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Abstract

A large body of research shows that biodiversity loss can reduce ecosystem functioning, thus providing support for the conservation of biological diversity. Much of the evidence for this relationship is drawn from biodiversity-ecosystem functioning experiments (hereafter: biodiversity experiments), in which biodiversity loss is simulated by randomly assembling communities of varying species diversity, and ecosystem functions are measured. This random assembly has led some ecologists to question the relevance of biodiversity experiments to real-world ecosystems, where community assembly may often be non-random and influenced by external drivers, such as climate or land-use intensification. Despite these repeated criticisms, there has been no comprehensive, quantitative assessment of how experimental and real-world plant communities really differ, and whether these differences invalidate the experimental results. Here, we compare data from two of the largest and longest-running grassland biodiversity experiments globally (Jena Experiment, Germany; BioDIV, USA) to related real-world grassland plant communities in terms of their taxonomic, functional, and phylogenetic diversity and functional-trait composition. We found that plant communities of biodiversity experiments have greater variance in these compositional features than their real-world counterparts, covering almost all of the variation of the real-world communities (82-96%) while also containing community types that are not currently observed in the real world. We then re-analysed a subset of experimental data that included only ecologically-realistic communities, i.e. those comparable to real-world communities. For ten out of twelve biodiversity-ecosystem functioning relationships, biodiversity effects did not differ significantly between the full dataset of biodiversity experiments and the ecologically-realistic subset of experimental communities. This demonstrates that the results of biodiversity experiments are largely insensitive to the inclusion/exclusion of unrealistic communities. By bridging the gap between experimental and real-world studies, these results demonstrate the validity of inferences from biodiversity experiments, a key step in translating their results into specific recommendations for real-world biodiversity management.