Diffusion behavior of water confined in deformed carbon nanotubes

We use molecular dynamics simulations to study the diffusion of water inside deformed carbon nanotubes, with different degrees of eccentricity at 300K. We found a water structural transition between tubular-like to single-file for the (7,7) nanotubes associated with a change from a high to low mobility regimes. The water which in the undeformed (9,9) nanotubes is frozen, becomes liquid for the distortion above a certain threshold. These water diffusion enhancement (suppresion) is related to a reduction (increase) in the number of hydrogen bonds. This suggests that the shape of the nanotube is a particularly important ingredient when considering the dynamical and structural properties of confined water.Comment: 16 pages, 9 figure

MÉTODOS DE INDEXAÇÃO DE INDICADORES NA AVALIAÇÃO DA QUALIDADE DO SOLO EM RELAÇÃO À EROSÃO HÍDRICA

A avaliação da qualidade dos solos agrícolas é importante para definição e adoção de práticas de manejo que garantam a sustentabilidade socioeconômica e ambiental. Os métodos de indexação dos indicadores de qualidade denominados Índice de Qualidade Integrado (IQI) e Índice de Qualidade Nemoro (IQN) foram utilizados neste estudo para avaliar a qualidade de solo em áreas experimentais de plantio de eucalipto. A seleção dos indicadores foi feita a partir de nove indicadores de qualidade do solo: diâmetro médio geométrico, permeabilidade à água, matéria orgânica, macro e microporosidade, volume total de poros, densidade do solo, resistência à penetração e índice de floculação, que estão relacionados à erosão hídrica. Os tratamentos constituíram de eucalipto plantado em nível, com e sem a manutenção dos resíduos, em desnível e solo descoberto, em dois biomas distintos, cujas vegetações nativas são Cerrado e Floresta. Os índices de qualidade do solo (IQS) apresentaram alta correlação com a erosão hídrica. Entre os sistemas manejados, o Eucalipto com manutenção do resíduo evidenciou valores mais elevados em ambos os índices, ressaltando-se a importância da cobertura vegetal e manutenção da matéria orgânica para conservação do solo e da água em sistemas florestais. Os IQS demonstraram alto coeficiente de correlação inversa com as perdas de solo e água. Em locais com as maiores taxas de erosão hídrica manifestaram também os menores valores de IQI e IQN. Assim, os índices testados permitiram avaliar com eficácia os efeitos dos manejos adotados sobre a qualidade do solo em relação à erosão hídrica

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