Medium and large mammals are an important protein source for many human populations, and, depending on the species, their populations may suffer reductions related to hunting and consumption, habitat degradation or both. The distribution and abundance of these animals can vary with the quality and quantity of the surrounding forests (influence of natural and human factors). The study of this variation may help define public policies for the management and conservation of species and to analyze the effectiveness of protected areas. This study aimed at improving the knowledge of the medium and large mammal distribution patterns in order to evaluate a public policy for the western part of the Para State, which was the implementation of Sustainable Forest District of BR-163. In a study case, the geographical distribution of a species of primate, the white marmoset (Mico leucippe) was expanded based on new records for the region. The Maximum Entropy algorithm was used to predict the potential distribution of species based on its potential ecological niche and assist in defining the geographical boundaries for future surveys. The result of this study served as a parameter for reviewing the conservation status of the species, which had its status changed to the category of "Least Concern" in the national and the IUCN Red lists. In the second part of the study population surveys were conducted to identify the factors influencing the pattern of distribution and abundance of medium and large mammals. For this purpose, densities of species were estimated based on linear transects surveys and analyses of the relation between the density distribution and environmental variables, such as temperature, rainfall and altitude, and anthropogenic variables, as a percentage of deforestation, distance to cities and towns, and distance to roads. There was low variation in species abundance along the DFS of the BR-163, and variation in responses depending on the species, but in general there was influence of rainfall (average annual rainfall and rainfall in the dry season) and anthropogenic factors (proximity roads) on density variation. Increment in the sampling
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effort was analyzed for the most abundant species and has led to increased precision in the density estimation but did not indicate substantial change in the estimate. The relationships found were not strong enough to allow a generalization about the area, but the results establish a parameter for future comparisons, given the good condition of the sampled areas. This was the first study of mammals in the region for that scale, which matched an actual public policy for the region.
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