Abstract

Context The negative effects of agricultural intensification and policies, use of pesticides, fertilisers and mechanised harvesting on several populations of pseudo-steppe birds have increasingly required more detailed and effective habitat suitability models. Distribution models of farmland species are prone to incur recordings of false absence data. Ecological Niche Factor Analysis (ENFA) allows identification of environmental predictors of species distribution by using presence data only. Aims We quantified the diurnal habitat preferences and niche width of one steppe species, the stone curlew (Burhinus oedicnemus), with unfavourable conservations status in a Mediterranean area and reclassified a map with respect to habitat suitability classes according to the resulting distribution model. Methods Ecological Niche Factor Analysis was used with GIS cartography customised with habitat and anthropogenic variables recorded during field surveys carried out in four study plots (~500 ha) and at different spatial scales. Key results The stone curlew selected areas with low vegetation cover, such as fields following artichoke harvesting and tillage, close to rural buildings and unpaved roads. In contrast, the stone curlew avoided areas with high vegetation cover and areas highly disturbed by human-induced fires. The occurrence of natural vegetation was neither preferred nor avoided. The most robust model was based on a large-scale analysis (200 m from the bird location points), according to which the optimal area for stone curlew distribution during its breeding season was restricted to 1% of the entire study area. Conclusions Two uncorrelated factors, ‘marginality’ and ‘tolerance’, described the stone curlew’s niche in the area. The first index indicated selection for habitats that were marginal with respect to those available in the area, whereas the second indicated a species with a medium–wide environmental niche. In particular, the stone curlew occupied a much more restricted niche (low tolerance) in relation to individual variables. The use of customised databases at a large scale of analysis was found to more effectively reveal ecological requirements of this marginal and specialised species. Implications Our results allowed us to indicate practical land management actions for the stone curlew, such as prevention of human-induced fires and increase of pastoral activities. Our results indicated a potentially positive role of little-disturbed service roads along rural buildings in stone curlew distribution, which warrants further research. In addition, studies are needed to verify the presence of an ecological trap in artichoke fields, their preferred habitat. As we showed for the stone curlew, niche analyses conducted at a large scale using customised databases could greatly improve habitat suitability models of farmland species.

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