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This special issue is the outcome of a workshop held at Purdue University in April 2022. It comprises thematic syntheses of five overarching dimensions of the Global-to-Local-to-Global (GLG) challenge to ensuring the long-term sustainability of land and water resources. These thematic dimensions include: climate change, ecosystems and biodiversity, governance, water resources and cyberinfrastructure. In addition, there are eight applications of GLG analysis to specific land and water sustainability challenges, ranging from environmental stress in the Amazon River Basin to groundwater depletion in the United States. Based on these papers, we conclude that, without fine-scale, local analysis, interventions focusing on land and water sustainability will likely be misguided. But formulating such policies without the broader, national/global context is also problematic – both from the point of view of the global drivers of local sustainability stresses, as well as to capture unanticipated spillovers. In addition, because local and global systems are connected to – and mediated by – meso-scale processes, accounting for key meso-scale phenomena, such as labor market functioning, is critical for characterizing GLG interactions. We also conclude that there is great scope for increasing the complexity of GLG analysis in future work. However, this carries significant risks. Increased complexity can outstrip data and modeling capabilities, slow down research, make results more difficult to understand and interpret, and complicate effective communication with decision-makers and other users of the analyses. We believe that research guidance regarding appropriate complexity is a high priority in the emerging field of Global-Local-Global analysis of sustainability.

We utilize a coupled economy–agroecology–hydrology modeling framework to capture the cascading impacts of climate change mitigation policy on agriculture and the resulting water quality cobenefits. We analyze a policy that assigns a range of United States government’s social cost of carbon estimates ($51, $76, and $152/ton of CO₂-equivalents) to fossil fuel–based CO₂emissions. This policy raises energy costs and, importantly for agriculture, boosts the price of nitrogen fertilizer production. At the highest carbon price, US carbon emissions are reduced by about 50%, and nitrogen fertilizer prices rise by about 90%, leading to an approximate 15% reduction in fertilizer applications for corn production across the Mississippi River Basin. Corn and soybean production declines by about 7%, increasing crop prices by 6%, while nitrate leaching declines by about 10%. Simulated nitrate export to the Gulf of Mexico decreases by 8%, ultimately shrinking the average midsummer area of the Gulf of Mexico hypoxic area by 3% and hypoxic volume by 4%. We also consider the additional benefits of restored wetlands to mitigate nitrogen loading to reduce hypoxia in the Gulf of Mexico and find a targeted wetland restoration scenario approximately doubles the effect of a low to moderate social cost of carbon. Wetland restoration alone exhibited spillover effects that increased nitrate leaching in other parts of the basin which were mitigated with the inclusion of the carbon policy. We conclude that a national climate policy aimed at reducing greenhouse gas emissions in the United States would have important water quality cobenefits.

Reducing nutrient loss from agriculture to improve water quality requires a combination of management practices. However, it has been unclear what pattern of mitigation is likely to emerge from different policies, individually and combined, and the consequences for local and national land use and farm returns. We address this research gap by constructing an integrated multi-scale framework for evaluating alternative nitrogen loss management policies for corn production in the US. This approach combines site- and practice-specific agro-ecosystem processes with a grid-resolving economic model to identify locations that can be prioritized to increase the economic efficiency of the policies. We find that regional measures, albeit effective in reducing local nitrogen loss, can displace corn production to the area where nitrogen fertilizer productivity is low and nutrient loss rate is high, thereby offsetting the overall effectiveness of the nutrient management strategy. This spatial spillover effect can be suppressed by implementing the partial measures in tandem with nationwide policies. Wetland restoration combined with split fertilizer application, along with a nitrogen loss tax could reduce nitrate nitrogen loss to the Mississippi River by 30% while only increasing corn prices by less than 2%.

Sustainable development requires jointly achieving economic development to raise standards of living and environmental sustainability to secure these gains for the long run. Here, we develop a local-to-global, and global-to-local, earth-economy model that integrates the Global Trade Analysis Project (GTAP)-computable general equilibrium model of the economy with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model of fine-scale, spatially explicit ecosystem services. The integrated model, GTAP–InVEST, jointly determines land use, environmental conditions, ecosystem services, market prices, supply and demand across economic sectors, trade across regions, and aggregate performance metrics like GDP. We use the integrated model to analyze the contribution of investing in nature for economic prosperity, accounting for the impact of four important ecosystem services (pollination, timber provision, marine fisheries, and carbon sequestration). We show that investments in nature result in large improvements relative to a business-as-usual path, accruing annual gains of $100 to $350 billion (2014 USD) with the largest percentage gains in the lowest-income countries. Our estimates include only a small subset of ecosystem services and could be far higher with inclusion of more ecosystem services, incorporation of ecological tipping points, and reduction in substitutability that limits economic adjustments to declines in natural capital. Our analysis highlights the need for improved environmental–economic modeling and the vital importance of integrating environmental information firmly into economic analysis and policy. The benefits of doing so are potentially very large, with the greatest percentage benefits accruing to inhabitants of the poorest countries.

Labor markets can shape the impacts of global market developments and local sustainability policies on agricultural outcomes, including changes in production and land use. Yet local labor market outcomes, including agricultural employment, migration and wages, are often overlooked in integrated assessment models (IAMs). The relevance of labor markets has become more important in recent decades, with evidence of diminished labor mobility in the United States (US) and other developed countries. We use the SIMPLE-G (Simplified International Model of agricultural Prices, Land use, and the Environment) modeling framework to investigate the impacts of a global commodity price shock and a local sustainable groundwater use policy in the US. SIMPLE-G is a multi-scale framework designed to allow for integration of economic and biophysical determinants of sustainability, using fine-scale geospatial data and parameters. We use this framework to compare the impacts of the two sets of shocks under two contrasting assumptions: perfect mobility of agricultural labor, as generally implicit in global IAMs, and relatively inelastic labor mobility (‘sticky’ agricultural labor supply response). We supplement the numerical simulations with analytical results from a stylized two-input model to provide further insights into the impacts of local and global shocks on agricultural labor, crop production and resource use. Findings illustrate the key role that labor mobility plays in shaping both local and global agricultural and environmental outcomes. In the perfect labor mobility scenario, the impact of a commodity price boom on crop production, employment and land-use is overestimated compared with the restricted labor mobility case. In the case of the groundwater sustainability policy, the perfect labor mobility scenario overestimates the reduction in crop production and employment in directly targeted grids as well as spillover effects that increase employment in other grids. For both shocks, impacts on agricultural wages are completely overlooked if we ignore rigidities in agricultural labor markets.

The rapid depletion of US groundwater resources and rising number of dying wells in the Western US brings attention to the significance of groundwater governance and sustainability restrictions. However, such restrictions on groundwater withdrawals are likely to generate spillover effects causing further environmental stresses in other locations and adding to the complexity of sustainability challenges. The goal of this paper is to improve our understanding of the implications of growing global food demand for local sustainability stresses and the implications of local sustainability policies for local, regional, and global food production, land use, and prices. We employ SIMPLE-G-US (Simplified International Model of agricultural Prices, Land use, and the Environment—Gridded version for the United States) to distangle the significance or remote changes in population and income for irrigation and water resources in the US. Then we examine the local-to-global impacts of potential US groundwater sustainability policies. We find that developments in international markets are significant, as more than half of US sustainability stresses by 2050 are caused by increased commodity demand from abroad. Furthermore, a US sustainable groundwater policy can cause overseas spillovers of US production, thereby potentially contributing to environmental stresses elsewhere, even as groundwater stress in the US is alleviated. These unintended consequences could include deforestation due to cropland expansion, as well as degradation in water quality due to intensification of production in non-targeted areas.