Amphibians are particularly sensitive to rapid climatic shifts, due to their eco-physiology, life history traits and high frequency of narrowly distributed species. The genus Speleomantes encompasses the only extant Western Palearctic plethodontids, with three species occurring in peninsular Italy and the remaining five endemic to Sardinia Island.
Given the restricted ranges of Speleomantes species and their vulnerability to environmental change, we implemented Ecological Niche Models (ENMs) to estimate the likely impacts of various global warming scenarios on the extent and geographical location of climatically suitable areas.
Current, with ENMs projected to 2030, 2050 and 2070 under alternative Shared Socioeconomic Pathways.
Italian Peninsula and Sardinia Island.
Speleomantes Dubois 1984 (Caudata: Plethodontidae).
Ensembles of ENMs were fitted for each Speleomantes species, using the ‘biomod2’ modelling platform in R environment. Then, post-modelling analyses were applied in GIS environment to highlight: (i) the primary geographic direction of predicted suitability shifts for each species and (ii) the proportion of stable, gained and lost suitable areas for each genetic lineage of the single species.
We found a noticeable shrinking of suitable areas for all Speleomantes species, being particularly extensive under ‘business-as-usual’ scenarios for the Sardinian ones. Moreover, core suitable areas were predicted to shift for most species and suitability losses emerged to differently affect distinct genetic lineages, posing additional challenges for designing effective conservation measures.
The predicted shrinkage and shifting of climatically suitable areas for most Speleomantes species point to the urgency of evaluating in due time alternative conservation strategies for these endemic urodeles, to prevent losses of taxonomic and genetic diversity. Our modelling framework may be applied to other species with similar traits (e.g., low dispersal ability and narrow environmental niche breadth) to predict climate-induced range contractions or shifts, using the gained information to optimise conservation outcomes.