Ecologia de peixes de riachos da bacia do rio Machado, RO: padrões, processos e conservação María Angélica Pérez-Mayorga María Angélica Pérez-Mayorga Ecologia de peixes de riachos da bacia do rio Machado, RO: padrões, processos e conservação São José do Rio Preto Agosto de 2015 María Angélica Pérez-Mayorga Ecologia de peixes de riachos da bacia do rio Machado, RO: padrões, processos e conservação Tese apresentada como parte dos requisitos para obtenção do título de Doutora em Biologia Animal, junto ao Programa de Pós- Graduação em Biologia Animal, do Instituto de Biociências, Letras e Ciências Exatas da Universidade Estadual Paulista “Júlio de Mesquita Filho”, Campus de São José do Rio Preto. Orientadora: Profa Dra Lilian Casatti Co-orientador: Prof. Dr. Fabrício Barreto Teresa São José do Rio Preto Agosto de 2015 María Angélica Pérez-Mayorga Ecologia de peixes de riachos da bacia do rio Machado, RO: padrões, processos e conservação Tese apresentada como parte dos requisitos para obtenção do título de Doutora em Biologia Animal, junto ao Programa de Pós- Graduação em Biologia Animal, do Instituto de Biociências, Letras e Ciências Exatas da Universidade Estadual Paulista “Júlio de Mesquita Filho”, Campus de São José do Rio Preto. São José do Rio Preto Agosto de 2015 BANCA EXAMINADORA Titulares Profa. Dra. Lilian Casatti UNESP – São José do Rio Preto Orientadora Prof. Dr. Mauricio Cetra UFSCar – Sorocaba Prof. Dr. Fernando Rodrigues da Silva UFSCar – Sorocaba Profa. Dra. Virgínia Sanches Uieda UNESP – Botucatu Prof. Dr. Francisco Langeani Neto UNESP – São José do Rio Preto Suplentes Profa. Dra. Mônica Ceneviva-Bastos UNESP – Assis Profa. Dra. Maria Elina Bichuette UFSCar – São Carlos Profa. Dra. Maria Stela Maioli Castilho Noll UNESP – São José do Rio Preto Data e horário da defesa: 29/07/2015 às 09:00 h Esta Tese foi realizada entre o período agosto de 2011 a junho de 2015, no Laboratório de Ictiologia, Departamento de Zoologia e Botânica, IBILCE, UNESP, sede São José do Rio Preto, e foi financiada pelo Programa de Apoio a Estudantes de Doutorado do Estrangeiro/Asociación Universitaria Iberoamericana de Postgrado (PAEDEX/AUIP), edital 2011, na forma de bolsa de Doutorado. As etapas de campo, os equipamentos e os materiais de consumo foram financiados pela Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP # 2010/17494-8). AGRADECIMENTOS Agradeço de coração a todas as pessoas que contribuírem nos aspectos acadêmico, profissional, e pessoal. Sem essa ajuda teria sido impossível chegar até aqui. A minha orientadora, Profa. Dra. Lilian Casatti, pela amizade, amor e apoio incondicional. Por ter facilitado minha adaptação no Brasil e permitir que pudesse fazer parte do lar “Laboratório de Ictiologia”. Pelo exemplo de amor e dedicação à ecologia de peixes de riachos. Pela ajuda incansável na construção do projeto, na fase de campo, na fase de laboratório, nas análises dos dados, na produção dos textos e jogo derivados desta pesquisa, e pela revisão do português e inglês da Tese. Ao Prof. Dr. Fabrício Barreto Teresa, pela paciência e explicações para poder executar e interpretar as análises dos capítulos um e dois, e pelas críticas e sugestões dos três capítulos. A Dra. Cristina da Silva Gonçalves, ao Prof. Dr. Francisco Langeani Neto e a Profa. Dra. Maria Stella Maioli Castilho Noll, pelas críticas e sugestões sobre a Tese durante a fase de qualificação. Ao Prof. Dr. Tadeu Siqueira pelas críticas e sugestões do capítulo um. Ao Cristiano Gomes Pastor e a Camila Gomes Pastor da empresa Iandé – Educação e sustentabilidade, pelas críticas e sugestões do capítulo três. A Profa. Dra. Maria Stella Maioli Castilho Noll, por permitir testar o jogo nas exposições dominicais do projeto “Você conhece a represa?”. Aos professores da Pós-graduação pelos ensinamentos ao longo destes quatro anos. Agradeço aos membros da banca de defesa desta tese, por disponibilizar parte do seu tempo para ler o manuscrito, participar da banca, e pelas valiosas críticas e sugestões para melhorar o trabalho. À equipe do Laboratório de Hidrologia Florestal da ESALQ que fez o levantamento prévio dos dados da paisagem: Me. Gabriel Lourenço Brejão, Me. Felipe de Paula Rossetti e Prof. Dr. Silvio Frosini de Barros Ferraz. À equipe que participou na fase de campo, Profa. Dra. Lilian Casatti, Dr. Mateus Ferrareze Feitosa, Dr. Fernando Rogério de Carvalho, Me. Gabriel Lourenço Brejão, Me. Felipe de Paula Rossetti, Me. Ângelo Rodrigo Manzotti, Wesclen Vilar Nogueira, Vanessa da Silva Bressan, Prof. Dr. Igor David da Costa, e pessoal das comunidades das RESEX. À equipe que ajudou na identificação do material, Dr. Fernando Rogério de Carvalho (IB/UFMT), Prof. Dr. Francisco Langeani Neto (IBILCE/UNESP), Profa. Ma. Fernanda de Oliveira Martins (IFPR); Dra. Barbara Borges Callegari (MCP/PUCRS); Profa. Dra. Ilana Fichberg (MZUSP); Prof. Dr. Flávio César Thadeu de Lima (UNICAMP); Prof. Dr. Leandro Melo de Sousa (UFPA); Dra. Manoela Maria Marinho Kho (MZUSP), Prof. Dr. Marcelo Ribeiro de Britto (MNRJ), Prof. Dr. Marcelo Rodrigues de Carvalho (IB/USP) e Me. William Massaharu Ohara (MZUSP). À equipe que ajudou na eterna contagem dos 22.875 peixinhos: Carol Rodrigues Bordignon, Ma. Roselene Silva Costa Ferreira, Me. Gabriel Lourenço Brejão, Ma. Jaqueline Oliveira Zeni, Tomas Suriane Fialho e Mariana Correia Molina. À equipe que ajudou na obtenção do banco de dados ecomorfológicos: Carol Rodrigues Bordignon e Erick Manzano Macías. Ao Erick Manzano Macías, pela obtenção de parte do banco de dados alimentares. Ao Me. Gabriel Lourenço Brejão, pela ajuda na definição da ocupação na coluna d’água dos peixes, os grupos tróficos funcionais, e pela elaboração dos mapas do capítulo um e dois. Ao Prof. Dr. Fabrício Barreto Teresa, pela montagem da filogenia dos peixes. Aos meus amigos irmãozinhos do laboratório de ictiologia, Dra. Mônica Ceneviva- Bastos, Me. Camilo Roa-Cifuentes, Ma. Jaqueline Oliveira Zeni, Carolina Rodrigues Bordignon, Dayane Boracini Prates, Marina Reghini Vanderlei, Me. Gabriel Lourenço Brejão, Mariana Correia Molina, Me. Ângelo Rodrigo Manzotti, Bruna Neves da Silveira, Dr. Fernando Rogério de Carvalho, Profa. Ma. Fernanda de Oliveira Martins, Ma. Roselene Silva Costa Ferreira, Me. Breno Neves de Andrade, Dra. Cristina da Silva Gonçalves, Ana Cláudia Santos e Me. Arturo Angulo Sibaja, pela amizade, apoio, conselhos, agradável companhia e críticas ao trabalho. Aos amigos da Pós e das aulas de pintura da UNESP, e a todos os amigos de São José do Rio Preto por aliviar os momentos de saudades. A minha amada família, minha força e inspiração, especialmente aos meus pais Carmenza Mayorga Flórez e Abelino Pérez Corrales, pelo amor infinito, pelo exemplo de vida, pelo apoio incondicional e por formarem a pessoa que sou hoje. Aos meus irmãozinhos René Mauricio Pérez Mayorga e Ma. Diana María Pérez Mayorga pelo amor, amizade e cumplicidade. Aos meus sobrinhos por trazer mais amor e felicidade para minha vida. Aos meus cunhados, tias, tio, primas, primos e família Manzano Macías, pelo amor e apoio recebido. A meu namorado Erick Manzano Macías pelo amor, paciência infinita para aguentar minhas ausências, apoio e pela bela história que temos construído juntos. “Este trabalho é dedicado a minha amada família” RESUMO Na presente Tese, foram analisados os efeitos de variáveis locais, de paisagem e espaciais sobre a composição, abundância, traços funcionais e filogenia das ictiocenoses de riachos. Foram organizados três capítulos a partir da coleta da ictiofauna e dos dados ambientais e espaciais em 52 (coletas de 2012) e 75 (coletas de 2011 e 2012) trechos de riachos localizados ao longo da bacia do rio Machado, no estado de Rondônia. O foco do capítulo 1 foram os padrões ecológicos de todas as espécies da metacomunidade e das assembleias de peixes segundo a especialização do hábitat (hábitat especialistas e hábitat generalistas). As três cenoses foram estruturadas ambientalmente, sugerindo que são os processos baseados em nicho os que explicam a sua estrutura. No capítulo 2, exploramos mais a fundo os processos ecológicos que provavelmente explicam os padrões obtidos. Foi comprovado que há agrupamento nos traços funcionais e na filogenia. Variáveis ambientais, tais como a proporção de ultisolo na microbacia e gramíneas e barranco nu no buffer ripário, estruturam as assembleias associadas aos riachos degradados (RD). Por outro lado, a proporção de floresta e de oxisolo na microbacia; litter grosseiro, arbustos e árvores no buffer ripário do riacho estruturam as assembleias associadas aos riachos preservados (RP). O ambiente também influencia, através de mecanismos de filtros ambientais, o consumo de algas e a posição nectônica na coluna d’água nos RD, ao passo que influencia o consumo de restos de invertebrados e a posição nectobentônica na coluna d’água nos RP. A posição dos RD e RP é coincidente com os diferentes usos do solo, sendo os primeiros mais concentrados na porção central da bacia, onde o solo é usado para pastagens, e os RP nos extremos da bacia, onde há maiores proporções de florestas. A maioria das espécies das famílias Loricariidae e Characidae está associada aos RD, por outro lado, Gymnotiformes, algumas espécies de Siluriformes, as espécies de Characiformes (exceto Characidae) e Perciformes estão associadas aos RP. No capítulo 3, traduzimos o conhecimento gerado em uma accessível, através de uma cartilha e jogo, para ensinar a importância dos peixes e a conservação da mata ciliar para crianças. No anexo está apresentado o inventário de espécies, com a lista de espécies, abundância e distribuição latitudinal das 139 espécies de peixes na bacia do rio Machado. Palavras-chave: Especialização do hábitat, filtro ambiental, traços funcionais, traços filogenéticos, agrupamento, educação ambiental. ABSTRACT In this thesis, the effects of local, landscape and spatial variables on composition, abundance, functional traits and phylogeny of stream ichthyocenoses were analyzed. Based on fish species, environmental and spatial datasets from 52 (2012 samples) and 75 (2011 and 2012 samples) stream reaches located in the Machado River basin, in the state of Rondônia, three chapters were organized. The highlight of the chapter one was the ecological patterns of all species of entire metacommunity and fish assemblages according to their degree of habitat specialization (habitat generalists and habitat specialists). The three cenoses were environmentally structured, suggesting that the niche-based processes explain their structure. In the chapter two, the ecological processes that probably explain the obtained patterns were explored more deeply. Both functional and phylogenetic clustering was confirmed. Environmental variables, such as the proportion of ultisol in the microbasin and of grasses and bared soil in the riparian buffer, structure the assemblages that are associated with degraded streams (DS). On the other hand, the proportion of forest and of oxisoil in the microbasin; coarse litter, shrubs and trees in the stream riparian buffer, structure the assemblages that are associated with the preserved streams (PS). The environment also influences through environmental filter mechanisms, the consumption of algae and the nektonic position in the water column in DS, whereas influences the consumption of invertebrates debris and the nektobenthic position in the water column in PS. The DS and PS position is coincident with the different land uses. DS are concentrated in the central portion of the basin, where the soil is covered by pastures, and PS are in the extremes of the basin, where there are greater proportions of forests. Most species of Siluriformes and of Characidae are associated with DS, on the other hand, Gymnotiformes, some species of Siluriformes, species of Characiformes (except Characidae), and Perciformes are associated with PS. In the chapter three, we translated the knowledge generated into a simple language, through a booklet and a game, in order to teach the importance of fishes and of the conservation of riparian vegetation to children and toddlers. In the appendix, a species inventory is presented, whit the species list, abundance and latitudinal distribution of 139 fish species. Keywords: Habitat specialization, environmental filtering, functional traits, phylogenetic traits, clustering, environmental education. SUMÁRIO INTRODUÇÃO ................................................................................................................................................................... 1 Prancha A ............................................................................................................................................................................ 6 Prancha B .......................................................................................................................................................................... 12 CAPÍTULO 1. PADRÕES: Metacommunity dynamics in an altered Amazonian river basin: shared or distinct responses among the entire metacommunity, habitat-generalist, and habitat- specialist stream fish? .................................................................................................................................................. 26 Abstract ..............................................................................................................................................................................26 Introduction ......................................................................................................................................................................26 Materials and Methods ................................................................................................................................................28 Results .................................................................................................................................................................................35 Discussion ..........................................................................................................................................................................38 References .........................................................................................................................................................................40 CAPÍTULO 2. PROCESSOS ECOLÓGICOS: Mudanças nos traços funcionais e filogenia das assembléias de peixes de riachos Amazônicos associadas ao gradiente de desmatamento ......... 49 Resumo. O tipo de solo e uso de solo na microbacia, buffer ripário e tipo de substrato do riacho agem como filtros ambientais ...............................................................................................................................49 Introdução .........................................................................................................................................................................50 Materiais e Métodos .....................................................................................................................................................51 Resultados .........................................................................................................................................................................59 Discussão ...........................................................................................................................................................................65 Literatura Citada..............................................................................................................................................................67 CAPÍTULO 3. CONSERVAÇÃO: Conhecendo os peixes de riachos das reservas da sub-bacia do rio Machado, Rondônia............................................................................................................................................... 72 Introdução .........................................................................................................................................................................72 Aplicação do jogo ..........................................................................................................................................................73 Figura 1 ...............................................................................................................................................................................73 Literatura Citada..............................................................................................................................................................74 Introdução ........................................................................................................................................................................ 78 1. Conceituação da bacia hidrográfica e seus compartimentos ................................................................. 79 2. Alguns dados sobre o rio Machado .................................................................................................................. 80 3. A mudança da cobertura do solo....................................................................................................................... 80 5. Estrutura dos riachos florestados e a sua ictiofauna .................................................................................. 84 6. Os riachos das reservas da sub-bacia do Rio Machado ............................................................................ 86 7. Vamos brincar? .......................................................................................................................................................... 87 CONSIDERAÇÕES FINAIS ........................................................................................................................................... 99 ANEXO. QUEM, QUANTAS, ONDE? The stream fish fauna from the rio Machado basin, Rondônia State, Brazil .................................................................................................................................................................... 101 1 INTRODUÇÃO Segundo a Organização das Nações Unidas para Alimentação e Agricultura (FAO), a superfície terrestre total do planeta, livre de gelo, é de 12,92 bilhões de hectares. Mais de um terço dela (4,91 bilhões de hectares) tem sido modificada pela eliminação dos ecossistemas originais e substituição por áreas de pastagens (3,38 bilhões de hectares) e de cultivos (1,53 bilhões de hectares). Atualmente, a agricultura está se expandindo rapidamente nos trópicos, sendo estimado que cerca de 80% das terras atuais de cultivos substituíram as florestas (Foley et al. 2011). A Floresta Amazônica apresenta uma das taxas mais altas de desmatamento. Nessa região, o estado de Rondônia vem sendo desmatado desde o início da década de 1960 (Alves et al. 1998). Nos anos 80, com a construção da BR-364 no estado de Rondônia, paralela e próxima ao rio Machado, ocorreu a facilitação do processo de desmatamento na bacia (Fernandes e Guimarães 2002). Atualmente, o desmatamento em Rondônia é estimado em aproximadamente 52 milhões de hectares (INPE Instituto Nacional de Pesquisas Espaciais 1998), o equivalente a 6,1% do território nacional brasileiro. Em 2001, 51% da área total foram desmatados, em 2004 esse percentual aumentou 57,1% e, em 2006, passou a 65,9% (INPE Instituto Nacional de Pesquisas Espaciais 2010). Nos municípios de Rondônia, encontram-se os assentamentos do período da colonização dirigida pelo INCRA, caracterizados pelo desmatamento do tipo 'espinha de peixe' (Casagrande 2009), que consiste no desmatamento ao longo de uma via principal, e depois ao longo de diversas trilhas perpendiculares à principal. O desmatamento na bacia do rio Machado ocorreu como consequência da política do Governo Federal nas décadas de 1970 e 1980, que apontava a abertura de novas fronteiras agrícolas e estímulo à ocupação territorial (Becker, 2001), e foi concentrado na porção média da bacia do rio Machado, onde há predominância do ultisolo (Ballester et al. 2012). Este solo de alta fertilidade (Krusche et al.2005) é hoje ocupado principalmente por pastagens (Fernandes et al. 2012). Nos locais onde ainda há cobertura vegetal florestal, há floresta madura, com árvores de 20 a 40 m; ou secundária, geralmente localizada entre a borda da agricultura extensiva e a floresta madura, com árvores de 5 a 20 m (Ferraz et al. 2005). A substituição dos ecossistemas naturais por ecossistemas simplificados de agricultura é considerada como a principal causa de perda de biodiversidade global (Matson et al. 1997; Tscharnkte et al. 2005; Flynn et al. 2009). No entanto, não só a biodiversidade terrestre é afetada, mas também os ecossistemas aquáticos. Deste modo, as mudanças feitas na paisagem pelo ser humano representam a principal ameaça para a integridade dos ecossistemas fluviais, afetando negativamente o hábitat, a qualidade da água e a biota aquática (Allan et al. 1997; Strayer et al. 2003; 2 Towsend et al. 2003, Allan 2004). Os principais mecanismos pelos quais as mudanças no uso do solo afetam negativamente o funcionamento dos riachos temperados são a sedimentação, o aumento de nutrientes, a poluição d’água, a remoção da vegetação ripária e a diminuição do ingresso de galhos e troncos (Allan, 2004). Para ecossistemas aquáticos sul-americanos, a principal causa de perda de biodiversidade é a perda de hábitat que está associada ao desmatamento, ao barramento de rios, a mineração, a poluição d’água e as práticas inadequadas de agricultura (Barletta et al. 2010). O desmatamento ao redor de cursos d'água tem levado à perda da biodiversidade aquática, relacionada principalmente aos peixes, o grupo de vertebrados dominante nesses ambientes. O escasso conhecimento sobre as espécies de peixes neotropicais e o funcionamento dos ecossistemas aquáticos neotropicais dificulta o estabelecimento de prioridades de conservação (Barletta et al. 2010). Portanto, é urgente analisar como as atividades antrópicas podem afetar a biodiversidade de peixes, e a divulgar este conhecimento para que sejam pensadas soluções que possam mitigar os problemas de perdas taxonômicas e funcionais relacionadas com a ictiofauna de água doce neotropical. Assim, o objetivo geral da tese foi avaliar os efeitos sobre os padrões [Capítulo 1] e processos ecológicos [Capítulo 2] da ictiofauna [Prancha A] de riachos [Prancha B] da bacia do rio Machado [Anexo] ocasionados pela perda de hábitat. Com estas informações espera-se disponibilizar o conhecimento gerado às crianças através da extensão universitária [Capítulo 3]. Cada um dos capítulos da tese e anexo tem um objetivo específico e questões principais. [Capítulo 1] Padrões Examinar as relações entre a especialização do hábitat da ictiofauna de riachos e as variáveis ambientais (locais e da paisagem) e espacial (distância fluvial entre trechos). Ú Existem diferenças entre todas as espécies da metacomunidade (AS), assembleia dos peixes hábitat-generalistas (HG) e dos hábitat-especialistas (HS)? Ú Por quais fatores são explicadas tais diferenças? [Capítulo 2] Processos ecológicos Examinar as relações entre a ictiofauna de riachos e as variáveis ambientais (locais e da paisagem), espacial (posição geográfica dos riachos), funcionais (dieta, ecomorfologia e posição na coluna d'água) e taxonômica (classificação dos peixes). Ú Existe agrupamento nos traços funcionais e filogenético? Ú Quais condições de traços são filtradas pelo ambiente? 3 Ú Quais variáveis ambientais contribuem para o arranjo de comunidades locais? Ú Onde atuam esses filtros? Ú Quais linhagens são afetadas por esses filtros? [Capítulo 3] Conservação Criar uma ferramenta de educação ambiental com o conhecimento gerado. Ú É possível transferir o conhecimento gerado numa linguagem acessível para ensinar a importância dos peixes e a conservação da mata ciliar para crianças? [Anexo] Quem, quantas, onde? Realizar o inventário da ictiofauna de riachos da bacia do rio Machado e avaliar a sua distribuição. Ú Quais são as espécies de peixes que habitam nos 75 riachos da bacia do rio Machado? Ú Quantos indivíduos há por espécie em cada um dos 75 riachos? Ú Como é a distribuição de cada uma das espécies? Literatura citada Allan, J. D. 2004. Landscapes and Riverscapes: The Influence of Land Use on Stream Ecosystems. Annual Review of Ecology, Evolution, and Systematics 35: 257−284. Allan, J. D., D. L. Erickson, e J. Fay. 1997. The influence of catchment land use on stream integrity across multiple spatial scales. Freshwater Biology 37: 149−161. Alves, D. S., J. L. G. Pereira, C. L. Sousa, J. V. Soares, e F. Yamaguchi. 1998. Classification of the deforested area in central Rondônia using TM imagery. 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Arbuckle. 2003. The influence of scale and geography on relationships between stream community composition and landscape variables: description and prediction. Freshwater Biology 48: 768−785. Tscharnkte, T., A. M. Klein, I. Steffan-Dewenter, e C. Thies. 2005. Landscape perspectives on agricultural intensification and biodiversity – ecosystem service management. Ecology Letters 8: 857−874. 6 Prancha A. Fotos dos trechos de riachos (R) amostrados da bacia do rio Machado. Créditos: María Angélica Pérez-Mayorga, Ângelo Manzotti, Igor David da Costa, Gabriel Lourenço Brejão, Felipe de Paula Rossetti, Wesclen Vilar Nogueira e Vanessa Bressan (2011-2012). Riachos 1-12 R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 7 Prancha A. Continuação. Riachos 13-18, 20-27 R13 R14 R15 R16 R17 R18 Sem imagem devido a problemas logísticos R19 R20 R21 R22 ReBio Jaru R23 ReBio Jaru R24 ReBio Jaru R25 ReBio Jaru R26 ReBio Jaru R27 ReBio Jaru 8 Prancha A. Continuação. Riachos 28-42 R28 ReBio Jaru R29 ReBio Jaru R30 ReBio Jaru R31 ReBio Jaru R32 R33 RESEX Rio Preto Jacundá R34 RESEX Rio Preto Jacundá R35 RESEX Rio Preto Jacundá R36 R37 R38 RESEX Castanheira R39 RESEX Castanheira R40 R41 R42 9 Prancha A. Continuação. Riachos 43-57 R43 RESEX Aquariquara R44 RESEX Aquariquara R45 RESEX Aquariquara R46 R47 R48 R49 R50 R51 R52 R53 R54 R55 R56 R57 10 Prancha A. Continuação. Riachos 58-72 R58 R59 R60 R61 R62 R63 R64 R65 R66 R67 R68 R69 R70 R71 R72 11 Prancha A. Continuação. Riachos 73-75 R73 R74 R75 12 Prancha B. Fotos das 139 espécies de peixes coletadas nos 75 trechos de riachos. Créditos: Fernando Rogério Carvalho, María Angélica Pérez-Mayorga e Fernanda Martins (2012-2013). Edição: Lilian Casatti e María Angélica Pérez-Mayorga (2012-2013). Myliobatiformes e Characiformes Potamotrygon orbignyi 740 mm – DZSJRP 17112 Parodon nasus 62.0 mm – DZSJRP 14506 Curimatopsis macrolepis 27.0 mm – DZSJRP 16692 Cyphocharax plumbeus 69.4 mm – DZSJRP 17238 Cyphocharax spiluropsis 115.0 mm - DZSJRP 14630 Steindachnerina cf. dobula 82.9 mm - DZSJRP 14512 Steindachnerina fasciata 166.6 mm – DZSJRP 14661 Steindachnerina guentheri 42.8 mm - DZSJRP 16782 Prochilodus nigricans 122.9 mm - DZSJRP 16799 Anostomus ternetzi 69.3 mm - DZSJRP 14664 13 Prancha B. Continuação. Characiformes Leporinus friderici 89.4 mm - DZSJRP 14763 Characidium aff. gomesi 53.5 mm - DZSJRP 14704 Characidium aff. zebra 48.3 mm - DZSJRP 14703 Characidium sp. 47.9 mm - DZSJRP 14335 Elachocharax pulcher 17.5 mm - DZSJRP 15057 Microcharacidium aff. weitzmani 16.5 mm - DZSJRP 14986 Microcharacidium sp. 24.2 mm - DZSJRP 16653 Melanocharacidium dispilomma 49.2 mm - DZSJRP 17205 Melanocharacidium pectorale 26.4 mm - DZSJRP 16678 Hemiodus unimaculatus 129.6 mm - DZSJRP 14672 14 Prancha B. Continuação. Characiformes Carnegiella strigata 28.7 mm - DZSJRP 14886 Amazonspinther dalmata 14.4 mm - DZSJRP 14947 Astyanax cf. bimaculatus 73.6 mm - DZSJRP 14419 Astyanax cf. maximus 71.5 mm - DZSJRP 14460 Astyanax maculisquamis 66.7 mm - DZSJRP 14700 Bario steindachneri 78.9 mm - DZSJRP 15090 Brachychalcinus copei 75.3 mm - DZSJRP 14769 Bryconella pallidifrons 29.9 mm - DZSJRP 16651 Bryconops caudomaculatus 79.4 mm - DZSJRP 14628 Bryconops piracolina 71.6 mm - DZSJRP 17278 15 Prancha B. Continuação. Characiformes ‘Cheirodon’ troemneri 37.7 mm - DZSJRP 14668 Creagrutus petilus 54.7 mm - DZSJRP 14733 Hemigrammus aff. ocellifer 23.5 mm - DZSJRP 15009 Hemigrammus bellotti 32.5 mm - DZSJRP 14524 Hemigrammus melanochrous 27.2 mm - DZSJRP 15100 Hemigrammus neptunus 25.9 mm – DZSJRP 14710 Hemigrammus sp. 25.9 mm – DZSJRP 15101 Hyphessobrycon aff. heterorhabdus 27.2 mm - DZSJRP 16929 Hyphessobrycon agulha 43.7 mm - DZSJRP 15103 Hyphessobrycon bentosi 25.2 mm - DZSJRP 15011 16 Prancha B. Continuação. Characiformes Hyphessobrycon copelandi 37.9 mm - DZSJRP 14673 Jupiaba citrina 43.9 mm - DZSJRP 14701 Jupiaba poranga 46.5 mm - DZSJRP 15107 Jupiaba zonata 57.1 mm - DZSJRP 19916 Knodus cf. smithi 42.5 mm – DZSJRP 14715 Knodus heteresthes 52.4 mm - DZSJRP 14651 Microschemobrycon guaporensis 27.6 mm - DZSJRP 14476 Moenkhausia aff. gracilima 42.3 mm - DZSJRP 16817 Moenkhausia cf. bonita 42.4 mm - DZSJRP 14717 Moenkhausia pankilopteryx 65.2 mm - DZSJRP 14526 17 Prancha B. Continuação. Characiformes Moenkhausia collettii 45.1 mm - DZSJRP 14639 Moenkhausia cotinho 47.5 mm - DZSJRP 14478 Moenkhausia grandisquamis 83.5 mm - DZSJRP 14962 Moenkhausia mikia 50.2 mm - DZSJRP 14447 Moenkhausia oligolepis 73.2 mm - DZSJRP 14479 Odontostilbe fugitiva 23.0 mm - DZSJRP 14545 Phenacogaster retropinnus 49.5 mm - DZSJRP 14450 Serrapinnus aff. notomelas 36.9 mm - DZSJRP 14659 Serrapinnus microdon 35.1 mm – DZSJRP 14658 Tetragonopterus argenteus 76.1 mm – DZSJRP 17040 18 Prancha B. Continuação. Characiformes Triportheus angulatus 173.4 mm - DZSJRP 14456 Tyttocharax madeirae 15.9 mm - DZSJRP 14945 Myleus sp. 52.1 mm - DZSJRP 14741 Serrasalmus rhombeus 79.4 mm - DZSJRP 14695 Acestrorhynchus falcatus 173,6 mm - DZSJRP 17072 Erythrinus erythrinus 42.0 mm – DZSJRP 16650 Hoplerythrinus unitaeniatus 127.8 mm – DZSJRP 16764 Hoplias malabaricus 135.5 mm - DZSJRP 14538 Nannostomus trifasciatus 27.1 mm - DZSJRP 14963 Pyrrhulina cf. australis 27.5 mm - DZSJRP 14634 19 Prancha B. Continuação. Characiformes e Siluriformes Pyrrhulina cf. brevis 36.4 mm - DZSJRP 15115 Pyrrhulina cf. zigzag 31.9 mm - DZSJRP 17280 Denticetopsis seducta 34.3 mm - DZSJRP 14887 Helogenes gouldingi 51.0 mm - DZSJRP 15099 Pseudobunocephalus amazonicus 60.4 mm - DZSJRP 14940 Ituglanis amazonicus 50.9 mm - DZSJRP 14676 Miuroglanis platycephalus 16.2 mm - DZSJRP 14963 Paracanthopoma sp. 20.0 mm - DZSJRP 14905 Corydoras acutus 68.8 mm DZSJRP 15023 Corydoras aff. ambiacus 70.3 mm - DZSJRP 16757 20 Prancha B. Continuação. Siluriformes Corydoras bondi 50.5 mm - DZSJRP 17229 Corydoras cf. melanistius 50.5 mm – DZSJRP 15124 Corydoras elegans 26.4 mm - DZSJRP 14422 Corydoras stenocephalus 31.4 mm - DZSJRP 17263 Corydoras trilineatus 42.4 mm - DZSJRP 14755 Hoplosternum littorale 83.7 mm - DZSJRP 14423 Megalechis picta 102.8 mm – DZSJRP 16753 Ancistrus lithurgicus 92.9 mm - DZSJRP 14418 Farlowella cf. oxyrryncha 115.1 mm - DZSJRP 14671 Hypostomus pyrineusi 56.2 mm - DZSJRP 14424 21 Prancha B. Continuação. Siluriformes Hypostomus sp. 47.4 mm - DZSJRP 17290 Lasiancistrus schomburgkii 82.2 mm - DZSJRP 14697 Loricaria cataphracta 130.5 mm - DZSJRP 14499 Otocinclus hoppei 29.0 mm - DZSJRP 14685 Parotocinclus aff. aripuanensis 16.9 mm - DZSJRP 14895 Rineloricaria heteroptera 65.5 mm - DZSJRP 14427 Rineloricaria sp. 60.2 mm - DZSJRP 14635 Spatuloricaria evansii 71.4 mm - DZSJRP 14511 Squaliforma emarginata 53.2 mm - DZSJRP 14712 Batrochoglanis cf. raninus 30.6 mm - DZSJRP 14969 22 Prancha B. Continuação. Siluriformes Batrochoglanis villosus 61.0 mm - DZSJRP 14665 Microglanis poecilus 30.6 mm – DZSJRP 16655 Cetopsorhamdia sp. 1 90.0 mm - DZSJRP 17295 Cetopsorhamdia sp. 2 49.3 mm - DZSJRP 17279 Cetopsorhamdia sp. 3 45.9 mm - DZSJRP 17216 Imparfinis cf. hasemani 69.9 mm - DZSJRP 14714 Imparfinis stictonotus 44.8 mm - DZSJRP 14471 Phenacorhamdia cf. boliviana 51.3 mm - DZSJRP 14688 Phenacorhamdia sp. 46.8 mm - DZSJRP 15019 Pimelodella cf. howesi 92.1 mm - DZSJRP 14656 23 Prancha B. Continuação. Siluriformes e Gymnotiformes Pimelodella sp. 72.1 mm - DZSJRP 14527 Rhamdia quelen 138.2 mm - DZSJRP 14770 Acanthodoras cataphractus 41.8 mm - DZSJRP 16687 Centromochlus cf. perugiae 23.9 mm - DZSJRP 17261 Parauchenipterus porosus 84.4 mm – DZSJRP 16852 Tatia aulopygia 63.8 mm - DZSJRP 14696 Gymnotus aff. arapaima 159.6 mm - DZSJRP 14649 Gymnotus carapo 149.4 mm - DZSJRP 14648 Gymnotus coropinae 102.2 mm - DZSJRP 15006 Eigenmannia trilineata 112.9 mm - DZSJRP 14406 24 Prancha B. Continuação. Gymnotiformes, Cyprinodontiformes e Beloniformes Sternopygus macrurus 117.3 mm - DZSJRP 14484 Gymnorhamphichthys petiti 122.1 mm - DZSJRP 14631 Brachyhypopomus sp. 1 62.9 mm - DZSJRP 14627 Brachyhypopomus sp. 2 74.6 mm - DZSJRP 15091 Brachyhypopomus sp. 3 85.9 mm - DZSJRP 15092 Hypopygus lepturus 58.1 mm - DZSJRP 14632 Apteronotus albifrons 154.0 mm - DZSJRP 14641 Platyurosternarchus macrostomus 162.3 mm - DZSJRP 14690 Rivulus sp. 31.4 mm - DZSJRP 14942 Potamorrhaphis eigenmanni 164.7 mm - DZSJRP 14949 25 Prancha B. Continuação. Synbranchiformes e Perciformes Synbranchus marmoratus 240.7 mm - DZSJRP 14485 Aequidens tetramerus 75.5 mm - DZSJRP 14626 Apistogramma cf. resticulosa 38.4 mm - DZSJRP 14994 Cichlasoma amazonarum 54.7 mm - DZSJRP 14462 Crenicichla johanna 94.5 mm - DZSJRP 14758 Crenicichla santosi 85.2 mm - DZSJRP 14757 Geophagus megasema 113.5 mm - DZSJRP 15004 Satanoperca jurupari 150.1 mm - DZSJRP 14636 Tilapia rendalli 17.1 mm - DZSJRP 14431 26 CAPÍTULO 1. PADRÕES: Metacommunity dynamics in an altered Amazonian river basin: shared or distinct responses among the entire metacommunity, habitat-generalist, and habitat-specialist stream fish? Revista alvo: Hydrobiologia Abstract Environmental and spatial variables can distinctly influence the degree of habitat specialization of stream fish. From a metacommunity perspective, we predict that habitat-generalists are governed by dispersal-based processes and in contrast, all species and the habitat-specialists ones are governed by niche-based processes. To test this, we separately analyzed three data sets, the entire metacommunity, the habitat-specialists and the habitat-generalists, using a forward selection of explanatory variables, and a partial Redundancy Distance Analysis. The fish and 30 variables of 52 stream reaches of the Machado River Basin were collected during the dry period of 2012. We found that the three data sets are governed by niche based-processes; however, different variables explained species distribution according to their different habitat specialization degree. Percentage of forest at microbasin and heterogeneity of percentage of trees at stream stretch riparian buffer and rocks at substrate for habitat-generalists; and percentage of forest, oxisol and ultisol, and heterogeneity of percentage of trees, fine roots, bared soil and current for habitat-specialists. Therefore, the maintenance of aquatic diversity in the studied basin depends on actions directed towards the protection of areas that consider the specific requirements of each species group. Key words Amazonian ichthyofauna, soil coverage change, deconstructive framework, habitat specialization, niche-based process. Introduction Metacommunity ecology is a relatively recent approach, which helps in understanding mechanisms of spatial community ecology (Logue et al., 2011; Winegardner et al., 2012). The metacommunity concept arose from metapopulation theory (Hanski & Gilpin, 1991; Wilson, 1992). Metacommunities can be defined as a set of local communities that are linked by dispersal of multiple potentially interacting species (Leibold et al., 2004). Recent studies have emphasized that different group of species may be governed by different process, such as the groups of species clustered to their functional traits (Algarte et al., 2014), their specialization degree (Pandit et al., 2009) or their rarity (Heino & Soininen, 2010; Siqueira et al., 2012; Petsch et al., 2015). Approaches like these encompass the deconstructive framework to study the entire metacommunity (sensu Marquet 27 et al., 2004). In one of these studies, Pandit et al. (2009) demonstrated that habitat specialists responded to niche process and habitat generalists are best explained by dispersal processes. These findings open an interesting avenue of research, suggesting that different predictions about the dynamics of specialists and generalists under different metacommunity models could be a more informative approach. In communities with high species richness, community patterns and the influence of environmental and spatial factors may be masked by the greater quantity of possible relationships. Therefore, it is necessary and recommended partitioning the communities to detect ecological patterns. Freshwater fish communities represent good models for metacommunity studies due to some characteristics: (a) they are restricted to the aquatic environment, being influenced by both local and landscape scales (reach, stream, microbasin, and basin) (Schlosser, 1991; Pusey & Arthington 2003; Lorion & Kennedy, 2009; Fausch et al., 2002; Fernandes et al., 2012); (b) they have a good displacement capacity (Schlosser, 1991; Fausch et al., 2002), which is influenced by the spatial scale; (c) they can be classified in groups according to their feeding tactics and micro and mesohabitat use (Brejão et al., 2013). In addition, fish communities from tropics represent diverse ecosystems, often with great richness and abundance in comparison to temperate ones (Lowe- McConnell, 1975). An example of such a high diverse system is the Madeira River, in the Brazilian Amazon. Contrary to most tropical waters in the world, the fish fauna of this region is sufficiently known because of recent efforts from taxonomists, who documented 920 species (Queiroz et al., 2013). For the entire Madeira basin, the number cited by Queiroz et al. (2013) is probably underestimated since streams and the upper region of the basin were not sampled. For example, in a tributary basin of the Madeira River (the Machado River), the stream fish fauna was composed by 140 species, some of them with low range of distribution (Casatti et al., 2013). In the present study we used a deconstructive approach based in a niche breadth, in order to explore the ecological process shaping stream fish fauna. We divided fish species from Machado River basin into three groups, habitat-generalist assemblage, habitat-specialist assemblage and all species, and postulated the three following responses: (i) that the habitat-generalist assemblage will respond more to spatial variables (dispersal based-processes) based on interfluvial distance among streams, proxy for dispersal limitation, than to environmental variables. This prediction assumes that habitat-generalist assemblage has broad environmental tolerances, so that environmental variables will account less for the variation explained in their abundance and spatial distribution; 28 (ii) on the other hand, we predicted that habitat-specialist assemblage will be explained mostly by environmental variables (niche based-processes). This prediction assumes that species with very specific habitat requirements have a strong relation with environmental variables. For example, some stream fish species live exclusively associated to coarse litter (Carvalho et al., 2013), to hard substrates (Casatti & Castro, 1998) (gravel, cobble and boulder) or woody elements (branches and tree trunks, fine roots, exposed coarse roots, and coarse litter); and (iii) considering the species abundance distribution theory (May,1975; Pielou, 1975; Hughes, 1986), where most of the species are represented by a small number of individuals (e.g. the habitat- specialist assemblage), and most of individuals belong to a small number of abundant species (e.g. the habitat-generalist assemblage), we expected that the entire metacommunity group reveal the same pattern of the habitat-specialist assemblage (niche based-processes) by influence of their highest species richness. Materials and Methods Study area and sampling design The Machado River is a tributary on the right side of the Madeira River, in the Western Amazon. The Machado River basin is situated in the state of Rondônia, Brazil (Fig. 1), comprises 75,400 km2, with an altitude gradient that varies between 75 and 600 m (Krusche et al., 2005). The main soil types in the basin are represented by oxisol and ultisol (47 and 24% of the total, respectively, Ballester et al., 2012). The climate is tropical wet, with average temperature varying between 19 and 33˚C and annual average precipitation of approximately 2,500 mm (Krusche et al., 2005). The Machado River basin has been modified since the 1970s, with introduction of settlement projects along the BR-364 highway (Alves et al., 1998). The central portion of the basin has a high degree of anthropic alteration, with extensive pasture areas, but the original vegetal cover is less modified in the upper and lower portions of the basin (Krusche et al., 2005). The soil of the region is covered by three successional stages of the vegetation (Ferraz et al., 2005): (i) open primary wet tropical forest, with no sign of disturbance and trees of 20 to 40 m height; (ii) secondary forest, between the edge of extensive agriculture and the mature forest (Helmer, 2000; Fernandes et al., 2012), with trees of 5 to 20 m height and some kind of natural or anthropic disturbance, being partially deforested areas, lands abandoned or previously taken up by pastures or crops (Brown & Lugo, 1990; Fernandes et al., 2012); and (iii) pastures, which are areas without forest that include large or small beef cattle farms (Fernandes et al., 2012). 29 Fig. 1 Location of the Machado River basin in the State of Rondônia (Brazil) (top right), the two main categories of soil coverage (forest and deforested) and location of the 52 stream sampled reaches (filled circles) We sampled 52 ‘terra-firme’ stream reaches. According to Pazin et al. (2006), the term ‘terra- firme’ refers to tropical rain forests, which are not seasonally inundated by adjacent rivers. The streams were chosen through thematic maps produced a priori. First, we generated the microbasins in the ArcSWAT (Soil and Water Assessment Tools) hydrological model, based on SRTM DEM satellite images (90 x 90 m resolution), originated from NASA and made available by the United States Geological Survey (USGS), considering a minimum contribution area of 1,000 ha. In the selected site, we have considered a maximum depth lower than 1.5 m to allow standardized use of the collection equipment, perennity of the streams, accessibility and 30 authorization of the owners to have access to the sampling reach. Each reach had an extension of 80 m and it was sampled during the dry period, in June and July 2012. The Machado River's hydrological regime, in accordance with the daily, monthly and multiannual (2008-2012) average of the water level, presents dry period between June and December, with the lowest level between August and September; and the rainfall period between January and May, with the highest level in February, according to data made available by ANA (2013). Sampling of variables In total, we sampled 29 environmental variables that were subdivided in local environment variables (S = 23) and landscape environment variables (S = 6) (Table 1). We quantified the local variables in sections of 20 m of extension for each sampling reach of 80 m; the hydrological and physical-chemical variables using a meter stick, a tape measure, a mechanical flow meter, a portable temperature and dissolved oxygen meter, and a conductivity meter. We estimated visually the composition of the substrate, through classification based on Krumbein (1963) and of the riparian buffer covering. The landscape environmental variables were the soil type and the soil coverage. The soil type consisted of five categories: eptisol, oxisol, ultisol, entisol, and alfisol in accordance with database generated by Ballester et al. (2012). The soil coverage consisted of mature forest areas and the secondary forest areas, which showed a low ratio (1.7 ± sd 2.0) in relation the other categories and occurred between the edge of the forest and the pasture areas. In general, the stream reaches situated in the microbasins where forests were removed, the local variables are homogenous, whit only sand in the bottom, and dominance of grass and rocks, or bared soil in the banks. On the other hand, the stream reaches situated in the microbasins with higher proportion of forests, the local variables are heterogeneous, with various substrate components, and fine roots, coarse roots exposed, shrubs, trees and riparian liter in the riparian buffer. To represent the spatial variables, we obtained the riverine distance between sites because this variable is able to capture spatial patterns that are not captured by overland distances (Landeiro et al., 2011). We obtained the triangular matrix containing the watercourse distance (m) between sites using the Network Analyst extension in the software ArcGIS 9.3 (ESRI Inc., 2008). From the triangular matrix containing the riverine distance between sites, we calculated the truncated distance matrix to retain the distance between neighbors. We then computed the PCoA of the truncated matrix, and retained its positive eigenvectors (Borcard et al., 2011) to be used as spatial predictors (Borcard & Legendre, 2002; Dray et al., 2006). 31 Table 1 Scales, codes, mean (± standard deviation) values, and the sampling description of the environmental (local and landscape) and spatial variables. Variable codes in bold indicate variables removed for further analyses due to many absences in the matrix or high correlation coefficients (≥ 0.8 or ≥ -0.8). Scales Variables Codes M ± sd Description Local Hydrological Depth (cm) DEP 15.6 ± 7.8 We took several measurements in each stream reach, and then calculated the standard deviationMedian width (cm) WID 3.0 ± 1.5 Physicochemical Current (cm/s) CUR 0.5 ± 0.3 We took four measurements every 20 m in each stream reach, and then calculated the standard deviation Water temperature (ºC) WTE 23.4 ± 1.8 Before fish sampling and net installation, we took one measurement in downstream section for each stream reach Dissolved oxygen (mg/l) DOX 6.6 ± 2.1 Conductivity (µS) CON 24.8 ± 22.3 Substrate Silt (0.004-0.05 mm) SIL 8.2 ± 22.1 We used the Krumbein (1963) substrate classification. We quantified on field the percentage values of substrate composition every 20 m for each stream reach, and then calculated the standard deviation Sand (0.05-2 mm) SAN 53.3 ± 27.9 Gravel (2-64 mm) GRAV 3.7 ± 7.3 Boulder (>256 mm) BOU 5.3 ± 1.2 Bedrock (>10 m) BED 1.2 ± 8.7 Attached vegetation (%) AVE 1.9 ± 4.9 Coarse litter (%) CLI 18.8 ± 17.4 Branches and tree trunks (%) BAT 12.5 ± 12.2 Riparian buffer Fine roots (%) FRO 2.2 ± 5.5 We quantified on field the percentage values of riparian buffer on both stream margins every 20 m for each stream reach, and then calculated the standard deviation of two sides Coarse roots exposed (%) CRO 4.1 ± 7.7 Grass (%) GRA 37.3 ± 39.1 Shrubs (%) SHR 18.5 ± 15.4 Trees (%) TRE 17.0 ± 18.8 Bare soil (%) BAS 7.5 ± 12.8 Rocks (%) ROC 5.3 ± 13.7 Pteridophytes (%) PTE 1.0 4.9 Riparian litter (%) RLI 12.7 ± 11.3 Landscape Soil type Eptisol (%) EP 0.4 ± 3.1 We estimated the percentage of each soil type for each microbasin using the Ballester et al. (2012) data set Oxisol (%) OX 48.9 ± 48.5 Ultisol (%) UL 38.1 ± 46.8 Entisol (%) EN 12.2 ± 30.4 Alfisol (%) AL 0.4 ± 2.8 Soil coverage Forest (%) FO 45.4 ± 35.3 We estimated the percentage of forest for each microbasin based on Landsat images, and were classified based on supervised classification method according Jensen (2000) in the software ERDAS 9.2 (Leica Photogrammetry, 2008) Spatial Fluvial distance between 52 sites of Machado River basin (km) DIS 356.5 ± 211.8 We estimated the fluvial distance and obtained the triangular matrix containing the watercourse distance between sites with the Network Analyst extension in the software ArcGIS 9.3 32 Fish sampling We collected fishes in each reach using two combined techniques, a hand seine (2 mm mesh) for stream portions without bank vegetation, and/or a dip net (2 mm mesh) for streams portions with trunks, branches and gravel on the banks or at the bottom. The hand seine was operated by two collectors and the collection effort was standardized for all reaches, being one hour along in each reach. We fixed the fishes in a 10% formalin solution and later transferred them to a 70% ethanol solution. We deposited all collected specimens in the fish collection of the Department of Zoology and Botany (DZSJRP), São Paulo State University (UNESP), São José do Rio Preto, São Paulo, Brazil. Definition of the three sets of species We used Smith's measure of niche breadth (Smith, 1982) to measure the habitat specialization of each species by calculating Where, FT = Smith's measure of niche breadth, R = is the total number of resource states, pi = is the proportion of resource i used, and qi = is the proportion of resource i available for use (Smith, 1982). We defined R as each sampling reach; pi as the quotient of number of individuals of one species divided by total number of all individuals of this species in all reaches; qi as the quotient of one sampling reach divided by total number of sampling reaches (1/52). FT is a standardized measure, varies from zero (minimal) to one (maximal) and it is a convenient measure to use because its sampling distribution is known (Krebs, 2014). FT for 121 species ranged from 0.100 to 0.800 (Fig. 2). Thus, species with higher FT values (0.451 to 0.800) and lower FT values (0.100 to 0.450) were considered habitat generalists and habitat specialists, respectively (Table 2). In this manner, we produced three data sets, one with all species (AS), one with only habitat-generalist species (HG), and one with habitat-specialist species (HS). 33 FT = 121*0.1*normal(x, 0.3012, 0.1606) 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 FT 0 10 20 30 40 50 N um be ro fo bs er va tio ns Figura 2. Histogram of Smith's measure of niche breadth (FT) for 121 fish species Table 2 Habitat-generalist and specialist stream fishes according a Smith's measure of niche breadth (FT). For species codes see Appendix Hábitat generalists (S=22) Hábitat specialists (S=99) Species FT Species FT Species FT Species FT Species FT Species FT aeqtet 0.635 acacat 0.223 coramb 0.139 hypagu 0.277 moebon 0.264 rhaque 0.237 anclit 0.491 acefal 0.240 corbon 0.139 hypben 0.223 moecot 0.391 rinsp 0.196 astbim 0.477 apires 0.437 corele 0.196 hypcop 0.266 moegrac 0.139 rivsp 0.139 bracop 0.591 aptalb 0.193 corste 0.186 hyphet 0.413 moegran 0.235 satjur 0.344 brycau 0.699 astmac 0.159 curmac 0.139 hyplep 0.385 moemik 0.326 squema 0.237 chazeb 0.753 astmax 0.270 cypplu 0.139 hyppyr 0.358 moepan 0.196 stefas 0.436 cortri 0.471 barste 0.139 cypspi 0.393 hypsp 0.139 mylsp 0.186 stegue 0.139 crepet 0.596 batran 0.267 densed 0.193 imphas 0.420 odofug 0.270 synmar 0.446 cresan 0.651 batvil 0.196 eigtri 0.401 impsti 0.415 otohop 0.186 tataul 0.139 gympet 0.522 brasp1 0.139 elapul 0.312 ituama 0.419 parari 0.183 tetarg 0.139 hopmal 0.627 brasp2 0.329 eryery 0.382 juppor 0.189 parnas 0.139 tytmad 0.139 jupcit 0.480 brasp3 0.253 faroxy 0.422 jupzon 0.185 parpor 0.231 knosmi 0.639 brypal 0.325 gymara 0.351 knohet 0.173 parsp 0.139 lassch 0.462 brypir 0.139 gymcar 0.314 lepfri 0.435 phebol 0.139 moecol 0.559 carstr 0.254 gymcor 0.406 lorcat 0.139 phesp 0.186 moeoli 0.744 cenper 0.139 helgou 0.195 megpic 0.280 pimhow 0.366 pheret 0.584 cetsp1 0.179 hembel 0.223 meldis 0.139 pimsp 0.240 pyraus 0.601 cetsp2 0.189 hemmel 0.255 melpec 0.139 poteig 0.139 rinhet 0.620 cetsp3 0.139 hemnep 0.170 micgua 0.356 potorb 0.139 sermic 0.497 chagom 0.139 hemoce 0.320 micpoe 0.139 pronig 0.139 sernot 0.462 cicama 0.261 hoplit 0.240 micsp 0.212 pseama 0.302 stemac 0.457 coracu 0.237 hopuni 0.240 micwei 0.272 pyrzig 0.139 34 Analysis To determine the importance of the environmental and spatial variables in the three groups, we partitioned the variation in species abundance among environmental and spatial predictors, after transforming procedures using the Hellinger series. We calculated the correlation coefficients of the set of environment variables and removed nine variables that had a high correlation (≥ 0.8 or ≥ -0.8) or many zeros in the matrix. Thus, for subsequent analyses, we took into account 19 environment explanatory variables and 39 spatial explanatory vectors (Table 1). Our subset of explanatory variables was composed by 19 environment explanatory variables (we used the standard deviation to assess the heterogeneity of local variables and the percentage for three landscape variables) and 39 spatial explanatory vectors, using the method proposed by Blanchet et al. (2008). In this method, the overall model using all explanatory variables is tested and the analysis goes on only if the result is significant (P < 0.05). If this criterion holds, two other criteria, namely the alpha significance level of each explanatory variable and the adjusted coefficient of multiple determination (R2 adjusted) calculated with all variables (Blanchet et al., 2008), are taking into account. Thus, an explanatory variable is retained if P < 0.05 and if its R2 adjusted is not higher than the R2 adjusted of the full model. If these criteria are not attained, the set of variables is non- significant and the procedure is interrupted (Blanchet et al., 2008). We used a partial Redundancy Analysis (pRDA) to quantify the relative importance of environmental (local and landscape) and spatial variables (fluvial distance) in explaining the variation in species composition and abundances. This method is an extension of the linear regression with corresponding R2 and measures the amount of variation (computed as the percentage of the total variation in the community matrix) that can be attributed exclusively to one or other set of explanatory environmental (E), or spatial (S) variables (Borcard et al., 1992). We used the unbiased variation partitioning method proposed by Peres-Neto et al. (2006) to obtain the variance explained exclusively by environmental and spatial components, and their respective adjusted coefficients of determination (Radj 2). We carried out a separated analysis for each group of species (AS, HG, and HS). The PCNM, pRDA and Variation Partitioning analysis were carried out in R (R Development Core Team, 2011), with the vegan, PCNM, AEM, spacemakeR, packfor packages. To reduce clutter in the ordination graphic, we used the orditorp function of the software. According to Borcard et al. (1992), the different components of environmental and spatial variation are: total explained variation [E + S], environmental variation [E], spatial variation [S], environmental variation without the spatial component [E|S]; and spatial variation without the environmental component [S|E]. We tested the 35 significance of these components with Monte Carlo permutation tests (999 permutations) and inferred which metacommunity perspectives best explain each data set, based in significance of each component (α = 0.05). Results The P-values of the global environmental model (PGenv) derived from RDA was significant for all data sets. The P-values of the global spatial model (PGspa) was only significant for HG set. The P-values of the pure environmental fraction (P[E|S]) was significant for all data sets, and the P-values of the pure spatial fraction (P[S|E]) was significant only for HG set (Table 3). Table 3 Results of the partial redundancy analysis for the entire fish metacommunity (all species), for the habitat-generalist and habitat-specialist stream fishes. PGenv P-values of global environmental models; PGspa P-values of global spatial models including eigenvectors associated with positive and negative eigenvalues; env. sel. selected environmental variables; spa. sel. selected spatial vector; P[E|S] P-values associated with the pure environmental fractions, P[S|E] P-values associated with the pure spatial fractions; MC P metacommunity perspectives inferred. P-values lower than 0.05 are indicated in bold; asterisks represent the alpha significance level of each explanatory variable (*** 0.001; ** 0.01; * 0.05). For environmental selected codes, see Table 1. Data set PGenv PGspa env. sel. spa. sel. R2 adj [E|S] R2 adj [S|E] R2 adj [E+S] P[E|S] P[S|E] MC P AS 0.001 0.251 FO***, TRE***, ROC**, UL*, OX* - 0.202 - - 0.001 - Niche based- processes HG 0.001 0.046 FO***, TRE**, ROC** 1***, 3** 0.064 0.036 0.117 0.001 0.002 HS 0.001 0.064 FO***, TRE***, UL*, OX*, FRO*, BAS*, CUR* - 0.160 - - 0.001 - Considering only the cases in which the global environmental model ([E|S]) was significant, higher adjusted coefficients of determination (R2 adjusted) were estimated for AS (20.2%) and HS (16.0%) (Fig. 2 and Table 3). For AS set, pure environmental fraction ([E|S] = 20.2%) was significant; for HG assemblage, pure environmental fraction ([E|S] = 6.4%), and pure spatial fraction ([S|E] = 3.6%) were significant, with [E|S] being higher than [S|E] (Fig. 2); and for HS assemblage, pure environmental fraction ([E|S] = 16.0%) was significant. According to the significant variance of the pure environmental fraction for all data sets; and the significant variance of the pure spatial fraction for HG assemblage, the three sets best fit the model that indicate the importance of niche-based processes (Table 3). 36 Fig. 2 Variance partitioning of the whole fish metacommunity, habitat-generalist assemblage, and habitat-specialist assemblage. [E|S] pure environmental fraction, [E+S] shared fraction, and [S|E] pure spatial fraction. [S|E] and [E+S] values for the whole fish metacommunity and habitat-specialist assemblage are not showed because they are non-significant fractions in the ichthyofauna structure explication For AS set, the permutation test for RDA (Fig. 3a) under reduced model significantly explained 21.2% of the variance (F = 3.58, P = 0.001). The five environmental variables significantly explained the fish abundances: the percentage of forest (F = 7.94, P = 0.001), the heterogeneity of trees in the riparian buffer (F = 4.09, P = 0.001), the heterogeneity of rock in the bottom (F = 2.11, P = 0.006), and the percentage of ultisol (F = 1.80, P = 0.023) and oxisol (F = 1.96, P = 0.008) in the microbasins. For HG assemblage, the permutation test for RDA (Fig. 3b) under reduced model significantly explained 7.1% of the variance (F = 2.33, P = 0.001). Two of the three environmental variables significantly explained the fish abundances, namely the percentage of forest (F = 3.01, P = 0.001), and the heterogeneity of rock in the bottom (F = 2.26, P = 0.005). For HS assemblage, the permutation test for RDA (Fig. 3c) under reduced model significantly explained 25.15% of the variance (F = 2.39, P = 0.001). Six of the seven environmental variables significantly explained the fish abundances: the percentage of forest (F = 4.49, P = 0.001), the heterogeneity of trees in the riparian buffer (F = 4.01, P = 0.001), the heterogeneity of ultisol (F = 1.45, P = 0.037) and oxisol (F = 2.32, P = 0.001) in the microbasins, the heterogeneity of fine roots at the riparian buffer (F = 1.52, P = 0.023), and the heterogeneity of bare soil in the banks (F = 1.55, P = 0.016). 37 Fig. 3 Partial Redundancy analysis (pRDA) biplot using the most important predictor variables (capital letters) for all data sets (a, b, and c), asterisks represent P-values (*** 0.001; ** 0.01; * 0.05). Arrow length corresponds to the strength of relationships between variables and axes; crosses represent fish species that were excluded from the representation after applying the orditorp function of vegan’s package. For variables codes, see Table 1 and for species codes see Appendix (a ) Al lf ish sp ec ie s (S = 12 1) (b ) H ab ita t- ge ne ra lis ts st re am fis h (S = 22 ) (c ) H ab ita t- sp ec ia lis ts st re am fis h (S = 99 ) *** *** ** ** * *** *** *** * * * *** ** 38 Discussion Only niche-based processes explained the fish communities, regardless the species sets. Contrary to our first expectation, although the HG assemblage were environmental and spatially structured (species sorting and mass effect models), the low percentage of the variation of pure spatial component invalid the dispersal-based processes inference. Dispersal is well recognized as key process structuring freshwater fish communities (Taylor & Warren, 2001), however, for stream fishes, the real role of dispersion is poorly known. What we have learned from other studies is that some stream fish demonstrate high endemism (as for HS species) due to their reduced capacity of displacement (Castro, 1999; Gerhard, 1999). They generally do not perform extensive migrations throughout their life cycle and remain isolated (Casatti et al., 2001), with exception of some small characids. The importance of niche-based processes are consistent with evidences registered in other deconstructive studies of aquatic metacommunities (Urban, 2004; Cottenie, 2005; Pandit et al., 2009; Algarte et al., 2014; Petsch et al., 2015). It is important to mention that there are two kinds of metacommunity-structuring forces of different origins, the natural and the anthropogenic ones (Heino, 2013). The fish metacommunity structure of the basin of the Machado River can be explained in the light of two causes, i) the biogeographic one (of natural origin), and ii) the one related to soil use (of anthropogenic origin). In the first case, one may expect some similarity of the ichthyofauna present in the headwater streams of the upper portion of the Machado River (south of the state of Rondônia) with the ichthyofauna of the Paraguay River, since the Paraguayan fish fauna was formed primarily by some migration events from neighboring tributaries of the Amazon basin (Carvalho & Albert, 2011). Moreover, the fish composition from protected areas in the north of the state of Rondônia presents more similarity with the fish fauna of the Madeira River. In an ecological time, the patterns of local-coexistence of similar species from a regional species pool are controlled by a tension between the tendency for co-existing species to have similar requirements (Leibold, 1998), and this pool can be structured by environmental filters (Cornwell et al., 2006). Secondly, the changes in land use represent one of the most important threats to aquatic communities, which lead to the reduction of connectivity between local communities (Heino, 2013) and modify metacommunity dynamics, which can speed up the extinction processes, by hindering the dispersal of the species pool from the main channel to the tributaries. Ordination results mirror the deforestation gradient since preserved sites are characterized by high percentage of oxisol and forest in the microbasin, and heterogeneity of trees and fine roots at the riparian buffer. By contrast, homogenized sites are characterized by high percentage of ultisol in the microbasin, and rocks and 39 bared soil in the banks. The strong relationship between soil type and environmental variables at local scale is explained by the model of development in the Machado River basin, which has been replacing forests by pasture and agriculture since the 80’s, starting in the most “fertile” ultisol areas (Krusche et al., 2005). Therefore, the composition and abundances of HG and HS sets in this basin are affected by the changes in land use, which influenced characteristics of local variables, such as riparian vegetation and substrate composition. The HG assemblage can exploit structurally simplified and/or heterogeneous streams. In simplified streams, the ichthyofauna responded to the degradation of the riparian buffer by shifting species composition and functional traits of species (Casatti et al., 2012), and by the dominance of opportunist and tolerant species (Casatti et al., 2009), like the Serrapinnus species, which represented almost 1/3 of all the collected fish. It is well known that riparian vegetation in headwater streams (orders 1-3) influences in several ways the instream environment (Vannote et al., 1980; Schlosser, 1982; Gregory et al., 1991; Pusey & Arthington, 2003). This riparian vegetation provides shadow (Vannote et al., 1980) and, therefore, limits local productivity (Sabater et al., 2000). By contrast, logged riparian buffers exhibit high local productivity, notably filamentous algae (Biggs et al., 1998). The relationships of the algivores (S. microdon and S. notomelas) and aquatics insectivores (K. smithi and P. retropinnus) (MAPM, pers. obs.) with degraded streams indicate that these species take advantage of autochthonous resources, the most abundant in such conditions. Contrariwise, in streams structurally heterogeneous, other species of HG assemblage, as the diurnal surface picker Pyrrhulina australis, the grazer Lasiancistrus schomburgkii, and the picker and browser Aequidens tetramerus, are associated with forest in the microbasin, probably these species take advantage of allochthonous resources (woody elements, substrate heterogeneity, mesohabitat heterogeneity) that are abundant in this scenario. The HS set had specific demands that depend on allochthonous structures (e.g., litter packs, branches, and trunks derived from trees in the riparian buffer). The organic material intake, deposited on the forest floor, can be moved into the streams by wind or other agents (Elosegi & Pozo, 2005). These elements can contribute to mesohabitat (e.g. pools, riffles, runs) and microhabitat (e.g. substrate type, water depth, velocity) variability (Frissell et al., 1986). In this context, the HS set usually exploit meso- and microhabitats for foraging, reproduction and shelter. In our ordination results, the HS assemblage confirms these expectations, since the most of species are in association with forested sites, which means greater intake of allochthonous material. For instance, the grubber Megalechis picta and the grazer Farlowella oxyrrhyncha associated to preserved streams with higher 40 proportions of mature forests microbasin and trees at riparian buffer, respectively, in accordance with its occurrence in particular microhabitats of preserved streams with heterogeneous substrate and high current. Megalechis forages close to margins, searching the bottom mainly on patches of accumulated fine particulate organic matter bottom; Farlowella forages in high current speed stream stretches, scratching algae attached to branches, in petioles of macrophytes and over gravel bottom (Brejão et al., 2013). These findings suggest that conservation and maintenance of regional biodiversity depends on the knowledge about the regional species pool taking into account the specific demands according to habitat specialization. Because traditional metacommunities analyses are conducted with the entire set of species, they neglect any conclusion about the specific requirements of species. Just as important as discriminating habitat requirements for each species set is to understand how different sets (and scales) of variables are related to different species sets. Specifically for river basins that were recently deforested, remnants of preserved areas could be of great value because they are still able to harbor subsets of specialized species that can play a role of source assemblages in the regional context. Acknowledgements This study was made possible by a collecting license provided by Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis IBAMA (4355-1) and by financial funding provided by Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP (#99/05193-2, 01/13340-7, 04/00545-8, and 04/04820-3) and Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPQ (306758/2010-5). The authors greatly thank Fernando Rodrigues da Silva, Mauricio Cetra, two anonymous reviewers of Hydrobiologia, Tadeu Siqueira, David Hoeinghaus, Virgínia Sanches Uieda and Francisco Langeani Neto for their useful comments on the manuscript. We thank the UEG by funding the manuscript translation; FBT is supported by the University Research and Scientific Production Support Program PROBIP/UEG. References Agência Nacional de Águas (ANA), 2013. HidroWeb Sistema de informações hidrológicas, Brasília [available on internet at http://hidroweb.ana.gov.br/]. Algarte, V. M., L. 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(2007) Orders and families Species and authors Species code N Myliobatiformes Potamotrygonidae Potamotrygon orbignyi (Castelnau, 1855) potorb 1 Characiformes Parodontidae Parodon nasus Kner, 1859 parnas 1 Curimatidae Curimatopsis macrolepis (Steindachner, 1876) curmac 6 Cyphocharax plumbeus (Eigenmann & Eigenmann, 1889) cypplu 1 Cyphocharax spiluropsis (Eigenmann & Eigenmann, 1889) cypspi 29 Steindachnerina fasciata (Vari & Géry, 1985) stefas 28 Steindachnerina guentheri (Eigenmann & Eigenmann, 1889) stegue 3 Prochilodontidae Prochilodus nigricans Spix & Agassiz, 1829 pronig 1 Anostomidae Leporinus friderici (Block, 1794) lepfri 28 Crenuchidae Characidium aff. gomesi Travassos, 1956 chagom 3 Characidium aff. zebra Eigenmann, 1909 chazeb 330 Elachocharax pulcher Myers, 1927 elapul 76 Microcharacidium aff. weitzmani Buckup, 1993 micwei 12 Microcharacidium sp. micsp 50 Melanocharacidium dispilomma Buckup, 1993 meldis 1 Melanocharacidium pectorale Buckup, 1993 melpec 1 Gasteropelecidae Carnegiella strigata (Günther, 1864) carstr 27 Characidae Astyanax cf. bimaculatus (Linnaeus, 1758) astbim 91 Astyanax cf. maximus (Steindachner, 1876) astmax 7 Astyanax maculisquamis Garutti & Britski, 1997 astmac 39 Bario steindachneri (Eigenmann, 1893) barste 1 Brachychalcinus copei (Steindachner, 1822) bracop 78 Bryconella pallidifrons (Fowler, 1946) brypal 695 Bryconops caudomaculatus (Günther, 1864) brycau 219 Bryconops piracolina Wingert & Malabarba, 2011 brypir 23 Creagrutus petilus Vari & Harold, 2001 crepet 357 Hemigrammus aff. ocellifer (Steindachner, 1882) hemoce 46 Hemigrammus bellotti (Steindachner, 1882) hembel 143 Hemigrammus melanochrous Fowler, 1913 hemmel 112 Hemigrammus neptunus Zarske and Géry, 2002 hemnep 58 Hyphessobrycon aff. heterorhabdus (Ulrey, 1894) hyphet 144 Hyphessobrycon agulha Fowler, 1913 hypagu 808 Hyphessobrycon bentosi Durbin, 1908 hypben 73 Hyphessobrycon copelandi Durbin, 1908 hypcop 24 Jupiaba citrina Zanata & Ohara, 2009 jupcit 272 Jupiaba poranga Zanata, 1997 juppor 4 Jupiaba zonata (Eigenmann, 1908) jupzon 55 Knodus cf. smithi Fowler, 1913 knosmi 387 47 Orders and families Species and authors Species code N Knodus heteresthes Eigenmann, 1908 knohet 596 Microschemobrycon guaporensis Eigenmann, 1915 micgua 61 Moenkhausia aff. gracilima Eigenmann, 1908 moegrac 1 Moenkhausia cf. bonita Benine, Castro & Sabino, 2004 moebon 75 Moenkhausia pankilopteryx Bertaco & Lucinda 2006 moepan 2 Moenkhausia collettii (Steindachner, 1882) moecol 986 Moenkhausia cotinho Eigenmann, 1908 moecot 66 Moenkhausia grandisquamis Müller and Troschel, 1845 moegran 6 Moenkhausia mikia Marinho and Langeani, 2010 moemik 102 Moenkhausia oligolepis (Günther, 1864) moeoli 191 Odontostilbe fugitiva Cope, 1870 odofug 301 Phenacogaster retropinnus Lucena & Malabarba, 2010 pheret 164 Serrapinus aff. notomelas (Eigenmann, 1915) sernot 3316 Serrapinnus microdon (Eigenmann, 1915) sermic 1211 Tetragonopterus argenteus Cuvier, 1816 tetarg 2 Tyttocharax madeirae Fowler, 1913 tytmad 16 Serrasalmidae Myleus sp. mylsp 5 Acestrorhynchidae Acestrorhynchus falcatus (Bloch, 1794) acefal 3 Erythrinidae Erythrinus (Bloch & Schneider, 1801) eryery 11 Hoplerythrinus unitaeniatus (Spix & Agassiz, 1829) hopuni 3 Hoplias malabaricus (Bloch, 1794) hopmal 53 Lebiasinidae Pyrrhulina cf. australis Eigenmann & Kennedy, 1903 pyraus 190 Pyrrhulina cf. zigzag Zarske & Géry, 1997 pyrzig 9 Siluriformes Cetopsidae Denticetopsis seducta (Vari, Ferraris & de Pinna, 2005) densed 3 Helogenes gouldingi Vari & Ortega, 1986 helgou 5 Aspredinidae Pseudobunocephalus amazonicus (Mees, 1989) pseama 27 Trichomycteridae Ituglanis amazonicus (Steindachner, 1882) ituama 88 Paracanthopoma sp. parsp 2 Callichthyidae Corydoras acutus Cope, 1872 coracu 4 Corydoras aff. ambiacus Cope, 1872 coramb 3 Corydoras bondi Gosline, 1940 corbon 1 Corydoras elegans Steindachner, 1876 corele 2 Corydoras stenocephalus Eigenmann & Allen, 1942 corste 5 Corydoras trilineatus Cope, 1872 cortri 60 Hoplosternum littorale (Hancock, 1828) hoplit 3 Megalechis picta (Müller & Troschel, 1849) megpic 49 Loricariidae Ancistrus lithurgicus Eigenmann, 1912 anclit 106 Farlowella cf. oxyrryncha (Kner, 1853) faroxy 53 Hypostomus pyrineusi (Miranda Ribeiro, 1920) hyppyr 11 Hypostomus sp. hypsp 1 Lasiancistrus schomburgkii (Günther, 1864) lassch 28 Loricaria cataphracta Linnaeus, 1758 lorcat 1 Otocinclus hoppei Miranda Ribeiro, 1939 otohop 39 Parotocinclus aff. aripuanensis Garavello, 1988 parari 6 Rineloricaria heteroptera Isbrücker & Nijssen, 1976 rinhet 92 Rineloricaria sp. rinsp 2 48 Orders and families Species and authors Species code N Squaliforma emarginata (Valenciennes, 1840) squema 4 Pseudopimelodidae Batrochoglanis cf. raninus (Valenciennes, 1840) batran 14 Batrochoglanis villosus (Eigenmann, 1912) batvil 4 Microglanis poecilus Eigenmann, 1912 micpoe 1 Heptapteridae Cetopsorhamdia sp. 1 cetsp1 24 Cetopsorhamdia sp. 2 cetsp2 8 Cetopsorhamdia sp. 3 cetsp3 6 Imparfinis cf. hasemani Steindachner, 1917 imphas 111 Imparfinis stictonotus (Fowler, 1940) impsti 45 Phenacorhamdia cf. boliviana (Pearson, 1924) phebol 1 Phenacorhamdia sp. phesp 10 Pimelodella cf. howesi Fowler, 1940 pimhow 37 Pimelodella sp. pimsp 3 Rhamdia quelen (Quoy & Gaimard, 1824) rhaque 4 Doradidae Acanthodoras cataphractus (Linnaeus, 1758) acacat 19 Auchenipteridae Centromochlus cf. perugiae Steindachner, 1882 cenper 1 Tatia aulopygia (Kner, 1858) tataul 1 Parauchenipterus porosus (Eigenmann & Eigenmann, 1888) parpor 5 Gymnotiformes Gymnotidae Gymnotus aff. arapaima Albert & Crampton, 2001 gymara 25 Gymnotus carapo Linnaeus, 1758 gymcar 29 Gymnotus coropinae Hoederman, 1962 gymcor 65 Sternopygidae Eigenmannia trilineata López & Castello, 1966 eigtri 159 Sternopygus macrurus (Bloch & Schneider, 1801) stemac 80 Rhamphichthyidae Gymnorhamphichthys petiti Géry & Vu-Tân-Tuê, 1964 gympet 207 Hypopomidae Brachyhypopomus sp. 1 brasp1 1 Brachyhypopomus sp. 2 brasp2 13 Brachyhypopomus sp. 3 brasp3 22 Hypopygus lepturus Hoedeman, 1962 hyplep 97 Apteronotidae Apteronotus albifrons (Linnaeus, 1766) aptalb 3 Cyprinodontiformes Rivulidae Rivulus sp. rivsp 3 Beloniformes Belonidae Potamorrhaphis eigenmanni Miranda Ribeiro, 1915 poteig 1 Synbranchiformes Synbranchidae Synbranchus marmoratus Bloch, 1795 synmar 18 Perciformes Cichlidae Aequidens tetramerus (Heckel, 1840) aeqtet 132 Apistogramma cf. resticulosa Kullander, 1980 apires 434 Cichlasoma amazonarum Kullander, 1983 cicama 11 Crenicichla santosi Ploeg, 1991 cresan 66 Satanoperca jurupari (Heckel, 1840) satjur 19 49 CAPÍTULO 2. PROCESSOS ECOLÓGICOS: Mudanças nos traços funcionais e filogenia das assembléias de peixes de riachos Amazônicos associadas ao gradiente de desmatamento Revista alvo: Ecology Resumo. O tipo de solo e uso de solo na microbacia, buffer ripário e tipo de substrato do riacho agem como filtros ambientais na bacia Amazônica do rio Machado. Aplicamos uma abordagem que permite avaliar os filtros ambientais num contexto geográfico, funcional e filogenético, usando como grupo de estudo os peixes de riachos. As amostragens dos peixes, das variáveis ambientais e espacial foram feitas no período seco dos anos 2011 e 2012 em 75 trechos de riachos (80 m). Foram mensuradas 22 variáveis ambientais (locais e da paisagem), a posição geográfica dos 75 riachos, 23 traços funcionais de cinco indivíduos adultos de 61 espécies de peixes, e a filogenia foi obtida de diversas fontes. A maioria das variáveis ambientais tiveram autocorrelação espacial significativa. Detectamos agrupamento nos traços funcionais e na filogenia (somente três traços funcionais apresentarem sinal filogenético). Depois de ligar todas as matrizes encontramos que diferentes filtros ambientais, da paisagem e locais, diferenciam dois cenários. Por um lado, o ultisolo na microbacia, as gramíneas e barranco nu no buffer ripário, estruturam os riachos degradados (RD); por outro lado, oxisolo e floresta na microbacia; litter grosseiro no substrato, e arbustos e árvores no buffer ripário do riacho, estruturam os riachos conservados (RP). Os filtros ambientais nos RD favorecem a algivoria e a posição nectônica na coluna d’água, ao passo que nos RP é favorecida a invertivoria e a posição nectobentônica na coluna d’água. A posição dos RD e RP é coincidente com os diferentes usos do solo, sendo os primeiros concentrados na porção central da bacia, onde o as florestas foram removidas para pastagens, e os RP nos extremos da bacia, onde há maiores proporções de florestas. A maioria das espécies das famílias Loricariidae e Characidae está associada aos RD, por outro lado, os Gymnotiformes, algumas espécies de Siluriformes, as espécies de Characiformes (exceto Characidae) e Perciformes estão associadas aos RP. O severo grau de desmatamento na porção central da bacia do rio Machado age como filtro ambiental e causa empobrecimento da estrutura interna e externa dos riachos. Com isso, traços funcionais e linhagens filogenéticas que apresentam ampla tolerância ao empobrecimento do hábitat são selecionados. Palavras-chave: ictiofauna, riachos amazônicos; desmatamento; agrupamento filogenético, agrupamento dos traços funcionais 50 Introdução A remoção dos ecossistemas naturais por ecossistemas simplificados de agricultura é a principal causa de perda de biodiversidade global (Flynn et al. 2009, Matson et al. 1997) e afeta a biodiversidade terrestre e a aquática. Assim, os distúrbios antropogênicos representam a principal ameaça para a integridade dos ecossistemas fluviais (Allan et al. 1997; Strayer et al. 2003; Towsend et al. 2003, Allan 2004). Nos ecossistemas aquáticos sul-americanos, segundo Barletta et al. (2010), a principal causa de perda de biodiversidade é a perda de hábitat que está associada ao desmatamento, ao barramento de rios, a mineração, a poluição d’água e as práticas inadequadas de agricultura. Na Amazônia brasileira, muitas florestas nativas têm sido derrubadas para uso do solo para agricultura ou pastagem. Esse processo conduz à degradação dos ecossistemas aquáticos, especialmente de pequenos riachos. Como exemplo da gravidade desse cenário de desmatamento, podemos citar o estado de Rondônia, que já teve 52 milhões de hectares de Floresta Amazônica removidos (INPE, 1998), o equivalente a 6,1% do território nacional brasileiro. Em 2001, 51% da área total de Rondônia foi desmatada, em 2004 esse percentual aumentou 57,1% e, em 2006, passou a 65,9% (INPE, 2010). Esse desmatamento é concentrado na porção central da bacia do rio Machado, onde se localizam os solos de maior fertilidade (Ballester et al., 2012) e facilitado pela proximidade com a rodovia BR-364 (Fernandes & Guimarães, 2002). O desmatamento ao redor de cursos d'água tem levado à perda da biodiversidade aquática, principalmente dos peixes, por ser o grupo de dominante dos vertebrados nesses ambientes. O escasso conhecimento sobre as espécies de peixes neotropicais e o funcionamento dos ecossistemas aquáticos neotropicais impede o estabelecimento de prioridades de conservação (Barletta et al. 2010). Quando a floresta ripária é retirada, a estrutura interna dos riachos é simplificada devido à diminuição ou ausência de recursos alóctones (Gregory et al. 1991, Pusey & Arthington 2003, Schlosser 1982, Vannote et al. 1980). Estas mudanças podem afetar a composição, abundancia riqueza de espécies e favorecer ou não as linhagens de peixes que habitam nestes ambientes e/ou seus traços funcionais (e.g. tipos de hábito alimentar, o uso da coluna d’água e morfologia). Os principais processos que estruturam as comunidades são os filtros ambientais (phenotypic attraction) e/ou a exclusão competitiva local de espécies similares (phenotypic repulsion) (Webb 2000, Webb 2002) e, em teoria, ess