Supporting exploration and sustainable utilization of the medicinal plant Uncaria rhynchophylla in Kyushu, Japan...

Sustainable utilization of wild medicinal plant resources requires reproducible approaches for locating and managing natural populations. In Japan, exploration and resource planning for wild medicinal plants rely heavily on expert knowledge, and reproducible approaches remain scarce. We developed a species distribution model (SDM) for Uncaria rhynchophylla (Rubiaceae), a botanical source of the crude drug Uncaria Hook used in Kampo medicine, to estimate its potential distribution and identify major environmental correlates in the Kyushu region, southern Japan. Using 122 occurrence records collected from 2021 to 2023 and nine environmental predictors, MaxEnt models were trained with background points and bootstrap replicates. Because mean minimum winter temperature in January and mean maximum summer temperature in August were highly correlated, three candidate models were compared using the small-sample corrected Akaike information criterion (AICc), test omission rates, and test area under the receiver operating characteristic curve (AUC). The model including winter minimum temperature was best supported (test AUC = 0.82; test omission rate = 24%), whereas adding summer maximum temperature provided limited improvement (ΔAICc = + 75.75). Variable importance and jackknife tests ranked winter minimum temperature as the most influential predictor, followed by slope angle and distance to the nearest rivers. The suitable area, defined using the maximum training sensitivity plus specificity (MTSS) threshold, covered 10,595 km² (25.9% of the terrestrial area) and formed continuous zones across hilly and low-montane regions. Targeted surveys in high-suitability areas confirmed three additional sites in the Kirishima Mountains. Overall, integrating SDM and geographic information systems provides a reproducible, data-driven, decision-support framework for the exploration, planning of sustainable harvesting, and resource management of wild medicinal plants.