Evaluating adaptive planting dates and elevated CO2 impacts on soybean yields under future climate scenarios

Crop simulation models depend on field-level management data such as planting dates, plant population, and selection of cultivar to capture yield responses under changing climate conditions. While many parameters exhibit relatively low variability from year to year, planting dates vary substantially due to weather conditions and individual management decisions. In the present study, the DSSAT CROPGRO-Soybean model was applied on a gridded scale to evaluate how a spring freeze probability-based early planting date strategy and elevated atmospheric CO 2 levels could mitigate the impacts of projected climate change on soybeans. The simulations incorporated projected climate data from six General Circulation Models (GCMs) under two shared socioeconomic pathways (SSPs), SSP2-4.5 and SSP5-8.5. Spring freeze probabilities were studied to derive location- and year-specific “adaptive planting dates”. Results indicated that elevated CO 2 significantly improved yield over the simulation period (2026–2100). However, the effectiveness of planting dates in mitigating the impact of climate change was statistically significant only under higher warming. When combined, the adaptive planting strategy and CO 2 fertilization improved yield by as much as 79% relative to a fixed-planting, fixed-CO 2 scenario, although it remained below baseline yield levels. Further, the adaptive planting dates help increase the shortened days-to-anthesis period, with a more pronounced effect under SSP5-8.5. These findings highlight the potential of adjusting planting schedules and leveraging CO 2 fertilization to help offset climate-induced yield losses. Nevertheless, these strategies alone cannot entirely negate the climate change-driven yield declines; additional measures such as using longer-maturity group cultivars or breeding thermally resilient varieties may be necessary to sustain rainfed soybean production in the face of climate change. • Grid-scale analysis of soybean yield under climate projections from six GCMs. • Spring freeze probability-based planting dates derived up to the year 2100. • Planting dates improved future soybean yield, especially under greater warming. • CO 2 and planting dates were able to partially mitigate climate change impacts.