Spatiotemporal dynamics and driving forces of global mangrove change

Abstract

Mangroves are vital coastal ecosystems that provide crucial ecological functions, but they exhibit pronounced dynamics of both gain and loss over time. Although previous studies have analyzed global drivers of mangrove change, integrated models that distinguish between gains and losses while accounting for regional variability remain limited. Using a global time-series dataset of mangrove distribution from 2000 to 2022, this study characterizes the spatiotemporal patterns of mangrove gain and loss, and employs machine learning models at global and regional scales to identify key drivers. Our results indicated a modest overall increase in global mangrove area over 2000-2022, accompanied by pronounced regional variability. Southeast Asia experienced substantial losses, whereas South Asia, Africa, and Oceania generally showed gains. Regional models demonstrated superior predictive power (R² up to 0.8949) compared to the global model, emphasizing localized driver effects such as coastline accessibility, protected area status, and agricultural suitability. The coexistence of mangrove gain and loss within similar areas highlights complex, non-linear ecosystem dynamics. These findings enhance understanding of mangrove change mechanisms and offer critical insights to inform targeted conservation and climate adaptation strategies worldwide.

Keywords

Coastal wetland ecosystems / Mangrove / XGBoost model / Climate change / Sustainable Development Goal

CRediT authorship contribution statement

Peng Tian: Writing - review & editing, Writing - original draft, Formal analysis, Data curation, Conceptualization. Yanyun Yan: Writing - review & editing, Supervision. Haitao Zhang: Resources, Methodology. Yongchao Liu: Writing - review & editing, Validation, Software, Funding acquisition. Fengqi Zhang: Writing - review & editing, Software, Resources. Chao Ying: Software, Resources. Jialin Li: Writing - review & editing, Supervision, Funding acquisition.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The study was jointly funded by the National Natural Science Foundation of China (Grants No 42276234 and 42206236), and The Open Funding of Zhejiang Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research (LHGTXT-2024-007). Thanks to Liangyun Liu and his team for providing the “Time-series global 30 m wetland maps from 2000 to 2022” dataset.

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2026.100433.

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