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

Acidúria L2-hidroxiglutárica: circulação do gene em cães da raça Staffordshire Bull Terrier no Brasil em 2008-2015

RESUMO: O objetivo do trabalho foi identificar a presença no Brasil do gene mutante L2HGDH em cães da raça Staffordshire Bull Terrier (SBT). Para tanto foi feito o teste genético em 76 cães provenientes de diferentes regiões do Brasil, no período de 2008 a 2015, sendo encontrados 55 animais (72,37%) livres do gene mutante L2-HGDH ou homozigotos dominantes, e 21(27,63%) portadores do gene mutante ou heterozigotos. Não foi encontrado nenhum animal homozigoto recessivo (afetado), porém pode-se observar que o gene circula no Brasil e que cães afetados podem aparecer

Controle das emissões de chumbo particulado no entorno de uma reformadora de baterias da cidade do Rio de Janeiro usando ar como indicador

No período entre abril a julho de 1999, foram realizadas determinações dos níveis de chumbo no ar ambiente nas proximidades de uma reformadora de baterias (RB) situada em Olaria (Rio de Janeiro, Brasil). A maioria das amostras coletadas a uma distância de até 25m da RB excederam o limite de 1,5mg.Pb.m-3 estabelecido pela Environmental Protect Agency (EPA), Estados Unidos. Esses resultados já foram publicados previamente (Quiterio et al., 2001). Neste trabalho, foram propostas a instalação de um sistema de exaustão Venture e algumas mudanças nos procedimentos operacionais. Após as modificações na RB, foi realizada uma nova campanha de monitoramento (agosto e setembro de 2000). As coletas foram realizadas nos três pontos considerados mais críticos, segundo as determinações anteriores. As concentrações medidas estiveram no intervalo 0,8-17,6mg.Pb.m-3, mostrando que as emissões de chumbo na atmosfera tiveram uma diminuição adequada. Contudo, a concentração na saída da chaminé é ainda maior que os limites estabelecidos pela EPA e, certamente, serão necessárias outras melhorias nas instalações e procedimentos