Ecological Niche Modeling of Three Fangfeng Species Under Present and Future Climate Scenarios

Global climate change poses a threat to medicinal plants by altering their habitats. This study assessed the impacts of climate change on three medicinally important species (<i>Saposhnikovia divaricata</i>, <i>Seseli mairei</i>, and <i>Ligusticopsis brachyloba</i>) across China via RF and MaxEnt models. We combined species occurrence data with bioclimatic, topographic, and soil variables to project their current and future distributions under current and future climate scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5 for both the 2050s and 2070s). Both models demonstrated strong predictive performance, with RF showing superior validation metrics. The potential distributions of three species are jointly influenced by climatic and topographic factors, although each species is predominantly governed by distinct drivers. <i>Saposhnikovia divaricata</i> is primarily regulated by altitude, precipitation during the warmest quarter (bio18), precipitation seasonality (bio15). <i>Seseli mairei</i> exhibits the strongest response to temperature seasonality (bio4) and annual precipitation (bio12). <i>Ligusticopsis brachyloba</i> is chiefly governed by temperature seasonality (bio4) and mean diurnal temperature range (bio7). The current distributions reveal that <i>S. divaricata,</i> primarily in northeastern and northern China, extends into central transitional zones, whereas <i>S. mairei</i> and <i>L. brachyloba</i> predominantly occupy southwestern regions. Future projections indicate (1) range contraction and southwestward migration for <i>S. divaricata</i>; (2) potential shift in distribution toward the Hengduan Mountains for <i>S. mairei</i>, although with reduced habitat stability; and (3) westward shifts for <i>L. brachyloba</i>, with model-dependent variability. Most critically, all species are projected to undergo reductions in stable habitat area. <i>L. brachyloba</i> is predicted to experience the greatest proportional decline, with the MaxEnt model estimating a 25.5% reduction. In contrast, <i>S. divaricata</i> is projected to show the smallest relative decline, although the RF model still forecasts a substantial 17.03% decrease. These findings provide critical baseline data for conservation prioritization and sustainable management of medicinal plant resources under changing climate conditions.