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Northeast China (NEC) is the most prominent grain‐producing region in China. However, it is currently facing significant impacts from climate change. Since the climate‐related impacts on crop yield in this region are a major concern for society in the future, quantifying climate change impacts on crop yields in NEC is essential to ensure future food security. This study aimed to quantify the effects of future climate change on crop yields in NEC and explore adaptation strategies using the Crop Growth Model (PCSE) driven by downscaled CMIP6 climate projections under four Shared Socioeconomic Pathways (SSPs) scenarios during 2015–2100. Results showed that there could be average reductions in crop yields of 21.4% for maize and 4.2% for soybean by the year 2100 under SSP585 compared to the 2015 baseline. The increasing temperature was the dominant factor in reducing yields, although elevated CO2 and precipitation offered partial compensation. The optimized planting date brought noticeable benefits for rice and soybean but had limited effects on maize due to heat stress. Relocating rice expansion eastward and implementing earlier planting increased yields by up to 50% but adversely decreased soybean and maize due to competition. This study enriches our comprehension of climate change impacts on NEC agriculture, while also quantifying potential benefits and constraints of evaluated adaptations. The proposed adaptations may help mitigate projected yield declines in other key agricultural regions across the globe. Adjusting crop management practices to capitalize on changing climate factors shows promise as a strategy for sustaining production globally. Plain Language Summary: Northeast China (NEC) is essential for achieving food accessibility and food security in China, but its agricultural production is seriously threatened by climate change. This study investigated how climate change could impact maize, rice, and soybean crop yields in this region from 2015 to 2100, using the PCSE crop model and forcing from the international Coupled Model Intercomparison Project 6 (CMIP6) climate projections. Simulation results suggested rising temperatures would negatively affect crop yields, especially for maize. Increased carbon dioxide and rainfall partially offset these losses. By 2100, average declines were projected for maize (−21%) and soybeans (−4%), respectively. Altering planting dates to match crop needs was an effective adaptation to boost yields, with rice benefiting the most. Relocating rice production eastward and expanding its area substantially increased simulated rice yields (+62%) but decreased other crops due to competition (−32% maize, −28% soybeans). Even with adaptations, some areas still showed yield declines, indicating extra measures may be needed to maintain production. Overall, this study suggests significant risks to crop yields from climate change in Northeast China, with adaptations like optimized planting and strategic crop relocation able to mitigate some but not all of the projected impacts. Key Points: Rising temperatures negatively impacted simulated future crop yields, especially for maizeAdjusting planting dates boosted yields for rice and soybeans but had limited benefits for maizeRelocating and expanding the rice area increased yields substantially [ABSTRACT FROM AUTHOR]

Enhancing soil organic carbon (SOC) sequestration and food supply are vital for human survival when facing climate change. Site‐specific best management practices (BMPs) are being promoted for adoption globally as solutions. However, how SOC and crop yield are related to each other in responding to BMPs remains unknown. Here, path analysis based on meta‐analysis and machine learning was conducted to identify the effects and potential mechanisms of how the relationship between SOC and crop yield responds to site‐specific BMPs in China. The results showed that BMPs could significantly enhance SOC and maintain or increase crop yield. The maximum benefits in SOC (30.6%) and crop yield (79.8%) occurred in mineral fertilizer combined with organic inputs (MOF). Specifically, the optimal SOC and crop yield would be achieved when the areas were arid, soil pH was ≥7.3, initial SOC content was ≤10 g kg−1, duration was >10 years, and the nitrogen (N) input level was 100–200 kg ha−1. Further analysis revealed that the original SOC level and crop yield change showed an inverted V‐shaped structure. The association between the changes in SOC and crop yield might be linked to the positive role of the nutrient‐mediated effect. The results generally suggested that improving the SOC can strongly support better crop performance. Limitations in increasing crop yield still exist due to low original SOC level, and in regions where the excessive N inputs, inappropriate tillage or organic input is inadequate and could be diminished by optimizing BMPs in harmony with site‐specific conditions. [ABSTRACT FROM AUTHOR]

Plant growth and crop harvest are impacted by both climate change and air pollution. However, their relative importance in crop yields remains elusive, especially in heavily polluted regions. Here we develop crop yield prediction models, based on a large volume of historical crop data, as well as climate and pollution records in China since 1980. A long‐term surface ozone concentration data set is developed from a machine‐learning model and various observations. An assessment of four climate and pollution factors reveals the critical role of particulate and ozone pollution in regulating interannual variations of crop yields in China. During 2010–2018, we find that the particulate pollution mitigation outweighs the negative impacts of concurrent climate change, resulting in 0.5%–1.9% net yield increases nationwide, despite of the ozone increases in the North China Plain. Looking to the future, the impacts of climate change, particularly from surface temperature increase, will dominate over pollution factors and profoundly reduce future maize and rice yields by 0.6 to 2.8% 10 yr−1 by 2050. Our findings call for attention on the threat to future global food security from the absence of pollution mitigation and the persistence of global warming. Plain Language Summary: We capitalize on 39‐year historical records of crop yields, climate variables, and pollution data to develop a robust crop yield prediction model. Utilizing this model, we show a critical role of particulate pollution in determining annual crop yields. Moreover, our analyses reveal that the recent abatement of anthropogenic emission in China results in a net crop gain, which masks the crop loss due to the increased temperature and precipitation. In the next 30 years, temperature dominant climate effects will emerge to steer the future trend of crop yields. The present study demonstrates the co‐benefit of the recent air pollution control policy from agriculture and food perspectives. However, this benefit will eventually be diminished after the air pollution becomes alleviated in the full scale, while persisting or even exacerbated global warming will pose larger threat on the future food security. Key Points: Robust crop yield prediction models are developed to assess climate change and air pollution impacts on agricultureDuring 2010–2018, the particulate pollution mitigation outweighs the negative impacts of concurrent climate change in ChinaExacerbated global warming will lead to crop yield reduction in spite of pollution alleviation in the future scenarios [ABSTRACT FROM AUTHOR]