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

A robótica educacional como ferramenta multidisciplinar: um estudo de caso para a formação e inclusão de pessoas com deficiência

DOI: http://dx.doi.org/10.5902/1984686X15932Esse trabalho apresenta os resultados do projeto de extensão com interface a pesquisa, “A Robótica e a Inclusão Social: Tecnologia e Acessibilidade Aplicadas ao Ensino”, no qual os objetivos primordiais foram de estabelecer uma dinâmica de interação com a comunidade externa da UFSJ oferecendo aulas de introdução da robótica para alunos do ensino fundamental e médio de escolas públicas de São João del-Rei com baixo desempenho no ENEM. Incluindo também nesse trabalho alunos com deficiência dessas instituições regulares de ensino. No total, participaram desse trabalho oito escolas, sendo dentre os alunos, quatro surdos, um esquizofrênico, um com síndrome de aspergem e um com déficit de inteligência. A hipótese colocada em cheque nesse trabalho é se em um grupo heterogêneo, irão se sobressair as qualidades individuais de cada elemento, para o bem do grupo, em detrimento de seus limitantes físicos e/ou cognitivos. Foram desenvolvidas atividades com o intuito de proporcionar maior interação e o trabalho em equipe entre os alunos durante as aulas. Ao final desse trabalho foi proposta a avaliação do projeto, sendo essa baseada nas discussões referentes às observações realizadas pelos instrutores do curso de robótica (graduandos em Engenharia Elétrica), alunos da Psicologia que acompanharam as aulas e professores orientadores do projeto. Com relação à hipótese que foi colocada a principio no projeto, após a análise sistemática das discussões e questionários pelos estudantes e professores da Engenharia Elétrica e Psicologia, concluiu-se que o trabalho em equipe dos alunos superou suas limitações físicas e cognitivas.   </p

Cladia aggregata (lichen) from Brazilian northeast: chemical characterization and antimicrobial activity

The chemical composition and antimicrobial activity of the Cladia aggregata (Sw.) Nyl. were evaluated. Barbatic acid, depside obtained from C. aggregata, was spectroscopically analyzed and tested, as well as organic extracts. The extracts and purified substance were tested against four Staphylococcus aureus multi-resistant strains. The structure of barbatic acid was confirmed through NMR (¹H; 13C) and elemental ® analysis. Biochromatographic assays showed action of this compound, along with other substances contained in organic extracts, suggesting a synergic action, MIC assays placed barbatic acid in the same level of inhibition to other studied lichen substances.<br>A composição química e a atividade antimicrobiana da Cladia aggregata (Sw.) Nyl. foram avaliadas. O ácido barbático, um depsideo obtido da C. aggregata, foi espectroscopicamente analisado e testado, bem como o extrato orgânico. o extrato e a substância purificada foram testadas contra 4 linhagens de Staphylococcus aureus multi resistentes. A estrutura do ácido barbático foi confirmada através de ensaios de CCD, CLAE, IV, RMN (¹H;13C), UV e analise elementar (r). O biocromatograma mostrou a ação deste composto junto com outras substâncias contidas no extrato orgânico, sugerindo a ação sinérgica, a CMI do ácido barbático mostrou o mesmo nível de inibição de outras substâncias liquênicas