TY - JOUR
T1 - Modelling mangrove dynamics in Mauritius
T2 - Implications for conservation and climate resilience
AU - Sunkur, Reshma
AU - Kantamaneni, Komali
AU - Bokhoree, Chandradeo
AU - Rathnayake, Upaka
AU - Fernando, Michael
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/6
Y1 - 2025/6
N2 - 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.
AB - 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.
KW - Climate change
KW - Mangroves
KW - Mauritius
KW - Species distribution modelling
UR - https://www.scopus.com/pages/publications/85217942441
U2 - 10.1016/j.jnc.2025.126864
DO - 10.1016/j.jnc.2025.126864
M3 - Article
AN - SCOPUS:85217942441
SN - 1617-1381
VL - 85
JO - Journal for Nature Conservation
JF - Journal for Nature Conservation
M1 - 126864
ER -