Remotely sensed vegetation resilience in the four major estuarine ecosystems of eastern China

Abstract

Estuarine wetlands are among the most productive ecosystems on Earth, but they have been experiencing severe degradation induced by human activities and climate change worldwide. Traditional assessments of degradation mostly rely on static indicators, which are insufficient to reflect dynamical ecosystem properties such as systemic resilience. Here, we used remote sensing data and critical slowing down indicators to evaluate ecological resilience of vegetation in four major estuaries in eastern China: the Liaohe Estuary, the Yangtze Estuary, the Minjiang Estuary, and the Pearl Estuary. We identified hotspots of resilience loss during the past two decades, and then assessed relative ecological risk using the Pressure–State–Response (PSR) framework. Using random forest modeling and SHAP (SHapley Additive exPlanations) analysis, we further identified key factors associated with the classification of resilience-loss hotspots. Our results showed that all four estuaries have undergone resilience loss, with resilience loss areas accounting for ∼40% of the total study area. Moreover, hotspots of resilience loss were found to be mostly/strongly/largely associated with faster sea level rise and macroclimate conditions, but showed a spatial mismatch with relatively high ecological risk areas. Defined as resilience-loss hotspots with relatively low ecological risk, potential risk areas accounted for ∼35% of the total area. Despite still exhibiting relatively favorable environmental conditions, these areas might degrade quickly under ongoing unprecedented environmental change and thus need further monitoring. Our study combined risk assessment with resilience evaluation to provide an integrated framework detecting unrecognized ecosystem states. The framework contributes to better understanding resilience dynamics of estuarine wetlands, and has useful implications for adaptive management of these important ecosystems in a changing world.