
NSF Org: |
SES Division of Social and Economic Sciences |
Recipient: |
|
Initial Amendment Date: | August 24, 2017 |
Latest Amendment Date: | June 14, 2022 |
Award Number: | 1739909 |
Award Instrument: | Continuing Grant |
Program Manager: |
Robert O'Connor
roconnor@nsf.gov (703)292-7263 SES Division of Social and Economic Sciences SBE Directorate for Social, Behavioral and Economic Sciences |
Start Date: | September 1, 2017 |
End Date: | May 31, 2023 (Estimated) |
Total Intended Award Amount: | $2,431,141.00 |
Total Awarded Amount to Date: | $2,431,141.00 |
Funds Obligated to Date: |
FY 2018 = $661,347.00 |
History of Investigator: |
|
Recipient Sponsored Research Office: |
1960 KENNY RD COLUMBUS OH US 43210-1016 (614)688-8735 |
Sponsor Congressional District: |
|
Primary Place of Performance: |
OH US 43210-1010 |
Primary Place of
Performance Congressional District: |
|
Unique Entity Identifier (UEI): |
|
Parent UEI: |
|
NSF Program(s): | Track 1 INFEWS |
Primary Program Source: |
01001819DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): |
|
Program Element Code(s): |
|
Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.075 |
ABSTRACT
Increased globalization through international trade, migration, and technological innovation has generated substantial wealth in the U.S. economy over the past 50 years. These gains , however, have been accompanied by job losses in the manufacturing sector, growing wealth inequality in society and environmental impacts abroad. Counter social and political trends reveal a potential for deglobalization, i.e., diminished integration of the U.S. with global markets. The goal of this project is to examine the potential effects of deglobalization on the sustainability of regional food-energy-water systems (FEWS) and well-being of FEW producers and consumers. We develop a new integrated modeling framework that accounts for individual land use and management decisions, regional demands for land, energy and water resources, and water quality and greenhouse gas emissions impacts. We apply the model to a five-state Great Lakes region: Illinois, Indiana, Michigan, Ohio, and Wisconsin and evaluate the implications of varying future deglobalization scenarios and policies for regional FEWS sustainability and societal well-being. Local and regional stakeholders are engaged throughout the research process via a participatory modeling approach to guide model specification, develop future scenarios, and identify sustainability metrics. The research results are used to guide discussion of potential Great Lakes regional futures with policymakers and other stakeholders.
The modeling framework builds from a Dynamic Stochastic General Equilibrium model that accounts for both the time evolution of key resource stocks and the behavioral dynamics of individuals. The model quantifies the effects of uncertain future changes in environmental, economic, or policy conditions at national and global scales on the regional production of food and energy services that use land, water, and energy resources and that depend on farmer, land use, and watershed heterogeneity. We account for these local heterogeneities using individual farmer behavioral and spatially explicit land data from the Maumee River basin. By creating a dynamic stochastic integrated modeling framework that also accounts for individual decision making and spatial land use-watershed heterogeneity, this research advances the integrated modeling of regional FEWS. The research team also devises a novel approach to sustainability assessment that builds on the unique features of the Dynamic Regional Food, Energy, Water Systems modeling framework to identify policies that are robust in achieving desirable outcomes under a range of uncertainty conditions. The participatory modeling approach with stakeholders improves model validity and generates innovations in how scientific knowledge is created, disseminated, and applied to the management of regional FEWS with specific application to the Great Lakes region.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external
site maintained by the publisher. Some full text articles may not yet be available without a
charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from
this site.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Recent trends indicate an overall slowdown in globalization, including fewer trade reforms and weakening support for open trade. To help understand the implications of this and other potential shifts in globalization for regional economies and ecosystems, our team modeled the ways in which changing global conditions can impact the Food, Energy, and Water Systems (FEWS) of the Great Lakes region (Ohio, Michigan, Indiana, Illinois and Wisconsin).
Our project focused specifically on understanding the potential impacts of changing global agricultural markets and environmental stewardship on the Great Lakes regional FEWS and quantifying the trade-offs among regional economic and environmental indicators of well-being. The work was guided by an external team of advisors from across the Great Lakes region who added their regional expertise in agriculture, energy, land use, economics, and environmental policy.
We developed a novel integrated dynamic regional economic-land-use-ecosystem services model that accounts for spatial and behavioral heterogeneity. We used this model to simulate future worlds based on different scenarios (Figure 1). These scenarios varied from current conditions and trajectories (referred to as the BAU) by having (a) higher or lower global conditions of environmental stewardship and (b) higher or lower openness to international trade. The BAU and four alternative combinations of High/Low Trade/Stewardship (HSHT, HSLT, LSHT, LSLT) resulted in five distinct scenarios (Figure 2).
The model produced a set of outcomes that we compared across scenarios to examine key trade-offs and variations in economic and environmental sustainability indicators. Main findings include:
- Despite differences in population and regional economic growth across the scenarios, total and per capita electricity consumption rose in all scenarios. Growth in solar- and wind-generated electricity was the highest in the HT scenarios. Fossil fuel use declined in all scenarios (Figure 3).
- Soybean production outpaced corn production in all scenarios due to its higher projected profitability and lesser reliance on fertilizer. Total cropland remained roughly constant under the BAU, declined in the HS scenarios, and increased under LSLT (Figure 4), reflecting favorable conditions including high productivity growth, higher export prices, and smaller increases in fertilizer cost.
- Land enrolled in the Conservation Reserve Program was diverted from cropland and increased markedly under the HS scenarios. Total forest acres increased marginally under the BAU and declined the most under LSHT due to higher population growth. Larger declines in wetlands occurred under the LT scenarios due to higher agricultural commodity prices and greater conversion of wetlands to agricultural use.
- The highest production-based GHG emissions occurred under LSHT, which has the highest population growth and least emissions restrictions. Net emissions decline rapidly in the BAU and two HS scenarios due to CO2 capture and storage. In the HS scenarios, higher oil and gas prices resulted in lower emissions from transportation and gas heating. GHG emissions from agriculture increased in all scenarios (Figure 5).
- Under the BAU, the 40% reduction target for spring phosphorus (P) loads in spring was reached by 2025 for dissolved P and by 2035 for total P. These declined more rapidly under the HS scenarios due to higher adoption rates and fewer cropland acres. Under the LS scenarios projected spring total P loads only reached the 40% reduction target by the mid-2040s.
- Per capita produced capital declined in all scenarios and were greater in the HT scenarios due to higher population growth that outpaced increases in built structures. Per capita natural capital, which reflects the value of agricultural land, forests, and wetlands, declined in most scenarios. Overall, the wealth from these combined capitals declined in all but the LSLT scenario (Figure 6), which had the lowest population growth and highest growth in cropland and forest land and per capital produced capital. These results underscore the importance of investing in manmade and natural capitals at a rate that matches or exceeds population growth.
The project generated substantial broader impacts, including:
- We found a high level of satisfaction and impact from participatory process. Results indicated that 82-94% of stakeholder advisors felt the scenarios and models were reliable/legitimate, credible/trustworthy, and relevant/realistic. Nearly all stakeholders reported that we generated improved understanding of the impacts of deglobalization on the regional FEWS system, effectively incorporated stakeholder input in final models, and produced useable information.
- The project provided tremendous interdisciplinary training opportunities for graduate students who were immersed in the development of the integrated model and collaborated deeply with each other and faculty researchers. This training has directly benefited their professional careers. Multiple PhD students have graduated and started positions that are a result of the training they received through this project.
- The project resulted in a set of eight lesson plans for high school science teachers in Ohio that can be inserted as a module into any course or used independently as a module on FEW systems.
Last Modified: 09/28/2023
Modified by: Elena G Irwin
Please report errors in award information by writing to: awardsearch@nsf.gov.