Journal Article

Including trait-based early warning signals helps predict population collapse

Clements, Christopher F., Ozgul, Arpat

2016

Overview

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. Predicting population collapse by monitoring key early warning signals in time-series data may highlight when interventions are needed. Here, the authors show that including information on phenotypic traits like body size can more accurately predict critical transitions than abundance data alone.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/158/1745 / 64 / Body Size / Ciliophora / Colony Collapse / Demography / Ecosystem / Endangered & extinct species / Extinction / Hearing protection / Humanities and Social Sciences / multidisciplinary / Paramecium caudatum / Phenotype / Population Dynamics / Science / Science (multidisciplinary) / Time series / Trends