Trait-Based Prediction of Extinction Risk and Conservation Strategy for Traditional Chinese Medicinal Plants in China 基于性状的中药植物灭绝风险预测与保护策略研究

Abstract

Traded plants, including traditional Chinese medicinal (TCM) species, contribute substantially to human health and economic activity but are increasingly threatened by human pressures and climate change in the Anthropocene. However, many species lack formal extinction risk assessments (i.e., Data Deficient (DD) or Not Evaluated (NE)), making strategic conservation planning challenging. We compiled a database of 11 correlates for 580 TCM plant species recorded in the Pharmacopoeia of the People's Republic of China (2020) and built random forest models to determine the most significant drivers of threats to TCM plants. We then applied the trait-based model to predict the extinction risk of unassessed medicinal plant species. Species occurring in fewer provinces, with narrower elevational ranges, shorter stature, monocot growth form, and harvested parts other than fruits or seeds were associated with higher extinction risks. Among 95 unassessed species (DD or NE), 16 species (17%) were predicted to be threatened. Spatial mapping analysis revealed emerging threat hotspots in provinces such as Guangxi and Guangdong. Our trait-based predictive models successfully identified key drivers of extinction risk and highlighted potentially threatened medicinal plant species, revealing protection gaps and geographic concentrations of risk. For currently and potentially threatened TCM plants, we recommend urgent conservation action and targeted management interventions.