Endemicity Analysis of the Ichtyofauna of the Rio Doce Basin, Southeastern Brazil

The Rio Doce is a very important freshwater system in Brazil running through the Atlantic Forest, however available information about its biodiversity is scarce. In 2015, the Rio Doce basin was damaged by a burst of Fundão tailing dam in Mariana (Minas Gerais) causing an extraordinary environmental damage, with consequences still incompletely known. In the present paper we analyzed 6042 latitude/longitude records of 208 fish species from the Rio Doce deposited in collections prior to November 2015, in order to identify areas of endemism in the river before the burst. Several areas of endemism were identified along the basin, most of them describing small and novel patterns. Our analyses helped to identify areas of major diversity along the basin as well as information gaps concerning fish sampling. We hope this contribution will help obtaining quantitative measures on the impact caused by the Fundão dam catastrophe on fish biodiversity and will be useful to orient general actions towards the restoration of the basin.Fil: Sarmento Soares, Luisa M.. Universidade Estadual de Feira de Santana; Brasil. Universidade Federal do Espírito Santo; Brasil. Instituto Nossos Riachos; BrasilFil: Martins Pinheiro, Ronaldo F.. Instituto Nossos Riachos; BrasilFil: Casagranda, Maria Dolores. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; Argentin

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

A new species of Characidium Reinhardt (Ostariophysi: Characiformes: Crenuchidae) from coastal rivers in the extreme south of Bahia, Brazil

Zanata, Angela M., Sarmento-Soares, Luisa M., Martins-Pinheiro, Ronaldo F. (2015): A new species of Characidium Reinhardt (Ostariophysi: Characiformes: Crenuchidae) from coastal rivers in the extreme south of Bahia, Brazil. Zootaxa 4040 (3): 371-383, DOI: 10.11646/zootaxa.4040.3.

Redescription of Moenkhausia doceana(Steindachner, 1877) (Ostariophysi: Characiformes): a characid from the Northeastern Mata Atlântica ecoregion, Brazil

Moenkhausia doceana is redescribed from the Northeastern Mata Atlântica ecoregion drainages in Espírito Santo, Minas Gerais, and Bahia states. The species is distinguished from its congeners by a long anal fin, with 29-34 (mode 32) branched rays; 4-7 (mode 5) maxillary teeth; and 7-8 (mode 7) scale rows above lateral line at dorsal-fin origin. Phylogenetic hypothesis about its relationships among the Characidae is also presented and commented

Ituglanis cahyensis, a new catfish from Bahia, Brazil (Siluriformes: Trichomycteridae)

Submitted by Sandra Infurna ([email protected]) on 2020-02-04T13:07:51Z No. of bitstreams: 1 RonaldoFM_Pinheiro_etal_IOC_2006.pdf: 466318 bytes, checksum: 4e8e85e817fd68ccbbfca8eb0f9727c1 (MD5)Approved for entry into archive by Sandra Infurna ([email protected]) on 2020-02-04T13:14:26Z (GMT) No. of bitstreams: 1 RonaldoFM_Pinheiro_etal_IOC_2006.pdf: 466318 bytes, checksum: 4e8e85e817fd68ccbbfca8eb0f9727c1 (MD5)Made available in DSpace on 2020-02-04T13:14:26Z (GMT). No. of bitstreams: 1 RonaldoFM_Pinheiro_etal_IOC_2006.pdf: 466318 bytes, checksum: 4e8e85e817fd68ccbbfca8eb0f9727c1 (MD5) Previous issue date: 2006Museu Nacional. Departamento de Vertebrados. Setor de Ictiologia. Rio de Janeiro, RJ, Brasil.Projeto BIOBAHIA. Prado, BA, Brasil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Referência Nacional em Simulídeos e Oncocercose. Coleção de Simulídeos. Convênio Faperj/Fiocruz. Rio de Janeiro, RJ, Brasil.Museu Nacional. Departamento de Vertebrados. Setor de Ictiologia. Rio de Janeiro, RJ, Brasil.É descrito um novo trichomycterídeo do gênero Ituglanis, capturado no rio Palmares, um tributário do rio Cahy, na costa sudeste do estado da Bahia, Brasil. Ituglanis cahyensis distingue-se das demais espécies congêneres por uma combinação de caracteres, como o canal laterosensorial supraorbital com os poros s3 e s6 presentes, um pequeno número de raios ramificados nas nadadeiras peitorais, e um pequeno número de costelas. Distingue-se ainda quanto a proporções morfométricas, como os barbilhões nasal, maxilar e rictal alongados, e o pequeno diâmetro ocular.A new trichomycterid catfish of the genus Ituglanis is described from the rio Palmares, a tributary of the rio Cahy in southeast Bahia State, Brazil. Ituglanis cahyensis is distinguished from all other congeners through a combination of characters, as the supraorbital laterosensory canal branch with pores s3 and s6 present, the low count of branched pectoral fin rays, and low number of paired ribs. It is further distinguished in proportional measurements, such as elongate nasal, maxillary, and rictal barbels, and small eye diameter