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.
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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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