Abstract
Food webs represent an important nexus between biodiversity and ecosystem functioning, yet considering changes in food webs around the world has been limited by data availability. Previous studies have predicted food web collapses and coextinction, but changes in food web structure have been less investigated under climate warming and anthropogenic pressures on a global scale. We systematically amassed information about species' diets, traits, distributions, habitat use, and phylogenetics in the real world and used machine learning to predict changes in global meta-food webs of terrestrial vertebrates under climate and land-use changes. By year 2100, terrestrial vertebrate food webs are expected to decrease in web size by 32% and trophic links by 49%. Projections predict declines of over 25% in modularity, predator generality, and diversity of trophic groups. Increased species' dispersal could ameliorate these trends but indicate disproportionate vulnerability of regional food webs. Unlike many previous studies, this work combines extensive empirical data with advanced modeling techniques, providing a more detailed and spatially explicit prediction of how global food webs will respond to climate and land-use changes. Overall, our study predicts terrestrial vertebrate food webs will undergo drastic and spatially heterogeneous structural changes.
Published Version
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