Integrated MaxEnt–InVEST modelling for habitat suitability and carbon storage analysis of endangered species

Global assessments by the Intergovernmental Panel on Climate Change and the United Nations Environment Programme have emphasized that coastal wetlands and transitional brackish ecosystems are critical nature-based solutions for carbon storage and biodiversity conservation. Coastal wetlands and brackish areas adjoining the ocean also possess significant ecological value in terms of carbon storage and marine biodiversity, and in some regions serve as critical habitats for endangered species in Korea. This study selected Clithon retropictus , an endangered species, as the focal species, and employed a habitat suitability prediction model to evaluate potential habitats. The study further subdivided the identified areas to compare and analyze carbon storage, a regulating ecosystem service.The MaxEnt analysis indicated high predictive performance (AUC = 0.932 ± 0.025), and spatial autocorrelation analysis using Global Moran’s I (I = 0.724, p < 0.001) confirmed that high-suitability areas were strongly clustered along the southern coast of Korea. Coastal hotspots were concentrated in Gyeongsangnam-do and Jeollanam-do, corresponding to estuarine and vegetated tidal environments. Among the three subregions in Jeollanam-do evaluated by both MaxEnt and InVEST, Region B (0.61 / 1,025.83 t C km⁻²) ranked highest in conservation priority, followed by Region C (0.57 / 694.93 t C km⁻²) and Region A (0.56 / 678.19 t C km⁻²). Correlation analysis between MaxEnt suitability and soil carbon storage revealed a statistically significant positive relationship (p = 0.026, R² = 0.22), indicating that areas predicted as suitable for the species tend to coincide with higher carbon storage capacity.In conclusion, the integrated analysis of MaxEnt and InVEST models demonstrated the potential for incorporating both marine biodiversity conservation and ecosystem services into conservation policy. This study also presents a novel integrated modeling approach, valuable for species with limited population data or where field surveys are impractical. The effective implementation of such approaches, however, also depends on enabling governance and policy conditions. As highlighted by international assessments from the United Nations Environment Programme and the Intergovernmental Panel on Climate Change, supportive legal, institutional, and socioeconomic frameworks are essential to translate scientific insights into practical conservation outcomes.