Tang J M, Xuan Z, Yin X J, et al. Simulation of Geographical Distribution and Identification of Priority Protected Areas of the Extremely Small Populations of Oyama sinensis[J]. Journal of Southwest Forestry University, 2025, 45(5): 1–8. DOI: 10.11929/j.swfu.202407027
Citation: Tang J M, Xuan Z, Yin X J, et al. Simulation of Geographical Distribution and Identification of Priority Protected Areas of the Extremely Small Populations of Oyama sinensis[J]. Journal of Southwest Forestry University, 2025, 45(5): 1–8. DOI: 10.11929/j.swfu.202407027

Simulation of Geographical Distribution and Identification of Priority Protected Areas of the Extremely Small Populations of Oyama sinensis

  • Based on the natural ecological factors, such as climate, soil and topography, combined with Oyama sinensis distribution sample data, the optimized Maximum Entropy Model(MaxEnt) was used to predict the potentially suitable distribution areas of O. sinensis. On this basis, according to the human disturbance factor calculated by the entropy assignment method, combined with the Marxan model, the study identified the priority conservation areas and explored the conservation vacancy areas for O. sinensis. The results showed that the AUC value of the optimized MaxEnt model was 0.969, indicating that the optimized MaxEnt model predicted extremely well. The potentially suitable areas for O. sinensis were roughly banded from Jinyang County, Liangshan Yi Autonomous Prefecture, to Nanjiang County, Bazhong City. The main natural ecological factors affecting it distribution were the annual difference in temperature, the precipitation in the driest month, the geological hazards, the altitude, the seasonal changes in temperature and the total exchangeable bases in the topsoil. Human disturbance factors were taken as the cost of protection, and the Marxan model was applied to identify the conservation vacancies of O. sinensis mainly located in the Tianquan River Nature Reserve, Gongga Mountain Nature Reserve, and the areas near the Giant Panda National Parks, Erlang Mountain National Forest Parks, and Hailuogou National Forest Park.
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