Assessing maize yield losses from stage-specific agro-meteorological stresses in China’s semi-humid and humid regions

Maize production in China is exposed to multiple agro-meteorological stresses throughout the growing season, posing challenges to grain supply and food security. Quantifying the stage-specific impacts of agro-meteorological stresses on maize is essential for targeted disaster prevention and mitigation. However, at the regional scale, it remains unclear which agro-meteorological stresses cause more severe potential maize yield losses across different growth stages, partly due to limited assessment methods. Here, we developed a growth-stage dynamic agro-meteorological stress impact framework (SASIF) to quantify maize yield loss rates and affected areas across China’s semi-humid and humid regions during 1991–2020. SASIF integrates the Agricultural Production Systems sIMulator (APSIM) maize model with statistical response functions derived from multiple controlled experiments. The statistical response functions link yield loss rates to drought, waterlogging, heat, and chilling stress indices, and capture stage-dependent sensitivities (R² = 0.32–0.76). The response functions showed that drought, heat, and waterlogging caused the largest yield losses during flowering–milk, flowering–15 d after flowering, and emergence–jointing, respectively. Historical assessments revealed pronounced seasonality and strong regional contrasts in impacts and areas with potential yield loss risk. Without considering agro-meteorological stress prevention measures, potential yield losses across the study region were dominated by drought, with the highest average loss (10.3%) occurring during the flowering–milk stage, mainly in northern China. Chilling stress resulted in an average yield loss of 3.0% during flowering–15 d after flowering, with high-latitude regions especially vulnerable. Heat stress resulted in average yield losses of 1.4% and 1.9% during the pre-flowering and post-flowering periods, respectively, mainly in the Huang-Huai-Hai region, while waterlogging caused its largest loss (1.0%) during the emergence–jointing stage, concentrated in Southern China. These findings highlight the need for region specific and stage targeted prevention and adaptation strategies to reduce maize stress impacts under a changing climate.