Generic Indicators of Ecological Resilience: Inferring the Chance of a Critical Transition

TLDR

Ecological resilience is the ability of a system to persist amid perturbations, yet its interpretation has remained largely qualitative. The study introduces an emerging family of observation‑based methods for quantifying ecological resilience. The methods include critical‑slowing‑down indicators that detect slower recovery near tipping points, indirect inference from natural fluctuations and spatial patterns, and probabilistic resilience estimates derived from large datasets such as long time series or satellite imagery. These generic approaches to measuring resilience complement the system‑specific knowledge needed to infer the effects of environmental change on the resilience of complex systems.

Abstract

Ecological resilience is the ability of a system to persist in the face of perturbations. Although resilience has been a highly influential concept, its interpretation has remained largely qualitative. Here we describe an emerging family of methods for quantifying resilience on the basis of observations. A first set of methods is based on the phenomenon of critical slowing down, which implies that recovery upon small perturbations becomes slower as a system approaches a tipping point. Such slowing down can be measured experimentally but may also be indirectly inferred from changes in natural fluctuations and spatial patterns. A second group of methods aims to characterize the resilience of alternative states in probabilistic terms based on large numbers of observations as in long time series or satellite images. These generic approaches to measuring resilience complement the system-specific knowledge needed to infer the effects of environmental change on the resilience of complex systems.