Abstract

Specialty crops with long economic life cycles have lower adaptability and flexibility to climate change, making long-term planning crucial. This study examines the impact of climate change on almond, citrus, pistachio, and walnut production in California, using a machine learning approach to estimate crop suitability under current and future environmental conditions. We used recent satellite-observed cropland data to generate an occurrence dataset for these crops. Ecological data including bioclimatic variables derived from global circulation models developed under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and surface variables were used to model suitability. The bioclimatic variables relating to temperature and precipitation had the largest effect on each crop’s suitability estimation. The results indicate that suitable areas for almonds, citrus, and walnuts will change significantly within 20 years due to climatic change, and the change will be even greater by the end of the century, indicating a potential loss of 94% of the current suitable area. The results for pistachios indicate change in the spatial distribution of suitable area but the total area is predicted to remain near the current suitable area. Policymakers, researchers, and farmers must work together to develop proactive adaptation strategies to mitigate the negative effects of climate change on specialty crop production. The application of a species distribution model for agriculture suitability provides critical information for future work on adaptation to climate change, identifying areas to target for further analysis.

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