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Prediction of Future Natural Suitable Areas for Rice under Representative Concentration Pathways (RCPs)

Author

Listed:
  • Peng Su

    (School of Geographic Science, Qinghai Normal University, Xining 810008, China)

  • Anyu Zhang

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Ran Wang

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Jing’ai Wang

    (School of Geographic Science, Qinghai Normal University, Xining 810008, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Yuan Gao

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Fenggui Liu

    (School of Geographic Science, Qinghai Normal University, Xining 810008, China
    Academy of Plateau Science and Sustainability, Xining 810008, China)

Abstract

Extreme temperature events, which are part of global climate change, are a growing threat to crop production, especially to such temperature-sensitive crops as rice. As a result, the traditional rice-growing areas are also likely to shift. The MaxEnt model was used for predicting the areas potentially suitable for rice in the short term (2016–2035) and in the medium term (2046–2065) and under two scenarios developed by the Intergovernmental Panel on Climate Change, namely representative concentration pathway (RCP) 4.5 (the intermediate scenario) and RCP 8.5 (sometimes referred to as the worst-case scenario). The predictions, on verification, were seen to be highly accurate: the AUC—area under the curve—value of the MaxEnt model was > 0.85. The model made the following predictions. (1) Areas highly suitable for rice crops will continue to be concentrated mainly in the current major rice-production areas, and areas only marginally suitable will be concentrated mainly in the rainforest region. (2) Overall, although the current pattern of the distribution of such areas would remain more or less unchanged, their extent will mainly decrease in the subtropics but increase in the tropics and in high-latitude regions. (3) The extent of such areas will decrease in the short term but increase in the medium term.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:3:p:1580-:d:492016
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    References listed on IDEAS

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    1. David B. Lobell & Adam Sibley & J. Ivan Ortiz-Monasterio, 2012. "Extreme heat effects on wheat senescence in India," Nature Climate Change, Nature, vol. 2(3), pages 186-189, March.
    2. Anderson, Robert P. & Gonzalez, Israel, 2011. "Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent," Ecological Modelling, Elsevier, vol. 222(15), pages 2796-2811.
    3. Ran Wang & Yao Jiang & Peng Su & Jing’ai Wang, 2019. "Global Spatial Distributions of and Trends in Rice Exposure to High Temperature," Sustainability, MDPI, vol. 11(22), pages 1-53, November.
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    Cited by:

    1. Weidong Ma & Wei Jia & Yuantao Zhou & Fenggui Liu & Jing’ai Wang, 2022. "Prediction of Suitable Future Natural Areas for Highland Barley on the Qinghai-Tibet Plateau under Representative Concentration Pathways (RCPs)," Sustainability, MDPI, vol. 14(11), pages 1-21, May.
    2. Yinglian Qi & Xiaoyan Pu & Yaxiong Li & Dingai Li & Mingrui Huang & Xuan Zheng & Jiaxin Guo & Zhi Chen, 2022. "Prediction of Suitable Distribution Area of Plateau pika ( Ochotona curzoniae ) in the Qinghai–Tibet Plateau under Shared Socioeconomic Pathways (SSPs)," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    3. Diego Portalanza & Finbarr G. Horgan & Valeria Pohlmann & Santiago Vianna Cuadra & Malena Torres-Ulloa & Eduardo Alava & Simone Ferraz & Angelica Durigon, 2022. "Potential Impact of Future Climates on Rice Production in Ecuador Determined Using Kobayashi’s ‘Very Simple Model’," Agriculture, MDPI, vol. 12(11), pages 1-16, November.
    4. Sujith S. Ratnayake & Michael Reid & Nicolette Larder & Harsha K. Kadupitiya & Danny Hunter & Punchi B. Dharmasena & Lalit Kumar & Benjamin Kogo & Keminda Herath & Champika S. Kariyawasam, 2023. "Impact of Climate Change on Paddy Farming in the Village Tank Cascade Systems of Sri Lanka," Sustainability, MDPI, vol. 15(12), pages 1-30, June.
    5. Shahzad Ali & Muhammad Umair & Tyan Alice Makanda & Siqi Shi & Shaik Althaf Hussain & Jian Ni, 2024. "Modeling Current and Future Potential Land Distribution Dynamics of Wheat, Rice, and Maize under Climate Change Scenarios Using MaxEnt," Land, MDPI, vol. 13(8), pages 1-26, July.
    6. 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.

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