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

利用 MaxEnt 和 ArcGIS 建模预测管花列当(列当科)的潜在分布。

阅读:4

Abstract

Phacellanthus tubiflorus 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 P. tubiflorus 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 P. tubiflorus, 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 P. tubiflorus, 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.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。