Compound Climate Extremes, Yield Shocks, and Climate-Smart Responses: Quantifying Adaptation–Mitigation–Productivity Trade-offs for Global Food Security

BackgroundClimate risks to agriculture are increasingly driven by compound climate extremes that occur together or in rapid sequence, such as heat combined with heavy rainfall or hot conditions followed by intense wet spells. These events can cause disproportionate crop losses, reduce recovery time within a season, and increase the likelihood of synchronized low-yield years across breadbasket regions—creating systemic risks for global food security. A rapidly emerging hazard is successive hot–pluvial extremes, which are reported to be increasing across growing seasons and associated with negative yield anomalies in major crops. Yet key uncertainties remain: the thresholds and timing windows that translate compound extremes into yield loss are still poorly constrained across crops and regions; the drivers of spatially synchronized yield shocks are not fully understood; and many assessments do not quantify how response options affect not only yields, but also greenhouse gas emissions and resource use.This Research Topic will advance climate-smart food systems science by linking compound-extreme risk to crop yield stability and food security outcomes, while explicitly evaluating adaptation–mitigation–productivity synergies and trade-offs. Adaptation measures that buffer yield losses (for example irrigation expansion, drainage, altered planting dates, nutrient management, or cultivar shifts) can also change mitigation outcomes through energy demand, fertilizer inputs, soil carbon dynamics, and nitrous oxide emissions. Quantifying these interactions is essential for climate-smart strategies that are effective, scalable, and aligned with sustainability goals.GoalsThis Research Topic aims to: (1) detect, characterize, and attribute compound climate extremes relevant to crops, including successive hot–pluvial sequences; (2) quantify impacts on yield levels, yield variability, and synchronized breadbasket failures for major staples; (3) identify actionable thresholds based on intensity, duration, sequence, and phenological timing; (4) improve modeling robustness using process-based crop models, machine learning, and hybrid methods with explicit uncertainty decomposition; and (5) evaluate climate-smart response portfolios by quantifying productivity gains, adaptation benefits, and mitigation implications (co-benefits and emissions trade-offs) under realistic management and policy constraints.ScopeWe welcome Original Research, Methods, Reviews, case studies, and Perspectives on: compound-extreme metrics aligned with crop calendars and phenology; breadbasket risk, yield synchrony, and food-security implications (including trade and price sensitivity); crop-impact modeling using statistical, machine-learning (e.g., XGBoost), and process-based approaches, including explainability and validation; downscaling, bias correction, and ensemble frameworks for extremes; attribution and uncertainty analysis across climate inputs, observations, and model structure; and evaluation of adaptation options (management, breeding targets, irrigation and drainage strategies, diversification, early warning and climate services). We especially encourage studies that quantify adaptation–mitigation–productivity trade-offs, such as emissions and energy impacts of irrigation and pumping, fertilizer and soil nitrogen pathways affecting nitrous oxide, soil carbon outcomes, and risk-reduction effectiveness under future climate variability. Topic editors: Fasil Mequanint, Rajiv Kumar Srivastava Source: https://www.frontiersin.org/research-topics/78331/compound-climate-extremes-yield-shocks-and-climate-smart-responses-quantifying-adaptation-mitigation-productivity-trade-offs-for-global-food-security