Atividade de extensão universitária com adolescentes na pandemia de COVID-19: Relato de experiência

Durante a pandemia, as restrições relativas ao distanciamento social representaram as principais medidas para reduzir a propagação do COVID-19, com potenciais implicações sobre a rotina dos adolescentes. Objetivo: relatar a experiência do processo de adaptação de um projeto extensionista e as vivências no desenvolvimento das atividades remotas realizadas com adolescentes durante a pandemia. Métodos: Projeto de extensão envolvendo docentes e discentes de Farmácia, Nutrição e Medicina da Universidade Federal do Paraná. Através de reuniões virtuais, as etapas de planejamento, diagnóstico, intervenção e avaliação foram adequadas, adotando o uso de ferramentas online para elaboração de questionário para avaliação dos comportamentos relacionados à saúde e aplicação em adolescentes de uma escola estadual em Curitiba-PR, além de ações educativas com os participantes. Resultados: participaram do questionário 59 adolescentes, de ambos os sexos, com média de idade de 15,38 anos. Foi possível detectar o aumento do comportamento sedentário, e frequência expressiva do consumo de alimentos ultraprocessados como lanches. Nos momentos síncronos online, onde houve uma maior participação comparado à etapa anterior (n=77), resultaram em interação dialógica entre os alunos da UFPR e os adolescentes. A maioria dos adolescentes avaliou positivamente as atividades realizadas pelo projeto, e demonstrou intenção de realizar modificações nos hábitos alimentares e na redução do tempo de tela. Conclusão: Apesar das adversidades diante da suspensão das atividades presenciais, a equipe do projeto conseguiu desenvolver suas ações por meio do exercício da capacidade criativa da equipe e reinvenção de métodos, servindo de aporte de vivência para a formação humana e profissional

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

Núcleos de Ensino da Unesp: artigos 2010: volume 4: as disciplinas escolares, os temas transversais e o processo de educação

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP