 2 0 0 0 0 0 0 1 1 2 2 2 1 1 2 1 1 2 1 2 2 2 3 1 6 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 0 0 0 0 0 0 0 0 8 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 2 1 8 1 1 1 16 1 1 3 1 2 1 7 1 1 1 1 1 1 4 1 3 3 3 1 1 1 1 1 1 3 1 2 2 2 1 1 2 1 1 2 1 2 2 2 3 1 6 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 0 0 0 0 1 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 100 Haplotipo VB (22) CE (91) PM (51) RU (86) PV (143) IQ (61) BR (45) Total Hap 121 Hap 122 Hap 123 Hap 124 Hap 125 Hap 126 Hap 127 Hap 128 Hap 129 Hap 130 Hap 131 Hap 132 Hap 133 Hap 134 Hap 135 Hap 136 Hap 137 Hap 138 Hap 139 Hap 140 Hap 141 Hap 142 Hap 143 Hap 144 Hap 145 Hap 146 Hap 147 Hap 148 Hap 149 Hap 150 Hap 151 Hap 163 Hap 152 Hap 154 Hap 155 Hap 156 Hap 157 Hap 158 Hap 159 Hap 160 Hap 161 Hap 162 Hap 163 Hap 164 Hap 165 Hap 166 Hap 167 Hap 168 Hap 169 Hap 170 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 3 1 1 1 1 1 1 1 2 1 1 2 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 The maximum likelihood tree constructed with the 170 haplotypes (CR, mtDNA, 952 bp) identified in the Bolivian, Peruvian and Brazilian Amazon, showed that all analyzed Plateado individuals form a monophyletic group but with no internal genealogical structure supported by high bootstrap value (e.g. bootstrap ≥ 70%). Differentiated haplo-groups with a common history (coalescing) cannot be distinguished within the tree (Figure 3.3.2.1). 101 Figure 3.3.2. 1 Maximum likelihood phylogene ogenetic tree (F84 + I + Γ = 0:51 = 0.62) constructed with 170 haplotyp plotypes (CR, mtDNA, 952 bp) from the fish Plateado originating in Upper Madera and central and western Amazon (Bolivian, Peruvian Peruv and Brazilian Amazon). Numbers next to nodes represent sent bootstrap values above 50%. The phylogenetic tree is rooted ed wit with two species of Brachyplatystoma (B. vaillantii - Bv and B. platynemum - Bp) and Platynematichthys notatus - Pn. The e Plateado Pla haplotypic phylegeny is not resolved and has a comb-like like topology. 102 The parsimony network analysis also revealed that there are no well differentiated lineages of Plateado separated and characterized by several mutational steps. The larger groups contain two or three central haplotypes (higher frequency), from which they derive several lesser ones which have no more than 10 mutational changes between them (Figure 3.3.2.2). Figure 3.3.2. 2 Haplotype network constructed with the principle of parsimony for the 170 haplotypes of Plateado from the Upper Madera and central and western Amazon (Bolivian, Peruvian and Brazilian Amazon). Circle size is proportional to the number of individuals. Red circles indicate hypothetical mutational steps not observed in the samples. The bold circle denotes the most basal haplotype as per the maximum likelihood tree. Similar to the general phylogram, the maximum likelihood phylogenetic tree of haplotypes (CR) from Plateado obtained only in the portion of the Upper Madera (Bolivian Amazon and Puerto Maldonado), showed that there is no genealogical structure at the geographical scale of this region (Figure 3.3.2.3). The topology of the tree resembles a comb-like form due to the low differentiation between haplotypes. 103 Figure 3.3.2. 3 Maximum likelihood phylogene ogenetic tree (F84 + I + Γ = 0:51 = 0.62) constructed with 160 haplotyp plotypes (CR, mtDNA, 1071 bp) of Plateado from Upper Madera dera (Bolivian Amazon and Puerto Maldonado). Numbers next to nodes represent bootstrap values above 50%. The phylogene genetic tree is rooted with two species of Brachyplatystoma (B. vaillantii vail - Bv and B. platynemum - Bp) and Platynematichthys nota notatus - Pn. 104 When the haplotypes of the 267 individuals originating from the Upper Madera and western Amazon (Bolivian and Peruvian Amazon) were distributed into the 3 clusters defined by BAPS and compared, no genetic structure was observed (FST and ϕST values were close to zero with p-values > 0.2; Table 3.3.2.3). Table 3.3.2. 2 Haplotype distribution of Plateado found in 267 samples from the Upper Madera and western Amazon (Bolivian and Peruvian Amazon), divided into three clusters (panmictic units) as identified by BAPS according to microsatellite data. Values in parentheses represent the number of individuals analyzed by the respective cluster. Haplotipo cluster 1 (80) cluster 2 (170) cluster 3 (17) Total Hap 1 Hap 2 Hap 3 Hap 4 Hap 5 Hap 6 Hap 7 Hap 8 Hap 9 Hap 10 Hap 11 Hap 12 Hap 13 Hap 14 Hap 15 Hap 16 Hap 17 Hap 18 Hap 19 Hap 20 Hap 21 Hap 22 Hap 23 Hap 24 Hap 25 Hap 26 Hap 27 Hap 28 Hap 29 Hap 30 Hap 31 Hap 32 Hap 33 Hap 34 Hap 35 Hap 36 Hap 37 Hap 38 Hap 39 Hap 40 Hap 41 Hap 42 Hap 43 Hap 44 Hap 45 Hap 46 Hap 47 Hap 48 Hap 49 3 7 6 1 2 1 4 2 1 11 1 1 1 1 1 1 1 1 1 6 1 2 2 1 1 1 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 5 8 13 0 1 0 1 1 0 11 0 0 3 0 0 0 0 0 1 9 0 0 9 2 1 0 9 0 0 0 0 0 0 2 2 0 0 1 1 1 0 0 1 1 1 1 1 2 1 1 2 3 0 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 2 0 0 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 17 22 1 4 1 5 3 1 24 1 1 4 1 1 1 1 1 2 17 1 2 14 3 2 1 14 1 1 1 1 1 1 3 3 1 1 2 2 2 1 1 1 1 1 1 1 2 1 105 Haplotipo cluster 1 (80) cluster 2 (170) cluster 3 (17) Total Hap 50 Hap 51 Hap 52 Hap 53 Hap 54 Hap 55 Hap 56 Hap 57 Hap 58 Hap 59 Hap 60 Hap 61 Hap 62 Hap 63 Hap 64 Hap 65 Hap 66 Hap 67 Hap 68 Hap 69 Hap 70 Hap 71 Hap 72 Hap 73 Hap 74 Hap 75 Hap 76 Hap 77 Hap 78 Hap 79 Hap 80 Hap 81 Hap 82 Hap 83 Hap 84 Hap 85 Hap 86 Hap 87 Hap 88 Hap 89 Hap 90 Hap 91 Hap 92 Hap 93 Hap 94 Hap 95 Hap 96 Hap 97 Hap 98 Hap 99 Hap 100 Hap 101 Hap 102 Hap 103 Hap 104 Hap 105 Hap 106 Hap 107 Hap 108 Hap 109 Hap 110 Hap 111 Hap 112 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 1 2 2 5 1 1 1 3 1 1 1 1 2 3 1 1 2 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 2 1 1 2 2 5 1 1 1 3 1 1 1 1 2 3 1 1 2 1 1 1 3 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 106 Table 3.3.2. 3 FST and ϕST (TN93, α = 0.81) .81) values (diagonal above) and their significance plus standard d deviation dev (diagonally below), calculated from the variation in haplotype haplot frequencies between pairs of clusters (panmictic units) of Plateado obtained with BAPS as per microsatellite data. Negative gative values represent a value of zero. N cluster luster 1 cluster 2 cluster 3 83 184 17 0.000 .000 0.228 .228 ± 0.005 0.752 .752 ± 0.005 0.001 0.000 0.817 ± 0.004 -0.008 -0.006 0.000 0.000 .000 0.777 .777 ± 0.011 0.961 .961 ± 0.005 -0.004 0.000 0.961 ± 0.006 -0.023 -0.021 0.000 F ST cluster 1 cluster 2 cluster 3 ϕ ST cluster 1 cluster 2 cluster 3 Genetic distance tree (Rouss usset 1997) established according to the e variation v in haplotype frequencies for the th geographical locations in each of the two main clusters A neighbor joining tree was created following the distance by Rouss Rousset (1997) considering haplotype frequenc quency variation. Each geographic sample was divided into the three clusters forming ing va various subsamples. It was noted that there is a concordant grouping consisten sistent with geography: the subsamples from the upper parts (Rurrenabaque-RU and Puerto Villarroel-PV) were close to each eac other in contrast to the subsamples ples ffrom the lower parts (Villa Bella-VB and Cachuela Esperanza EC) (Figure 3.3.2.4). 3.3.2.4 Only Puerto Maldonado (PM) did d not follow the same geographical coherence ence. It is important to note that the subsample ple fr from Iquitos and Brazil was linked to the subsamples of Rurrenabaque and Puerto uerto Villarroel, which are at the top of the upper uppe basin of the Madera River (Figure 3.3.2.4 .3.2.4). a) 107 b) Figure 3.3.2. 4 a) Unrooted tree derived from haplotype frequency (CR) variations between geographic sub-samples within the clusters of Plateado defined by BAPS, built with the grouping criterion of Neighbor-Joining and linearization of FST according to Slatkin (1995) (FST/1-FST). c1: cluster 1; c2: cluster 2; VB: Villa Bella; CE: Cachuela Esperanza; PM: Puerto Maldonado; RU: Rurrenabaque; PV: Puerto Villarroel; IQ: Iquitos; BR: Brazil. The dotted line corresponds to the lower area of the Upper Madera basin (Bolivian Amazon including Puerto Maldonado - PM); the hashed line encloses the headwater area; the dot and hash line represents the lower part of the western Amazon including the haplogroup from Brazil (BR) which did not differ significantly from Iquitos (IQ) in the overall analysis by location according to the estimator θ of FST. b) Spatial schematic of haplogroup (CR) subset (location) affinity within the clusters (1 and 2) defined by BAPS in Upper Madera and western and central Amazon (Bolivian, Peruvian and Brazilian Amazon). It can be assumed that haplotypes of the Amazon’s main stem in Brazil are close to those found in Iquitos (IQ), based on the result of the estimator θ of FST. The nomenclature is similar to a above, and includes the following locations on the Amazon’s main stem in Brazil, represented by a star: Tabatinga (TB), Manaus (AM) and Belén (BE). Oblique black bars represent the rapids series in the Upper Madera basin, between Bolivia and Brazil. Considering that the three sets of haplotypes distributed among the microsatellite clusters (as defined by BAPS), did not have significant differences between them and that the nearest neighbor tree showed a general grouping among the closest geographical locations, an analysis was made between the different locations studied. The values and significance of the estimator θ (FST) between pairs of haplotypes per locality, revealed that the headwaters of the Beni (Rurrenabaque) and Mamoré (Puerto Villarroel, Ichilo River) rivers have a similar distribution of their haplotypes without significant differentiation. Similar results were obtained for comparisons between Cachuela Esperanza and Puerto Maldonado, and between Iquitos (Peru) and Brazil (Tabatinga-Manaus-Belen). Thus, Plateado haplotypes (CR) are structured into four haplogroups (defined by the haplotypic frequencies) positioned in the areas of Iquitos + Brazil, Villa Bella, Cachuela Esperanza + Puerto Maldonado, and Rurrenabaque + Puerto Villarroel. ϕST results were similar to those found with FST, except that VB did not differ significantly from CE, PM, RU, PV y BR (Table 3.3.2.4). 108 Table 3.3.2. 4 FST and ϕST values (TN93, α = 0.81) (diagonal above) and their significance plus the standard deviation (diagonal below) obtained for the comparisons between pairs of geographic samples considering the variation at their haplotype level. VB: Villa Bella; CE: Cachuela Esperanza; PM: Puerto Maldonado; RU: Rurrenabaque; PV: Puerto Villarroel; IQ: Iquitos (Peru); BR: Brazil (Tabatinga-Manaus-Belén). Fields marked in gray correspond to significant values. Negative values represent a zero value. F ST VB CE PM RU PV IQ BR VB 0.000 0.024 0.023 0.040 0.044 0.041 0.055 CE 0.021 ± 0.001 0.000 -0.006 0.020 0.019 0.024 0.039 PM 0.047 ± 0.002 0.939 ± 0.003 0.000 0.021 0.024 0.025 0.041 RU 0.001 ± 0.000 0.000 ± 0.000 0.000 ± 0.000 0.000 0.002 0.013 0.025 PV 0.000 ± 0.000 0.000 ± 0.000 0.000 ± 0.000 0.189 ± 0.004 0.000 0.012 0.018 IQ 0.000 ± 0.000 0.000 ± 0.000 0.000 ± 0.000 0.004 ± 0.001 0.000 ± 0.000 0.000 0.000 BR 0.000 ± 0.000 0.000 ± 0.000 0.000 ± 0.000 0.002 ± 0.001 0.000 ± 0.000 0.437 ± 0.005 0.000 VB 0.000 0.018 0.024 0.028 0.024 0.047 0.031 CE 0.112 ± 0.003 0.000 -0.009 0.015 0.039 0.051 0.054 PM 0.096 ± 0.003 0.930 ± 0.003 0.000 0.019 0.040 0.040 0.044 RU 0.062 ± 0.003 0.020 ± 0.001 0.004 ± 0.001 0.000 0.003 0.043 0.037 PV 0.073 ± 0.003 0.001 ± 0.000 0.030 ± 0.002 0.214 ± 0.004 0.000 0.040 0.024 IQ 0.010 ± 0.001 0.000 ± 0.000 0.003 ± 0.001 0.000 ± 0.000 0.001 ± 0.000 0.000 -0.008 BR 0.052 ± 0.002 0.000 ± 0.000 0.004 ± 0.001 0.005 ± 0.001 0.025 ± 0.002 0.832 ± 0.004 0.000 ϕ ST Genetic distance tree (Rousset 1997) established according to microsatellite polymorphism: combination of the microsatellite (clusters) and haplotypes (haplogroups) results Geographic samples differentiated by FST, calculated according to the distribution of haplotype frequencies (Table 3.3.2.4), formed a haplogroup. Each haplogroup, split into the clusters, formed several sub-haplogroups. The sub-haplogroups were placed on a nearest neighbor tree built from the genetic distance by Rousset (1997) established according to microsatellite polymorphism. 109 a) b) Figure 3.3.2. 5 a) Unrooted tree derived from microsatellite allelic variations (frequency) between subhaplogrou logroups (combination of haplogroups - CR and clusters defined d by BAPS), built with the Neighbor-Joining grouping approach and Rousset’s R (1997) distance. Haplogroups correspond to Iquitos (IQ), Villa Bella (VB), Cachuela Esperanza + Puerto Maldonado Maldo (CE+PM), Rurrenabaque + Puerto Villarroel (RU+PV). PV). c1: cluster 1 (pink background) c2: cluster 2 (green backgroun ground); c3: cluster 3 (blue background). b) Spatial representation tion o of the combination of data provided by the clusters and haplogro logroups presented in section a. Cluster 3 is also present in locatio locations IQ and VB but in a reduced number of individuals as indic indicated in the text. Oblique black bars represent the rapidss seri series in the Upper Madera basin, between Bolivia and Brazil. The nomenclature follows the same terminology used in part a. In each cluster, the same e ten tendency was observed where sub-haplogro plogroups were distributed according to a down downstream – upstream pattern: cluster 1, Villa Bella (VB), Cachuela Esperanza (CE)) + P Puerto Maldonado (PM), Rurrenabaque e (RU (RU) + Puerto 110 Villarroel (PV); cluster 2, Iquitos (IQ), Villa Bella, Cachuela Esperanza + Puerto Maldonado, Rurrenabaque + Puerto Villarroel; cluster 3, Cachuela Esperanza + Puerto Maldonado, Rurrenabaque + Puerto Villarroel. Unlike the tree constructed with the distance obtained from haplotype frequencies (Figure 3.3.2.4a), the Iquitos samples in cluster 2 was closer to a subsample from Villa Bella, located at the entrance to the upper basin of the Madera River (Figure 3.3.2.5). Demography Differences between pairs (mismatch) The three clusters defined by BAPS using the panmixia criterion, had an average number of differences between pairs of nucleotides (k) varying from 7.12 to 8.46. Their haplotype diversity (h) ranged from 0.98 to 0.94, and nucleotide diversity (π) from 0.0067 to 0.0079. The Tajima (D) statistic was negative and not significant (p > 0.05) for the three populations and indicates that we cannot reject the hypothesis of selective neutrality. In turn, negative and significant values (except for population 3) of the statistic Fu (Fs), suggests that selection, population reduction (bottleneck) or population expansion would be involved in the changes the populations are going through. In the particular case of population 3, the non-significance observed in the Fs value may be due to the small number of individuals (17) assigned and analyzed in this group (Table 3.3.2.5). Table 3.3.2. 5 Population genetic parameters and neutrality tests for haplotypes (CR, mtDNA, 1041 bp) of 267 Plateados, from the Upper Madera and western Amazon (Bolivian and Peruvian Amazon), divided into three clusters as identified by BAPS based on microsatellite information. N: number of individuals; k: average number of differences between pairs; h: haplotype diversity; π: nucleotide diversity; sd: standard deviation; D sim: D simulated; D obs: D observed; Fs sim: Fs simulated; Fs obs : Fs observed; difference between pairs: mismatch; τ: Tau, SSD: square sum deviation; DSC sim: DSC simulated; DSC obs: DSC observed; r: Harpending's raggedness index; rag sim r simulated rag obs: r observed; de: demographic expansion; se: spatial expansion. N No. de Haplotipos k ± ds h ± ds π ± ds D de Tajima P (D sim < D obs) Fs de Fu P (Fs sim ≤ Fs obs) Diferencia entre pares τ DSC (de) P (DSC sim ≥ DSC obs) (de) r (de) P (rag sim ≥ rag obs) (de) DSC (se) P (DSC sim ≥ DSC obs) (se) r (se) P (rag sim ≥ rag obs) (se) cluster 1 cluster 2 cluster 3 80 42 8.430 ± 3.942 0.960 ± 0.010 0.008 ± 0.004 -1.095 0.121 -18.670 0.000 8.343 9.621 0.002 0.770 0.006 0.782 0.004 0.650 0.006 0.977 170 88 8.457 ± 3.932 0.978 ± 0.004 0.008 ± 0.004 -1.204 0.081 -24.488 0.000 8.295 9.584 0.001 0.846 0.004 0.847 0.003 0.334 0.004 0.988 17 10 7.122 ± 3.515 0.934 ± 0.036 0.007 ± 0.004 -0.386 0.373 -0.457 0.414 6.956 8.336 0.024 0.145 0.050 0.161 0.022 0.363 0.050 0.497 The distribution of differences between pairs of haplotypes (mismatch distribution) showed a well-defined unimodal pattern for clusters 1 and 2, and approximate for cluster 3 due to the small number of individuals analyzed. This pattern, supported by the negative values of Fs (Fu) and D (Tajima), is consistent with a sudden population 111 and spatial expansion model from a small number of fish (Figure 10). Both the Sum of Square Deviations (SSD) and the raggedness index, (r) suggested that the observed distribution curves do not differ significantly from the simulated distribution curves under a population expansion and spatial expansion model (Table 3.3.14, Figure 3.3.2.6). a) P (DSC) = 0.770 P (r) = 0.782 P (DSC) = 0.650 P (r) = 0.977 Tamaño poblacional (NeƬ) Bayesian skyline plot - clus 1 millones de años b) P (DSC) = 0.846 P (r) = 0.847 P (DSC) = 0.334 P (r) = 0.988 Tamaño poblacional (NeƬ) Bayesian skyline plot - clus 2 millones de años c) P (DSC) = 0.363 P (r) = 0.497 Bayesian skyline plot - clus 3 Tamaño poblacional (NeƬ) P (DSC) = 0.145 P (r) = 0.161 millones de años Figure 3.3.2. 6 Distribution of the difference between pairs of haplotypes (mismatch distribution) based on a population expansion (left) and spatial expansion (center) model for to sequences of the CR (mtDNA, 1071 bp) in three clusters (a: clus 1, b: clus 2 c: clus 3) of plateado - Brachyplatystoma rousseauxii - defined by BAPS, from the Upper Madera and western Amazon (Bolivian and Peruvian Amazon). P (DSC) is the probability that DSC simulated ≥ DSC observed, P (r) represents the probability that the Harpending's raggedness index simulated (r) ≥ r observed, CI: confidence intervals at different thresholds. Bayesian Skyline Plots (m = 10 for clusters 1 and 2, and m = 5 for the cluster 3) are to the right of graphs a b and c. They are derived from the samples (n = 80 clus1, n = 170 clus2; clus3 n = 17) of sequences corresponding to each cluster (Control Region, mtDNA). The x-axis represents time over millions of years. The y-axis represents Ne τ (product between the effective population size of females in millions of years and generation time in years). The solid center line is the estimated median, and the surrounding blue band show the 95% limits for the highest probability density. 112 Demographics inferred through coalescence Bayesian Skyline Plots (BSP) showed that the effective size of females in cluster 1 remained relatively constant until about 200 000 years ago. Subsequently, the effective population began a steep exponential growth process between 200 000 – 100,000 years ago. Population size appears to have remained stable ever since (Figure 3.3.2.6). Similar to cluster 1, cluster 2 had a slight progressive increase to about 250,000 years ago. After this period, the effective size significantly increased exponentially between 250,000 – 50,000 years ago. Population size has remained stable ever since (Figure 3.3.2.6). Unlike the two previous clusters, the BSP of cluster 3 haplotypes, show no significant trend over its demographic history. According to the Bayesian analysis, the effective size of this group appears to have remained relatively constant over the last 400,000 years, but this could be the result of the small number of individuals (17) and haplotypes (10) identified in this cluster (Figure 3.3.2.6). 3.4 Discussion 3.4.1 Nuclear DNA (microsatellite) Data from the nine microsatellites used in this study showed a significant deviation from panmixia when tested in one group (Upper Madera & western Amazon). Similarly, when sets of genotypes were grouped according to their geographical origin (5 locations in the upper basin of the Madera River and one in the UcayaliAmazonas), it was observed that the genotype frequencies of the Upper Madera deviated significantly from the expected proportions under the Hardy-Weinberg equilibrium (panmictic population). Because of this, an inference was made on the population structure to define the most likely panmitic clusters from the samples of Plateado obtained in the different geographic locations studied, using a Bayesian model which groups individuals according to their allelic frequencies (BAPS). This procedure was justified by the significant deviation from panmixia observed in the overall grouping of the geographic locations studied (analysis of a single group), and the migratory nature of the species that need not conform to a genetic structure dependent on geography: admixture of individuals from different populations continuously on the move. The results of the analysis with BAPS, suggest that in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon), there are at least three clusters of Plateado with a partially overlapping geographic distribution. The groups created were considered as panmictic genetic units because none of them deviated significantly from the expected proportions (genotypes) under the Hardy-Weinberg equilibrium (panmixia) model, and the difference between them was significant. Thus, cluster 1 included only individuals from the five localities studied in the upper basin of the Madera River (Bolivian Amazon mainly). Individuals from the locations in the upper basin (Rurrenabaque and Puerto Villarroel) were greater in proportion. Cluster 2, which was the largest in terms of number of individuals, consisted of specimens from all the locations studied, but with the following specifics: this cluster included all individuals from the Ucayali-Amazonas (Peru) system, except for one (64 out of 65), and a substantial proportion (45%) of the fish caught in the 113 lower reaches of the upper Madera River (Villa Bella, Cachuela Esperanza and Puerto Maldonado). Finally, Cluster 3 was the most genetically distinct, the smallest in size and included individuals from all the localities visited, even though only one specimen of the Ucayali-Amazonas system was assigned to this group. The degree of differentiation observed between the clusters identified by BAPS (FST: 0.028 – 0.043), was small relative to that observed in other groups of migratory fish in the Neotropics (see Abreu et al. 2009, FST: 0.229, Pereira et al. 2009, FST: = 0.034 – 0.164). According to Wright (1978) and Hartl & Clark (1997), FST values between 0 and 0.05 mean little differentiation, between 0.05 to 0.15 moderate differentiation, between 0.15 to 0.25 large differentiation, and above 0.25 very large differentiation. However, these data should be considered broadly and carefully (e.g. Wright (1978) calculated the limits based on allozymes), because there is a substantial variation in these values between organisms (Balloux & Lugon-Moulin 2002). The FST values found for the Plateado are inferior to those of some continental migratory species, like Pseudoplatytoma (Siluriformes, Pimelodidae), but close to or above those of other marine and continental species (Table 3.4.1). In general, the observed FST values for the Plateado are higher than those found in migratory and non-migratory marine fishes. Actually, the observed difference is about 10 times greater than that of marine fish with large migrations (e.g. Gadus morhua – Knutsen et al. 2003; Knutsen et al. 2011; Salmo salar – Dionne et al. 2008) or local migration (e.g Hoplostethus atlanticus – Carlsson et al. 2011) (Table 3.4.1). Based on these comparisons and on studies that demonstrate the biological significance of low FST values obtained using microsatellites in migratory and non-migratory marine species (e.g. Knutsen et al. 2011, Stefánsson et al. 2009), it can be considered that the differences found among Plateado clusters reflect the existence of a population structure (at least three gentic units) in the Amazon. Therefore, despite low FST values, our results clearly indicate the existence of a population structure for the Plateado in the Amazon basin. The important gene flow observed among populations (Nm based on FST values: 8.76, 6.31, 5.51 – Table 3.3.1.5) is not enought to prevent the population structuration. The observation of private alleles cannot be the consequence of a strong structuration and is therefore likely due to the different sample size of populations. Clusters were defined under the panmixia criterion, independently from geographical aspect. But when the clusters were split into sub-samples corresponding to the geographic locations, however, the same trend was observed in their genetic structure: individuals of the same cluster came closer together, as expected, and geographic subunits within populations followed a general pattern consistent with spatial proximity or relative position in the drainage (connectivity) (Figure 3.3.4). An interesting observation on this representation is that the individuals obtained in the Iquitos market (Ucayali-Amazonas) were closer to the ones at the entrance to the Bolivian Amazon (Villa Bella), than to the locations higher up the Upper Madera. This relationship is consistent with the displacements that adults and juveniles of this species would make from downstream (Lower Madera and / or Central Amazon) towards the main tributaries of the upper basin of the Madera River. The results obtained using microsatellite analyses, are a new contribution to the knowledge about the Plateado. The identification of three populations in the two systems studied in the Amazon basin, one of them observed as exclusive of the Upper Madera basin, suggests the possibility of a homing event. So far, the 114 presence of the species along the main channel of the Amazon and its main tributaries has raised speculation that the commercial fishery exploits a single stock that moves continuously between the headwaters and the estuary (Barthem & Goulding 2007). This idea has recently been corroborated by Batista (2010), who has evaluated 483 individuals from 13 locations using eight microsatellite and sequences of the CR. This work was focused on the main channel of the SolimõesAmazon but also considered several tributaries, including the Madera River (60 samples) and the Madre de Dios River (tributary of the Madera, with 43 samples). The Bayesian method used in Batista’s study to identify populations, was implemented in the program STRUCTURE (Pritchard et al. 2009), which uses a different algorithm than the one used in this work with BAPS. According to this author, the STRUCTURE analyses did not identify differentiated homogeneous genetic units (K = 1) among the 13 locations studied, and there was not sufficient evidence to reject the existence of a single population at the scale of the sites studied in the Amazon basin. FIS values at each location were near zero and showed no genetic differentiation among localities. Batista (2010), however, did not show the value and significance of the deviation from zero of the global or overall FIS, to confirm a general panmixia. Consequently, relatively high gene flow rates were observed among the 13 localities sampled and the occurrence of philopatric (homing) movements (Batista & Alves-Gomez 2006) to the upper parts of the basin was discarded (although not completely). The different conclusions reached by Batista (2010) in relation to the results of this study could be due to the number of samples examined from the Upper Madera basin and the nature of the populations identified in this system. This author analyzed samples mainly from the Amazon River’s main channel, and considered only two locations in the Upper Madera basin (Madre de Dios and Porto Velho). Jointly the Madera River samples totalled 103 samples, of which 43 came from the upper basin. Based on the BAPS results, it was found that cluster 1 appears private to the Upper Madera River, cluster 2 (largest in number) is present almost exclusively in the Iquitos (Ucayali-Amazon) sample and cluster 3, the most differentiated, consists of a small number of individuals, all belonging to the Upper Madera except for one individual from Iquitos. The degree of differentiation observed between the three clusters was small but significant (FST: 0.028 – 0.043), and therefore its signal in the total grouping is low. Given this information, it is possible that the signal from cluster 1 or 3 was not detected in samples from Batista (2010) containing a small number of individuals from the Upper Madera River in relation to its total sampling. Additionally, it is possible that along the main channel of the Amazon River (Peru and Brazil) and in the lower reaches of its main tributaries, there is a population dominant in number that corresponds to cluster 2, as identified by BAPS for the locality of Iquitos. 115 Table 3.4. 1 FST values comparison chart (microsatellites) for clusters of Plateado (Brachyplatystoma rousseauxii) defined by BAPS in the Upper Madera and western Amazon (Bolivian and Peruvian Amazon), and other freshwater, brackish and marine fish species. References with asterisks (*) denote comparisons between groups of fish that do not necessarily have enough evidence to be considered panmictic populations or units. Order Family Species Environment(s) Behaviour Nº loci F ST limits (p<0.05) Reference Siluriformes Siluriformes Siluriformes Characiformes Perciformes Cypriniformes Cypriniformes Pimelodidae Pimelodidae Pimelodidae Serrasalmidae Cichlidae Cyprinidae Balitoridae Brachyplatystoma rousseauxii (Castelnau, 1855) Pseudoplatystoma corruscans (Agassiz & Spix 1829) Pseudoplatystoma reticulatum Eigenmann & Eigenmann 1889 Piaractus mesopotamicus (Holmberg, 1887) Amphilophus citrinellus (Günther, 1864) Coreius guichenoti (Sauvage & Dabry de Thiersant 1874) Barbatula barbatula (Linnaeus 1758) continental continental continental continental continental continental continental migratory-anfidromous migratory-potamodromous migratory-potamodromous migratory-potamodromous no migratory migratory-potamodromous migratory-potamodromous 9 7 7 8 7 11 5 0.028 - 0.043 0.034 - 0.164 0.229 0.052 - 0.065 0.018 - 0.086 0.022 - 0.047 0.010 - 0.110 present study Pereira et al . (2009)* Abreu et al . (2009)* Calcagnotto & DeSalle (2009) Barluenga & Meyer (2004) Zhang & Tan (2010) Barluenga & Meyer (2005) Atheriniformes Salmoniformes Atherinopsidae Salmonidae Odontesthes argentinensis (Valenciennes 1835) Thymallus thymallus (Linnaeus 1758) marine, brackish, continental continental, brackish no migratory no migratory 9 17 0.010 - 0.096 0.030 - 0.740 Beheregaray & Sunnucks (2001) Koskinen et al . (2002) Salmoniformes Salmonidae Salmo salar Linnaeus 1758 marine, brackish, continental migratory-anadromous 8 0.027 - 0.072 McConnell et al. (1997) Salmoniformes Salmoniformes Salmoniformes Gadiformes Gadiformes Gadiformes Gadiformes Perciformes Clupeiformes Beryciformes Anguilliformes Scorpaeniformes Carchariniformes Carchariniformes Salmonidae Salmonidae Salmonidae Gadidae Gadidae Gadidae Gadidae Gobiidae Clupeidae Trachichthyidae Anguillidae Sebastidae Carcharhinidae Carcharhinidae Salmo salar Linnaeus 1758 Thunnus thynnus thynnus (Linnaeus 1758) Thunus thynnus (Linnaeus, 1758) Gadus morhua Linnaeus 1758 Gadus morhua Linnaeus 1758 Gadus morhua Linnaeus 1758 Gadus morhua Linnaeus 1758 Pomatoschistus minutus (Pallas 1770) Clupea harengus Linnaeus 1758 Hoplostethus atlanticus Collett 1889 Anguilla anguilla (Linnaeus 1758) Sebastes mentella Travin 1951 Negaprion brevirostris (Poey, 1868) Carcharhinus limbatus (Müller & Henle, 1839) marine, brackish, continental marine marine marine marine marine marine marine, brackish marine marine marine marine marine, brackish marine, brackish migratory-anadromous migratory-oceanodromous migratory-oceanodromous migratory-oceanodromous migratory-oceanodromous migratory-oceanodromous migratory-oceanodromous no migratory-oceanodromous migratory-oceanodromous no migratory-oceanodromous migratory-catadromous no migratory-oceanodromous migratory-oceanodromous migratory-anfidromous 13 9 8 5 5; 6 10 13 8 4 8 22 9 4 8 0.002 - 0.039 0.009 0.005 - 0.012 0.008 - 0.011 0.004; 0.007 0.0013 - 0.005 0.002 - 0.006 0.009 - 0.025 0.008 - 0.037 0.002 - 0.011 0.005 - 0.015 0.009 0.016 - 0.034 0.004 - 0.067 Dionne et al . (2008) Carlsson et al . (2004) Carlsson et al. (2007) Ruzzante et al . (1998) Ruzzante et al . (2001) Knutsen et al . (2003) Knutsen et al . (2011) Larmuseau et al. (2010) Shaw et al . (1999) Carlsson et al . (2011) Pujolar et al . (2011) Stefánsson et al . (2009) Feldheim et al . (2001) Keeney et al . (2005) 116 Under these results and assumptions, in the near future, efforts should focus in defining the distribution of the identified populations in the Amazon basin, in order to facilitate priority research measures (e.g. life history traits, fishing) and conservation at a regional level. Figure 3.41 shows a comparison of the results obtained by Batista (2010) and the present study using microsatellites. a) b) Figure 3.4. 1 Comparison of the geographical boundaries of genetic units of Plateado identified by the use of microsatellites in the Amazon basin by Batista (2010) (a large population) (a), and in the western Amazon and the Upper Madera in this study (3 clusters in the western Amazon and the Upper Madera) (b). Red circles represent localities studied by Batista (2010) in the subsection a. Oblique black bars represent the rapids series in the Upper Madera basin, between Bolivia and Brazil. 3.4.2 Mitochondrial DNA (Control Region -CR) The maximum likelihood (ML) tree of control region sequences (170 haplotypes, 506 individuals) originating in the Bolivian, Peruvian and Brazilian Amazon, did not show any structure supported by high bootstrap values (Figure 3.3.5). The geographical origin of the haplotypes did not have a significant influence on their genealogy and several haplotypes were shared among different locations. However, it was noted that each geographic location consisted of a fraction of haplotypes unique to that location (singletone), a typical feature of species undergoing recent expansions (Excoffier et al. 2009) (Table 3.3.10). The haplotype network built on the principle of parsimony (minimum spanning network) also did not show the formation of nuclei of differentiated haplotypes. Similar to the general ML tree, the tree built only for haplotypes of the upper basin Madera River basin, did not show the formation of significantly different groups. At this geographic level and with the available data, it was not possible to identify groups of individuals with a common genealogical history. The distribution and comparison of haplotypes sorted by BAPS-defined clusters showed no significant differences (FST and φST values did not deviate significantly from zero between pairs of clusters). However, in each BAPS-defined cluster, the subsamples are 117 positioned according to their geographical position (according to a downstreamupstream pattern) and, in part, to the altitudinal levels of the systems and their latitude. Four haplogroups were identified, one in the system Ucayali-Amazonas (Peru and Brazil) and three in the upper Madera River (Bolivia and Peru). The haplogroup from the Amazon’s main channel identified between Iquitos (3600 kilometers from the Atlantic, Upper Amazon) and Belém (Amazon Estuary) is below 85 m.a.s.l. and in a system without any physical barriers to fish movements, like rapids. In the upper Madera River, above the series of rapids on a stretch of about 300 km, two haplogroups were defined in the lower area of the system and one in the upper area. In the lower portion, the individuals caught at the confluence of the waters that give rise to the Madera River proper (Villa Bella) formed a uniform haplogroup. Next to this haplogroup was another made up of individuals captured in Cachuela Esperanza (Beni River, 111 m.a.s.l.) and Puerto Maldonado (Madre de Dios River, 170 m.a.s.l). The haplogroup from the upper parts of the basin consisted of samples collected in the headwaters of the Beni (Rurrenabaque) and Ichilo (Puerto Villarroel) rivers, both at >180 m.a.s.l. At the scale of the Upper Madera River, there is a noticeable genetic structure (3 haplogroups) which is not seen in a long stretch of the Amazon (3600 km), where one haplogroup was identified with the data generated and available from GenBank. The observed structure may be linked to the ecological and geomorphological heterogeneity of the Amazon system in its upper portion. Regarding the main channel, Batista (2010) mentions that she found significant differences among the towns of Tabatinga (54 individuals), Manaus (43 individuals) and Belen (54 individuals), but the presentation of these results is a bit confusing. She also mentions that she observed a significant difference between samples from the Madera River and from the Japurá River after a Bonferroni correction to the φST value. However, overall she did not find a strong population structure related to the basin’s major tributaries and 98.9% of the variation observed (652 individuals) was contained within each of the 15 sites she studied. The demographic analysis showed a fairly close fit between the distribution of differences between pairs (mismatch distribution) of haplotypes corresponding to the clusters defined by BAPS with microsatellites, and the expected distribution under a model of rapid population and spatial expansion (Rogers & Harpending 1992). Mode values (Tau,τ) in each distribution were similar. The value τ of cluster 3 was one unit less than that of the other two clusters, but the difference could be due to its small number of individuals (17) and haplotypes (10). A greater number of individuals from this cluster must be included to determine more precisely if it went through a demographic and / or spatial expansion event, and at what point in the specie’s history this may have occurred. Bayesian Skyline Plots (BSP), which graphically represent the demographic history of populations, showed that cluster 3 appears to have remained stable over the last 400,000 years. However, this result could be an effect of the small number of individuals analyzed, as mentioned above. In contrast to cluster 3, the BSPs of clusters 1 and 2 showed significant historical variation in their demographics. The effective size of females in clusters 1 and 2 underwent two demographic and spatial expansions in recent times, but with different amplitudes. Cluster 1 had a surge in the last 200,000 – 100,000 years, and cluster 2, a less pronounced increase between the 118 last 250,000 – 50,000 years. The dynamics of both clusters were stabilized after the expansion processes they went through between those estimated time frames. The approximate time of rapid expansion process that these clusters (1 and 2) experienced suggests that the observed demographic changes may have occurred during the late Pleistocene. This period began about 130 000 years ago (warmest stage of the last interglacial), along with an increase in regional precipitation (Haffer 1969; Whitemore & Prance 1987, Harris & Mix 1999) that could have led to an expansion of aquatic environments and / or an increase in habitat / resources used by this species. Similar situations have been proposed for the demographic history of Neotropical fish groups at different time frames (e.g. Hubert et al. 2007b, Cooke et al. 2009). 3.4.3 Discrepancy between nuclear and mitochondrial DNA data Genetic information obtained through microsatellite (nuclear descriptor) and CR sequences (mitochondrial descriptor) analyses showed that there is a population structure of the Plateado in the upper Madera River (Bolivia and Peru) and the UcayaliAmazonas (Peru) system. Microsatellites showed that the Plateado is structured in at least three clusters (panmictic units) with partly overlapping distributions, except in the Ucayali-Amazonas (Peru) system where only two of the three clusters (clusters 2 and 3) were observed. In turn, CR sequences revealed that the species is geographically divided into four haplogroups: three haplogroups were identified in the Upper Madera River (Villa Bella; Cachuela Esperanza + Puerto Maldonado; Rurrenabaque + Puerto Villarroel) and one along the Ucayali-Amazonas (Peru and Brazil) main channel. The reorganisation of the haplotypes in sub-haplogroups taking into account the structure obtained with the microsatellites (populations) and the CR sequences (haplogroups) indicated a preponderant influence of their geographic origin. This means that subhaplogroups from the same location, divided into different clusters, are closer to each other than to the other sub-haplogroups of their own cluster. Below, we propose possible hypothesis that could explain the genetic structure found in the Plateado with the available data. Hypothetical scenarios that could explain the discrepancies observed between mtDNA - CR and nDNA – microsatellites Considering that the nuclear marker information is the most appropriate to define a genetic population (regarding panmixia), and that microsatellites allow discrimination in genetically close fish populations (Wright and Bentzen 1994), the discrepancies observed with CR could be due to several, non-exclusive explanations: genetic drift, homoplasy, demographic expansion, selection, differential behaviour. - Genetic drift: the effects of genetic drift within each cluster may go undetected in microsatellites for having an effective size larger than the mtDNA in a current population structure. An important geographical effect is seen within each cluster, revealed by the CR, which is not consistent with the panmixia defined by microsatellites among several locations. If the differences between clusters are very recent, the internal structure 119 within them would go unnoticed because there are still no signs or sufficient differences to reject genetic homogeneity. - Homoplasy: the observed discrepancies between mtDNA and nDNA could be caused by a bias generated by the homoplasy that exists in microsatellite loci with high numbers of alleles. However, in a simulation study Estoup et al. (2002) showed that homoplasy has a lesser effect on the estimation of population differentiation than migration and genetic drift. In this respect, most of the loci analyzed in Plateado in the current study had a relatively low number of alleles (8-27, average 13). - Demographic expansion: as microsatellites are more sensitive to the differentiation of reproductive units (panmictic populations) than mitochondrial descriptors (e.g. Larmuseau et al. 2010), it is possible that within each cluster there is a structure, imperceptible because of the demographic expansions recently experienced (except in cluster 3). These expansions could be masking the existing differentiation between subunits (subhaplogroups) visualized by CR sequences. - Selection: one could assume that there are differential selection effects on the descriptors, as there are few nDNA loci (microsatellites) that show discordant data with mtDNA. Theoretically, the two descriptors used are exempt of selection pressure (they are neutral), and our results showed that the disequilibrium is not conditioned by a few loci, but by their combination. - Differential behaviour: the observed discrepancies between mtDNA and nDNA might also be accounted for by an occasional exchange of females between populations (clusters) whereas males would be more faithful to their population. Hence, panmictic group maintain their integrity as populations and the composition of haplotypes is similar in some geographic zones. The observed spatial structure may be due to a phylopatric behaviour of females depending on ecological characteristics, altitude or some factor linked to latitude. 120 Chapter 4 CONCLUSIONS AND PERSPECTIVES The main goals of this study were to determine the phylogenetic position of the Plateado (Brachyplatystoma rousseauxii) in the family Pimelodidae (Teleostei, Siluriformes - catfish), and the population structure of this species in the Upper Madera River watershed (Bolivia and Peru), and the Western and Central Amazon (Peru, Brazil). For this purpose, mitochondrial and nuclear genomic markers were used. The most significant findings of this work are summarized below, along with recommendations on what needs to be taken into account to improve the conservation status, fishing, and knowledge of the Plateado in the Amazon watershed. Phylogeny of the Pimelodidae family (Siluriformes) and the phylogenetic position of the Plateado (Brachyplatystoma rousseauxii), as revealed by mitrocondrial (Control Region and Cytochrome Oxidase 1) and nuclear (F-reticulon4) sequences The combined analysis of the three molecular markers revealed that the family Pimelodidae conforms a monophyletic group (bootstrap value of 88%), with the genus Phractocephalus at its base, and has several unresolved genera-level relationships. The deduced molecular phylogeny was conflicting, for the most part, with the current recognized phylogeny of pimelodids based on their known morphological characteristics. The family was separated into two major morphological groups Pimelodus-Calophysus group and Sorubiminae. The Pimelodus-Calophysus relationship (bootstrap 79) was partially resolved with Megalonema at the base of the ((Pinirampus + Calophysus) (bootstrap 100) + Pimelodina) (bootstrap 90) + Aguarunichtys (bootstrap 56)) group. In contrast, the Sorubiminae only showed a significant relationship between Platysilurus and Platystomatichthys (bootstrap 100), and species of the tribe Brachyplatystomatini sensu Lundberg & Akama (2006) (Platynematichthys + Brachyplatystoma (bootstrap 77)). Inside the Brachyplatystomatini, two major groups were distinguished. These are partly inconsistent with the relationship proposed based on morphological characteristics. One was composed of B. tigrinum + (B. juruense + B. platynemum (bootstrap 100)) (bootstrap 53), and another of the species of the subgenus Malacobagrus (division resurrected by Lundberg & Akama 2006), as a sister group of Platynematichthys notatus + B. vaillantii (bootstrap 79). Within the morphological subgenus defined as Malacobagrus, B. rousseauxii appeared as the sister group (bootstrap 100) to B. filamentosum + B. capapretum (bootstrap 96). The genus Brachyplatystoma thus did not form a monophyletic group and the interspecific relationships were in disagreement with the proposed morphological phylogeny for the group, except within the subgenus Malacobagrus. 121 Based on the results of the present study, the tribe Brachyplatystomatini and genus Brachyplatystoma appear to be more restricted groups and should undergo a review and reclassification guided by the molecular phylogeny. The genus Brachyplatystoma would contain only species of the subgenus Malacobagrus with B. vaillantii as the basal taxa. This group, reclassified as Brachyplatystoma, together with Platynematichthys notatus at the base, would form the tribe Brachyplatystomatini. The remaining species, currently assigned morphologically to the Brachyplatystoma group, would represent other genera that may give rise to the former monotypical genus Merodontotus Britsky 1981 (B. tigrinum) and Goslinia Myers 1941 (B. platynemum). In this proposal, B. juruense could represent another genus as proposed in past works (e.g. genus Ginesea Fernandez-Yepez 1951). To clarify and redefine the species relationship classified morphologically within the tribe Brachyplatystomatini (sensu Lundberg & Akama 2006), a new exhaustive morphological review of the group is recommended, taking into account the molecular information, and including complementary information from other molecular descriptors (e.g. RAG genes). Additionally, it is worth noting that the different markers provided complementary information at the different levels of the Pimelodidae phylogeny and the concatenated information gave the more relevant tree. Results of the present study were consistent with a recent publication by Lundberg et al. (2011), using different mitochondrial and nuclear genes. Although Lundberg et al. (2011) used almost all genera of the family in their analyses, results and conclusions of the present work were similar at the Pimelodidae clade and Brachyplatystoma nonmonophyly conformation. Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by nuclear DNA (microsatellites) The analysis of the total sample of multilocus allele frequencies (nine loci) of Plateado showed a significant panmictic deviation or imbalance (FIS overall). This indicates that the species is not formed by a single reproductive genetic unit. Following this result, a search was made for clusters (groups in which one cannot reject panmixia) with genotypically similar individuals. A Bayesian method, which minimizes the differences within each group (overall FIS ~ 0) and maximizes the differences between them (FST significant) was used. With this analysis, it was found that in the study area (Upper Madera and the Western Amazon), the Plateado comprised at least three panmictic clusters that correspond to three biological populations. Two populations were numerically abundant (184 and 83 individuals), whereas the third held only 17 individuals. The populations were represented at several of the sample sites, but with a dissimilar distribution between them: 122 - Population 1 (83 individuals) was present in all samples from the Upper Madera, but was not found at Iquitos (Western Amazon). This distribution suggests the existence of an exclusive, or predominant, population in the Upper Madera that could be low in abundance along of the Amazon main stem. - Population 2 (184 individuals) was found at all sample sites, but in particular contained 64 of the 65 individuals from Iquitos. As discussed below, the Plateado from Iquitos were not significantly different from those studied in the central Amazon at the microsatellite (Batista 2010) and CR (Batista & Alves-Gomez 2006) levels. These results suggest that this population (cluster 2 in our study) would be numerically dominant in the Amazon basin and particularly along the main channel. - Population 3 (17 individuals) was present at all the study sites, including a single individual from the western Amazon (Iquitos). Its low numerical representation in the samples and reduced abundance in the western Amazon suggest the existence of smaller populations embedded into a larger one (cluster 2 in our analysis) that masks their genetic signal. This hypothesis would account for why Batista (2010) observed a unique population (cluster 2 in our study) along the main channel of the Amazon and failed to detect the other populations identified in the present study. It is therefore possible that other populations (abundant in their tributaries of origin) may be present in the main channel of the Amazon, in relatively lower abundance compared to cluster 2. Differences between these clusters, despite relatively low Fst values (FST = 0,028 to 0.043), were about ten times greater than those observed for populations of other marine or freshwater migratory fish species (e.g. Dionne et al. 2003; Knutsen et al. 2011). The identification of three stocks of Plateado in two large areas of the Amazon basin (Upper Madera and western Amazon) shows that this species has a complex population structure, different from that shown by other researchers (e.g. Barthem & Goulding 1997, 2007; Batista & Alves-Gomez 2006; Batista 2010). Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by mitochondrial DNA (Control Region - CR) The analyses of the highly variable mitochondrial DNA portion (Control Region - RC) of the Plateado (B. rousseauxii) showed two main results: Firstly, they showed that a significant phylogenetic signal of coalescence was not identified in the 506 haplotype sequences originating from the Upper Madera and the western and central Amazonia, including 45 of the GenBank coming from Brazil. Consequently, the maximum likelihood (ML) family tree has comb-like shape. The haplotypes of the three major geographic regions are associated independently of their origin in this tree, in groups with short branches without significant support in their nodes. 123 Secondly, the analysis of the distribution of haplotype frequencies (FST), revealed the existence of four significantly distinct geographic haplogroups, rather than just one as had been reported by other authors for the western and central Amazonia (Batista & Alves-Gomez 2006; Ferreira 2007; Magalhães 2003; Batista 2010). These haplogroups correspond to individuals who were captured in the main Amazon channel (Western and Central Amazon, 106 ind), at the confluence of the Beni and Mamoré rivers (origin of the Madera River - Villa Bella, 22 ind), the lower portion of the Beni River and the intermediate portion of the Madre de Dios River (Cachuela Esperanza + Puerto Maldonado, 142 ind), and the upper region of the Beni and Mamoré (Ichilo) rivers (Rurrenabaque + Puerto Villarroel, 229 ind). Demographic analyses of populations (mismatch distribution and Bayesian Skyline Plot) suggest that each of these haplogroups underwent a demographic expansion between 200 000 – 100 000 (population 1) and 250 000 – 50 000 (population 2) years ago in the late Pleistocene period. The general genealogical topology, which was found for the haplotypes, is consistent with the postulated population expansions that these populations have undergone. It is worth noting that, along the main channel of the Amazon River from Belem to Iquitos (more than 3 000 km), a single unit (at the haplotype frequencies level), was observed. This genetic makeup is consistent with the absence of visible geographical barriers and the similarity of the aquatic habitat throughout the channel. The other three haplogroups are in a southern latitudinal gradient that rises and enters into the upper basin of the Madera River, towards the southwestern boundary of the river basin. This apparent relationship with latitude and / or height above sea-level, but not restricted to individual tributaries, could be related to hydrology (flood pulses, water speed, etc), water temperature, oxygen levels, quantity of fine sediments, precipitation, quantity of food, availability of breeding habitat, amongst other factors that should be investigated in more detail in future work. The existence of a geographically associated population structure, suggests that the Plateado is composed of haplotypical units with phenotypic affinity for geographic sites with particular characteristics that are unknown. This phenotypic affinity, at least by females (as the mitochondrial DNA technique only tracks the maternal inheritance), could have been established long ago or could be in its infancy. A significant part of the haplotypes present between localities and the haplotypical frequencies still define the haplo-groups. It is recommended that more detailed studies be carried out to identify the extrinsic (e.g. environmental variables) and intrinsic (e.g. life-history traits, ecology) factors related to the differentiation of the populations, assisting in the development of appropriate policies for the conservation and sustainable use of the species. Population structure of the Plateado (Brachyplatystoma rousseauxii) as revealed by nuclear DNA (microsatellites) and mitochondrial DNA (Control Region - CR) The information obtained from the nuclear and mitochondrial molecular markers (microsatellite-nDNA and CR-mtDNA respectively) did not coincide with the delineation of genetic units (clusters and haplogroups) in the Upper Madera and the Western 124 Amazon. On the one hand, the CR analysis suggests the existence of units related to their geographical origin, whereas the microsatellite analysis indicates the presence of three populations (clusters) distributed amongst the geographical locations studied (Figure 4.1). The subdivision, within the clusters, of microsatellite data by geographic location and allelic variation showed a similar tendency in each cluster where subsamples organize themselves according to a downstream-upstream pattern (Figure 3.3.1.6). Individuals from the Western Amazon (Iquitos) were closer to the individuals from the town of Villa Bella, at the confluence of the Beni and Mamoré rivers (entrance to the Upper Madera watershed). On the other hand, when the genetic relationship was analyzed from the point of view of variation in haplotype frequencies, greater closeness between subsamples from the same geographic area was observed, regardless of the cluster to which they were assigned (Figure 3.3.2.4). Additionally, unlike the microsatellites, higher affinity between haplotypes of Western Amazon (Iquitos + Brazil) and haplotypes of the upper parts of the Upper Madera (Rurrenabaque + Puerto Villarroel) was observed. In conclusion, three genetic populations (clusters) were observed which are distributed in partially overlapping geographical areas, and four haplogroups are positioned more distinctly in geographical areas. In addition, geographical influence is perceived within each cluster (downstream-upstream pattern). These results do not correspond completely with any of the four initial hypotheses proposed in the introduction, but could be explained by hypothesis c and d. In order to explain this complex genetic organization and the apparent discrepancy between mtDNA and nDNA markers, a hypothesis is proposed of differential behavior between females and males: “geo-faithful female and population-faithful but geounfaithful male” (Chapter 3, Figure 4.1). In this hypothesis, at the scale of the Upper Madera, the females are more sedentary while males more nomadic within their populations. Considering the genetic difference observed between the Upper Madera and the Western Amazon at the mtDNA and nDNA levels, the hypothesis of homing on a scale of large watersheds cannot be rejected (hypothesis c). It has been observed in the Bolivian Amazon that during the low water season mature females are mostly caught in deep and turbulent areas (pers. obs.). This gender-specific behaviour, while requiring corroboration, could explain in part the deduced genetic organization of B. rousseauxii. This thesis has highlighted the importance of both geography and behavior in the evolution of B. rousseauxii population genetics. The complexity of the genetic organization and life-history features of this species, while requiring better understanding, suggest the existence of a sexually asymmetrical homing propensity that is more pronounced among females than among males. 125 a) b) Figure 4. 1 a) Spatial representation of the genetic population structure of Plateado (Brachyplatystoma rousseauxii) in the Upper Madera of the Western and Central Amazon (Bolivian, Peruvian and Brazilian Amazon), as identified by microsatellite and Control Region (CR) mitochondrial molecular markers. The clear squares represent regions in Brazil that have (CR) sequences deposited in GenBank by Batista & Alves-Gomez (2006). The clusters correspond to panmictic genetic population units bounded by BAPS using (nine) microsatellites for the Upper Madera and Western Amazon (Bolivia, Peru). Haplogroups are genetic units bounded by CR sequences from the Upper Madera of the Western and Central Amazon (Bolivia, Peru and Brazil). b) Schematic of the direction of preferential gene flow for female and male Plateado in the Upper Madera and the main stem of the Amazon which would explain the discrepancies obtained with the nuclear (microsatellites) and mitochondrial (CR) markers. Plateado females are hypothesized to have phylopatric behavior, which defines the haplogroups, but at times move from one population to another in certain geographic areas. In contrast, males are hypothesized to be more mobile across geographic areas, but faithful to the populations to which they belong in spawning. The black dots represent localities in Brazil that have (CR) sequences deposited in GenBank by Batista & Alves-Gomez (2006). Oblique black bars represent the rapids series in the Upper Madera basin, between Bolivia and Brazil. 126 Perspectives So far, the B. rousseauxii species was believed to be composed of a single population with high gene flow between the main river channel and its tributaries (panmictic). The sampling design and analyses carried out during this study, permitted to demonstrate the existence of a more complex population structure, and gave rise to new questions about the history and biology of the species. While clear distinguishing biological or environmental characteristics of the identified populations and their distribution are not yet clear, it is possible that further study will identify isolating temporal and / or spatial differences in reproductive, behavior and / or ecology (e.g. maximum sizes and breeding seasons seem to vary within the tributaries). To determine these relationships, specific studies must be carried out to help decipher migration patterns (e.g. with telemetry), define spawning areas (e.g. monitoring of larvae drifting using barcoding), understand timing of spawning events (e.g. correlation with environmental factors and total vs. pulse spawning). Barcoding analysis of the fish larvae (composition and temporal variation) from the head waters of the Upper Amazon watershed tributaries, are an alternative to verify hypothesis c and d proposed in the introduction. It is noteworthy that the recognition of these different populations will have a substantial impact on the strategies for conservation and management of this species in the Amazon basin, which is threatened by overfishing, pollution, habitat destruction and increased climatic variability in the four countries. With respect to fishing, the Plateado has a significant commercial value in all countries that share the Amazon basin, contributing to livelihoods and food security in several large population centers in the different regions (e.g. Iquitos, Leticia, Santarem, Manaus). There will be substantial challenges involved in managing and conserving this resource on a regional basis, recognizing the newly identified distinct genetic stocks and considering the different fishing regulations and customs of each country. With respect to pollution, mercury is of prime concern. It enters Amazonian rivers from naturally high levels in soils that are being increasingly eroded, and from increasing levels of gold mining. The element accumulates in fish tissue in relation to their size and trophic position (Sampaio da Silva et al. 2005). Thus, the fish found at the top of food chains, such as Plateado, are more vulnerable to its toxic effects. Average mercury values in the Madera River basin have been reported to be above the maximum permissible limit of 0.50 mg / kg for human consumption in several piscivorous fish, including Plateado (Bastos et al. 2008). There is thus a high risk of mercury poisoning to Amazon fish which could lead to reproductive

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Phylogeny and population genetics of the fish performing the largest migration known in freshwater, the Amazonian catfish Brachyplatystoma rousseauxii: revelations from the Upper Madera Basin

Phylogeny and population genetics of the fish performing the largest migration known in freshwater, the Amazonian catfish Brachyplatystoma rousseauxii: revelations from the Upper Madera Basin

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