18 research outputs found

    UV-Vis spectroscopy and chemometrics applied to residues monitoring in sewage

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    Edible oil residues (EOR) and detergents/soaps (NBDS) are a considerable problem in the water systems. The layer due to presence of these residuals covers the water surface damaging the aquatic life by hampering the sun light to touch its bottom, diminishing algae quantity and, consequently, microorganisms and fishes, which depend on it to survive, changing the local biosphere. Knowing this potential effect, the objective was monitor edible oil residues and detergents/soaps presence in two sewage treatment station located in Brazil. To this, samples were collected from 3 different sewage treatment stages and evaluated by ultraviolet-visible spectroscopy. Chemometrics was applied to recover spectra profiles and relative concentration of residuals. The results indicate that the proposed methodology is feasible to monitoring these residues in sewage

    Pervasive gaps in Amazonian ecological research

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    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

    Get PDF

    Pervasive gaps in Amazonian ecological research

    Get PDF
    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

    Giants of the Amazon:How does environmental variation drive the diversity patterns of large trees?

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    Resumos em andamento - Educação

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    Resumos em andamento - Educaçã

    Resumos em andamento - Educação

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    Resumos em andamento - Educaçã

    Resumos concluídos - Saúde Coletiva

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    Resumos concluídos - Saúde Coletiv

    Núcleos de Ensino da Unesp: artigos 2012: volume 2: metodologias de ensino e a apropriação de conhecimento pelos alunos

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