Micropolíticas: devir, cooperação dissonante e experiência pura

This article traces the definition of the concept of micropolitics in a singular perspective of Critical Semiotics. It seeks supplements in the theories of Deleuze and Guattari to think of it as an underlying force to alliances that produce zones of becoming. Regarding the propositions of Rolnik and Guattari, it proposes the understanding of micropolitics as a process of dissonant cooperation among subjects positioned in distinct subjectivities, a process that makes these existential models deterritorialize themselves. Concerning the phenomenal characteristics of this process, it uses the thought of James and Lapoujade to understand that micropolitics is produced and intensified based on what these thinkers called pure experience.O artigo traça um percurso de definição do conceito de micropolítica em uma visada singular da Semiótica Crítica. Busca suplementos nas teorizações de Deleuze e Guattari para pensá-la enquanto força subjacente a alianças que produzem zonas de devir. Em relação às proposições de Rolnik e Guattari, projeta a compreensão da micropolítica enquanto processo de cooperação dissonante entre sujeitos posicionados em subjetividades distintas, processo que faz esses modelos existenciais desterritorializarem-se. Já considerando as características fenomênicas desse processo, recorre ao pensamento de James e de Lapoujade para compreender que a micropolítica é produzida e intensificada a partir do que esses filósofos chamaram de experiência pura

Processos de escrita e autoria sobre a ação docente enquanto prática formativa

Este artigo apresenta os processos de escrita e autoria enquanto prática formativa. O objetivo é analisar os significados e sentidos atribuídos pelos professores ao trabalho de escrita e autoria sobre sua ação docente. Para isso, analisa a correspondência eletrônica que foi trocada entre professores da Educação Básica e professores-pesquisadores da Universidade envolvidos em um projeto de pesquisa-ação colaborativa. A análise evidencia a escrita como ato solitário e fruto de um trabalho reflexivo caracterizado como árduo, semelhante à gestação e ao trabalho de parto. Embora descrito como penoso, o processo de escrita e autoria sobre a atividade docente é entendido como estratégia eficaz para o processo de formação continuada e como potência para a aprendizagem da docência

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