Restoration-oriented multi-tiered framework for ecosystem degradation diagnosis: a coastal bay case study - Zhang, Dian; Yu, Weiwei; Chen, Bin; Huang, Huamei; Liao, Jianji; Feng, Lingyang; Chen, Guangcheng; Ma, Zhiyuan; Fang, Qinhua; Chen, Shunyang; Xie, Bin; Kan, Zhiyi; et al. (Frontiers in Marine Science, 2025)
IntroductionUnderstanding ecosystem degradation and estimating its extent are essential to enact decision-making policies in biodiversity conservation, ecosystem restoration, and management. Although many approaches have been proposed to identify the degradation status of an ecosystem, the heavy data burden required lacks targeted degradation information to inform such decision-making restoration policies.MethodsThis study proposes a multi-tiered decision-making framework to diagnose ecosystem degradation based on the most common restoration models that link degradation to restoration. The degradation diagnosis process can be executed step-by-step (i.e., in a physical to chemical to biological order). This study selected a limited number of coastal bay indicators from each layer, and a conceptual ecosystem response profile was applied to guide their degradation criteria settings: stepped for physical indicators, hump-shaped for chemical indicators, and smooth for biological indicators. Daya Bay in China was selected for this case study.ResultsIn total, 62% of the bay has degraded by varying degrees, including completely degraded, heavily degraded, moderately degraded, and slightly degraded percentages were 4.64%, 3.78%, 15.16%, and 38.43%, respectively. Moreover, there has been a gradual but continuous spatial change in its degradation degree from north to south and from west to east.DiscussionResults from this study can be used to identify and prioritize restoration processes. Human-assisted restoration efforts should prioritize its moderately degraded western section and its heavily degraded coastal areas along Yaling Bay and Fanhe Harbour. Our framework provides an efficient, science-based, and novel approach to diagnose the degradation status of the coast, particularly in the absence of long-term observational data, which can be effectively applied to any region or ecosystem.