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

2 Methods 2.1 GCAM background GCAM couples human and physical Earth systems to explore the impacts of economic and environmental policies. GCAM is calibrated to historical data through 2010 and then simulates forward from 2010 to 2100 in five year timesteps by incorporating changes in quantities such as population, GDP, technology, and policy to produce outputs that include land use, emis- sions, and commodity prices. Specifically, GCAM can assimilate high spatial resolution infor- mation on the global distribution of crop yields and analyze its effects on the coupled system of global agriculture markets. This and previous versions of GCAM track long term trend behavior rather than interannual variability (such as price spikes). All scenarios in this study follow Shared Socioeconomic Pathway 2 (SSP2) [19], the "middle-of-the-road" socio-economic scenario. The associated GCAM scenario provides the reference against which we measure impacts in this study. GCAM represents the energy system in 32 economic regions, and it represents global pro- duction in 384 agricultural and land-use regions. Each of the 384 land units in GCAM repre- sents a water basin-economic region combination. Twenty-three of these lie within the U.S. With each land unit, GCAM allocates land across more than a dozen types based on cover and use. Allocation is based on a logit formulation to optimize profitability, with details provided in Wise et al [20]. Important to this study, GCAM models production of a range of agricultural

commodities (crops), each with four different management types (with and without irrigation, high and low fertilizer). S1 Fig illustrates the land competition nests used by GCAM v5.2 in each GCAM land unit (updated from [20]). S1 Table in the S1 File provides the mappings between crops in the FAOSTAT database [21] and GCAM commodities. Some GCAM com- modities are straightforward (Corn, Wheat, Rice), but some GCAM commodities are eco- nomic aggregates, such as MiscCrop (including high value cash crops) and OilCrop (which includes soybeans). The span of GCAM commodities allows a relatively full modeling of the agricultural sector of economies. On the supply side of agricultural crop production in GCAM, the "no impacts" baseline yield change assumptions (derived from Food and Agriculture Organization data) are read in exogenously. These yield changes are used by GCAM to calculate the profitability of a GCAM crop-irrigation-fertilizer combination in each GCAM land unit at each time step. This profit- ability determines land allocated to each land type (crop-irrigation-fertilizer combination, grassland, shrubland, pasture, forest, etc.). The combination of exogenous yields and endoge- nous land allocation gives production of each crop-irrigation-management combination in each land unit. Because land shares allocated to rainfed versus irrigated, high versus low fertil- izer versions of each crop may change, the aggregate yield for each crop output by GCAM will differ from the input yields. In other words, there is endogenous yield intensification in

GCAM. AgMIP yield impacts are incorporated as multipliers on the exogenous yield assump- tions used by GCAM (details in Section 2.2). The production of irrigated crops is constrained by water availability and prices (see [22–24] for more details on water supply and demand in GCAM). The GCAM food demand system creates a slightly elastic portion of demand for each crop type, based on the exogenous population and GDP assumptions GCAM takes as inputs. There- fore, the minimum quantity defined by the food demand system must be met globally by GCAM agricultural crop production. Other demand sectors (biofuels, animal feed, non-food demand, etc.) are more elastic. For some GCAM agricultural commodities, such as Corn and OilCrop, this leads to an overall more elastic total demand function because GCAM explicitly models the energy sector and the accompanying price-sensitive demand for use of these crops 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 3 / 11