Classificação climática de Thornthwaite e sua aplicabilidade agroclimatológica nos diferentes regimes de precipitação em Pernambuco

Knowing the annual climatic conditions is of great importance for appropriate planning in agriculture. However, the systems of climatic classification are not widely used in agricultural studies because of the wide range of scales in which they are used. A series with data from 20 years of observations from 45 climatological stations in all over the state of Pernambuco was used. The probability density function of the incomplete gamma distribution was used to evaluate the occurrence of dry, regular and rainy years. The monthly climatic water balance was estimated using the Thornthwaite and Mather method (1955), and based on those findings, the climatic classifications were performed using the Thornthwaite (1948) and Thornthwaite and Mather (1955) for each site. The method of Kriging interpolation was used for the spatialization of the results. The study classifications were very sensitive to the local reliefs, to the amount of rainfall, and to the temperatures of the regions resulting in a wide number of climatic types. The climatic classification system of Thornthwaite and Mather (1955) allowed efficient classification of climates and a clearer summary of the information provided. In so doing, it demonstrated its capability to determine agro climatic zones.

Imagens aéreas multiespectrais na identificação de zonas de manejo em áreas de algodão para aplicação localizada de insumos

Crop yield is influenced by several factors with variability in time and space that are associated with the variations in the plant vigor. This variability allows the identification of management zones and site-specific applications to manage different regions of the field. The purpose of this study was the use of multispectral image for management zones identification and implications of site-specific application in commercial cotton areas. Multispectral airborne images from three years were used to classify a field into three vegetation classes via the Normalized Difference Vegetation Index (NDVI). The NDVI classes were used to verify the potential differences between plant physical measurements and identify management zones. The cotton plant measurements sampled in 8 repetitions of 10 plants at each NDVI class were Stand Count, Plant Height, Total Nodes and Total Bolls. Statistical analysis was performed with treatments arranged in split plot design with Tukey’s Test at 5% of probability. The images were classified into five NDVI classes to evaluate the relationship between cotton plant measurement results and sampling location across the field. The results have demonstrated the possibility of using multispectral image for management zones identification in cotton areas. The image classification into three NDVI classes showed three different zones in the field with similar characteristics for the studied years. Statistical differences were shown for plant height, total nodes and total bolls between low and high NDVI classes for all years. High NDVI classes contained plants with greater height, total nodes and total bolls compared to low NDVI classes. There was no difference in Stand Count between low and high NDVI classes for the three studied years. The final plant stand was the same between all NDVI classes for 2001 and 2003 as it was expected due to the conventional seeding application with the same rate of seeds for the entire field.

Prevendo mudanças climáticas: resposta da meiofauna a mudanças na distribuição espacial de espécies-chave

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Zonas Estratégicas e Estruturais para os Trânsitos Ilícitos (ZEETI): desafios à zona de paz na América do Sul

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Gerenciamento de contingências climáticas: do monitoramento de riscos aos benefícios oriundos pela adoção de práticas de baixo carbono

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A atuação internacional do Brasil para as mudanças climáticas: as COP de 2009 a 2015

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise das projeções de mudanças climáticas do quinto relatório do IPCC dentro das áreas protegidas brasileiras

Entre os impactos das mudanças climáticas previstas para este século estão as possíveis alterações no padrão de distribuição de espécies, comunidades, e até mesmo biomas. Tais impactos ocorrerão, sem distinção, tanto dentro como fora de áreas protegidas. No Brasil, as unidades de conservação (UCs) estão organizadas segundo o Sistema Nacional de Unidades de Conservação (SNUC). Porém, a lei federal 9985/2000 que rege o SNUC não contempla a ocorrência de mudanças climáticas e as possíveis ações de manejo para contornar o problema dentro delas. Sendo assim, esta pesquisa pretende, de forma pioneira, iniciar a investigação das mudanças climáticas a ocorrerem dentro das áreas protegidas (AP) em âmbito nacional. Para isso, fez-se uma análise geográfica das mudanças de temperatura e precipitação oriundas de vários modelos climáticos utilizados pelo IPCC no seu quinto relatório dentro das áreas compreendidas dentro das UCs cadastradas no SNUC e Terras Indígenas. Tal análise pautou-se pelos diversos tipos de áreas protegidas e também pelas macrorregiões geográficas do Brasil. Nossos resultados mostram que as APs passíveis de mudanças climáticas mais extremas (aumento de temperatura > 3ºC e redução de precipitação >50mm/mês) são aquelas que contemplam a presença de populações tradicionais na região Norte e Centro-Oeste do país. Ao final do projeto os resultados do projeto foram apresentados em Brasília no Instituto Chico Mendes de Conservação da Biodiversidade. Tal interação demonstrou a inexistência de uma estratégia do governo federal para a adaptação das áreas protegidas Brasileiras aos efeitos de mudanças climáticas futuras

Um estudo da vulnerabilidade socioclimática no Brasil e no mundo

The Socio Climate Vulnerability Index (IVSC, Portuguese acronym) aims to expose spatially and in a comparative basis, human settlement areas that are more susceptible to the potential risks posed by climate change. To access this vulnerability, the IVSC draws on the aggregation of adaptive capacity and sensitivity indicators (Human Development Index and population density) and an indicator of projected climate change (Regional Climate Change Index-IRCM). The IVSC can be applied to any spatial scale, as long as data in reasonable resolution.is available. Knowing the spatial distribution of vulnerability is an important strategic step in development and implementation of measures that seeks to improve human development and the preparedness of society for future environmental changes. In addition, the production and comparison climate change vulnerability indexes is an important exercise to improve gradually the quality of information provided to decision makers and stakeholders in the management of measures involving climate change adaptation