Spatially explicit conservation issues for threatened bird species in Mediterranean farmland landscapes

Abstract

Coupling habitat models based on GIS and on ground variables could help identify suitable areas (by means of landscape models obtained by GIS variables) to concentrate management actions for species' conservation. In this study, the habitat requirements of Lesser Greys (LGS) and Woodchat Shrikes (WS), two threatened farmland bird species declining in Europe, were assessed in Apulia (south-eastern Italy) by means of binary logistic regression at two different levels: landscape (using GIS-measured variables); and, territory (using ground-measured variables) scales. The LGS occurrence at landscape scale was correlated to steppe-like areas and cereal crops. At the territory level, significant effects were detected for deciduous forests and the presence of isolated trees and shrubs. The WS occurrence at landscape scale was promoted by steppe-like areas and cereal crops, whereas, at the territory level significant effects were detected for steppe-like areas positively and suburban areas negatively. The landscape model was extrapolated to the entire region. Within highly suitable areas (occurrence probability higher than 0.66 according to the landscape model), we measured average habitat features and compared them with the optimal mosaic depicted by the territory level models. This allowed us to give spatially explicit and site-specific management recommendations for these two threatened species. LGS will mostly benefit from an increase in isolated shrubs and trees; whereas for WS, the most widespread recommendations are to increase steppe-like habitat and to prevent further urbanisation.Coupling "coarse" landscape models with the species ecology provided by fine-scaled models can integrate relevant information on species potential distribution and territory level requirements, making planning fine-tuned habitat management (within potentially suitable landscapes) in a spatially explicit way possible. © 2013 Elsevier GmbH.