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

Abstract

Agricultural crop yields are susceptible to changes in future temperature, precipitation, and other Earth system factors. Future changes to these physical Earth system attributes and their effects on agricultural crop yields are highly uncertain. United States agricultural producers will be affected by such changes whether they occur domestically or internationally through international commodity markets. Here we present a replication study of previous investigations (with different models) showing that potential direct domestic climate effects on crop yields in the U.S. have financial consequences for U.S. producers on the same order of magnitude but opposite in sign to indirect financial impacts on U.S. producers from climate effects on crop yields elsewhere in the world. We conclude that the analysis of country-specific financial climate impacts cannot ignore indirect effects arising through international markets. We find our results to be robust across a wide range of potential future crop yield impacts analyzed in the multi-sector dynamic global model GCAM. 1 Introduction Research is increasingly showing that agricultural crop yields will be susceptible to future changes in temperature, precipitation, length of growing seasons, and carbon dioxide (CO2) concentrations [1-9]. While future climate is uncertain, the potential for important effects on major agricultural crop producers such as the U.S. is clear [4, 8, 10-14]. The quantity and composition of U.S. agricultural crop production, where crops are grown, trade, and economic value of U.S. crop production could be affected. An important challenge in understanding these implications is that agricultural products are traded across the globe. The U.S. is both a major agricultural importer and exporter of agricultural crops, meaning that U.S. agriculture may be affected not only by future climate in the U.S., but also future climate outside of the U.S. via international trade. These international linkages raise questions about the relative importance of the direct and indirect effects on U.S. agriculture; that is, is the potential for changes in temperature and precipitation in the U.S. (referred to here as domestic effects) more or less important than the potential for changes outside of the U.S. (referred to here as international effects) to U.S. agricultural crop producers?

Estimating global land system impacts of timber plantations using MAgPIE 4.3.2

“…GLOBIOM when coupled with G4M also circumvents the myopic nature of recursive dynamic models as G4M results are linked to GLOBIOM for making appropriate land-use change decisions regarding wood production and forest land-use. GCAM models competition between land-uses via land competition nests (Snyder et al, 2020) where land-use categories belonging to the same category in the nest (e.g. crops) are assumed to compete more directly with each other than with land-uses in other category (e.g.…”

The Implications of Global Change for the Co‐Evolution of Argentina's Integrated Energy‐Water‐Land Systems

“…Assessing the implications of climate impacts on crop yields requires assessing global trends because Argentina's agriculturally oriented economy is strongly connected to the rest of the world via agricultural trade. Climate impacts in other regions of the world, for both crop yields and water availability, could be just as important as those within Argentina (Baker et al., 2018; Calvin & Fisher‐Vanden, 2017; Calvin et al., 2020; Snyder et al., 2020). The pDSSAT model captures effects from temperature (e.g., higher temperatures can inhibit crop yields), CO 2 fertilization (e.g., higher ambient CO 2 concentrations can increase crop yields), and water constraints (e.g., rainfed crops may experience inhibited yields compared to irrigated crops).…”

“…GCAM in turn applies these climate change-impacted annual change rates to exogenously determined crop yield time series, which changes the relative profit rates across crops and basins. The post-processing approach is used and described in Calvin et al (2020) and Snyder et al (2020). Regarding irrigated crop yields, while it is true that our pDSSAT results assume changing precipitation patterns do not pose a constraint to crop yields, GCAM does account for the economic effects changing water availability on irrigated cropland allocation decisions.…”

“…Second, sectors within a given country or region are increasingly affected by a range of forces across a range of spatiotemporal scales (Taherzadeh et al., 2020). For example, water resources availability in one river basin is connected not only to conditions within the basin, but also to other basins' conditions (e.g., through agricultural trade) (Baker et al., 2018; Dolan et al., 2021; Snyder et al., 2020; Turner et al., 2019). An opportunity exists to enhance the traditional single sector‐oriented approach to national and regional EWL planning (Cai et al., 2018) by characterizing sectoral connectivity and using it to make more informed planning decisions (Khan et al., 2021; Miralles‐Wilhelm, 2016; Ringler et al., 2013).…”

Climate-Land-Energy-Water Nexus Models Across Scales: Progress, Gaps and Best Accessibility Practices

“…These models have also been used in the last decade to inform the Intergovernmental Panel for Climate Change (IPCC) on the correlations between human energy use and production with climate, and their scope has been expanded in recent years to also incorporate a representation of land and water systems Parkinson et al (2019); Bauer et al (2020); Calvin et al (2019); Bijl et al (2018a); Van Vuuren et al (2019). Decarbonization analyses have shown that nexus modeling is needed at multiple scales to better assess the interaction with policies impacting different sectors and administrative levels Sattler et al (2012); Hejazi et al (2015); Snyder et al (2020). Spatial and temporal scales are therefore important factors that affect no only the structure of nexus models and the representations of energy, water and food supply but also the couplings and feedbacks between sectors Bijl et al (2018b); Kahil et al (2018); Köberle et al (2020).…”