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

Author

Listed:
  • Zhi Wang

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Minmin Luo

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China
    College of Horticulture and Gardening, Yangtze University, Jingzhou 434023, China)

  • Lixia Ye

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Jue Peng

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Xuan Luo

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Lei Gao

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Qiong Huang

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Qinghong Chen

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

  • Lei Zhang

    (Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit Trees, Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan 430064, China)

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.

Suggested Citation

  • Zhi Wang & Minmin Luo & Lixia Ye & Jue Peng & Xuan Luo & Lei Gao & Qiong Huang & Qinghong Chen & Lei Zhang, 2024. "Prediction of the Potentially Suitable Areas of Actinidia latifolia in China Based on Climate Change Using the Optimized MaxEnt Model," Sustainability, MDPI, vol. 16(14), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:5975-:d:1434178
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    References listed on IDEAS

    as
    1. Yining Ma & Xiaoling Lu & Kaiwei Li & Chunyi Wang & Ari Guna & Jiquan Zhang, 2021. "Prediction of Potential Geographical Distribution Patterns of Actinidia arguta under Different Climate Scenarios," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    2. Peng Su & Anyu Zhang & Ran Wang & Jing’ai Wang & Yuan Gao & Fenggui Liu, 2021. "Prediction of Future Natural Suitable Areas for Rice under Representative Concentration Pathways (RCPs)," Sustainability, MDPI, vol. 13(3), pages 1-19, February.
    3. Zhao, Jiongchao & Wang, Chong & Shi, Xiaoyu & Bo, Xiaozhi & Li, Shuo & Shang, Mengfei & Chen, Fu & Chu, Qingquan, 2021. "Modeling climatically suitable areas for soybean and their shifts across China," Agricultural Systems, Elsevier, vol. 192(C).
    4. Freeman, Elizabeth A. & Moisen, Gretchen G., 2008. "A comparison of the performance of threshold criteria for binary classification in terms of predicted prevalence and kappa," Ecological Modelling, Elsevier, vol. 217(1), pages 48-58.
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