Predicting the potential distribution of (Orobanchaceae): a modeling approach using MaxEnt and ArcGIS.

Sieb. et Zucc, a vascular plant species, is believed to possess pharmacological properties including anti-fatigue and immunoenhancement. However, its distribution data is limited. Owing to the prospective medicinal relevance of this species, we proposed a comprehensive investigation for conservation and utilization. In this study, we aimed to scrutinize the plant holistically, ranging from the macroscopic to microscopic level. Specifically, we developed an ecological model using 51 records of subjected to seven environmental conditions. This model attained an exceptional area under curve (AUC ) value of 0.990 with a standard deviation of 0.004, and true skill statistic (TSS) value of 0.989, indicating a potently predictive capacity. Through the MaxEnt model, we completed a systematic depiction of the ecological niche of , revealing its primary global distribution. We carried out field surveys in the Changbai Mountain region to validate the model's accuracy and conducted observations focusing on the phenological attributes of , highlighting its largely subterranean existence. Factors such as seasonality of precipitation and temperature were found to sway its distribution, engendering comparably stable acclimation habitats. This research contributes to the data repository for facilitating subsequent studies on this species. Integrating botanical and ecological approaches, we proposed a more profound comprehension and evaluation of a species' behavior, survival strategies, and associations with other populations within specific habitats. Furthermore, this inclusive approach would assist in addressing pivotal environmental issues related to species conservation, biodiversity, and land development.