Climate change poses a significant threat to cotton production in the Southeastern United States, necessitating adaptive management strategies that enhance yield stability and system resilience. This study integrates 33 years of field data (1986–2018) with simulations from the DSSAT v4.7 model, driven by downscaled climate data from the Weather Research and Forecasting (WRF) model under Representative Concentration Pathway (RCP 4.5 and RCP 8.5) scenarios, to assess the effects of two tillage systems (conventional and no-tillage) and four cover crop treatments (hairy vetch (HV), crimson clover (CC), winter wheat (WW), and no cover (NC)) on cotton lint yield. Yield stability was evaluated using three metrics: Yield Stability Index (YSI), Production Stability Index (PSI), and Yield Variability Index (YVI). The combination of HV and no-tillage resulted in the highest performance, with historical average lint yields exceeding 1,460 lb·acre⁻¹, a YSI of 0.97, and the lowest yield variability (YVI = 0.11). In contrast, the NC under conventional tillage treatment showed the lowest yield (~900 lb·acre⁻¹), lowest YSI (0.68), and highest variability (YVI = 0.32). Under future projections, lint yields declined across all treatments but at different rates. By 2050, under RCP 8.5, HV–NT maintained relatively stable yields (~1,350 lb·acre⁻¹), whereas NC–CT dropped below 1,000 lb·acre⁻¹, reflecting a decline of over 30% from baseline. Notably, conservation systems such as HV–NT and CC–NT showed up to 200–250 lb·acre⁻¹ higher yields than conventional treatments under the same climate conditions. These findings underscore the importance of conservation agriculture as a viable climate adaptation strategy. Integrating biological (cover crops) and mechanical (reduced tillage) soil management practices can sustain cotton productivity while improving system resilience in the face of increasing climate uncertainty.
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Mohil et al. (2026) studied this question.
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