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Prediction of the potentially suitable areas of Leonurus japonicus in China based on future climate change using the optimized MaxEnt model
- Source :
- Ecology and Evolution, Vol 13, Iss 10, Pp n/a-n/a (2023)
- Publication Year :
- 2023
- Publisher :
- Wiley, 2023.
-
Abstract
- Abstract Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126‐2090s scenario and the highest under the SSP585‐2090s scenario.
- Subjects :
- climate change
ENMeval
Leonurus japonicus
MaxEnt
niche modeling
Ecology
QH540-549.5
Subjects
Details
- Language :
- English
- ISSN :
- 20457758
- Volume :
- 13
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- Ecology and Evolution
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.85cea5576b9342a7a2a0c699fec98567
- Document Type :
- article
- Full Text :
- https://doi.org/10.1002/ece3.10597