Early warning signals of population productivity regime shifts in global fisheries

Abstract

Abstract Early warning signals (EWSs) are indicators of critical transitions, and their ability to forecast ecological regime shifts depends on a priori understanding of underlying mechanisms. Conversely, performances of EWSs may indicate the mechanisms underlying observed ecological regime shifts. I evaluate the performances of two EWSs, i.e. standard deviation (SD) and autoregressive coefficient (AR1), in predicting the observed productivity regime shifts of 191 global fisheries populations. Signals of SD and AR1 are simultaneously detected in less than 50% population regime shifts and SD has higher positive likelihood ratio than AR1, suggesting critical transition may not be the major cause of observed regime shifts. However, when EWSs are correctly detected, they tend to provide more than five years warning time for more than 50% populations. The detection rate and warning time of SD and AR1 differ among fish orders, and rockfish populations show higher probability of true positive detection and longer warning time. EWSs are not definitive indicators of mechanisms underlying ecological regime shifts, but they may provide guidance in situations where ecological knowledge are limited.