The dried leaves of Turpinia arguta (Lindl.) Seem, a traditional Chinese medicinal herb, have been used for the treatment of tonsillitis, sore throat, throat arthralgia, and novel coronavirus pneumonia. This plant possesses significant medicinal, economic, and ecological values. Assessing its distribution patterns and its response to global climate change is critical for the conservation and sustainable use of its resources. This study used GIS technology and ENMTools v1.3 to select 247 distribution records of T. arguta and employed the kuenm R package (running on R v4.4.3, package version 2.0.1) to optimize the MaxEnt model parameters. Based on current and future climate data, this study predicted the current and future potential suitable areas of T. arguta in China during the periods of the 2050s (2041–2060), 2070s (2061–2080), and 2090s (2081–2100) under three SSP emission scenarios (SSP126, SSP245, and SSP585). Additionally, it identified the key environmental variables driving its distribution patterns and conducted a quality suitability regionalization analysis using sample chemical content data. The results show that under current climatic conditions, the highly suitable areas for T. arguta are mainly distributed across five provinces: Jiangxi, Guangdong, Guangxi, Fujian, and Hunan. The distribution of T. arguta is primarily influenced by precipitation and temperature. The suitable ranges of key environmental variables are as follows: average temperature in September > 26 °C (optimal range: 28–32 °C), precipitation in April 175–250 mm, precipitation in September 100–160 mm, annual mean temperature 20–30 °C (optimal range > 22.5 °C), and annual precipitation 1500–2000 mm (peak value: 1750 mm). Quality analysis reveals a positive correlation between ligustroflavone content and the mean diurnal temperature range, as well as between rhoifolin content and soil sand content. Compared with current suitable areas, the total suitable areas of T. arguta are projected to contract by varying degrees across all scenarios in the future. This study will provide a robust scientific basis for guiding the sustainable development/utilization of its resources and optimizing artificial cultivation practices.
Hu et al. (Sun,) studied this question.