For evaluating climate change impacts on biodiversity, extensive experiments are urgently needed to complement popular non-mechanistic models which map future ecosystem properties onto their current climatic niche. Here, we experimentally test the main prediction of these models by means of a novel multi-site approach. We implement rainfall manipulations--irrigation and drought--to dryland plant communities situated along a steep climatic gradient in a global biodiversity hotspot containing many wild progenitors of crops. Despite the large extent of our study, spanning nine plant generations and many species, very few differences between treatments were observed in the vegetation response variables: biomass, species composition, species richness and density. The lack of a clear drought effect challenges studies classifying dryland ecosystems as most vulnerable to global change. We attribute this resistance to the tremendous temporal and spatial heterogeneity under which the plants have evolved, concluding that this should be accounted for when predicting future biodiversity change.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4205856PMC
http://dx.doi.org/10.1038/ncomms6102DOI Listing

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