Climate Change Data Portal
DOI | 10.1016/j.compag.2024.108688 |
Compound drought and hot stresses projected to be key constraints on maize production in Northeast China under future climate | |
Zhang, Chuanwei; Gao, Jiangbo; Liu, Lulu; Wu, Shaohong | |
发表日期 | 2024 |
ISSN | 0168-1699 |
EISSN | 1872-7107 |
起始页码 | 218 |
卷号 | 218 |
英文摘要 | Climate change and the increasing frequency of climate extremes associated with warming have been the most important climatic stressors for maize production. However, crop -model based assessments of the major determinants of yield variability at regional scale under future climate conditions are still underrepresented. In this study, we simulated maize yield in Northeast China at a reference period (1986-2005), and two future periods (2030 s: 2020-2039, 2050 s: 2040-2059) of Shared Socioeconomic Pathways (SSPs) of SSP1-2.6, SSP2-4.5 and SSP5-8.5 using Agricultural Production sIMulator (APSIM). We first characterized the variations of maize yield under climate change based on the simulations, and further investigated the key determinants of yield variability using machine learning techniques. The results suggest that maize yield would decrease by 14.8 % to 19.6 % (depending on the climate scenarios) compared to the reference period without adaption. Random forest performed best in explaining yield variability in a suite of machine learning models (extreme gradient boosting, gradient boosting, classification and regression tree, ridge and lasso regression and random forest), with a mean R2 of 0.77, a mean RMSE of 1239.2 kg/ha, a mean MAE of 885.1 kg/ha. Extreme climate indicators show a greater ability to explain yield variability in over half agro-ecological regions under higher warming levels such as SSP5-8.5. Cumulative precipitation (CPR) and compound drought and hot days (CDH) during growing seasons are the most important mean and extreme climate indicators affecting yield variability, respectively. Moreover, the effect sizes of CPR and CDH on yield variability are 1898 kg/ha and 5596 kg/ha, respectively. Therefore, CDH will be a key constraint on maize production. Future adaptive measures such as irrigation, breeding hot- or drought -tolerant cultivars should be implemented to enhance the resilience of maize crops in the face of climate change. |
英文关键词 | Compound drought and hot; Climate change; Maize; APSIM; Northeast China |
语种 | 英语 |
WOS研究方向 | Agriculture ; Computer Science |
WOS类目 | Agriculture, Multidisciplinary ; Computer Science, Interdisciplinary Applications |
WOS记录号 | WOS:001184746400001 |
来源期刊 | COMPUTERS AND ELECTRONICS IN AGRICULTURE
![]() |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/309472 |
作者单位 | Chinese Academy of Sciences; Institute of Geographic Sciences & Natural Resources Research, CAS |
推荐引用方式 GB/T 7714 | Zhang, Chuanwei,Gao, Jiangbo,Liu, Lulu,et al. Compound drought and hot stresses projected to be key constraints on maize production in Northeast China under future climate[J],2024,218. |
APA | Zhang, Chuanwei,Gao, Jiangbo,Liu, Lulu,&Wu, Shaohong.(2024).Compound drought and hot stresses projected to be key constraints on maize production in Northeast China under future climate.COMPUTERS AND ELECTRONICS IN AGRICULTURE,218. |
MLA | Zhang, Chuanwei,et al."Compound drought and hot stresses projected to be key constraints on maize production in Northeast China under future climate".COMPUTERS AND ELECTRONICS IN AGRICULTURE 218(2024). |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。