22 resultados para SEASONAL VARIABILITY


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Several competing hypotheses attempt to explain how environmental conditions affect mass-independent basal metabolic rate (BMR) in mammals. One of the most inclusive and yet debatable hypotheses is the one that associates BMR with food habits, including habitat productivity. These effects have been widely investigated at the interspecific level under the assumption that for any given species all traits are fixed. Consequently, the variation among individuals is largely ignored. Intraspecific analysis of physiological traits has the potential to compensate for many of the pitfalls associated with interspecific analyses and, thus, to be a useful approach for evaluating hypotheses regarding metabolic adaptation. In this study, we investigated the effects of food quality, availability, and predictability on the BMR of the leaf-eared mouse Phyllotis darwini. BMR was measured on freshly caught animals from the field, since they experience natural seasonal variations in environmental factors ( and, hence, variations in habitat productivity) and diet quality. BMR was significantly correlated with the proportion of dietary plants and seeds. In addition, BMR was significantly correlated with monthly habitat productivity. Path analysis indicated that, in our study, habitat productivity was responsible for the observed changes in BMR, while diet per se had no effect on this variable.

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The emphasis in this research is to evaluate the spatial distribution of the precipitation using a geostatistics approach. Seasonal time scales records considering DJF, MAM, JJA e SON periods performed the analysis. Procedures to evaluate the variogram selection and to produce kriging maps were performed in a GIS environment (ArcGIS®). The results showed that kriging method was very suitable to detect both large changes in the whole area as those local small and subtle changes. Kriging demonstrated be a powerful statistical interpolation method that might be very useful in regions with great complexity in climatology and geomorphology.