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The impact of climate warming on species diversity across scales: Lessons from experimental meta-ecosystems
Vinicius A G Bastazini1, Núria Galiana1, Helmut Hillebrand2,3,4
1Centre for Biodiversity Theory and Modelling, Theoretical and Experimental Ecology Station, French National Center for Scientific Research and Paul Sabatier University, Moulis, France.
Aim:
The aim was to evaluate the effects of climate warming on biodiversity across spatial scales (i.e., α-, β- and γ-diversity) and the effects of patch openness and experimental context on diversity responses.
Location:
Global.
Time Period:
1995-2017.
Major Taxa Studied:
Fungi, invertebrates, phytoplankton, plants, seaweed, soil microbes and zooplankton.
Methods:
We compiled data from warming experiments and conducted a meta-analysis to evaluate the effects of warming on different components of diversity (such as species richness and equivalent numbers) at different spatial scales (α-, β- and γ-diversity, partitioning β-diversity into species turnover and nestedness components). We also investigated how these effects were modulated by system openness, defined as the possibility of replicates being colonized by new species, and experimental context (duration, mean temperature change and ecosystem type).
Results:
Experimental warming did not affect local species richness (α-diversity) but decreased effective numbers of species by affecting species dominance. Warming increased species spatial turnover (β-diversity), although no significant changes were detected at the regional scale (γ-diversity). Site openness and experimental context did not significantly affect our results, despite significant heterogeneity in the effect sizes of α- and β-diversity.
Main Conclusions:
Our meta-analysis shows that the effects of warming on biodiversity are scale dependent. The local and regional inventory diversity remain unaltered, whereas species composition across temperature gradients and the patterns of species dominance change with temperature, creating novel communities that might be harder to predict.
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