A Bayesian network approach to trophic metacommunities shows habitat
loss accelerates top species extinctions
- Johanna Häussler,
- Gyorgy Barabas,
- Anna Eklöf
Abstract
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