Journal
ECOLOGY LETTERS
Volume 23, Issue 12, Pages 1849-1861Publisher
WILEY
DOI: 10.1111/ele.13607
Keywords
Bayesian network; habitat loss; metacommunity; spatial food web
Categories
Funding
- German Research Foundation (DFG) [FOR 1748, RA 2339/2-2]
- German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig - German Research Foundation [FZT 118]
- Swedish Research Council [VR 2017-05245, VR 2016-04919]
- Swedish Research Council [2016-04919] Funding Source: Swedish Research Council
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We develop a novel approach to analyse trophic metacommunities, which allows us to explore how progressive habitat loss affects food webs. Our method combines classic metapopulation models on fragmented landscapes with a Bayesian network representation of trophic interactions for calculating local extinction rates. This means that we can repurpose known results from classic metapopulation theory for trophic metacommunities, such as ranking the habitat patches of the landscape with respect to their importance to the persistence of the metacommunity as a whole. We use this to study the effects of habitat loss, both on model communities and the plant-mammal Serengeti food web dataset as a case study. Combining straightforward parameterisability with computational efficiency, our method permits the analysis of species-rich food webs over large landscapes, with hundreds or even thousands of species and habitat patches, while still retaining much of the flexibility of explicit dynamical models.
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