The domestic and international implications of future climate for U.S. agriculture in GCAM

yields are aggregated (separately for each crop-irrigation pair) to the GCAM land units using MIRCA2000 harvested area data for weighting [26]. At the basin scale, time series of yields are converted to multipliers by dividing by the historical baseline average yield for each crop-irri- gation-basin combination. Finally, these crop-irrigation-basin specific multipliers are con- verted from the crop model specific crop types to multipliers for each GCAM commodity- irrigation-basin combination using GTAP harvested area weights from the GCAM data system [27] for aggregation. This method for incorporating climate driven yield changes as multipliers on GCAM’s exogenous yield assumptions follows methods used in the broader literature [4, 24, 28–32]. GCAM’s biomass crop commodity receives the median of impacts to all other commodities, for each irrigation-management practice combination, in each basin. Fig 1 is a schematic summarizing this processing pipeline. S2 Table in S1 File lists the mapping between AgMIP model crops and GCAM commodities used to estimate multipliers. Corresponding water supply constraints for irrigated crops are used for each scenario [22–24]. Impacts are not applied to grassland or forest to isolate the role of impacts on crop yields. From this suite of agricultural impacts, we construct GCAM scenarios that isolate the effect of agricultural impacts occurring outside the U.S. and impacts occurring within the U.S. For each climate-crop combinations, we run alternative variants that 1. Limit change to the U.S. alone, denoted ‘Domestic’ in results.

2. Apply the change across the whole world, including the U.S. and denoted ‘Full’ in results. 3 Results and discussion Results are presented for a variety of physical and economic output variables from GCAM. Due to both the variability and the relatively small sample size of spatially heterogeneous cli- mate-crop impact scenarios available for this paper, summary statistics across scenarios are not presented. Rather, the results presented here focus on relationships between the Domestic and the Full scenarios that emerge in each of the different climate-crop impact combinations considered. To this end, Figs 2 and 3, and S3 Fig illustrate the percent change relative to the no impacts reference GCAM scenario for several economic and physical variables in 2050 at the aggregate U.S. level for different GCAM commodities, under for all scenarios in the work. Fig 2 focuses results on Corn and OilCrop, globally important commodities for which the U.S. is a major producer. Fig 3 presents results for Rice and Wheat, important commodities with more spatially distributed production across the globe. S3 Fig presents results for the remaining GCAM commodities. The variables plotted include Area allocated to each commodity (summed across management practices and GCAM land units), the U.S. commodity Price, the production Prod of each commodity (summed across management practices and GCAM land units), and the aggregate endogenous yield change EndYld (area-weighted averages across basin and management practices). Results are also included for changes in revenue Rev (total

U.S. production multiplied by U.S. commodity prices) to examine an aggregate direction of change between Price and Prod, as both variables are important to U.S. producers. Fig 1. Schematic of data processing. Schematic illustrating the processing of global gridded yield time series into time series of yield multipliers for GCAM commodities in each basin under perfect irrigation and rainfed conditions. https://doi.org/10.1371/journal.pone.0237918.g001 PLOS ONE The domestic and international implications of future climate for U.S. agriculture in GCAM PLOS ONE | https://doi.org/10.1371/journal.pone.0237918 August 28, 2020 5 / 11