Dynamic Estimation of Mangrove Carbon Storage in Hainan Island Based on the InVEST-PLUS Model

Mangrove ecosystems are pivotal to the global carbon budget. However, there is still a dearth of research addressing the impact of regional mangrove land use and land cover change (LUCC) on carbon sequestration and its associated spatial distribution patterns. To investigate the impact of different development scenarios on the carbon storage capacity of mangrove ecosystems, we focused on Hainan Island. We used LUCC data from 2010 to 2020 from mangrove-inhabited regions. The Markov-PLUS model was applied to predict the spatiotemporal dynamics of mangrove coverage under the natural increase scenario (NIS) and the mangrove protection scenario (MPS) over the next 40 years. Carbon storage was estimated using the InVEST model based on field-measured carbon density data. The outcomes show the following: (1) The Markov-PLUS model, with an overall accuracy of 0.88 and a Kappa coefficient of 0.82, is suitable for predicting mangrove distribution patterns on Hainan Island. (2) Environmental factors were the main drivers of historical mangrove changes on Hainan Island, explaining 54% of the variance, with elevation, temperature, and precipitation each contributing over 13%. (3) From 2025 to 2065, the mangrove area on Hainan Island is projected to increase by approximately 12,505.68 ha, mainly through conversions from forest land (12.73% under NIS and 12.37% under MPS) and agricultural land (39.72% under NIS and 34.53% under MPS). (4) The carbon storage increment within Hainan Island’s mangroves is projected at 2.71 TgC over the whole island, with notable increases expected in the eastern, northern, and northwestern regions, and modest gains in other areas. In this study, we comprehensively investigated the spatiotemporal dynamics and future trends of carbon storage in the mangroves of Hainan Island, offering invaluable guidance for the long-term management of mangrove ecosystems and the realization of carbon neutrality goals by 2060.