Spatiotemporal Patterns of Carbon Storage in Hainan Bamen Bay Mangroves Based on a Decision Tree Classification

Mangroves play a vital role in climate change mitigation due to their exceptional carbon sequestration capacity, as a highly productive blue carbon ecosystem. Current research on mangroves in Bamen Bay has been limited to short-term observations, lacking systematic analysis of long-term spatiotemporal dynamics and carbon storage. This study developed a decision tree method integrating SWIR1, NDVI, and NDMI, achieving high-accuracy mangrove mapping. Spatiotemporal dynamics from 2000 to 2020 were analyzed using the dynamic degree model, standard deviation ellipse, centroid model, and landscape pattern indices. Carbon storage was quantified through the InVEST model, grey prediction model, and scenario analysis. The results reveal significant mangrove expansion, with substantial net growth. Spatial aggregation strengthened despite persistent fragmentation, characterized by a shrinking standard deviation ellipse and northeastward centroid migration. Carbon storage increased considerably over the two decades. Under the baseline scenario, carbon storage would continue to grow by mid-century. Among alternative scenarios, the Green Revival scenario achieves the highest carbon storage, outperforming the baseline, while the Hard Preservation scenario achieves slightly above the baseline. The Missed Opportunity and Ecological Collapse scenarios project declines. This study provides a valuable framework for mangrove monitoring, carbon assessment, and ecological restoration, supporting regional conservation and carbon neutrality goals.