Chujie Liu, Xiaoyun Li, Jordan Chamberlin, Liangzhi You
{"title":"Climate Change-Driven Shifts in Staple Crop Structure: Evidence From Northern China","authors":"Chujie Liu, Xiaoyun Li, Jordan Chamberlin, Liangzhi You","doi":"10.1111/agec.70093","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Climate change is reshaping agricultural production, with adjustments in crop structure serving as a vital climate adaptation strategy. Drawing on county-level agricultural data (1985–2019) and climate data (1965–2019), this study employs a panel fixed effects model to assess the impacts of climate change on the area shares of wheat, maize, and rice in Northern China, as well as their implications for grain production. The results reveal heterogeneous crop-specific responses. The growing degree days (GDDs) is positively associated with maize area—with each 10°C·day increase in GDD associated with an approximately 0.24% rise in maize area share—while having a significantly negative effect on wheat. These effects are more pronounced in colder regions and in a single-cropping system, reflecting agroecological heterogeneity. On the other hand, increased precipitation is associated with expansions in both wheat and maize area shares, with the effect being more evident for wheat. These climate-driven adjustments in Northern China contributed to an estimated 1.42% increase in China's total grain output over the study period. Further mechanism analysis, using competing crops as a case, shows that the positive impact of GDD on spring maize productivity is notably greater than that for spring wheat, suggesting that higher GDD enhances the comparative advantage of maize, thereby expanding its area share while reducing that of spring wheat. We also find that increased precipitation is significantly associated with multiple cropping index (MCI) increases, offering an additional adjustment pathway. By incorporating socio-economic factors into the analytical framework, our results indicate that improved irrigation capacity can effectively moderate the impacts of climate change on cropping patterns—by mitigating the negative effect of GDD on area shares of wheat and rice, and strengthening the positive effect of GDD on maize. Additionally, the adverse impact of GDD on wheat is substantially weaker in major grain-producing counties compared with nonmajor ones. These findings enhance our understanding of how staple crop structure in Northern China responds to climate change and the attendant implications for food security. Our analysis can help policymakers to formulate more targeted adaptation strategies that optimize land use and sustain stable grain production.</p>\n </div>","PeriodicalId":50837,"journal":{"name":"Agricultural Economics","volume":"57 2","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2026-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Economics","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/agec.70093","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ECONOMICS & POLICY","Score":null,"Total":0}
引用次数: 0
Abstract
Climate change is reshaping agricultural production, with adjustments in crop structure serving as a vital climate adaptation strategy. Drawing on county-level agricultural data (1985–2019) and climate data (1965–2019), this study employs a panel fixed effects model to assess the impacts of climate change on the area shares of wheat, maize, and rice in Northern China, as well as their implications for grain production. The results reveal heterogeneous crop-specific responses. The growing degree days (GDDs) is positively associated with maize area—with each 10°C·day increase in GDD associated with an approximately 0.24% rise in maize area share—while having a significantly negative effect on wheat. These effects are more pronounced in colder regions and in a single-cropping system, reflecting agroecological heterogeneity. On the other hand, increased precipitation is associated with expansions in both wheat and maize area shares, with the effect being more evident for wheat. These climate-driven adjustments in Northern China contributed to an estimated 1.42% increase in China's total grain output over the study period. Further mechanism analysis, using competing crops as a case, shows that the positive impact of GDD on spring maize productivity is notably greater than that for spring wheat, suggesting that higher GDD enhances the comparative advantage of maize, thereby expanding its area share while reducing that of spring wheat. We also find that increased precipitation is significantly associated with multiple cropping index (MCI) increases, offering an additional adjustment pathway. By incorporating socio-economic factors into the analytical framework, our results indicate that improved irrigation capacity can effectively moderate the impacts of climate change on cropping patterns—by mitigating the negative effect of GDD on area shares of wheat and rice, and strengthening the positive effect of GDD on maize. Additionally, the adverse impact of GDD on wheat is substantially weaker in major grain-producing counties compared with nonmajor ones. These findings enhance our understanding of how staple crop structure in Northern China responds to climate change and the attendant implications for food security. Our analysis can help policymakers to formulate more targeted adaptation strategies that optimize land use and sustain stable grain production.
期刊介绍:
Agricultural Economics aims to disseminate the most important research results and policy analyses in our discipline, from all regions of the world. Topical coverage ranges from consumption and nutrition to land use and the environment, at every scale of analysis from households to markets and the macro-economy. Applicable methodologies include econometric estimation and statistical hypothesis testing, optimization and simulation models, descriptive reviews and policy analyses. We particularly encourage submission of empirical work that can be replicated and tested by others.