The estimate of density of wildlife populations is still a difficult task, especially when working with spatially-open populations when one must relax the assumption of closure, which is at the base of most methods currently used. Further difficulties arise to obtain density estimates at small spatial scales. Using eight years (1996-2003) of monitoring data from a roe deer (Capreolus capreolus) population, living in a sub-Mediterranean environment in central Italy, we were able to estimate local density (at a spatial scale of one home range) using a large sample of radio-marked animals. Local density estimates could be obtained only in zones where radio-marked deer were available in sufficient number. To estimate local density over the whole study area, we developed a calibration model which allowed us to infer density where radio-marked deer were absent or scarce. To do this, we compute the mark-resight density estimates (using radio-marked animals) and we relate these estimates to linear and non-linear functions of animal count and surface area of fields, to obtain a set of density estimators. Then we select a linear combination of such estimators, whose quality was assessed by cross-validation. Our results show that the method we propose can be effective to investigate small-scale spatial structure of density in a roe deer population. There are several potential applications of this method for both research and management.
Key words: roe deer, Capreolus capreolus, population estimate, local density, calibration model, Apennines