Environmental favourability as a cost-efficient tool to estimate carrying capacity

摘要: Aim The way in which environmental conditions determine the distribution and abundance of species is a crucial topic ecology, biogeography conservation. It especially important to understand nature this relationship regarding threatened species. The ability forecast local densities over geographic range provides link population ecology biogeography. Particularly, our aim was test whether predictions derived from modelling data provide useful information on spatial patterns and, consequently, may act as surrogates for density estimates. Location Andalusia (southern Spain). Methods Logistic regression favourability function were applied tools presence–absence compare predicted results with current abundance. This approach identification priorities target whenever broad-scale surveys need be performed. Results The model included variables related topography, vegetation location explain presence Bonelli's eagle. A positive found between both probability species, but triangular fit only favourability, suggesting that physiological ecological requirements study area are better reflected model. Main conclusions We suggest models insights into valuable carrying capacity large scales. To minimize costs, maximize output optimize results, priority could given detecting instead investing resources aimed at estimating abundance, more expensive.