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Physics > Geophysics

arXiv:2310.03261 (physics)
[Submitted on 5 Oct 2023 (v1) , last revised 27 Nov 2023 (this version, v2)]

Title: Climate Change and Future Food Security: Predicting the Extent of Cropland Gain or Degradation

Title: 气候变化与未来粮食安全:预测耕地增加或退化的程度

Authors:Tanushkina Daria, Shevchenko Valeriy, Lukashevich Aleksander, Bulkin Aleksandr, Grinis Roland, Kovalev Kirill, Narozhnaia Veronika, Sotiriadi Nazar, Krenke Alexander, Maximov Yury
Abstract: Agriculture is crucial in sustaining human life and civilization that relies heavily on natural resources. This industry faces new challenges, such as climate change, a growing global population, and new models for managing food security and water resources. Through a machine learning framework, we estimate the future productivity of croplands based on CMIP5 climate projections on moderate carbon emission scenario. We demonstrate that Vietnam and Thailand are at risk with a 10\% and 14\% drop in rice production, respectively, whereas the Philippines is expected to increase its output by 11\% by 2026 compared with 2018. We urge proactive international collaboration between regions facing crop land gain and degradation to mitigate the climate change and population growth impacts reducing our society's vulnerability. Our study provides critical information on the effects of climate change and human activities on land productivity and uses that may assist such collaboration.
Abstract: 农业在维持人类生命和依赖自然资源的文明中至关重要。 该行业面临新的挑战,如气候变化、不断增长的全球人口以及管理粮食安全和水资源的新模式。 通过机器学习框架,我们根据中等碳排放情景下的CMIP5气候预测,估计了耕地的未来生产力。 我们证明,越南和泰国的水稻产量分别可能下降10%和14%,而菲律宾预计到2026年相比2018年产量将增加11%。 我们呼吁面临耕地增减地区的积极国际合作,以缓解气候变化和人口增长的影响,减少我们社会的脆弱性。 我们的研究提供了关于气候变化和人类活动对土地生产力影响的关键信息,这可能有助于此类合作。
Comments: 24 pages, 21 figures
Subjects: Geophysics (physics.geo-ph)
Cite as: arXiv:2310.03261 [physics.geo-ph]
  (or arXiv:2310.03261v2 [physics.geo-ph] for this version)
  https://doi.org/10.48550/arXiv.2310.03261
arXiv-issued DOI via DataCite

Submission history

From: Mikhail Bulkin [view email]
[v1] Thu, 5 Oct 2023 02:34:35 UTC (8,100 KB)
[v2] Mon, 27 Nov 2023 04:30:08 UTC (8,100 KB)
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