Distribution patterns, conservation status and suitable habitat areas of highly valuable medicinal plants in China

Medicinal plants represent a critical component of biodiversity. This study focuses on the most valuable species listed in the <i>Red Data Book of Chinese Medicinal Plants</i> (RCMPs) to analyze their distribution patterns, identify diversity hotspots, assess conservation status, and predict suitable habitats across China. Results reveal that RCMPs are primarily concentrated in southwestern China, particularly the Qilian Mountains, Qinling-Bashan Mountains, and southeastern Xizang. As the hotspot threshold increases, the conservation effectiveness of provincial nature reserves is surpassed by that of national reserves. Concurrently, overall effectiveness declines, with over 16.43% of hotspot grids (containing >91.48% of species) remaining unprotected, indicating persistent conservation gaps in southwestern China and Xinjiang. Predictive modeling suggests a potential decrease in RCMPs richness in southeastern and central China. Under the RCP 2.6 and 8.5 scenarios for 2070, approximately 42.99% and 57.01% of RCMPs are projected to experience habitat contraction and expansion, respectively. Based on these findings, we propose a comprehensive priority conservation framework to inform future protection planning and promote the long-term conservation and sustainable use of China's medicinal plants.

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Publication Details

Journal
Frontiers in Plant Science
Published
2025-12-03
DOI
https://doi.org/10.3389/fpls.2025.1657997
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
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article

Distribution patterns, conservation status and suitable habitat areas of highly valuable medicinal plants in China

Bengang Zhang, Ruyu Yao, Sheng‐Xiang Yu, Jiejing Gao et al.
Frontiers in Plant Science
Species Distribution and Climate Change
article

Distribution patterns, conservation status and suitable habitat areas of highly valuable medicinal plants in China

Bengang Zhang, Ruyu Yao, Sheng‐Xiang Yu, Jiejing Gao, Sudhindra R. Gadagkar, Jianhe Wei, Yaodong Qi, Yi‐Heng Li, Zhirong Zheng, Xiuli Gao, Sanling Jin, Buhe
article en

Abstract

Medicinal plants represent a critical component of biodiversity. This study focuses on the most valuable species listed in the <i>Red Data Book of Chinese Medicinal Plants</i> (RCMPs) to analyze their distribution patterns, identify diversity hotspots, assess conservation status, and predict suitable habitats across China. Results reveal that RCMPs are primarily concentrated in southwestern China, particularly the Qilian Mountains, Qinling-Bashan Mountains, and southeastern Xizang. As the hotspot threshold increases, the conservation effectiveness of provincial nature reserves is surpassed by that of national reserves. Concurrently, overall effectiveness declines, with over 16.43% of hotspot grids (containing >91.48% of species) remaining unprotected, indicating persistent conservation gaps in southwestern China and Xinjiang. Predictive modeling suggests a potential decrease in RCMPs richness in southeastern and central China. Under the RCP 2.6 and 8.5 scenarios for 2070, approximately 42.99% and 57.01% of RCMPs are projected to experience habitat contraction and expansion, respectively. Based on these findings, we propose a comprehensive priority conservation framework to inform future protection planning and promote the long-term conservation and sustainable use of China's medicinal plants.

Frontiers in Plant ScienceVol. 16
Midwestern University (US), Kunming Institute of Botany (CN), Guizhou Normal University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Beijing Botanical Garden (CN), State Key Laboratory of Plant Genomics (CN), Hulunbuir University (CN), Research Center for Eco-Environmental Sciences (CN), Chinese Research Academy of Environmental Sciences (CN), Institute of Botany (CN), University of Chinese Academy of Sciences (CN), China Agricultural University (CN)
Openalex Percentile: Top 79%
Species Distribution and Climate Change
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