34 research outputs found

    Pervasive gaps in Amazonian ecological research

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    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‚Äď7 vast areas of the tropics remain understudied.8‚Äď11 In the American tropics, Amazonia stands out as the world‚Äôs 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‚Äď15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon‚Äôs 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‚Äôs vulnerability to environmental change. 15%‚Äď18% 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

    Neotropical freshwater fisheries : A dataset of occurrence and abundance of freshwater fishes in the Neotropics

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    The Neotropical region hosts 4225 freshwater fish species, ranking first among the world's most diverse regions for freshwater fishes. Our NEOTROPICAL FRESHWATER FISHES data set is the first to produce a large-scale Neotropical freshwater fish inventory, covering the entire Neotropical region from Mexico and the Caribbean in the north to the southern limits in Argentina, Paraguay, Chile, and Uruguay. We compiled 185,787 distribution records, with unique georeferenced coordinates, for the 4225 species, represented by occurrence and abundance data. The number of species for the most numerous orders are as follows: Characiformes (1289), Siluriformes (1384), Cichliformes (354), Cyprinodontiformes (245), and Gymnotiformes (135). The most recorded species was the characid Astyanax fasciatus (4696 records). We registered 116,802 distribution records for native species, compared to 1802 distribution records for nonnative species. The main aim of the NEOTROPICAL FRESHWATER FISHES data set was to make these occurrence and abundance data accessible for international researchers to develop ecological and macroecological studies, from local to regional scales, with focal fish species, families, or orders. We anticipate that the NEOTROPICAL FRESHWATER FISHES data set will be valuable for studies on a wide range of ecological processes, such as trophic cascades, fishery pressure, the effects of habitat loss and fragmentation, and the impacts of species invasion and climate change. There are no copyright restrictions on the data, and please cite this data paper when using the data in publications

    Pervasive gaps in Amazonian ecological research

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    Pervasive gaps in Amazonian ecological research

    Get PDF
    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%‚Äď18% 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

    Additional file 7 of Management of early-stage triple-negative breast cancer: recommendations of a panel of experts from the Brazilian Society of Mastology

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    Additional file 7: Table S7.1. Comparison between the panelists and the SBM affiliated breast surgeons regarding the questions related to diagnosis. Table S7.2. Comparison between the panelists and the SBM affiliated breast surgeons regarding the questions related to surgery. Table S7.3. Comparison between the panelists and the SBM affiliated breast surgeons regarding the questions related to radiotherapy. Table S7.4. Comparison between the panelists and the SBM affiliated breast surgeons regarding the questions related to systemic treatment

    Correlação da qualidade da água com uso do solo e declividade no Arroio Doze Passos, Ouro, SC

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    Water is the main factor for the development and growth of communities, especially the rural ones. The objectiveof this study was to evaluate the relation of soil use and slope steepness with the water quality of the Arroio Doze Passos. Thisstudy was conducted in the watershed Arroio Doze Passos in the Midwest region of Santa Catarina State, Southern Brazil, fromNovember 2004 to October 2009. This watershed has an area of 17.78 km¬≤, where intensive agriculture is developed (mainlycorn and wheat) and livestock (mainly pigs, dairy cattle and poultry). It was observed that the stream water has low qualitydue the high values of total P, ortho P, turbidity, total coliform bacteria, and fecal coliforms. The main factor of poor waterquality is the presence of organic-origin manure, which is caused by land use out of its fitness ability, coupled with inadequatemanagement of waste, and lack of environmental planning. However, water quality, in general, improved from the stream‚Äôsspring to its mouth.A √°gua √© o principal fator para o desenvolvimento e crescimento das comunidades, especialmente das rurais. Este¬†trabalho foi desenvolvido na microbacia Arroio Doze Passos, na regi√£o Meio-Oeste do Estado de Santa Catarina, no per√≠odo de¬†novembro de 2004 a outubro de 2009. O objetvo foi avaliar a rela√ß√£o do uso do solo e a declividade com a qualidade da √°guadesse arroio. Essa microbacia tem √°rea de 17,78km¬≤, onde √© desenvolvida intensa atvidade agr√≠cola (principalmente lavouras¬†de milho e trigo) e de cria√ß√£o de animais (principalmente su√≠nos, gado leiteiro e aves). Observou-se que a √°gua do arroio¬†encontra-se com baixa qualidade devido aos altos teores de P total, P orto, turbidez e coliformes totais e fecais. A principalcausa da baixa qualidade da √°gua √© a presen√ßa de dejetos de origem org√Ęnica, os quais s√£o causados pela utliza√ß√£o do solo¬†fora de sua capacidade de aptd√£o, pelo manejo inadequado dos dejetos e pela falta de planejamento paisag√≠stco-ambiental.¬†Entretanto, a qualidade da √°gua, de forma geral, melhora da nascente para a foz

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

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    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data
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