Integrating <scp>MaxEnt</scp> and <scp>PLUS</scp> for Predictive Modeling of Mangrove Suitability and Land Use Impacts in Coastal Guangdong, China

Mangroves, as one of the most efficient carbon-sequestering ecosystems globally, provide critical ecological services including coastal protection, water purification, and biodiversity conservation. This study integrates remote sensing and ecological modeling to assess the spatial-temporal dynamics and restoration potential of mangroves in coastal Guangdong, China, under alternative socioeconomic pathways. Using Sentinel-2 imagery and hybrid classification, we mapped the 2020 mangrove distribution with high accuracy, estimating a total area of 110.28 km<sup>2</sup>. The MaxEnt model, driven by 37 climatic, hydrological, topographic, soil, and land use/land cover (LUCC) variables, identified a maximum potential habitat area of 1908 km<sup>2</sup>. However, when LULC constraints were introduced, the suitable area decreased to 1221 km<sup>2</sup>, highlighting LULC as a major limiting factor. Variable importance analysis revealed that LULC (38.2%), annual temperature range (20.8%), and distance to coastline (11.7%) jointly explained over 70% of the variation in habitat suitability, underscoring the interplay of anthropogenic and natural drivers. By coupling MaxEnt with LULC projections from the Patch-generating Land Use Simulation (PLUS) model under three SSP scenarios for 2040, we further identified dominant land-use constraints and generated multi-scenario distribution predictions. Results suggest that the SSP126 (low-emission) pathway provides the greatest restoration opportunities, whereas SSP585 (high-emission) favors limited climatic suitability gains but widespread habitat loss due to urban expansion. Our findings emphasize that integrating ecological niche modeling with advanced LULC simulation provides a novel decision-support framework that links potential habitat prediction with realistic land-use governance. The study not only identifies high-priority restoration and conservation zones but also offers actionable strategies-such as pond-to-forest conversion, hydrological connectivity restoration, and zoning-based adaptive management-to reconcile coastal development with long-term ecosystem resilience.

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Journal
Ecology and Evolution
Published
2025-12-01
DOI
https://doi.org/10.1002/ece3.72561
Primary Topic
Land Use and Ecosystem Services
Type
article
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article

Integrating MaxEnt and PLUS for Predictive Modeling of Mangrove Suitability and Land Use Impacts in Coastal Guangdong, China

Lihao Yao, Ruoying Tang, Zixin Liang, Géza Várady et al.
Ecology and Evolution
Land Use and Ecosystem Services
article

Integrating MaxEnt and PLUS for Predictive Modeling of Mangrove Suitability and Land Use Impacts in Coastal Guangdong, China

Lihao Yao, Ruoying Tang, Zixin Liang, Géza Várady, Rui Zhang
article en

Abstract

Mangroves, as one of the most efficient carbon-sequestering ecosystems globally, provide critical ecological services including coastal protection, water purification, and biodiversity conservation. This study integrates remote sensing and ecological modeling to assess the spatial-temporal dynamics and restoration potential of mangroves in coastal Guangdong, China, under alternative socioeconomic pathways. Using Sentinel-2 imagery and hybrid classification, we mapped the 2020 mangrove distribution with high accuracy, estimating a total area of 110.28 km<sup>2</sup>. The MaxEnt model, driven by 37 climatic, hydrological, topographic, soil, and land use/land cover (LUCC) variables, identified a maximum potential habitat area of 1908 km<sup>2</sup>. However, when LULC constraints were introduced, the suitable area decreased to 1221 km<sup>2</sup>, highlighting LULC as a major limiting factor. Variable importance analysis revealed that LULC (38.2%), annual temperature range (20.8%), and distance to coastline (11.7%) jointly explained over 70% of the variation in habitat suitability, underscoring the interplay of anthropogenic and natural drivers. By coupling MaxEnt with LULC projections from the Patch-generating Land Use Simulation (PLUS) model under three SSP scenarios for 2040, we further identified dominant land-use constraints and generated multi-scenario distribution predictions. Results suggest that the SSP126 (low-emission) pathway provides the greatest restoration opportunities, whereas SSP585 (high-emission) favors limited climatic suitability gains but widespread habitat loss due to urban expansion. Our findings emphasize that integrating ecological niche modeling with advanced LULC simulation provides a novel decision-support framework that links potential habitat prediction with realistic land-use governance. The study not only identifies high-priority restoration and conservation zones but also offers actionable strategies-such as pond-to-forest conversion, hydrological connectivity restoration, and zoning-based adaptive management-to reconcile coastal development with long-term ecosystem resilience.

Ecology and EvolutionVol. 15(12)
Guangdong Ocean University (CN), University of Pecs (HU)
Openalex Percentile: Top 63%
Land Use and Ecosystem Services
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