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, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications 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, 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

Silicose em ex-mineiros de extração de cobre Silicosis among former copper mine workers

Existe escassez de estudos brasileiros analisando o efeito da exposição contínua à sílica em ex-trabalhadores de minas de cobre. Os achados radiográficos produzidos pela silicose têm recebido atenção médica especial. O objetivo deste estudo foi caracterizar clinica e radiologicamente a silicose em ex-mineiros de extração de cobre. Foi feito um estudo transversal com 100 ex-mineiros de extração de cobre. Os itens foram coletados através de entrevista pessoal, dados clínicos ocupacionais e foram realizados exames radiológicos. Na entrevista foi verificada a idade, o sexo e o tempo de trabalho na extração de cobre. Os pacientes que já realizaram exame radiológico de tórax trouxeram estes para comparação. Os mineiros assinaram um termo de consentimento para realização dos exames radiológicos o qual foi aplicado pelo radiologista que os interpretou. Entre os 100 ex-mineiros, 35% são portadores de silicose, 11% apresentaram alterações pulmonares que podem ter outras causas, como tuberculose, enfisema e doença broncopulmonar obstrutiva crônica, e 54% não apresentaram nenhuma alteração pulmonar. A alta freqüência de silicose encontrada reforça a recomendação de suspender a exposição à sílica tão logo se tenha uma radiografia sugestiva da doença.<br>There is a dearth of Brazilian studies analyzing the effect of ongoing exposure to silica among former copper mine workers, as radiographic readings for silicosis have received widespread medical attention. The scope of this study is to investigate the clinical and radiological manifestations of silicosis among former copper mine workers. A sample of 100 former copper miners had their clinical and occupational histories recorded and underwent chest radiography in a cross-sectional study that included personal interviews in which their age, sex and time worked in copper extraction were recorded. Patients with recent chest X-Rays brought them with them, or they signed a term of consent and X-Rays were taken and analyzed by the radiologist using the Student t Test and Pearson test. Among the 100 miners, 35% had silicosis, 11% had conditions other than silicosis, such as tuberculosis, emphysema, chronic pulmonary obstructive disease, and 54% had no pulmonary lesions. The high incidence of silicosis reinforces the recommendation that exposure should be halted as soon as an X-ray detects the condition

A república e o sonho The republic and its dream

O desencanto com a República brasileira tem sido tema de reflexões desde os seus momentos iniciais. Buscando os conteúdos concretos dos sonhos republicanos na década de 1880 e na Primeira República vamos achar uma importante defasagem entre eles não exatamente em função do marco cronológico, mas do grupo social que, respectivamente, os acalentou.<br>The disillusion with the Brazilian Republic since its first days has been a topic of academician reflexions. Examinating the concrete contents of the 1880`s and the First Republic republican dreams we will find a substantive difference between them. To be exact, this difference must not be related to the chronological demarcation but to the social group that embraced each of them