Biodiversity of intertidal food webs in response to warming across latitudes

International audience Global warming threatens community stability and biodiversity around the globe. Knowledge on the underlying mechanisms depends heavily on generic food-web models that do not account for changes in network structure along latitudes and temperature gradients. Using 124 marine ro...

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Bibliographic Details
Published in:Nature Climate Change
Main Authors: Gauzens, Benoit, Rall, Björn, Mendonça, Vanessa, Vinagre, Catarina, Brose, Ulrich
Other Authors: Universitätsklinikum Friedrich-Schiller-University (FSU), Friedrich-Schiller-Universität = Friedrich Schiller University Jena Jena, Germany, Deutsche Forschungsgemeinschaft - German Research Foundation (DFG)
Format: Article in Journal/Newspaper
Language:English
Published: HAL CCSD 2020
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Online Access:https://hal.science/hal-04404724
https://hal.science/hal-04404724/document
https://hal.science/hal-04404724/file/final_version_accepted.pdf
https://doi.org/10.1038/s41558-020-0698-z
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Summary:International audience Global warming threatens community stability and biodiversity around the globe. Knowledge on the underlying mechanisms depends heavily on generic food-web models that do not account for changes in network structure along latitudes and temperature gradients. Using 124 marine rockpool food webs sampled across four continents, we show that despite substantial variation in ambient temperature (mean 11.5-28.4°C) similar empirical food-web and body-mass structures emerge. We used dynamic modelling to test if communities from warmer regions were more sensitive to warming and found a general humped-shaped relationship between simulated biodiversity and temperature (gradient from 0-50°C). This implies that an expected anthropogenic warming by 4°C should increase biodiversity in arctic to temperate regions while biodiversity in tropical regions should decrease. Interestingly, simulations of synthetic networks did not yield similar results, which stresses the importance of considering the specificities of natural food webs for predicting community responses to environmental changes.