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Early warning signals of recovery in complex systems.

Christopher F ClementsMichael A McCarthyJulia L Blanchard
Published in: Nature communications (2019)
Early warning signals (EWSs) offer the hope that patterns observed in data can predict the future states of ecological systems. While a large body of research identifies such signals prior to the collapse of populations, the prediction that such signals should also be present before a system's recovery has thus far been overlooked. We assess whether EWSs are present prior to the recovery of overexploited marine systems using a trait-based ecological model and analysis of real-world fisheries data. We show that both abundance and trait-based signals are independently detectable prior to the recovery of stocks, but that combining these two signals provides the best predictions of recovery. This work suggests that the efficacy of conservation interventions aimed at restoring systems which have collapsed may be predicted prior to the recovery of the system, with direct relevance for conservation planning and policy.
Keyphrases
  • genome wide
  • public health
  • electronic health record
  • climate change
  • machine learning
  • big data
  • gene expression
  • wastewater treatment