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Reducing the Eltonian shortfall with trophic interaction models
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  • Dominique Caron,
  • Luigi Maiorano,
  • Wilfried Thuiller,
  • Laura J. Pollock
Dominique Caron
McGill University
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Luigi Maiorano
University of Rome La Sapienza
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Wilfried Thuiller
Laboratoire d'Ecologie Alpine
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Laura J. Pollock
McGill University
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Abstract

While species interactions are fundamental for linking biodiversity to ecosystem functioning and for conservation, large-scale empirical data are lacking for most species and ecosystems. Accumulating evidence suggests that trophic interactions are predictable from available functional trait information, but we have yet to understand how well we can predict interactions across large spatial scales and food webs. Here, we built a model predicting predator-prey interactions based on functional traits for European vertebrates. We found that even models calibrated with very few known interactions (100 out of 71k) estimated the entire food web reasonably well. However, predators were easier to predict than prey, with prey in some clades being particularly difficult to predict (e.g., fowls and storks). Local food web connectance was also consistently over-estimated. Our results demonstrate the potential for filling gaps in sparse food webs, an important step towards a better description of biodiversity with strong implications for conservation planning.
09 Aug 2021Submitted to Ecology Letters
10 Aug 2021Submission Checks Completed
10 Aug 2021Assigned to Editor
11 Aug 2021Reviewer(s) Assigned
15 Sep 2021Review(s) Completed, Editorial Evaluation Pending
24 Sep 2021Editorial Decision: Revise Major
04 Nov 20211st Revision Received
05 Nov 2021Assigned to Editor
05 Nov 2021Submission Checks Completed
05 Nov 2021Reviewer(s) Assigned
01 Dec 2021Review(s) Completed, Editorial Evaluation Pending
04 Dec 2021Editorial Decision: Revise Major
23 Dec 20212nd Revision Received
03 Jan 2022Assigned to Editor
03 Jan 2022Submission Checks Completed
03 Jan 2022Review(s) Completed, Editorial Evaluation Pending
03 Jan 2022Editorial Decision: Accept