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Forest conservation strategies and plans can be unsuccessful if the new habitat conditions determined by climate change are not considered. Our work aims at investigating the likelihood of future suitability, distribution and diversity for some common European forest species under the projected changes in climate, focusing on Southern Europe. We combine an Ensemble Platform for Species Distribution Models ( SDMs) to five Global Circulation Models ( GCMs) driven by two Representative Concentration Pathways ( RCPs), to produce maps of future climate-driven habitat suitability for ten categories of forest species and two time horizons. For each forest category and time horizon, ten maps of future distribution (5 GCMs by 2 RCPs) are thus combined in a single suitability map supplied with information about the 'likelihood' adopting the IPCC terminology based on consensus among projections. Then, the statistical significance of spatially aggregated changes in forest composition at local and regional level is analyzed. Finally, we discuss the importance, among SDMs, that environmental predictors seem to have in influencing forest distribution. Future impacts of climate change appear to be diversified across forest categories. A strong change in forest regional distribution and local diversity is projected to take place, as some forest categories will find more suitable conditions in previously unsuitable locations, while for other categories the same new conditions will become less suited. A decrease in species diversity is projected in most of the area, with Alpine region showing the potentiality to become a refuge for species migration. [ABSTRACT FROM AUTHOR]

The Mediterranean basin is one of the most varied areas worldwide in terms of biodiversity and species richness due to its climatic and geomorphological features, and it is characterized by multi-faceted habitats where forests play a crucial role. Nowadays, the geographic distribution of forest species is well known and multiple geographic datasets are available with different spatial details. However, protection and conservation strategies need more specific information to identify areas with high conservation priority or more vulnerable to the ongoing environmental change ("hot spots"). To this purpose, tree species distribution data were investigated through hot spot analysis using Geographic Information Systems. The analysis was carried out on presence data of ten relevant forest tree species/classes across Mediterranean Europe. By combining spatial analysis and spatial statistics, we identified high and very high hot spot areas for the selected species/classes, which were validated by assessing their biological significance. Given the sub-continental extent of the study, a multiple scale approach was applied ranging from regional, subregional to local scale, coherently with the potential multi-level and multi-sector users of similar data and tools. Our results confirm the feasibility of the approach used to increase the quality and quantity of information achievable from available forest distribution datasets. The hot spot maps obtained are a useful support for further spatial evaluations, and may help environmental decision makers to identify priority areas for forest protection and conservation. [ABSTRACT FROM AUTHOR]

Abstract: This study describes a GIS-based software tool for the qualitative assessment of desertification risk. The tool integrates results from several land degradation models into ArcGIS using the object-oriented programming language Visual Basic. The integration of GIS and models is based on different coupling approaches. The proposed methodology was developed and tested on Sardinia Island (Italy). Six driving factors of desertification (overgrazing, vegetation productivity, soil fertility, water erosion, wind erosion and seawater intrusion) were model-simulated over two time periods to investigate the spatio-temporal evolution pattern of desertification-prone areas. Model results were normalized, weighted and combined into an Integrated Desertification Index (IDI) ranging from 0 to 1 (representing the best and the worst conditions, respectively), and classified into five desertification risk levels. The implementation, performance of the methodology and benefits provided by the modelling approach to land management authorities for monitoring processes of land degradation are fully described in the paper. [Copyright &y& Elsevier]