世界のトウモロコシ・小麦生産における歴史的な豊作・凶作への気候変動影響の検出
Detecting climate change impacts on historical good and bad harvests in global maize and wheat production (原題)
R. Yoshida, Toshichika Iizumi
🤖 gxceed AI 要約
日本語
ランダムフォレストを用いた収量異常データセットで、2000〜2019年のトウモロコシ63カ国・小麦53カ国の豊作・凶作に対する人為的気候変動の影響を検出。温暖化なしのシミュレーションと比較した結果、負の影響が正の影響より広範で、凶作悪化は中緯度で顕著、豊作増加は高緯度で見られた。全体として気候変動の悪影響が好影響を上回り、食料安全保障には緩和策が必要と結論。
English
Using a random forest-based yield anomaly dataset, this study detects anthropogenic climate change impacts on good and bad harvests of maize (63 countries) and wheat (53 countries) during 2000–2019, comparing historical yields with non-warming simulations. Negative impacts were more widespread than positive ones: bad harvests worsened mainly in mid-latitudes, while good harvests improved at high latitudes. Overall, adverse effects outweigh favorable ones, underscoring the need for mitigation to sustain global food security.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本は食料自給率が低く輸入穀物に依存するため、主要生産国の凶作リスクは調達・食料安全保障に直結する。SSBJや有報の気候関連リスク開示において、農業・食品セクターの物理的リスク評価の基礎資料となりうる。
In the global GX context
This adds empirical evidence to the physical-risk side of TCFD/ISSB disclosure, particularly for agriculture and food supply chains. It supports scenario analysis on climate impacts on commodity production, relevant to transition and adaptation finance discussions globally.
👥 読者別の含意
🔬研究者:気候変動の収量影響を豊作・凶作別に定量化した手法は、農業気候リスク研究の参照点となる。
🏢実務担当者:食品・農業関連企業は調達リスク評価や気候シナリオ分析の根拠として活用できる。
🏛政策担当者:食料安全保障政策や農業適応策の設計において、地域別の影響差を踏まえた検討材料となる。
📄 Abstract（原文）
Abstract Stable crop production is the basis for global food security. Climate change has increased extreme climate events, often leading to low yields (bad harvests). However, favorable climatic conditions and elevated carbon dioxide concentrations may also enhance the yields of good years (good harvests) in some locations and seasons. Here, we detect the historical impacts of climate change on good and bad harvests of maize and wheat in 63 and 53 countries, respectively. Good and bad harvests were defined as the three highest and lowest yield years during 2000–2019. Using a random forest-based yield anomaly dataset, we analyzed yield anomalies under historical and non-warming (NW) climate conditions. The NW simulations represent yields without anthropogenic climate change. The impacts of human-induced climate change were quantified as the difference between the two. Negative yield impacts were more widespread than positive impacts. Climate change has worsened bad harvests in 76% of the maize-producing countries and 55% of the wheat-producing countries, both of which are mainly located in the mid-latitudes. In contrast, enhancements in good harvests occurred in 32% and 21% of the countries primarily located at high-latitudes. As a result, the amplitude of interannual yield variability increased in 13% and 6% of maize- and wheat-producing countries, respectively, owing to both enhanced good harvests and worsened bad harvests. During the study period, growing-season mean temperatures in most producing countries remained below the crop-specific optimum levels; therefore, warming improved the thermal conditions for crop growth. Human-induced changes in precipitation play a more important role in bad harvests than temperature, as growing-season precipitation is often below the crop water needs. The findings of this study suggest that the adverse effects of climate change on maize and wheat production outweigh the favorable effects, underscoring the need for climate change mitigation to sustain global food security.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/2976-601x/aea0d6first seen 2026-09-20 04:35:26
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