Predicting the Future Geographic Distribution of the Traditional Chinese Medicinal Plant Epimedium acuminatum Franch. in China Using Ensemble Models Based on Biomod2

This study employs the Biomod2 model, along with 22 bioclimatic variables, to predict the geographic distribution of the medicinal plant <i>Epimedium acuminatum</i> Franch. for the current period and three future timeframes (2050s, 2070s, and 2090s). Ultimately, 11 key environmental variables were identified as critical for assessing the habitat suitability of the medicinal plant. These include the annual mean temperature (Bio 1), isothermally (Bio 3), temperature seasonality (Bio 4), maximum temperature of the warmest month (Bio 5), minimum temperature of the coldest month (Bio 6), mean temperature of the driest quarter (Bio 9), mean temperature of the coldest quarter (Bio 11), precipitation of the driest quarter (Bio 17), elevation (Elev), aspect, and slope. The results indicate that the current high suitability areas are primarily distributed across Yunnan, Chongqing, Sichuan, Hunan, Guangxi, and Hubei provinces. In the future, the extent of high suitability areas is expected to increase. This study aims to provide a theoretical reference for the conservation of <i>E. acuminatum</i> genetic resources from a geographic distribution perspective.

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Publication Details

Journal
Plants
Published
2025-03-30
DOI
https://doi.org/10.3390/plants14071065
Citations
6
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
11.03

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article

Predicting the Future Geographic Distribution of the Traditional Chinese Medicinal Plant Epimedium acuminatum Franch. in China Using Ensemble Models Based on Biomod2

Zhihang Zhuo, Danping Xu, Biyu Liu, Yaqin Peng et al.
6 citations
Plants
Species Distribution and Climate Change
11.03
article

Predicting the Future Geographic Distribution of the Traditional Chinese Medicinal Plant Epimedium acuminatum Franch. in China Using Ensemble Models Based on Biomod2

Zhihang Zhuo, Danping Xu, Biyu Liu, Yaqin Peng, Zhiling Wang
article en
6 citations

Abstract

This study employs the Biomod2 model, along with 22 bioclimatic variables, to predict the geographic distribution of the medicinal plant <i>Epimedium acuminatum</i> Franch. for the current period and three future timeframes (2050s, 2070s, and 2090s). Ultimately, 11 key environmental variables were identified as critical for assessing the habitat suitability of the medicinal plant. These include the annual mean temperature (Bio 1), isothermally (Bio 3), temperature seasonality (Bio 4), maximum temperature of the warmest month (Bio 5), minimum temperature of the coldest month (Bio 6), mean temperature of the driest quarter (Bio 9), mean temperature of the coldest quarter (Bio 11), precipitation of the driest quarter (Bio 17), elevation (Elev), aspect, and slope. The results indicate that the current high suitability areas are primarily distributed across Yunnan, Chongqing, Sichuan, Hunan, Guangxi, and Hubei provinces. In the future, the extent of high suitability areas is expected to increase. This study aims to provide a theoretical reference for the conservation of <i>E. acuminatum</i> genetic resources from a geographic distribution perspective.

PlantsVol. 14(7)
China West Normal University (CN)
Fundamental Research Funds of China West Normal University
Life in Land
Openalex Percentile: Top 2%
Species Distribution and Climate Change
11.03
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Predicting the Future Geographic Distribution of the Traditional Chinese Medicinal Plant Epimedium acuminatum Franch. in China Using Ensemble Models Based on Biomod2 — Zhihang Zhuo, Danping Xu, et al. · Plants (2025) | TGRS Research Map | TGRS