Using food-web theory to conserve ecosystems

E. McDonald-Madden (), R. Sabbadin, E. T. Game, P. W. J. Baxter, I. Chadès and H. P. Possingham
Additional contact information
E. McDonald-Madden: School of Geography, Planning and Environmental Management, University of Queensland
R. Sabbadin: Unité de Mathématiques et Informatique Appliquées, Toulouse
E. T. Game: The Nature Conservancy, Conservation Science
P. W. J. Baxter: Centre for Applications in Natural Resource Mathematics, School of Mathematics and Physics, The University of Queensland
I. Chadès: CSIRO, Ecosciences Precinct
H. P. Possingham: School of Biological Sciences, University of Queensland

Nature Communications, 2016, vol. 7, issue 1, 1-8

Abstract: Abstract Food-web theory can be a powerful guide to the management of complex ecosystems. However, we show that indices of species importance common in food-web and network theory can be a poor guide to ecosystem management, resulting in significantly more extinctions than necessary. We use Bayesian Networks and Constrained Combinatorial Optimization to find optimal management strategies for a wide range of real and hypothetical food webs. This Artificial Intelligence approach provides the ability to test the performance of any index for prioritizing species management in a network. While no single network theory index provides an appropriate guide to management for all food webs, a modified version of the Google PageRank algorithm reliably minimizes the chance and severity of negative outcomes. Our analysis shows that by prioritizing ecosystem management based on the network-wide impact of species protection rather than species loss, we can substantially improve conservation outcomes.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.nature.com/articles/ncomms10245 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms10245

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/ncomms10245

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().