Early warning indicators capture catastrophic transitions driven by explicit rates of environmental change

Abstract

In response to external changes, ecosystems can undergo catastrophic transitions. Early warning indicators aim to predict such transitions based on the phenomenon of critical slowing down at bifurcation points found under a constant environment. When an explicit rate of environmental change is considered, catastrophic transitions can become distinct phenomena from bifurcations, and result from a delayed response to noncatastrophic bifurcations. We use a trophic metacommunity model where transitions in time series and bifurcations of the system are distinct phenomena. We calculate early warning indicators from the time series of the continually changing system and show that they predict not the bifurcation of the underlying system but the actual catastrophic transition driven by the explicit rate of change. Predictions based on the bifurcation structure could miss catastrophic transitions that can still be captured by early warning signals calculated from time series. Our results expand the repertoire of mechanistic models used to anticipate catastrophic transitions to nonequilibrium ecological systems exposed to a constant rate of environmental change.

Stochastic dynamics of phycocyanin in years of contrasting phosphorus load

“…Long passage times could be dangerous if decision-makers assume that the ecosystem has a single attractor and cannot transition to a different state. In such cases, statistical early warnings could provide critical information in time to prevent harm (Arumugam et al, 2024;Biggs et al, 2009;Pace et al, 2017). Better environmental decisions depend on the good characterization of stochastic ecosystem dynamics, and the necessary evidence can only come from long-term frequent data as presented here.…”