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Early warning signals of recovery in complex systems
Citation
Clements, CF and McCarthy, MA and Blanchard, JL, Early warning signals of recovery in complex systems, Nature Communications, 10, (1) Article 1681. ISSN 2041-1723 (2019) [Refereed Article]
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Copyright Statement
Copyright 2019 the authors. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/
DOI: doi:10.1038/s41467-019-09684-y
Abstract
Early warning signals (EWSs) offer the hope that patterns observed in data can predict the future states of ecological systems. While a large body of research identifies such signals prior to the collapse of populations, the prediction that such signals should also be present before a system’s recovery has thus far been overlooked. We assess whether EWSs are present prior to the recovery of overexploited marine systems using a trait-based ecological model and analysis of real-world fisheries data. We show that both abundance and trait-based signals are independently detectable prior to the recovery of stocks, but that combining these two signals provides the best predictions of recovery. This work suggests that the efficacy of conservation interventions aimed at restoring systems which have collapsed may be predicted prior to the recovery of the system, with direct relevance for conservation planning and policy.
Item Details
Item Type: | Refereed Article |
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Keywords: | early warning signals, tipping points, marine fish populations |
Research Division: | Environmental Sciences |
Research Group: | Environmental management |
Research Field: | Conservation and biodiversity |
Objective Division: | Animal Production and Animal Primary Products |
Objective Group: | Fisheries - wild caught |
Objective Field: | Fisheries - wild caught not elsewhere classified |
UTAS Author: | Blanchard, JL (Professor Julia Blanchard) |
ID Code: | 144013 |
Year Published: | 2019 |
Funding Support: | Australian Research Council (DP170104240) |
Web of Science® Times Cited: | 30 |
Deposited By: | Ecology and Biodiversity |
Deposited On: | 2021-04-14 |
Last Modified: | 2021-05-04 |
Downloads: | 17 View Download Statistics |
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