Posted on June 22, 2026
Abstract
Rapid coastal development and climate change drive global coastal ecosystem degradation, prompting widespread cross-regional and multi-ecosystem marine restoration initiatives. However, the effectiveness of such initiatives remains difficult to assess nationally or globally due to the lack of scalable indicators and accessible data. Here, we present a marine ecological restoration effectiveness index as a framework for cross-regional, multi-ecosystem assessment, emphasizing data accessibility and multidimensional evaluation of restoration stability, ecological benefits, and economic benefits. Applying the index to 81 projects within 2016-2022 China’s Marine Eco-environmental Restoration Programme reveals high restoration stability, alongside significant gains in median natural coastline retention (38.62% to 79.44%), median fractional vegetation cover (36.58% to 55.29%), total carbon accumulation rate (37690.30 to 73438.87 Mg C year−1), and total ecosystem service value (5.73×109 to 8.12×109 Int$ year−1). Overall, this national application establishes a transferable tool and a state-led benchmark for assessing cross-regional, multi-ecosystem marine restoration efforts worldwide.
Acknowledgements
We are particularly grateful to the students and colleagues for their dedicated efforts in the manual interpretation and correction process. We also thank all the experts who participated in the expert survey for the analytic hierarchy process. We thank Marine Big Data Center of the Institute for Advanced Ocean Study of Ocean University of China for providing super computing cluster and the corresponding high-performance computational support, as well as the professional and technical services provided by Yujie Dong. X.B. discloses support for the research and publication of this work from Special Scientific Survey Program on Basic Science and Technology Resources [grant number 2025FY200100], Ocean Space Planning Institute, China Oceanic Development Foundation [grant number GJ1119209] and National Natural Science Foundation of China [grant number 42076010]. Xinping C. discloses support for the research of this work from the National Key R&D Program of China [grant number 2023YFC3007900]. D.S. discloses support for the research of this work from the National Natural Science Foundation of China [grant number 42476158], and Special Funds for Taishan Scholar Project [grant number tsqn202211056]. Xiao C., N.W., W.W., P.D., S.W., J.Y., L.Z. and Y.D. declare no relevant funding.
