Vulnerability of biodiversity hotspots to global change

International audienceAimGlobal changes are predicted to have severe consequences for biodiversity; 34 biodiversity hotspots have become international priorities for conservation, with important efforts allocated to their preservation, but the potential effects of global changes on hotspots have so far received relatively little attention. We investigate whether hotspots are quantitatively and qualitatively threatened to the same order of magnitude by the combined effects of global changes. LocationWorldwide, in 34 biodiversity hotspots. MethodsWe quantify (1) the exposure of hotspots to climate change, by estimating the novelty of future climates and the disappearance of extant climates using climate dissimilarity analyses, (2) each hotspot's vulnerability to land modification and degradation by quantifying changes in land-cover variables over the entire habitat, and (3) the future suitability of distribution ranges of 100 of the world's worst invasive alien species', by characterizing the combined effects of climate and land-use changes on the future distribution ranges of these species. ResultsOur findings show that hotspots may experience an average loss of 31% of their area under analogue climate, with some hotspots more affected than others (e.g. Polynesia-Micronesia). The greatest climate change was projected in low-latitude hotspots. The hotspots were on average suitable for 17% of the considered invasive species. Hotspots that are mainly islands or groups of islands were disproportionally suitable for a high number of invasive species both currently and in the future. We also showed that hotspots will increase their area of pasture in the future. Finally, combining the three threats, we identified the Atlantic forest, Cape Floristic Region and Polynesia-Micronesia as particularly vulnerable to global changes. Main conclusionsGiven our estimates of hotspot vulnerability to changes, close monitoring is now required to evaluate the biodiversity responses to future changes and to test our projections against observations