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, 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

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 produção do conhecimento científico e as políticas de saúde pública: reflexões a partir da ocorrência da filariose na cidade do Recife, Pernambuco, Brasil Scientific knowledge and public health policies: reflections on the occurrence of filariasis in Recife, Pernambuco, Brazil

O artigo discute a relação entre a produção científica sobre a ocorrência da filariose bancroftiana no Brasil e o processo de formulação e implementação da política de saúde voltada ao seu controle. Para tanto, realiza uma revisão da produção do conhecimento e das políticas específicas, no período compreendido desde a criação do Programa de Combate à Filariose, em meados do século passado, até a criação do SUS, no marco da descentralização do controle das endemias. Centrando suas observações empíricas na ambiência da cidade do Recife, espaço urbano no qual ainda prevalece a filariose, ressalta os processos institucionais e destaca o papel dos distintos atores neles envolvidos. Partindo da hipótese de que se até à primeira metade do século vinte faltavam o conhecimento científico e o desenvolvimento tecnológico para o controle do problema, a seguir, quando esses avanços são disponibilizados, outros requerimentos, agora do campo da política, irão se impor, atuando como determinantes da persistência da endemia na cidade.<br>This article discusses the relationship between the production of scientific knowledge on filariasis in Brazil and health policy-making and implementation related to control of the disease. The study presents a review of scientific output on filariasis from the creation of the Program to Combat Filariasis in the mid-20th century until the creation of the Unified National Health System (SUS) within the framework of decentralized control of endemic diseases in the country. The focus on empirical observations in Recife, a city where filariasis is present, highlights the relevant institutional processes and the role of various players. The hypothesis is that in the first half of the 20th century there was a lack of scientific knowledge and technological development to control the problem, but that after these advances were obtained, new requirements of a political nature came into play and acted as determinants for persistence of the endemic in the city