EDUCAFISIO - Projeto de extensão para promoção de saúde na escola Dom Pedro II: relato de experiência

O presente trabalho objetivou promover a saúde, conscientizando e proporcionando a reflexão crítica e a mudança de atitudes dos alunos da escola Dom Pedro II e da comunidade escolar. Participaram do projeto 40 estudantes, de 12 a 13 anos, do 7º e 8º ano, entre os períodos de maio a dezembro de 2022. Foram realizados 11 encontros quinzenais, nos quais trabalharam-se temas relacionados aos eixos alimentação saudável, vida ativa e bem-estar emocional.  Cada encontro durava cerca de 50 minutos, sendo 45 minutos destinados à exposição teórico-prática e 5 minutos para a avaliação de processo, que englobava a satisfação e a contribuição do conhecimento. Além disso, foram realizadas avaliações de bloco, ao final de cada eixo aprendido, as quais avaliaram conhecimento, reflexão e comportamento. Posto isso, observou-se que houve um aumento na satisfação e contribuição de conhecimento para os alunos, quando comparado a primeira e última atividade realizada. Ademais, nas avaliações de bloco, percebeu-se a obtenção do aprendizado, a reflexão crítica e a mudança de atitudes pelos discentes, por meio de seus relatos. Por fim, conclui-se que a promoção da saúde em instituições de ensino é uma boa iniciativa, capaz de gerar resultados impactantes na vida dos adolescentes e da comunidade ao seu redor. Palavras-Chave: Educação em Saúde. Alimentação Saudável. Vida Ativa. Bem-estar Emocional. Ambiente Escolar

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