Habitat selection by capybaras (Hydrochoerus hydrochaeris) in natural and anthropic landscapes in Brazil

Abstract

Wildlife distribution is driven by a variety of intrinsic and extrinsic factors that limit species to habitats with the adequate resources and conditions to maintain their survival. The selection of specific habitats by wildlife is modified by, among other things, predator’s presence and human-related disturbance, which is proved to have directly effects in wild species behavior. Thus, species as the capybara (Hydrochoerus hydrochaeris), that occurs both in natural and anthropic areas, may present different patterns of habitat selection since “risk” is generated by different agents in these landscapes. This study aims to model and compare selection of the main components of capybara habitat (forests, water sources and open areas dominated by grasses / shrubs) in natural landscapes of the Brazilian Pantanal, where predator’s abundance is massive and human density is low, and anthropic areas of São Paulo state, where the opposite occurs, using Resource Selection Functions (RSF). The results shown that, in Pantanal, areas within and nearby forest patches were not selected by capybaras and the species presented preferences for areas close to water sources. This response is mainly related to the great predation risk in this landscape full of predators. In human dominated landscapes of São Paulo state, capybaras presented high selection for areas within and nearby forest patches and close to water sources, especially during the day when human disturbance is more pronounced. The high selection for areas within forest patches is probably related to the Brazilian Spotted Fever (BSF) epidemiology and the depredation of water springs in São Paulo state. Besides that, according to the results founded by this study it is recommended that selection for open areas with grasses / shrubs in anthropic/agricultural landscapes should be modeled by including food items in different classes, considering the temporal dynamics of crop fields, which can generate more refined results.