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Article

Prediction of the Potentially Suitable Areas of Actinidia latifolia in China Based on Climate Change Using the Optimized MaxEnt Model

1
Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China
2
College of Horticulture and Gardening, Yangtze University, Jingzhou 434023, China
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(14), 5975; https://doi.org/10.3390/su16145975
Submission received: 28 May 2024 / Revised: 22 June 2024 / Accepted: 10 July 2024 / Published: 12 July 2024

Abstract

Actinidia latifolia, with the highest vitamin C content in its genus, is a unique wild relative of kiwifruit that could be important for genetic breeding research. Climate change significantly influences the distribution range of wild plants. Accurately assessing the potential distribution of wild kiwifruit and its response to climate change is crucial for the effective protection and sustainable utilization of its germplasm resources. In this study, we utilized the optimized MaxEnt model to predict the potential habitats of A. latifolia in China, employing the jackknife test to assess the importance of environmental variables in our modeling process. The results showed that annual precipitation (Bio12) and temperature annual range (Bio7) emerged as the most influential environmental variables affecting the distribution of this kiwifruit wild relative. As radiative forcing and time increase, the potential habitats of A. latifolia in China are projected to shrink southward, thereby exacerbating habitat fragmentation. This research offers significant scientific references for the investigation, protection, cultivation, and application of wild relatives of the kiwifruit.
Keywords: kiwifruit; maximum entropy method; climate change; environmental factors; suitable habitat; conservation biology kiwifruit; maximum entropy method; climate change; environmental factors; suitable habitat; conservation biology

Share and Cite

MDPI and ACS Style

Wang, Z.; Luo, M.; Ye, L.; Peng, J.; Luo, X.; Gao, L.; Huang, Q.; Chen, Q.; Zhang, L. Prediction of the Potentially Suitable Areas of Actinidia latifolia in China Based on Climate Change Using the Optimized MaxEnt Model. Sustainability 2024, 16, 5975. https://doi.org/10.3390/su16145975

AMA Style

Wang Z, Luo M, Ye L, Peng J, Luo X, Gao L, Huang Q, Chen Q, Zhang L. Prediction of the Potentially Suitable Areas of Actinidia latifolia in China Based on Climate Change Using the Optimized MaxEnt Model. Sustainability. 2024; 16(14):5975. https://doi.org/10.3390/su16145975

Chicago/Turabian Style

Wang, Zhi, Minmin Luo, Lixia Ye, Jue Peng, Xuan Luo, Lei Gao, Qiong Huang, Qinghong Chen, and Lei Zhang. 2024. "Prediction of the Potentially Suitable Areas of Actinidia latifolia in China Based on Climate Change Using the Optimized MaxEnt Model" Sustainability 16, no. 14: 5975. https://doi.org/10.3390/su16145975

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