Identifying potentially suitable nesting habitat for golden eagles applied to 'important bird areas' design

Geographic information systems (GIS)-based habitat-suitability modelling is becoming an essential tool in conservation biology. A multi-scale approach has been proposed as a particularly useful way to identify different factors affecting habitat preferences. In this paper, we developed predictive models of potentially suitable habitat for golden eagles Aquila chrysaetos at three spatial scales in a representative Mediterranean area on the Iberian Peninsula. We used logistic regression through a generalized linear model (GLM) to model golden eagle breeding habitat preferences. The best-occurrence GLM models were those that involved topographic factors as independent predictors. Golden eagles seemed to prefer rugged and higher places of the study area for nesting. Climatic factors identified cold temperatures in January and temperate ones in July as the best predictors of eagles' occurrence. This was also higher in places with less agricultural areas and higher surface of pine forests. The distribution of potentially suitable area matches the distribution of mountain ranges, mainly in inner sectors of the study area. In contrast, potentially suitable nest sites in coastland areas remain unoccupied by golden eagles. Avoidance of coastland places for nesting may be due to the synergistic effects of human avoidance and the occurrence of potential competitors, like the endangered Bonelli's eagle Hieraaetus fasciatus. When mapped at a fine spatial resolution, the best GLM model identified large areas that fall outside the current network of protected areas. We therefore propose three new important bird areas for the region.