Mapeamento de potenciais de impactos ambientais da queima de cana-de-açúcar no Brasil.

O artigo apresenta a distribuição espacial de alguns potenciais de impactos das emissões de monóxido de carbono (CO), metano (CH4), óxidos de nitrogênio (NOx) e óxido nitroso (N2O) causadas pela queimada de cana-de-açúcar no Brasil utilizando o SIG ArcGIS. As categorias de potenciais de impactos ambientais avaliados são: aquecimento global, formação de ozônio troposférico, acidificação e toxicidade humana

Ciclagem interna de nitrogênio em solo cultivado com capim Tifton-85 e irrigado com esgoto tratado.

O objetivo desta pesquisa foi avaliar o efeito da irrigação com água, efluente secundário de nitrogenada na produção vegetal, na quantidade de liteira depositada e nos conteúdos de matéria orgânica particulada em uma pastagem de capim-Bermuda tifton 85. O delineamento experimental foi composto de quatro blocos ao acaso e seis tratamentos: SI (controle, sem fertilização e sem irrigação); W100, irrigação com água e 100% da dose de fertilizante nitrogenado recomendado; E0, E33, E66 e E100, irrigado com esgoto tratado e adição de 0, 33; 66 e 100% da dose recomendada, respectivamente. Amostras de efluente/água, solo, produção vegetal e liteira foram coletadas no período de abril a outubro de 2007. A maior oferta de N nos tratamentos E66, E100 e A100, através da fertilização, irrigação e ciclagem interna pela Bermuda Tifton 85 em período pós chuvas (abril?junho de 2007). No sistema avaliado, a deposição de liteira foi mais diferentes tratamentos. Maiores conteúdos médios de MOP foram observados no solo dos tratamentos irrigados e fertilizados.1 CD-ROM

Climate change-related risks and adaptation potential in Central and South America during the 21st century

Climate-related risks in Central and South America have received increased attention and concern in science and policy, but an up-to-date comprehensive review and synthesis of risks and adaptation potential is currently missing. For this paper we evaluated over 200 peer-reviewed articles and grey literature documents published since 2012. We found that climate change in Central and South America during the 21st century may increase the risk to severe levels for the following topical risk clusters: (a) Food insecurity; (b) Floods and landslides; (c) Water scarcity; (d) Epidemics of vector-borne diseases; (e) Amazon Forest biome shift; (f). Coral bleaching; (g) Coastal risks of sea level rise, storm surges and erosion; (h) Systemic failure due to cascading impacts of hazards and epidemics. Our synthesis also identified feasible adaptation measures for each risk. The impacts of the risks will be heterogeneous throughout the region, with rural communities, Indigenous peoples, Afro-Latin Americans, women, disabled people, and migrants identified as being the most severely affected. We refer to a number of adaptation options for each risk. However, unabated climate change together with low adaptive capacity will strictly limit adaptation options. Immediate strengthening of policies for building adaptive capacity and increase of research on the risk-adaptation nexus in Central and South America are paramount. Our findings might contribute to guide the adjustment and emphasis of adaptation policies and climate risk management strategies from local to national level

Perfil tecnológico e socioeconômico das principais atividades agrossilvipastoris do Nordeste Paulista.

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Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian Semiarid region, for use in Dynamic Global Vegetation Models.

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caating