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

Analisando as pesquisas em educação especial no Brasil Analysing research in special education in Brazil

Nosso objetivo foi examinar a articulação lógica entre o problema e a proposição teórico-metodológica das produções na área da Educação Especial, focando os seus pressupostos epistemológicos. Nos fundamentamos nos pressupostos das tendências empírico-analítica, fenomenológica-hermenêutica, crítico-dialética e do paradigma da complexidade. O procedimento adotado foi interpretar todas as dissertações/teses produzidas nos Programas de Pós-Graduação em Educação e Educação Especial do Brasil, que versam sobre Educação Especial, produzidas nos anos de 2001, 2002 e 2003, disponíveis no banco de teses da CAPES. Encontramos as tendências empírica, fenomenológica e dialética. Os equívocos encontrados foram a não inserção da pesquisa entre as produções na área; ausência de criticidade; não posicionamento numa determinada concepção de educação; construção teórica fundamentada em concepções diferentes; falta de coerência nos pressupostos teórico-metodológicos; não explicitação metodológica; não descrição dos procedimentos éticos; e má elaboração dos resumos. Concluímos pela necessidade da melhoria das dissertações/teses para que possamos avançar na produção de conhecimento na área da Educação Especial.<br>Our objective was to analyze the logical articulation between the problem and the theoretical-methodological proposal of studies in the field of Special Education, focusing on the epistemological issues. We based our study on the empiric-analytical tendencies, phenomenology-hermeneutic, critical-dialectical and the complexity paradigm. The procedure that was adopted was interpreting all dissertations/thesis produced in Post-Graduate programs in Education and Special Education in Brazil, which focus on Special Education, produced in 2001, 2002 and 2003, available online at CAPES' thesis database. We found empirical, phenomenological and dialectic tendencies. The errors encountered included the failure to include the research among the productions in the field; lack of critical approach; lack of making explicit what educational conception the study was based on; theoretical construction based on different conceptions; lack of coherence in the theoretical-methodological proposals; lack of methodological specification; absence of ethical procedural descriptions; and poorly written abstracts. We came to the conclusion that improvements in theses /dissertations are necessary so as to continually move forward in the production of knowledge in the field of Special Education