title: Including trait-based early warning signals helps predict population collapse.
abstract: 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.
authors.affiliation: Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich CH-8057, Switzerland.
authors.forename: Christopher F
authors.initials: CF
authors.lastname: Clements
authors.affiliation: Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich CH-8057, Switzerland.
authors.forename: Arpat
authors.initials: A
authors.lastname: Ozgul
mesh_terms: D049628:Body Size; D016798:Ciliophora; D056631:Colony Collapse; D017753:Ecosystem; D048488:Paramecium caudatum; D010641:Phenotype; D011157:Population Dynamics