Early warning signals, nonlinearity, and signs of hysteresis in real ecosystems

Early warning signals (EWS) might dramatically improve our ability to manage nonlinear ecological change. However, the degree to which theoretical EWS predictions are supported in empirical systems remains unclear. The goal of this study is to make recommendations for identifying the types of ecological transitions that are expected to show EWS. We conducted a review and meta-analysis of published studies and comparative analysis of eight northeast Pacific Ocean time series to illustrate the importance of testing for nonlinearity in empirical EWS studies. We found that published studies demonstrating nonlinearity in ecosystem dynamics are more likely to support EWS predictions than studies with linear or undetermined dynamics. The northeast Pacific time series in our analysis were often too short for formal tests of nonlinearity, a common problem in empirical studies. To assess the evidence for nonlinear dynamics in these data, we tested for state-dependent driver-response relationships consistent with hysteresis, a central feature of nonlinear ecological models. This analysis supported the results of the literature meta-analysis. Four time series with driver-response relationships consistent with hysteresis generally supported theoretical EWS predictions, while four without evidence of hysteresis failed to support EWS predictions. Theoretical support for EWS is largely generated from nonlinear models, and we conclude that tests for either nonlinear dynamics or hysteresis are needed before employing EWS.