Abstract

AbstractEvery human needs sufficient, safe, and nutritious food to live an active and healthy life. Climate change, especially more frequent extreme climate events, increasingly affects crop yields. Unpredictable losses in crop production pose a high risk to our food systems, thus threatening agricultural producers and consumers worldwide. This study analyzes the effect of climate change on wheat, maize, and barley yield anomalies for the major producing countries in the EU. Applying the Random Forest machine learning model, climate indicators, comprising mean and extreme climate conditions, explain 18% of crop yield anomalies across crops and countries from 1961 to 2020. The predictive power of climate indicators is highest for maize with 24%, followed by barley with 22% and wheat with 3%. However, mean climate indicators are stronger associated with crop yield anomalies than extreme climate indicators. Temperature‐ and soil moisture–related indicators are more important than precipitation‐related indicators. The results reveal a nonlinear relationship between climate indicators and crop yields. Thresholds lead to a sharp decrease or increase in crop yields. Under SSP3‐7.0, rising temperatures tend to increase crop yield losses until 2100 without effective adaptation measures. The impact of changing soil moisture–related indicators depends on crop and country. Our study discusses adaptation strategies but also emphasizes the relevance of global mitigation efforts to reduce climate‐induced crop risk and to improve our food system's resilience.

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