Using food-web theory to conserve ecosystems

Nature Communications
E McDonald-MaddenHugh Possingham

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.

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Citations

Sep 5, 2017·Global Change Biology·Gary P GriffithJayson M Semmens
Jun 29, 2018·Ecology Letters·Taku KadoyaKevin S McCann
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Nov 3, 2021·Proceedings of the National Academy of Sciences of the United States of America·Charles A WainrightShawn P Devlin

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