Modelling mangrove dynamics in Mauritius: Implications for conservation and climate resilience

Abstract

Mangroves are vital ecosystems offering services such as coastal protection and carbon sequestration. However, climate change will substantially impact these ecosystems, especially on island states. Currently, there is a lack of detailed studies that predict changes in mangrove distribution under future climate scenarios and those that exist rarely address the unique vulnerabilities and challenges faced by island ecosystems. The present study aimed to fill in this gap by using MaxEnt to predict mangrove distribution at Le Morne, Mauritius, under two climate change scenarios (SSP126 and SSP245) across four time periods: 2021–2040, 2041–2060, 2061–2080 and 2081–2100. Key predictors used were LULC, temperature seasonality, DEM and slope. All AUC values were in the range of 0.89–0.9 indicating robust model performance. Results indicated mangrove inward migration constrained by existing land uses, potentially reducing ecosystem services such as carbon sequestration and biodiversity support. These findings are crucial for conservation efforts at Le Morne, a famous tourist site, where mangroves sustain local livelihoods. The study also supports SDGs 6, 8, 13 and 14 and the methodology can be scaled and replicated globally. Decision makers, researchers and relevant stakeholders can leverage these findings to guide proactive conservation strategies and effective planning efforts to increase climate change resilience.