Including trait-based early warning signals helps predict population collapse.
- Clements CF Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich CH-8057, Switzerland.
- Ozgul A Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich CH-8057, Switzerland.
- 2016-03-25
Published in:
- Nature communications. - 2016
English
Foreseeing population collapse is an on-going target in ecology, and this has led to the development of early warning signals based on expected changes in leading indicators before a bifurcation. Such signals have been sought for in abundance time-series data on a population of interest, with varying degrees of success. Here we move beyond these established methods by including parallel time-series data of abundance and fitness-related trait dynamics. Using data from a microcosm experiment, we show that including information on the dynamics of phenotypic traits such as body size into composite early warning indices can produce more accurate inferences of whether a population is approaching a critical transition than using abundance time-series alone. By including fitness-related trait information alongside traditional abundance-based early warning signals in a single metric of risk, our generalizable approach provides a powerful new way to assess what populations may be on the verge of collapse.
- Language
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- English
- Open access status
- gold
- Identifiers
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- DOI 10.1038/ncomms10984
- PMID 27009968
- Persistent URL
- https://sonar.rero.ch/global/documents/147311
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