A methodological assessment of Species Distribution Models as tools to plan species conservation and niche modelling

Knowing species distribution is essential to understand a species’ ecology and conservation needs. Species distribution models (SDMs) adopt a correlative approach to infer the ecological requirements of species from field observations based on statistically or theoretically derived response surfaces. SDMs have become a widely used technique and an increasingly important tool in many fields of natural and biological sciences to address various issues in applied ecology and conservation biology. The most basic of such aims is to understand the relationships between a species and its abiotic and biotic environment and to identify areas where a given species is likely to occur. The aim of this thesis was to evaluate the effectiveness of SDMs for supporting conservation actions. In particular, we used SDMs to focus on important but less handled issues and present three case studies. In the first case, we analysed the influence of spatial scale on SDMs’ ability to detect niche differences for two sympatric species of high conservation value, the bat Barbastella barbastellus and the cerambycid beetle Rosalia alpina, which apparently share the same habitat and ecological requirements. Broad scale SDMs revealed limited differences in preferred environmental predictor variables while failed to detect differences in microhabitats occupied. Only a small-scale niche analyses provided detailed ecological differences characterizing the two species and gave information on the type of management that such species need. In the second case, we evaluated the effectiveness of SDMs in managing the conservation of a mammal species reintroduced to Serbia and Bosnia-Herzegovina, the Eurasian beaver Castor fiber, during the post-release phase. We were able to predict suitable areas that beavers might colonize in the near future and to evaluate the potential risk posed to the expanding population by the very low degree of protection offered by the national reserve network. Finally, in the third case we focused on the importance of considering species’ phenology in presence record datasets to develop SDMs. We demonstrated that SDMs developed using different seasonal data separately, i.e. records of sites used by six European bat species for hibernation or reproduction may predict only partial species’ ecological niches. Then, we suggested a more valuable method for data collection to obtain a dataset featuring equally represented seasonal records for SDMs that take into account the potential ecological requirements of the species during its complete life cycle and predict a more realistic potential geographical range. My thesis offers important guidance in the development of conservation plans, e.g. by allowing more exhaustive gap analyses, helping detect corridors or low-suitability areas in need of restoration to improve the conservation status of management-dependent species.