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Predicting Potential Habitat of Aconitumcarmichaeli Debeaux in China Based onThree Species Distribution Models
Summary
Researchers applied three species distribution models (MaxEnt, GARP, and Bioclim) using 14 environmental variables and 449 specimen records to predict suitable habitat for the medicinal plant Aconitum carmichaelii Debeaux across China. All three models achieved AUC values above 0.85, identifying the highest-quality habitats in Sichuan, western Hubei, southern Shaanxi, and northern Guizhou provinces, with key climatic drivers identified through Jackknife analysis.
Aconitum carmichaelii Debeaux is a perennial herb and medicinal plant, which has the effects of warming Yang and dispelling cold, warming meridians and relieving pain, dispelling wind and dehumidification, supplementing fire and helping Yang. In recent years, affected by the destruction of shrubs and climate warming, the habitat of A. carmichaeli wild resources has been seriously damaged, indicating of great significance to the artificial protection and cultivation of A. carmichaeli to predict its potential suitable habitat using species distribution models (SDMs). In this paper, 14 environmental variables and 449 specimen distribution records were applied to three models, i.e. MaxEnt, GARP and Bioclim to simulate the distribution of A. carmichaeli. Our results showed that, the AUC average values of the three models were all above 0.85 and the Kappa average values were above 0.75, justifying their applications for predicting the potential areas of A. carmichaeli. Furthermore, simulation of MaxEnt showed that, the highly suitable habitats were concentrated in the middle east of Sichuan (17.0710 4 km 2 ), western Hubei (7.3410 4 km 2 ), southern Shaanxi (7.210 4 km 2 ), north central Guizhou (6.7410 4 km 2 ), eastern Chongqing (5.6210 4 km 2 ) and western Hunan (5.2110 4 km 2 ) and scattered in the middle of Zhejiang (3.0710 4 km 2 ), the southwest Anhui (1.8710 4 km 2 ) and western Henan (1.4310 4 km 2 ). Jackknife test and response curves determined that the key variables affecting the distribution of A. carmichaeli were annual precipitation (751.25-1580.72 mm), precipitation of warmest quarter (422.71-717.21 mm), min temperature of coldest month (-6.85-3.12C), temperature annual range (24.83-31.97C), elevation (145.87-2769.22 m) and human footprint (<4.01).
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