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Predicting the Potential Distribution of IOxalis debilis/I Kunth, an Invasive Species in China with a Maximum Entropy Model
by
Qin, Xinsheng
, Li, Mingxin
in
Environmental monitoring
/ Methods
/ Phytogeography
2023
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Predicting the Potential Distribution of IOxalis debilis/I Kunth, an Invasive Species in China with a Maximum Entropy Model
by
Qin, Xinsheng
, Li, Mingxin
in
Environmental monitoring
/ Methods
/ Phytogeography
2023
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Predicting the Potential Distribution of IOxalis debilis/I Kunth, an Invasive Species in China with a Maximum Entropy Model
Journal Article
Predicting the Potential Distribution of IOxalis debilis/I Kunth, an Invasive Species in China with a Maximum Entropy Model
2023
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Overview
Oxalis debilis Kunth, an invasive plant native to South America, has already spread extensively throughout various regions in China including West China, East China, Central China, and South China. It poses a certain degree of damage to the local ecosystem and demonstrates significant invasive potential. Utilizing distribution information along with environmental variables such as bioclimate, soil factors, elevation, and UV-B radiation, the MaxEnt model combined with ArcGIS was employed to forecast the potential distribution of O. debilis in China. The ROC curve was employed to assess the accuracy of the model, while the jackknife test was utilized to identify dominant environmental variables and determine their optimal values. The simulated AUC value was 0.946 ± 0.004, and the predicted results exhibited a remarkable concordance with the actual outcomes, thereby indicating that the Maxent model demonstrated a high level of confidence in its predictive capabilities. The potential distribution of O. debilis in China spanned 18,914,237 km[sup.2] , accounting for 19.70% of the total land area. This distribution was primarily observed in East, Central, and South China, with Guangdong, Guangxi, and Guizhou being identified as highly suitable habitats for O. debilis. Furthermore, it was observed that the distribution of O. debilis is primarily influenced by environmental variables such as the precipitation of the driest month, the monthly diurnal range, the mean temperature of the wettest quarter, and the isothermality. The findings can serve as a valuable point of reference for the prevention and monitoring of O. debilis spread, thereby contributing to the protection of China’s agricultural, forestry, and ecological environments. It is imperative to acknowledge the hazards associated with O. debilis, closely monitor its invasion, and prevent uncontrolled dissemination.
Publisher
MDPI AG
Subject
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