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Predicting Mangrove Distributions in the Beibu Gulf, Guangxi, China, Using the MaxEnt Model: Determining Tree Species Selection
Mangrove restoration is challenging within protected coastal habitats. Predicting the dominant species distributions in mangrove communities is essential for appropriate species selection and spatial planning for restoration. We explored the spatial distributions of six mangrove species, including their related environmental factors, thereby identifying potentially suitable habitats for mangrove protection and restoration. Based on six dominant mangrove species present in the Beibu Gulf, Guangxi, China, we used a linear correlation analysis to screen environmental factors. In addition, we used the maximum entropy model to analyze the spatial distributions of potential mangrove afforestation areas. Based on the spatial superposition analysis, we identified mangrove conservation and restoration hot spots. The findings indicate that topographic and bioclimatic factors affect the distribution of suitable mangrove habitats in the Beibu Gulf, followed by land use type, salinity, and substrate type. We identified 13,816 hm2 of prime mangrove habitat in the Beibu Gulf that is primarily distributed in protected areas. The protection rate for existing mangroves was 42.62%. According to the predicted spatial distributions of the mangrove plants, the findings suggest that mangrove restoration should be based on suitable species and site selection.
Predicting Mangrove Distributions in the Beibu Gulf, Guangxi, China, Using the MaxEnt Model: Determining Tree Species Selection
Mangrove restoration is challenging within protected coastal habitats. Predicting the dominant species distributions in mangrove communities is essential for appropriate species selection and spatial planning for restoration. We explored the spatial distributions of six mangrove species, including their related environmental factors, thereby identifying potentially suitable habitats for mangrove protection and restoration. Based on six dominant mangrove species present in the Beibu Gulf, Guangxi, China, we used a linear correlation analysis to screen environmental factors. In addition, we used the maximum entropy model to analyze the spatial distributions of potential mangrove afforestation areas. Based on the spatial superposition analysis, we identified mangrove conservation and restoration hot spots. The findings indicate that topographic and bioclimatic factors affect the distribution of suitable mangrove habitats in the Beibu Gulf, followed by land use type, salinity, and substrate type. We identified 13,816 hm2 of prime mangrove habitat in the Beibu Gulf that is primarily distributed in protected areas. The protection rate for existing mangroves was 42.62%. According to the predicted spatial distributions of the mangrove plants, the findings suggest that mangrove restoration should be based on suitable species and site selection.
Predicting Mangrove Distributions in the Beibu Gulf, Guangxi, China, Using the MaxEnt Model: Determining Tree Species Selection
Lifeng Li (author) / Wenai Liu (author) / Jingwen Ai (author) / Shuangjiao Cai (author) / Jianwen Dong (author)
2023
Article (Journal)
Electronic Resource
Unknown
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