[Prediction of suitable habitats for Chrysanthemum indicum under climate change based on Biomod2 ensemble modeling]
De-Hua Wu1, Chuan-Zhi Kang2, Wan-Heng Meng3
1State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences Beijing 100700, China Guangdong Pharmaceutical University Guangzhou 510006, China.
Abstract:
With increasing market demand for traditional Chinese medicine(TCM)and intensifying global climate change, the conservation of wild medicinal plant resources has become a critical issue. This study investigates the dynamics of suitable planting areas for Chrysanthemum indicum under both climate change and human activities. Using integrated species distribution models(SDMs) and the climate, soil, and human footprint data, this study predicted the current and future distribution patterns of this plant under different carbon emission scenarios. Key findings revealed that human activities exerted the most significant constraint on C. indicum distribution, surpassing climate and soil factors. Exclusion of human interference expanded the suitable habitats by 19.3%, with highly suitable areas extending towards north and northeast China. Under the SSP126 scenario, the area of suitable habitats was projected to have a marginal increase(+0.37%) by 2100, accompanied by expansion of highly suitable habitats along the middle and lower reaches of the Yangtze River. Conversely, the SSP585 scenario projected significant habitat contraction(-11.57%) with enlarged centroid shifts, exposing traditional highly suitable regions like Hunan and Guizhou provinces to degradation risks. This study pioneers in quantifying the overwhelming influence of human activities on C. indicum distribution and highlights the protective role of low-carbon policies in mitigating habitat loss. The outcomes provide scientific support for developing climate-resilient management strategies that balance resource utilization and ecological conservation, while demonstrating the practical value of multi-model integration in sustainable use of medicinal plant resources. Future studies should incorporate real-time monitoring data to enhance dynamic predictions, thereby help the TCM industry to respond to global change.
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