RESUMO
Global efforts to avoid anthropogenic conversion of natural habitat rely heavily on the establishment of protected areas. Studies that evaluate the effectiveness of these areas with a focus on preserving the natural habitat define effectiveness as a measure of the influence of protected areas on total avoided conversion. Changes in the estimated effectiveness are related to local and regional differences, evaluation methods, restriction categories that include the protected areas, and other characteristics. The overall objective of this study was to evaluate the effectiveness of protected areas to prevent the advance of the conversion of natural areas in the core region of the Brazil's Cerrado Biome, taking into account the influence of the restriction degree, governmental sphere, time since the establishment of the protected area units, and the size of the area on the performance of protected areas. The evaluation was conducted using matching methods and took into account the following two fundamental issues: control of statistical biases caused by the influence of covariates on the likelihood of anthropogenic conversion and the non-randomness of the allocation of protected areas throughout the territory (spatial correlation effect) and the control of statistical bias caused by the influence of auto-correlation and leakage effect. Using a sample design that is not based on ways to control these biases may result in outcomes that underestimate or overestimate the effectiveness of those units. The matching method accounted for a bias reduction in 94-99% of the estimation of the average effect of protected areas on anthropogenic conversion and allowed us to obtain results with a reduced influence of the auto-correlation and leakage effects. Most protected areas had a positive influence on the maintenance of natural habitats, although wide variation in this effectiveness was dependent on the type, restriction, governmental sphere, size and age group of the unit.
Assuntos
Ecossistema , Modelos Biológicos , BrasilRESUMO
A água tem importante papel na sociedade humana, especialmente no Brasil. Seus usos são múltiplos, incluindo o abastecimento, produção energética e lazer, entre outros. A própria Política Nacional de Recursos Hídricos (Lei nº 9.433/97) traz entre seus artigos a sua importância segundo os seus usos múltiplos, priorizando o abastecimento humano e a dessedentacão de animais. Neste enfoque é importante considerar a qualidade físico-química da água para atender a estas demandas, escopo do enquadramento dos corpos d'água segundo seus usos preponderantes, com o objetivo de garantir qualidade compatível com os usos mais exigentes a que for destinada e diminuir os custos de combate à poluição mediante ações preventivas permanentes. Entre os vários parâmetros que buscam analisar a qualidade físico-química da substância busca-se entender a distribuição espacial da turbidez na superfície do lago, uma vez que a variação dos componentes que alteram este parâmetro pode ser detectada por meio do sensoriamento remoto passivo. A aplicação do Modelo linear de mistura espectral permitiu, de forma satisfatória, identificar a distribuição espacial da turbidez no espelho de água.
The water has an important role in human society, especially in Brazil. Its uses are multiple, including supply, energy production, recreation and others. The National Policy for Water Resources (Law Nº 9.433/97) states in its articles the importance of water use in accordance to their multiple uses, prioritizing the supply for humans and animals. In this approach, it is important to consider the physical and chemical quality of water to meet these demands, scope of the legal framework applied to the Brazilian water bodies according to their main uses, in order to guarantee the water quality compatible with the most demanding uses and to reduce the costs of pollution control through ongoing preventive actions. Among the various parameters that seek to analyze the physical and chemical quality of water it is intended to understand the spatial distribution of turbidity in the lake's surface, since the variation of the components that alter this parameter can be detected by means of passive remote sensing. The application of the Linear spectral mixture model allowed, satisfactorily, the identification of turbidity spatial distribution patterns in the lake.
