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A Bayesian network approach to trophic metacommunities shows habitat loss accelerates top species extinctions
  • Johanna Häussler,
  • Gyorgy Barabas,
  • Anna Eklöf
Johanna Häussler
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Corresponding Author:[email protected]

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Gyorgy Barabas
Linkopings universitet
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Anna Eklöf
Linköping University
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We develop a novel approach to 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 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 parameterizability 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.
20 Feb 2020Submitted to Ecology Letters
21 Feb 2020Submission Checks Completed
21 Feb 2020Assigned to Editor
27 Feb 2020Reviewer(s) Assigned
31 Mar 2020Review(s) Completed, Editorial Evaluation Pending
10 Apr 2020Editorial Decision: Revise Major
24 Jun 20201st Revision Received
25 Jun 2020Submission Checks Completed
25 Jun 2020Assigned to Editor
01 Jul 2020Reviewer(s) Assigned
12 Aug 2020Review(s) Completed, Editorial Evaluation Pending
14 Aug 2020Editorial Decision: Accept