Spatial ecology of the European wildcat in a Mediterranean ecosystem: dealing with small radio-tracking datasets in species conservation

Despite some populations of European wildcat Felis silvestris in central Europe are stable or increasing, the Iberian subpopulation is in decline and is listed as 'vulnerable'. In Portugal, little is known about wildcat populations, making conservation policies extremely difficult to define. Furthermore, the secretive behaviour of these mammals, along with low population densities, make data collection complicated. Thus, it is crucial to develop efficient analytical tools to interpret existing data for this species. In this study, we determine the home-range size and environmental factors related to wildcat spatial ecology in a Mediterranean ecosystem using a combined analysis of habitat selection and maximum entropy (Maxent) modelling. Simultaneously, we test the feasibility of using radio-tracking locations to construct an ecologically meaningful distribution model. Six wildcats were captured and tracked. The average home-range size (MCP95) was 2.28 km(2) for females and 13.71 km(2) for one male. The Maxent model built from radio-tracking locations indicated that the abundance of the European rabbit Oryctolagus cuniculus and limited human disturbance were the most important correlates of wildcat presence. Habitat selection analysis revealed that wildcats tend to use scrubland areas significantly more than expected by chance. A mosaic of scrublands and agricultural areas, with a higher proportion of the former, benefits wildcat presence in the study area; however, species distribution is mainly constrained by availability of prey and resting sites. The Maxent model validation with camera-trapping data indicated that highly adequate model performance. This technique may prove useful for recovering small radio-tracking datasets as it provides a new alternative for handling data and maximizing the ecological information on a target population, which can then be used for conservation planning.