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Country‑level climate‑crop yield relationships and the impacts of climate change on food security

机译:国家一级的气候作物产量关系与气候变化对粮食安全的影响

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摘要

Projected climate change has stimulated increasing interest in the interactive effects between carbon dioxide ( CO_2) and temperature on crop yields. Crop yields are anticipated to decline if Earth continues to warm but increase as CO_2 concentration rises. These two factors tend to work in opposite directions, and the interactive effect is not yet clear. There are also significant concerns that climate change is going to undermine global food security. Our purpose is to examine the quantitative relationship between CO_2 and temperature on crop yields and to explore food security or insecurity in the presence of climate change. To do so, we perform a historical analysis on the crop yield trends in 57 selected countries from 1961 to 2013 on a yearly basis employing a fixed-effects panel regression model. The model is based on CO_2 levels measured at Mauna Loa, Hawaii, and weighted-average temperatures in each country in corresponding years. We also incorporate other socio-economic factors, including purchasing power parity adjusted gross domestic product (PPP GDP) and education levels measured by Human Capital Index (HCI), that might affect crop yields. In addition, we control for other factors such as technological changes that contribute to increased yields. We find mixed evidence regarding CO_2- fertilization and rising temperatures where some crops benefits and others are damaged. We identify four tipping points for CO_2 beyond which CO_2 is no longer beneficial for wheat, maize, rapeseed, and rice, where maize is expected to sustain benefits from CO_2- fertilization up until 800 ppm. We also find that rice is damaged by rising temperatures beyond 44 °C.
机译:预计的气候变化刺激了在二氧化碳(CO_2)和作物产量上的温度之间的互动效应的兴趣。如果地球继续温暖但随着CO_2浓度升高,则预计作物产量将下降。这两个因素往往朝着相反的方向工作,互动效果尚不清楚。气候变化也会有重要的担忧将破坏全球粮食安全。我们的目的是检查CO_2和温度对作物产量之间的定量关系,并在气候变化存在下探索粮食安全或不安全感。为此,我们每年从1961年到2013年的57个选定国家的作物产量趋势进行历史分析,每年是在雇用固定效果面板回归模型的基础上。该模型基于在同期在每个国家的Mauna Loa,夏威夷和加权平均气温下测量的CO_2级别。我们还纳入了其他社会经济因素,包括采购权力平价调整后的国内生产总值(PPP GDP)和受人资本指数(HCI)衡量的教育水平,可能会影响作物产量。此外,我们控制其他因素,例如有助于提高产量的技术变革。我们发现有关CO_2-受精和上升温度的混合证据,其中一些作物益处和其他人受损。我们识别出于800 ppm的玉米,玉米,玉米,玉米,玉米,玉米,玉米,玉米,才能识别4个筹码。我们还发现,在超过44°C超过44°C的温度下,米损坏。

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