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

Consenso brasileiro de monitorização e suporte hemodinâmico - parte III: métodos alternativos de monitorização do débito cardíaco e da volemia

JUSTIFICATIVA E OBJETIVOS: A interpretação do débito cardíaco e da pré-carga como números absolutos não traz grandes informações sobre a hemodinâmica do paciente crítico. Em contrapartida, a monitorização da resposta do débito cardíaco à expansão volêmica ou suporte inotrópico é uma ferramenta muito útil na unidade de terapia intensiva, quando o paciente apresenta algum sinal de má perfusão tecidual. Apesar do CAP ser considerado como " padrão-ouro" na avaliação destes parâmetros, foram desenvolvidas tecnologias alternativas bastante confiáveis para a sua monitorização. MÉTODO: O processo de desenvolvimento de recomendações utilizou o método Delphi modificado para criar e quantificar o consenso entre os participantes. A AMIB determinou um coordenador para o consenso, o qual escolheu seis especialistas para comporem o comitê consultivo. Outros 18 peritos de diferentes regiões do país foram selecionados para completar o painel de 25 especialistas, médicos e enfermeiros. Um levantamento bibliográfico na MEDLINE de artigos na língua inglesa foi realizado no período de 1966 a 2004. RESULTADOS: Foram apresentadas recomendações referentes à análise da variação da pressão arterial durante ventilação mecânica, débito cardíaco contínuo por contorno de pulso arterial, débito cardíaco por diluição do lítio, Doppler transesofágico, bioimpedância transtorácica, ecocardiografia e reinalação parcial de gás carbônico. CONCLUSÕES: As novas e menos invasivas técnicas para medida do débito cardíaco, pré-carga e fluidoresponsividade apresentam adequada precisão e podem ser uma alternativa ao uso do CAP em pacientes graves