Predicting mangrove forest distribution driven by land uses in Guangdong Province
CHAO Bi-xiao1, WANG Yu-yu1, YU Wei-wei2,3, MA Zhi-yuan2,3, CHEN Guang-cheng2,3, CHEN Bin2,3, HU Wen-jia2,3
1. School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China; 2. Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; 3. Fujian Provincial Key Laboratory of Marine Ecological Conservation and Restoration, Xiamen 361005, China
Abstract：In order to explore the influence of land use option on the potential distribution of mangrove forests, MaxEnt model and Dyna-CLUE model were coupled to establish a quantitative relationship between mangrove distribution and land use, using Guangdong Province, which has the largest mangrove distribution area in China, as a research area. MaxEnt model was used to simulate the theoretical suitable area of mangroves under natural conditions. Dyna-CLUE model was used to predict land use change in 2030 under three scenarios. The simulated land use patterns were used as constrains to estimate future mangrove distribution. The results showed that the potential suitable area for mangrove forest in Guangdong Province was about 34531hm2 in 2020. The potential suitable area of mangroves could reach 47525hm2 under conservation scenario by implementing comprehensive ecological protection and restoration projects. Under the sustainable development scenario, mangrove aera would increase to 38125hm2 through returning part of current aquaculture to wetland. However, the mangrove forest areas would be reduced to 24375hm2 (i.e. a reduction of 58.61%) in 2030under the business-as-usual scenario. The model coupling method developed in this study could effectively predict the potential distribution of mangroves under different coastal land use strategies. The results of the study found that different land use policies would have a significant impact on the future mangrove distribution. The findings provide scientific support for policy makers to protect and restore mangrove forests.
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