Predicting Potential Habitats of the Endangered Mangrove Species Acanthus ebracteatus Under Current and Future Climatic Scenarios Based on MaxEnt and OPGD Models

Climate change threatens coastal biodiversity, necessitating proactive conservation for endangered species like the mangrove <i>Acanthus ebracteatus.</i> This study integrated the MaxEnt and OPGD models to simulate its potential suitable habitats under current and three future SSP scenarios (SSP126, SSP245, and SSP585). Based on the MaxEnt model, sea surface salinity (SSS_range), sea surface temperature (SST_max), soil texture (T_silt, T_sand), and annual precipitation (Bio12) were identified as the dominant factors influencing its distribution, with SSS_range emerging as the key constraint. Furthermore, interaction analysis using the OPGD model revealed significant synergistic effects, particularly between salinity and soil properties (q > 0.8), underscoring the importance of multi-factor interactions in ecological niche modeling. Under the three SSP scenarios, the suitable habitat is projected to expand northeastward, accompanied by a poleward shift in the distribution centroid, driven predominantly by warming temperatures and altered rainfall patterns. KDE analysis revealed that existing protected areas do not fully cover regions with high habitat suitability. We propose a stratified conservation strategy that enhances in situ protection in core zones, initiates assisted restoration in potential habitats, and promotes experimental outplanting in future climatically suitable areas. This study provides scientific insights for the conservation and management of <i>Acanthus ebracteatus</i> under global climate change.

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Publication Details

Journal
Plants
Published
2025-09-10
DOI
https://doi.org/10.3390/plants14182827
Citations
2
Primary Topic
Coastal wetland ecosystem dynamics
Type
article
Field-Weighted Citation Impact
3.43
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article

Predicting Potential Habitats of the Endangered Mangrove Species Acanthus ebracteatus Under Current and Future Climatic Scenarios Based on MaxEnt and OPGD Models

Qianqi Qiu, Chunhua Xia, Yi Wang, Chongcheng Yang et al.
2 citations
Plants
Coastal wetland ecosystem dynamics
3.43
article

Predicting Potential Habitats of the Endangered Mangrove Species Acanthus ebracteatus Under Current and Future Climatic Scenarios Based on MaxEnt and OPGD Models

Qianqi Qiu, Chunhua Xia, Yi Wang, Chongcheng Yang, Liuping Wu, Jiaqi Chen, Zhixin Li
article en
2 citations

Abstract

Climate change threatens coastal biodiversity, necessitating proactive conservation for endangered species like the mangrove <i>Acanthus ebracteatus.</i> This study integrated the MaxEnt and OPGD models to simulate its potential suitable habitats under current and three future SSP scenarios (SSP126, SSP245, and SSP585). Based on the MaxEnt model, sea surface salinity (SSS_range), sea surface temperature (SST_max), soil texture (T_silt, T_sand), and annual precipitation (Bio12) were identified as the dominant factors influencing its distribution, with SSS_range emerging as the key constraint. Furthermore, interaction analysis using the OPGD model revealed significant synergistic effects, particularly between salinity and soil properties (q > 0.8), underscoring the importance of multi-factor interactions in ecological niche modeling. Under the three SSP scenarios, the suitable habitat is projected to expand northeastward, accompanied by a poleward shift in the distribution centroid, driven predominantly by warming temperatures and altered rainfall patterns. KDE analysis revealed that existing protected areas do not fully cover regions with high habitat suitability. We propose a stratified conservation strategy that enhances in situ protection in core zones, initiates assisted restoration in potential habitats, and promotes experimental outplanting in future climatically suitable areas. This study provides scientific insights for the conservation and management of <i>Acanthus ebracteatus</i> under global climate change.

PlantsVol. 14(18)
Guangdong Ocean University (CN)
Openalex Percentile: Top 8%
Coastal wetland ecosystem dynamics
3.43
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