ArticleScientific reports2025
Biomod2 modeling for predicting the potential ecological distribution of Lilium Davidii var. Willmottiae (E. H. Wilson) Raffill.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Optimized MaxEnt Models Predict Species-Specific Habitat Suitability Shifts for Three Dryland Fabaceae Species in Xinjiang.Plants (Basel, Switzerland) · 2026Article
- Assessing Habitat Suitability and Climate-Change Responses of Raptors in Hunan Province, China, Using Ensemble Species Distribution Models.Animals : an open access journal from MDPI · 2026Article
- Predicting the global risk of chikungunya virus under climate change using ensemble species distribution models.Frontiers in cellular and infection microbiology · 2026Article
- Article
- Assessing the impacts of climate change on the potential distribution of the medicinal plantFrontiers in plant science · 2026Article
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Authors and funding
6 authors.
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Abstract
Lilium davidii var. willmottiae (E. H. Wilson) Raffill (L. davidii), a unique sweet lily variety globally, has been cultivated in China for over a century. It holds significant cultural and economic value, recognized as a national geographical indication product. This study aimed to accurately simulate and predict the potential suitable habitats for L. davidii in China using species distribution modeling (SDM) techniques and comprehensive environmental data. By leveraging geographic distribution data of L. davidii within China and integrating it with climate and topographical variables within the biomod2 modeling framework, the potential suitable habitats for L. davidii under current conditions were assessed. An in-depth analysis of the key environmental variables determining its distribution pattern was also conducted. The biomod2 ensemble model demonstrated high accuracy in identifying suitable habitats for L. davidii, achieving an AUC of 0.855 and a TSS of 0.957. The analysis revealed that temperature seasonality (bio4), elevation (Elev), and the minimum temperature of the coldest month (bio6) are the core environmental factors significantly influencing its suitable distribution range. These findings enhance the scientific understanding of the ecological adaptability of L. davidii and provide a scientific basis for optimizing planting layouts, precision agriculture practices, rational expansion of planting areas, germplasm resource protection, and formulating sustainable utilization strategies. Ultimately, this research contributes to promoting the development of specialty agriculture and protecting the ecological environment for this important species.
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