Source: OHIO STATE UNIVERSITY submitted to NRP
REGIONAL INTEGRATED MODELING OF FARMER ADAPTATIONS TO GUIDE AGROECOSYSTEM MANAGEMENT IN A CHANGING CLIMATE
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
AFRI COMPETITIVE GRANT
Reporting Frequency
Annual
Accession No.
1015579
Grant No.
2018-68002-27932
Cumulative Award Amt.
$1,175,500.00
Proposal No.
2017-07339
Multistate No.
(N/A)
Project Start Date
Aug 1, 2018
Project End Date
Jun 30, 2024
Grant Year
2018
Program Code
[A3171]- Climate and Land Use
Recipient Organization
OHIO STATE UNIVERSITY
1680 MADISON AVENUE
WOOSTER,OH 44691
Performing Department
Environmental and Natural Reso
Non Technical Summary
Climate change in the eastern Corn Belt Region (ECBR) of the United States is projected to bring higher temperatures, more variable and extreme levels of precipitation, and longer growing seasons. These changes will influence land use and management adaptations, which depend on the behavioral heterogeneity of individual famers as well as economic, policy and technological conditions imposed by broader human systems. These broader systems also respond to anticipated climate variability, e.g., through changes in agricultural production systems, policies and markets. The ECBR is embedded in other national and global systems as well: climate change is projected to be even more severe in coastal and drought-prone areas, potentially creating greater pressure for food production in the ECBR and inducing human migration to the ECBR. While these possibilities imply opportunity for the ECBR, managing change will be increasingly challenging. Stakeholders at household, firm, industry, community, and regional levels need more information and a better understanding of the system-wide implications of these changes.We propose research that will elevate the capacity of decision makers in the ECBR to adapt to an increasingly variable climate and the associated changes that this increased variability may bring. To do this we demonstrate an integrated regional approach that can be applied to guide more sustainable and resilient agroecosystems across the nation. The ECBR is an appropriate study region given it contains some of the most intensive agricultural production in the Midwest as well as significant urban and forested areas. Our approach is to identify how changing seasonal and extreme precipitation patterns induce changes in ECBR land use and management patterns due to adaptations by heterogeneous farmers and the broader human system. Because the ECBR agroecosystem is managed with agricultural production, conservation, and societal well-being goals in mind, we will build an integrated set of models of the climate system, regional economy, and agroecological outcomes and use this to evaluate policies and programs by projecting their impacts on the sustainability and resilience of this regional agroecosystem under varying future scenarios. A participatory modeling approach is used throughout the project to engage a key group of stakeholders in developing the model and scenarios and identifying relevant adaptations and policies.Our team includes Ohio State University researchers affiliated with the College of Food, Agriculture, and Environmental Sciences, Arts and Sciences College, and the Byrd Polar and Climate Research Center working collaboratively across the natural and social sciences to address the program area priority of "Climate, Land use and Land Management". Specifically, our research will increase our understanding of climate-agroecosystems interactions and the implications of land use and management adaptations to climate change for agroecosystem sustainability and resilience. Our stakeholder engagement will ensure that the outcomes generated will be useful to decision makers across the agricultural system. These key outcomes include: (i) innovations in coupling downscaled climate projections with models of heterogeneous farmer behavior and regional land use and management models; (ii) innovations in modeling the impacts of future climate variability on a regional agroecosystem that can be applied in other regions; (iii) increased awareness of how climate has changed over the last century in the ECBR; (iv) increased understanding of future climate scenarios and likely agroecosystem responses in the ECBR; and (v) improved stakeholder confidence in the ability to mitigate climate-induced risks through more informed programs, policies and land use and management.
Animal Health Component
70%
Research Effort Categories
Basic
20%
Applied
70%
Developmental
10%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1320430207020%
1120199107010%
1316030307020%
9030430303010%
6036199301025%
6106199208015%
Knowledge Area
603 - Market Economics; 112 - Watershed Protection and Management; 132 - Weather and Climate; 903 - Communication, Education, and Information Delivery; 610 - Domestic Policy Analysis; 131 - Alternative Uses of Land;

Subject Of Investigation
6199 - Economy, general/other; 0430 - Climate; 0199 - Soil and land, general; 6030 - The farm as an enterprise;

Field Of Science
2070 - Meteorology and climatology; 3070 - Psychology; 1070 - Ecology; 2080 - Mathematics and computer sciences; 3010 - Economics; 3030 - Information and communication;
Goals / Objectives
Our short-term goal is to increase the capacity of decision makers in the eastern cornbelt region (ECBR) to identify adaptive strategies that mitigate the risks posed by climate extremes.Our long-term goal is to demonstrate a holistic integrated approach for assessing adaptation policies at a regional scale that can be applied to other agroecosystems. Such an approach is needed to guide the sustainable and resilient management of agroecosystems that balances agricultural production and critical ecosystem services.We will implement this research through the following objectives:1) Establish a stakeholder advisory team (SAT) to identify likely adaptations, policies and future scenarios. Specifically, we will create and engage a SAT and assess the impact of the stakeholder engagement process.2) Develop future climate projections for the ECBR. Specifically, we will obtain robust scientifically-vetted future climate change projections for the ECBR; explore historical climate extremes and verify the LOCA dataset for the ECBR; identify the most likely set of future climate projections for the ECBR; and identify the most exterme set of future climate projections for the ECBR.3) Specify a model of farmer land use/management adaptations for a range of plausible future scenarios that incorporates climate variability and behavioral heterogeneity. Specifically, we will work with the SAT to develop a set of coherent future scenarios, including policies and programs, and a range of likely farmer adaptations under varying future scenarios; develop a structural model of farmer utility maximization that reflects both profit and non-profit motives and estimate the reduced form to identify the net effect of climate variability on land use/management choices; conduct choice experiments with the target farm population in the ECBR to estimate the influence of heterogeneity at the individual and farm level on land use and management choices under varying future scenarios of uncertain climate and agricultural system conditions; and develop a predictive model of an individual farmer's land use and management responses under varying future scenarios.4) Develop a multi-sector regional economic model to simulate land use and management patterns across the ECBR under future scenarios. Specifically, we will develop version 1.0 of the regional economic model without explicit uncertainty; parameterize and simulate version 1.0 for the baseline scenario; develop and parameterize version 2.0 of the regional economic model to account for uncertainty; and simulate version 2.0 land use and management outcomes for future baseline and alternative scenarios.5) Model the impacts of climate variability and changes in land use/management on agricultural yields and ecosystem services under future scenarios. Specifically, we will quantify changes in crop yields given future climate variability; quantify changes in carbon sequestration potential; assess water quality impacts; and estimate biophysical climate regulation services.6) Identify optimal policies that are robust to uncertain future climate and agroecosystem conditions. Specifically, we will create a principal-agent model and determine the optimal policy ensemble for each future scneario.?7) Engage farmers and agricultural system stakeholders to inform decision making under a variable climate. Specifically, we will disseiminate project results thorugh existing networks, while creating a range of new educational products
Project Methods
We will i) develop an integrated model of land use/management that accounts for the impacts of greater climate variability on the biophysical, ecological, behavioral, and economic dimensions of agroecosystems and (ii) apply this model to assess the sustainability and resilience of agricultural and land conservation policies and programs, defined in consultation with stakeholders, for the eastern Corn Belt region (ECBR) under alternative regional climate-agroecosystem scenarios.This will be done through a combination of 1) working with key stakeholder groups in a structured participatory process to identify plausible farmer and system-wide adaptations to climate variability in the ECBR and a set of coherent future scenarios and potential policies and program to evaluate with the regional integrated model;2) assessing and analyzing high-resolution climate data, specifically projections of future precipitation and temperature variability for this region and critically evaluatingthe particular stresses that might impact future agricultural systems; 3)parameterizinga series of farmer choice models based on a utility maximization model with heterogeneous motives and risk preferences using a combination of qualitative, historical and experimental data on farmer land use/management decisions; 4)developing a regional economic model that predicts equilibrium prices and heterogeneous farmer land use/management adaptations under each future scenario and given specified levels of uncertainty around these future conditions; 5)quantifying the impact ofland use/management changes on four key ecosystem services--crop production, carbon sequestration, water quality, and biophysical climate regulation - using land use and process-based agroecosystem models; 6)creatinga principal-agent model in which government as the principal decides on an ensemble of policies, while agents (heterogeneous farmers and firms) choose their optimal decisions of land use, crop and investment under the ensemble of policies and a given future scenario; and 7)educatingand engagingdiverse stakeholders about future climate variability and sustainable responses in the agroecosystem.Evaluation will consist of monitoring overall project implementation throughout the duration of the grant period. The external evaluators will work closely with the PD and project personnel to determine if the planned activity goals are met, e.g., desired numbers of participants; development of the models; and outputs such as presentations, publications, informational resources and stakeholder workshop.

Progress 08/01/18 to 06/30/24

Outputs
Target Audience:Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs (Certified Crop Advisors), Extension Specialists and Educators, agricultural interest groups, conservation interest groups, and representatives of the agribusiness sector. We also provided experiential learning opportunities for student researchers. Changes/Problems:We had originally budgeted $25,000 for a project end stakeholder workshop but decided to use those funds to support the development of translational products that could be more broadly disseminated to our stakeholders through an initial online dissemination event, and long-term hosting of an online decision support tool on our website. We were working with our Knowledge Exchange to develop those products over the winter, but that office was then unexpectedly disbanded and they were not able to do the work. We pivoted to hiring someone over the summer to still build the translational products, but we did not have the capacity to build the interactive online decision support tool. We do still plan to hold the online dissemination event and to distribute those products, but that event will occur in October 2024 after the report is submitted. What opportunities for training and professional development has the project provided?The project has resulted in interdisciplinary training opportunities and learning for graduate students and postdoctoral researchers. Project-supported students and researchers were immersed in the development of the integrated model and in deeply collaborating with each other and the faculty researchers to ensure the successful integration of multiple modeling components. They have made multiple novel contributions that are advancing the frontier of regional integrated modeling of human-natural systems. This training has directly shaped and benefited the professional careers of these students and postdoctoral scholars. Multiple students graduated in this last year of the project and started positions that are directly related, and a result of, the integrated modeling and assessment training that they received through this project. Specifically ,the project has provided Junyoung Jeong (GRA) training on developing and calibrating a dynamic CGE model and integrating it with other models in the project. The project has provided an opportunity for Khyati Malik (graduate student) to gain detailed knowledge of and implement the Environmental Policy Integrated Climate Model (EPIC) for simulating crop yields, soil carbon sequestration, surface runoff, percolation, and other water quality indicatorsgiven various land management practices. C. Dale Shaffer-Morrison, a former post-doc, received training in interdisciplinary collaboration, and integrating behavioral data into land use/management models. How have the results been disseminated to communities of interest?We published 8 additional papers in scientific outlets, and gave 11 additional presentations to audiences ranging from disciplinary and interdisciplinary scientific audiences to farmer and agricultural professionals. We also developed a series of handout that will be made available on our website that present the results of the scenario analyses highlighting tradeoffs in expected services given different land use and lanad management choices. Finally, we are presenting the highlights of our results at a webinar that we will record on October 14th, 2024 and post to our website. With several weeks yet to advertise, we already have 20 participants signed up ranging from scientists at other Universities to USDA personnel to congressional staffers. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? In line with Objective 1, we continued to engage our Stakeholder Advisory Team (SAT) regularly (i.e., quarterly conference calls, with one of those being an annual in-person meeting). We also assessed the impact of the stakeholder engagement process through four (to date) annual assessments and questions asked of advisory team member during the SAT meetings. We will follow-up with our SAT after our final dissemination event on October 14th, 2024, to conduct one final assessment. SAT participants contributed beneficial ideas for improving educational materials and evaluation measures, clarifying models that have been developed, and planning project and outreach activities. Overall, our evaluation of the stakeholder engagement and the quality of the project from the stakeholder perspectives indicates that SAT participants felt their contributions were valued, and that engagement in the project increased their understanding of climate and the agroecosystem, and the results would be useful in their jobs. Furthermore, we feel we had an outstanding group of individuals who were knowledgeable about agricultural issues in the Eastern Corn Belt and significantly improve the validity of the project. Objective 2 was completed during previous reporting periods. Members of the climate modeling team still attend monthly project team meetings, contributing expertise to the modeling discussions as needed. In line with Obj 3, we generated a Great Lakes-wide database containing agricultural field-level data on crop rotations, historical weather patterns, topography, and soil conditions. We used these data to develop a sampling strategy of agricultural fields for biophysical modeling simulations, as further described in Obj 5. We also worked towards an integrated model which combines previous work on farmer management heterogeneity with the biophysical model outputs from EPIC. In line with Obj 4, we further refined our dynamic regional economic model, focusing on its stability and calibration. Additionally, in relation to Obj 3 and Obj 6, we enhanced the integration of the economic and land use/management models. The model is potentially adaptable for integration with the EPIC model to incorporate its agricultural yield estimates, which will serve as the basis for analyzing the impacts of climate change, policy interventions, or market conditions on the regional economy and ecosystems. In line with Obj 5, we determined crop yields and carbon sequestration in different watersheds in the Midwest United States. Within each watershed, we identified the different soil types of agricultural fields and, based on the fraction of the area of the soil types, randomly selected a subset of fields. For those fields, we simulated crop yields, carbon sequestration, and water quality outcomes for baseline and alternative conservation practice scenarios for a period of 30 years (1985-2014). The simulations were performed using EPIC. In line with Obj 6, we identified management scenarios that range from conventional practices to conservation practices to land retirement. These scenarios were defined by different combinations of tillage, crop rotation, and (presence or absence) of cover crops. These management scenarios resulted from discussions with members of the research and stakeholder advisory teams regarding the most common practices that align with each of the three scenarios. We calculated the effect of each scenario on ecosystem services at a field level in each watershed - namely N and P loss (to present water quality), short-term and long-term carbon storage (to represent carbon sequestration) and bushels per acre for corn, soy and wheat (to represent food production). We then packaged these results for stakeholders to highlight the service tradeoffs across each scenario. In line with Obj.7, the team has continued to seek partners with whom to disseminate the interactive lesson built for the project. The lesson is also being used to inform activities under development for a new Ohio 4-H project book focused on weather, climate, and climate change. The project website has been continually updated to reflect new publications of the project team. While there is no future reporting period, we do plan to continue this work. Specifically, we have continued to work on the integrated modeling to fine-tune the outputs over the course of the summer after the funding ended. We also met one last time in September 2024 with our stakeholder advisory team to present our final outputs, and seek their feedback on the online dissemination event to be held in October. Following the dissemination event, which will be recorded and put on our website, we will continue to work on publications related to project, including a minimum of 4 currently in preparation. We will also further integrate the various models, which will allow us to forecast future changes in ecosystem services given variability in the regional economy, climate change and farmer decision making.

Publications

  • Type: Journal Articles Status: Under Review Year Published: 2024 Citation: Li, Y., K. Zhao, et al. Beyond radiation-use efficiency: a mechanistic crop photosynthesis scheme for agroecosystem modeling. In review. Computer in Electronics in Agriculture.
  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Li, Yang, Michael A Wulder, Zhe Zhu, Jan Verbesselt, Dainius Masili?nas, Yanlan Liu, Gil Bohrer, Yongyang Cai, Yuyu Zhou, Zhaowei Ding, Kaiguang Zhao (2024). DRMAT: A multivariate algorithm for detecting breakpoints in multispectral time series. Remote Sensing of Environment, 315, 114402 (15 pages). https://www.sciencedirect.com/science/article/abs/pii/S0034425724004280
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Randall, A., & Ogland-Hand, J. (2023). Validity and Validation of Computer SimulationsA Methodological Inquiry with Application to Integrated Assessment Models. Knowledge, 3(2), 262-276.
  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Randall, A,, Jones, M, and Irwin, E.G. 2024. Weak Sustainability at Regional Scale, Sustainability 16 (in process).
  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Shaffer-Morrison, C.D., & Wilson, R.S.(2024). The Nutrient Reduction Index: A parsimonious and continuous measure of conservation practice adoption among farmers. Journal of Soil and Water Conservation, 79(1), 1-7.
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Hu, T., Zhang, X., Bohrer, G., Liu, Y., Zhou, Y., Martin, J., Li, Y. and Zhao, K. 2023. Crop yield prediction via explainable AI and interpretable machine learning: Dangers of black box models for evaluating climate change impacts on crop yield. Agricultural and Forest Meteorology, 336, p.109458. https://doi.org/10.1016/j.agrformet.2023.109458
  • Type: Journal Articles Status: Published Year Published: 2024 Citation: Hu, T., Zhang, X., Khanal, S., Wilson, R., Leng, G., Toman, E. M., Wang, X., Li, Y., and Zhao, K. 2024. Climate change impacts on crop yields: A review of empirical findings, statistical crop models, and machine learning methods. Environmental Modelling & Software, Volume 179, 106119, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2024.106119
  • Type: Journal Articles Status: Under Review Year Published: 2024 Citation: Shaffer-Morrison, C.D.* and R.S. Wilson. In revision. Climate stress among the most vulnerable farmers: Harnessing a future time perspective as a resource for greater climate adaptation. British Journal of Social Psychology.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: R.S. Wilson. 2023. Barriers to implementing conservation in agriculture. Invited Alan R. Bender Memorial Lecturer at the South Dakota Student Water Conference. Brookings, South Dakota.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: R.S. Wilson. 2023. Understanding farmer adaptation to guide management in changing climate. Invited speaker at the Eastern South Dakota Water Conference. Brookings, South Dakota.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: R.S. Wilson and C. Dale Shaffer-Morrison. 2023. Barriers to Implementing Conservation in Agriculture. Invited presenter at The Nature Conservancy farmer outreach event. Defiance, OH.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: R.S. Wilson and C. Dale Shaffer-Morrison. 2023. Motivational Barriers to Conservation Implementation. Invited presenter at the Conservation Drainage Network Annual Meeting. Easton, MD.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: J. Jeong. A Dynamic Regional Integrated Assessment Model to Assess the Impacts of Deglobalization and Environmental Stewardship on the Regional Economy and Water Quality. 6th Annual Social Cost of Water Pollution Workshop. Washington, D.C. October 11-13, 2023
  • Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: J. Jeong. A Dynamic Regional Integrated Assessment Model to Assess the Impacts of Changing Globalization and Environmental Stewardship on the Regional Economy and Water Quality. 2024 ASSA Annual Meeting. San Antonio, Texas. January 5-7, 2024
  • Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: " Soil to Savings: An Economic Framework for Farmer Compensation Based on Carbon Sequestration in the Midwest United States, Selected Paper Presentation at the Camp Resources Workshop XXX, August 04-06, 2024, Asheville, North Carolina, USA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: " Soil to Savings: An Economic Framework for Farmer Compensation Based on Carbon Sequestration in the Midwest United States, Selected Paper Presentation at the 2024 Annual Conference of the Agricultural and Applied Economics Association (AAEA), July 28-30, 2024, New Orleans, Louisiana, USA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2024 Citation: " Soil to Savings: An Economic Framework for Farmer Compensation Based on Carbon Sequestration in the Midwest United States, Invited Talk at the Lal Carbon Center, April 5, 2024, The Ohio State University, Columbus, Ohio, USA.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: " Soil to Savings: An Economic Framework for Farmer Compensation Based on Carbon Sequestration in the Midwest United States, Selected Poster Presentation at the Heartland Environmental and Resource Economics Workshop, October 28-29, 2023, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA.


Progress 08/01/22 to 07/31/23

Outputs
Target Audience:Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs (Certified Crop Advisors), Extension Specialists and Educators, agricultural interest groups and conferences, conservation interest groups, and representatives of the agribusiness sector. We also provided experiential learning opportunities for student researchers.Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs (Certified Crop Advisors), Extension Specialists and Educators, agricultural interest groups and conferences, conservation interest groups, and representatives of the agribusiness sector. We also provided experiential learning opportunities for student researchers. Changes/Problems:We had originally budgeted $25,000 for a project end stakeholder workshop but have decided to use those funds to support the development of translational products instead that can be more broadly disseminated to our stakeholders through an initial online dissemination event, and long-term hosting of an online decision support tool on our website. We also lost two of our key team members (Brian Cultice and C. Dale Shaffer-Morrison to new positions). This caused some delays in our model integration and ability to run our full policy simulations. We are requesting a 6 month no-cost extension to accommodate their shifting schedules and ensure that we can deliver on all of our key outcomes - namely identifying a suite of sustainable and resilient policies or programs. Otherwise, we have met all of our key outputs and outcomes (i.e., improved confidence in the ability to adapt and mitigate risks, increased understanding of the implications of climate variability on the agroecosystem, innovations in the science of IAM including incorporation of behavioral heterogeneity, spatial-temporal concerns and ecosystem impacts, and a solvable model at the regional scale. What opportunities for training and professional development has the project provided?The project has resulted in interdisciplinary training opportunities and learning for graduate students and postdoctoral researchers. Project-supported students and researchers were immersed in the development of the integrated model and in deeply collaborating with each other and the faculty researchers to ensure the successful integration of multiple modeling components. They have made multiple novel contributions that are advancing the frontier of regional integrated modeling of human-natural systems. This training has directly shaped and benefited the professional careers of these students and postdoctoral scholars. Multiple students graduated in this last year of the project and started positions that are directly related, and a result of, the integrated modeling and assessment training that they received through this project. Specifically ,the project has provided Junyoung Jeong (GRA) training on developing and calibrating a dynamic CGE model and integrating it with other models in the project. The project has provided an opportunity for Brian Cultice (graduate student) to develop expertise in analyzing geospatial land use data (NLCD land cover and USDA Cropland Data Layer) and estimating land use transitions (this individual is funded on a complementary NSF project) and for Khyati Malik (graduate student) to understand the implementation of Environmental Policy Integrated Climate Model (EPIC) for simulating the amount of soil carbon sequestration that can be achieved through various land management practices. C. Dale Shaffer-Morrison, a post-doc, is receiving training in interdisciplinary collaboration, and integrating behavioral data into land use/management models. Undergraduate graphics design intern Haylen Scott received experience with science communication and iterative design through development of a stop motion animation. How have the results been disseminated to communities of interest?Regarding agricultural industry professionals and the research community at large, we presented predictors of farmer heterogeneity in conservation practice adoption, as a function of farmer's beliefs about conservation and on- farm resources. This presentation was held at the annual meeting of the American Society of Agricultural and Biological Engineers. Other agricultural industry professionals were reached through ongoing extension events and publication through Dr. Aaron Wilson's extension program. What do you plan to do during the next reporting period to accomplish the goals?Obj 1: With the project ending in a few months, we are planning just one more stakeholder advisory team monthly update in October. We are however planning a translational decision support tool to help communicate our model results, and will likely engage with our stakeholder advisory team and our broader stakeholder audience one final time to share our results. Obj 2: No future plans Obj 3: A manuscript which tests the relationship between responsiveness to changing conditions and the tendency to think about, and plan for, the future is underway. The goal is to have this manuscript submitted in Fall 2023, and published by Fall 2024. Obj 3: We will complete the fine-scaled spatial model of land use/management and integrate heterogeneous farmer decisions for specified management decisions that are impacted by changing weather or economic/policy conditions, including decisions related to planting date, tile drainage, wetlands restoration, and agricultural conservation enrollment. Obj 4: We will integrate the heterogeneous land use/management model with the regional economic model to simulate specific policy scenarios, including a range of plausible payments for the modeled land management practices and plausible changes in agricultural input prices and commodity prices. We will continue to work to publish a paper on a dynamic regional general equilibrium model with a carbon tax. The goal is to submit the manuscript in Spring 2024. We will keep improving model calibration and working on the incorporation of uncertainty in the model. Obj 5: We will complete the ecosystem services modeling so that we can run policy simulations, forecasting how different types of market interventions might shift farmer land use and management decisions, leading to different outcomes related to critical services (sequestration, water quality, and food production) given climate change. Obj 6: We will complete the policy analysis, which involves identifying the mechanistic paths in the model by which each market-based policy intervention could lead to changes in land use/mgmt and associated changes in ecosystem services. Obj 7: As mentioned previously, we will package our modeling results in an online decision support tool developed in cooperation with the College of Food, Agricultural, and Environmental Sciences Knowledge Exchange (https://kx.osu.edu/). This tool and other findings will be shared broadly with stakeholders at an online dissemination event. Evaluation: The evaluator will continue to attend project team and advisory team meetings, examine implementation and objectives, and assess the impact of educational outreach activities. A final questionnaire will be sent to advisory team members to assess the overall impact of the project and obtain input for planning educational and outreach activities to disseminate knowledge gained from this project.

Impacts
What was accomplished under these goals? In line with Obj 1, we have been engaging the Stakeholder Advisory Team (SAT) regularly (quarterly conference calls, with one of those being an annual in-person meeting. We are also assessing the impact of the stakeholder engagement process through five (to date) annual assessments and questions asked of advisory team member during the SAT meetings. SAT participants have contributed beneficial ideas for improving educational materials and evaluation measures, clarifying models that have been developed, and planning project and outreach activities. Objective 2wascompleted during the last reporting period. Members of the climate modeling team still attend monthly project team meetings, contributing expertise to the modeling discussions as needed. In line with Obj 3, we identified potential policy futures, including changes in commodity and input prices, as well as changes in local and federal policies. The set of policies includes selected agricultural and land use policies, including enrollment in agricultural conservation and wetlands protection. We worked with the SAT to identify policies that are the greatest interest to stakeholders. An index of conservation behaviors is now in press. Further, a manuscript based on completed choice experiment analyses is under development and nearing completion. This paper examines heterogeneity in farmer responsiveness to changing climate conditions, as a function of the tendency to think about and plan for the future. In line with Obj 3, we continue to conceptualize plausible farmer responsiveness to changing economic and climate conditions in ways that are realistic to the realities of farm operations, as well as being informed by choice experiment results. We estimated a two-step random effects model of farmer Conservation Reserve Program (CRP) enrollment using the farmer survey data and integrated this module into the land use/management model to estimate heterogeneous farmer enrollment over time. In addition, we respecified the land use change module using the National Land Cover Database (NLCD) for years 2001-2019 to estimate land use transitions and began work on a downscaled version of the land use change model that operates at the 150m x 150m grid-cell level. This fine-scaled approach is necessary to more fully develop the heterogeneous farmer model of land use/management decisions. In line with Obj 4, we completed developing our multi-sector dynamic regional economic model that is composed of two separate submodels, a regional dynamic model and a multi-state general equilibrium model. We continue to improve the model performance by recalibrating model parameters. In addition, related to Obj 3 and Obj 6, we developed an integrated framework of the economic and land use/mgmt models to potentially examine the shifts in policy interventions or market conditions. In line with Obj 5, our students completed their training on developing ecosystem services models in EPIC, and are working to calibrate and validate the model so that the land use/management forecasts can be used to forecast future services (carbon sequestration, water quality, and food production). In addition, we fully tested a new version of EPIC called EPIC-RP--a next-generation agroecosystem model that couples the water, energy, and carbon cycles; the model is still under peer-review and will be released to the public once the manuscript is accepted. Our manuscript on statistical modelling for crop yield prediction was accepted, and we delivered a new explainable AI algorithm that outperformed most of the state-of-the-art machine learning algorithms currently available. Our model offered the most accurate crop yield prediction under climate change when tested upon Ohio's crop survey data. The algorithm implementation was released to the public at https://github.com/zhaokg/bm. It will be further developed as a R and Python package aimed for generic usage to the wider science community. We are also using the new data analytic capability to examine the various environment, climate, and landscape controls on stream water quality based on the USGS gauge data at the HUC 12 level In line with Obj 6, we have made significant progress on the policy analysis piece of the project. We have identified our approach, which is to explore deviation from a "business as usual" scenario given specific policy interventions. We will be examining how market-induced mechanisms may increase (or decrease) targeted land use transitions and land management changes that are significant for food production, water quality and carbon sequestration. The land use/mgmt changes we are examining are shifts in productive land into wetlands and/or retirement programs, and shifts in the management of productive land into cover crops and no-till. We will examine how objectives related to these ecosystem services can be achieved through particular market-based policy interventions. In line with Obj. 7, a video, including both an overview by researcher Yang Li and stop motion animation created by undergraduate intern Haylen Scott, was released in fall 2022 and available at https://u.osu.edu/agroecosystemresilience/videos/. The tabletop exercise that was created for use at agricultural events and in schools was piloted by an undergraduate class taught by PI Robyn Wilson in fall 2022 and with the advisory board in winter 2023. Additional attempts to pilot the materials with vocational agriculture teachers, including at a statewide conference, via university programs, and through one-on-one contacts were unsuccessful. Researchers Aaron Wilson and Jason Cervenec anticipate using the exercise with future programs prior to drafting a manuscript.

Publications

  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Cai, Y., and K. Judd (2023). A simple but powerful simulated certainty equivalent approximation method for dynamic stochastic problems. Quantitative Economics, 14, 651687.
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Cultice, B. , Irwin, E.G., Jones, M. (2023). Accounting for spatial economic interactions at local and meso scales in integrated assessment model (IAM) frameworks: challenges and recent progress. Environmental Research Letters. 18 (3) Article No. 035009.
  • Type: Journal Articles Status: Published Year Published: 2023 Citation: Wilson, R. S., Shaffer-Morrison, C. D., & Walpole, H. (2023). Climate-exacerbated impacts may drive maladaptive action in agriculture. Weather, Climate, and Society, 15(2), 437-450.
  • Type: Journal Articles Status: Accepted Year Published: 2023 Citation: Shaffer-Morrison, C.D*. and R.S. Wilson. In press. The Nutrient Reduction Index: A parsimonious and continuous measure of conservation practice adoption among farmers. Journal of Soil and Water Conservation.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2023 Citation: Wilson, R.S. 2023. Integrating heterogeneity in decision making into simulation models. Decisions and Climate Workshop. The Ohio State University: Columbus, OH.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: R.S. Wilson. 2022. The role of risk beliefs versus identity in climate adaptation decisions. Presented at the Society for Risk Analysis Annual Meeting. Tampa, FL.
  • Type: Other Status: Other Year Published: 2023 Citation: Shaffer-Morrison, C.D. and Wilson, R.S. 2023. Selectively collective: Social-psychological forces in cooperative agricultural solutions. Presented at the American Society of Agricultural and Biological Engineers Annual Meeting. Omaha, NE.


Progress 08/01/21 to 07/31/22

Outputs
Target Audience:Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs (Certified Crop Advisors), Extension Specialists and Educators, agricultural interest groups, conservation interest groups, and representatives of the agribusiness sector. We also provided experiential learning opportunities for student researchers. Changes/Problems:Coming out of the COVID-19 pandemic there were still some challenges this past year, but they have now largely ended. As a result, we have done fewer presentations to external audiences through normal extension activities. What opportunities for training and professional development has the project provided?The project has provided Junyoung Jeong (GRA) training on developing regional dynamic models,calibrating the models, and writing GAMS code to solve them. The project has provided an opportunity for Brian Cultice (graduate student) to develop expertise in analyzing geospatial land use data (NLCD land cover and USDA Cropland Data Layer) and estimating land use transitions (this individual is funded on a complementary NSF project) and for Khyati Malik (graduate student funded in spring and summer 2022) to develop and apply machine learning skills to model land management decisions using the survey data. The project provided Yang Li (PhD student) with training to develop state-of-the-art data-model fusion capabilities for integrated applications across domains. Whitney Baxter and Haylen Scott undergraduate design students, received training in iterative design to create science content infographics and video content to convey information to non-technical audiences.C. Dale Shaffer-Morrison, a post-doc, is receiving training in interdisciplinary collaboration, and integrating behavioral data into land use/management models. How have the results been disseminated to communities of interest?Engagement with the ag-related community throughout Ohio included the dissemination of climate results from this project at 6 programs, ~300 participants. We detailed the project to date (Objs. 2 and 3) in an article to the OSU Agronomics Crops Team C.O.R.N. Newsletter titled "Extension and Ag Researchers Work Toward Agroecosystem Resilience" in March 2022, reaching more than 2000 subscribers. These presentations and products are also made publicly available through our website (https://u.osu.edu/agroecosystemresilience). What do you plan to do during the next reporting period to accomplish the goals?Obj 1: We will continue to meet with our stakeholder advisory team monthly to update them on project progress and seek their input on various components. We are planning our next conference call in December 2022, and a fourth and final in-person (or virtual if necessary) meeting in March 2023. Obj 2: The climate team will continue to coordinate with other objective leads for model integration. The climate team will continue to contribute to dissemination per the goals stated for Obj. 7. Obj 3: In line with Obj 3.1, we will continue to refine our models in preparation for scenario and policy simulations. Preliminary runs suggest a need to increase the intensity of carbon abatement effort in the high sustainability scenarios, and perhaps to add a scenario in which attainment of net-zero C emissions is required by constraint. We will also finalize the set of local/regional policies that will be incorporated into the scenarios based on SAT feedback. We expect to complete scenario and policy simulations in the next periodto assess what type of interventions may best promote sustainability and resilience in the agroecosystem. In line with Obj 3.2/3.3, we will continue to analyze the survey data and finalize several papers in preparation or review (one paper is in revision at Weather, Climate and Society, and several are in prep).One paper examines the relationship between future time perspective and in-field conservation practices. A second describes farmer heterogeneity in responses to plausible changes in weather conditions. Regarding this latter paper, we also plan to publish a dataset that includes experimentally-predicted heterogeneity in farmer responses to plausible climate futures along several spatially-relevant dimensions. In line with Obj 3.4, we will finalize the estimated land management models using the data from the farmer survey and link the land use and management models using variables that the two models have in common, which include crop choices, county population, economic growth, and historical land uses. County-scale land use models are currently used in the model with farmer heterogeneity determined by variation in aggregate county characteristics. We will conduct work to downscale this modeling to the field or grid cell level, which will allow for more heterogeneity to be introduced at the scale of farmer decision-making. We will integrate the projected changes in land use and management into the ecosystem services models for the targeted watersheds. Obj 4: We will continue to work to publish three papers on dynamic regional general equilibrium with carbon tax, dynamic stochastic spatial equilibrium, and pandemic impact. . We will keep updating models and calibrating for addressing uncertainty and analyzing the impact of the scenarios developed in Obj 3.1. We will also keep working with Obj 6 to develop the principal-agent models and simulate their results. Obj 5: Two manuscripts on crop-climate interaction and prediction of crop yields are still under peer-review: both are well received and in major revision. One new manuscript on developing a new generation of agroecosystem modeling has been finished and will be submitted to Environmental Modeling and Software. The new agroecosystem model termed as EPIC-RP represents a significant improvement over the community EPIC model, with the inclusion of more realistic plant growth (especially for C4 plants such as corn). This change will give more confidence in simulating the effect of climate change and farmer adaptation on our proposed suite of ecosystem services, such as soil carbon balance and water quality. Once the manuscript gets accepted, the software and code of EPIC-RP will be also released to the public domain (e.g., deposited on Github). We also plan to submit a land cover/land use detection algorithm paper by the mid-Nov. This work also represents a paradigm shifting in leveraging satellite time series to detect landscape change; the derived information will be used to inform observation-based quantification of ecosystem services (e.g., carbon footprints and climate regulation). Obj 6: We will design the principal-agent model to incorporate state-of-the-art formulations of sustainability criteria and decision criteria that are robust to uncertainty, especially asymmetric risks. Optimization will be assessed through experiments with the model. Sustainability criteria will include weak sustainability adapted to the regional economy, and strong sustainability restrictions on critical resources and environmental services, with particular attention to carbon-greenhouse gases and water quality. We will explore the implications of scale (e.g., farm, county, whole region) on achievement of sustainability. Simulations will address BAU and four alternative scenarios and examine the implications of alternative policies. Obj 7: Research and model outputs will continue to be used to share project findings with specific audiences through both planned presentations to key audiences, and through dissemination of these products in newsletters, on our website, etc. (see dissemination plan). The team developed a learning activity that will also gather embedded evaluation data. The intent of the learning activity is to improve comprehension and retention of climate information and promote dialogue about available actions through a blend of individual rankings, small group discussion, and whole group reporting/presenting. The team has already user-tested the learning activity with undergraduate students to refine format, instructions, and pacing. Additional user testing experiences are being booked for this winter/spring in the agricultural community. Embedded evaluation data will be collected at various points in the activity to measure participant change. Another video product is nearing completion, highlighting the land use options; their impact on albedo, evapotranspiration, and warming; and connecting this content to the project themes.We will also be planning a series of project end workshops to disseminate results to a variety of stakeholders in an interactive fashion. Evaluation of educational presentations and related materials will continue throughout the next reporting period. All efforts will continue to be monitored by the project evaluator. The evaluator will attend all project team meetings, work closely with the PD and team members, seek input into evaluation measures as appropriate, and present evaluation findings.

Impacts
What was accomplished under these goals? In line with Obj 1.1, we engaged the Stakeholder Advisory Team (SAT) regularly (quarterly conference calls, with the annual in-person meeting actually conducted in-person this year after several years of being virtual due to COVID). In line with Obj 1.2, we also assessed the impact of the stakeholder engagement process through four (to date) annual assessments. During the meetings, SAT participants have contributed beneficial ideas for improving educational materials and evaluation measures, clarifying models that have been developed, and planning project and outreach activities. To complete Objectives 2.1-2.4, the climate team's paper titled "Climate extremes and their impacts on agriculture across the Eastern Corn Belt Region of the U.S." was published inWeather and Climate Extremes. Based on our work, guidance and data have been provided to an NSF-sponsored Food-Energy-Water project, to which many co-investigators on this project are a part of, to help guide their modeling decisions concerning water quality and land use changes in the Maumee River basin. Dissemination of results continued through Ag-related events in Ohio and the Midwest (See Objective 7). In line with Obj 3.1, we are continuing the conceptualization of scenarios and policies for modeling and simulation. Our scenarios are based on the UN's Representative Concentration Pathways and Shared Socioeconomic Pathways, including a business-as-usual scenario and four alternative scenarios representing the possible combinations of high vs low sustainability, and rivalry vs cooperation among nations. Initial model runs suggest scope for increasing the intensity of pro-sustainability effort in high sustainability scenarios. We are well-along with establishing trajectories through 2050 for agricultural best management practices, agricultural yield, energy technology capital cost reductions due to technological learning, state populations, CO2emissions, etc. The policies we will model are mostly efforts by state and local governments to augment federal policy requirements and incentives and/or address issues that have not elicited a federal response. Particular policies continue to attract attention and commentary in our SAT meetings. In line with Obj 3.2 and 3.3, we continued to work on papers from our farmer decision making models. An index of conservation behaviors was developed that combines several in-field conservation practices (tillage, cover crops, small grains in rotation) into a single measure. This measure gives credit for scale of on-farm implementation and the estimated impact of each practice on nutrient runoff management. A paper regarding this scale's utility is under review. Further, heterogeneity in response to changing weather conditions is currently being examined through analyses of choice experiment survey data. Specifically, we are examining how responses to changes in rainfall, planting date, and other factors affects conservation practices, and how responses might differ by farm conditions like soil type. In line with Obj 3.4, we estimated adaptive land management decisions (e.g., no till, tile drainage, etc) and no adaptation as functions of climate, field, and farm variables taken from the survey data, including: changes in climate conditions that alter the length of the growing season, planting and harvesting dates, conservation payments, crop rotations, farm size, soil characteristics, and number of years in farming of the farm operator. For developing these functions, we first used Least Absolute Shrinkage and Selection Operator (LASSO) to identify the variables that contribute to the land management decisions. Then, we developed these functions using multinomial logit regression. These estimated functions are then linked to land use and management models. We have also continued to develop the land use change model for the broader study region using spatially disaggregate remotely sensed data on land use. We improved overall model fit using regularization methods to create parse models of land use transitions primarily composed of the variables that are outputs of the dynamic regional model in order to improve the land use-economic model coupling. We also added a module to the integrated economic-land use model to represent the agricultural conservation reservation enrollment using price elasticity elicited from analysis of farmer choice survey. In line with Obj 4, we continued to work on the paper from our dynamic regional models integrating the multi-sector economic system and a health system modeling the COVID-19 spreading process in Ohio. We continued to improve our models by updating functions, recalibration, and adding endogenous estimation of carbon emissions, direct carbon removal and its cost, fossil fuel capitals and their cost, and emission target constraints. For each scenario developed in Obj 3.1, we also recalibrate its related parameters in the model. We are also working on papers on dynamic regional general equilibrium model, and dynamic stochastic spatial equilibrium model. In line with Obj 5.1-5.4, we made further progress in quantifying and evaluating various potential ecosystem services. Foremost, we improved our understanding of how bioenergy crops impact local climate via biophysical processes, determining the main contributor of such impact, and refining the life cycle assessment of bioenergy crops by incorporating the biophysical component. These objectives are achieved through combining datasets of remote sensing and reanalysis products.Second, our systematic review on modeling crop-climate relationships is still under review (major revision) in Ecological Modeling. Third, to facilitate observation-based quantification of ecosystem changes and services,we developed a new multivariate time series analysis algorithm to map land cover/land change, forest loss, and land management activities. This algorithm represents the state-of-the-art and will be submitted to a top journal in the field. The algorithm development will be further used to aid in climate impact assessment from alternative land management. In line with Obj 6.1, development of the principal agent model is occurring. We have conceptualized and reported a framework that treats weak sustainability (WS) as a default sustainability criterion while invoking strong sustainability (SS) or safety instruments to address specific acute challenges to sustainability. Two articles have been published in 2022, one of them arguing in favor of assessing changes in, rather than the absolute value of, inclusive wealth (IW). We have estimated changes in inclusive wealth from 2010 to 2017 and net carbon emissions for all 3,000+ counties in the US. This will enable comparison of the IW and SS for carbon approaches for our region and for the nation. Initial applications of SS methods to atmospheric carbon accounting for the non-urban counties show that corn-producing counties tend to release carbon in excess of their downscaled planetary boundaries, whereas forested counties are more likely to be sustainable in that dimension. We have conceptualized, and are preparing to simulate, a carbon-trading scheme that, combined with aggressive carbon sequestration efforts, can reduce the costs of reducing net carbon emissions in the region by assigning more of the abatement responsibility to counties with lower abatement costs. For Obj.7.1, we disseminated climate related results at venues including private consulting and insurance firms (e.g., Ag Credit, Ohio Agribusiness Association's Industry Conference, Al Davis Insurance Risk Management Seminar), Ag events (e.g., Conservation Tillage and Technology Conference and Farm Science Review), and at various commodity group meetings (e.g., Ohio Corn and Wheat, Soybean Council).

Publications

  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Randall, A. 2022. Driving with Eyes on the Rear-View Mirror  Why Weak Sustainability Is Not Enough. Sustainability 14, 10203. https://doi.org/10.3390/su141610203
  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Randall, A. 2022. How Strong Sustainability Became Safety. Sustainability 14 (8), 4578. https://doi.org/10.3390/su14084578.
  • Type: Journal Articles Status: Published Year Published: 2022 Citation: Wilson, A. B., A. Avila-Diaz, L. F. Oliveira, C. F. Zuluaga, and B. Mark, 2022: Climate extremes and their impacts on agriculture across the Eastern Corn Belt Region of the U.S. Weather and Climate Extremes, 37, 100467, https://doi.org/10.1016/j.wace.2022.100467.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2021 Citation: R.S. Wilson. 2021. Understanding climate adaptation and mitigation decisions in large-scale agriculture. Invited speaker at the The Ohio State University Department of Marketing Brownbag. Columbus, OH.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: R.S. Wilson. 2022. Preparing for a Hotter World. Invited plenary speaker at the American Psychological Association Division 34 Annual Meeting. Virtual Event.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: R.S. Wilson. 2022. Speed Science Talk. Invited faculty speaker at the Decision Sciences Collaborative Symposium. Columbus, OH.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: R.S. Wilson. 2022. Climate and Resilience in Midwestern Food-Energy-Water Systems. Panelist at the Global Council for Science and the Environment Annual Conference. Virtual Meeting.
  • Type: Journal Articles Status: Under Review Year Published: 2022 Citation: Walpole, H. and R.S. Wilson. In revision. Identifying who engages in sustainable adaptations in large-scale commodity agriculture. Weather, Climate and Society. Preprint available at: https://www.researchsquare.com/article/rs-936827/v1
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Cai, Y (Invited presenter). Methods and Applications of Integrated Assessment Models with Uncertainty. Institutes of Science and Development, Chinese Academy of Sciences (virtual), August 2022.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Cai, Y (Invited presenter). Integrated Assessment Model and Uncertainty. Center for Energy and Environmental Policy Research, Beijing Institute of Technology (virtual), July 2022.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Cai, Y (Invited presenter). A Simple but Powerful Simulated Certainty Equivalent Approximation Method for Dynamic Stochastic Problems. School of Economics and Management, University of Chinese Academy of Sciences (virtual), June 2022.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Irwin, E., B. Bakshi, J. Bielicki, Y.Cai, S. Chun, B. Cultice, M. Doidge, Z. Gong, Z. Guo, D. Jackson-Smith, M. Jones, J. Kast, J. Martin, A. Randall, C.D. Shaffer-Morrison, I. Sheldon, R. Wilson, Y. Xue (2022). A Regional Integrated Assessment Modeling Framework to Assess the Sustainability of the Great Lakes Economy and Food, Energy, Water Systems. Association of Environmental and Resource Economists (AERE) Annual Meeting. Miami, FL.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Irwin, Elena and Brian Cultice (2022). Spatially explicit economic interactions within and across sub-national regions. GLASSNET Conference: Managing the Global Commons. Sustainable agriculture and use of the worlds land and water resources in the 21st Century. Purdue University.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2022 Citation: Randall, Alan, Mackenzie Jones, Elena Irwin, Bhavik Bakshi, Ying Xue (2022). Weak and Strong Sustainability Assessment at Regional Scale  A Contribution to Regional Integrated Assessment Modeling with an Application to the Great Lakes Region. Association of Environmental and Resource Economists (AERE) Annual Meeting. Miami, FL.


Progress 08/01/20 to 07/31/21

Outputs
Target Audience:Target audiences reachedthrough extension and outreach, and through our advisory teamengagement,include farmers in Ohio and across portions of the easterncornbelt/Midwest,soiland water conservation districts,CCAs (Certified Crop Advisors),Extension Specialists and Educators,agricultural interest groups, conservation interest groups, and representatives of the agribusiness sector.We alsoprovidedexperientiallearning opportunities for student researchers.? Changes/Problems:The COVID-19 pandemic created some challengesin 2020 and 2021,in particular havingto moveall ofour meetings and outreach to virtualfor the entirety of this reporting cycle.We have been able to do fewer presentations to external audiences through normal extension activities, and those that we were able to do were conducted virtually.? What opportunities for training and professional development has the project provided?The project has provided Ziyu Guo (GRA) training on finding data for the regional model (particularly when direct data are missing), how to parameterize functions, and how to calibrate amodel, and how to write GAMS code to solve dynamic general equilibrium problems.The project has provided an opportunity for MacKenzie Jones and Brian Cultice (GRAs) todevelop expertise in analyzing geospatial land use data (USDA Cropland Data Layer) and estimating land use transitions(these individuals are funded on a complementary NSF project).The project provided interdisciplinary team training and meta-analysis skills to Tongxi Hu, a PhD student who volunteered to assist with the efforts in Objective 5and was funded on the project in Summer 2021.MS student Shelby Taber also received interdisciplinary team training as well as skills in conducting literature reviews and report writing, while Postdoc Hugh Walpole received interdisciplinary team training and experience analyzing farmer adaptation data and manuscript writing.Whitney Baxter, an undergraduate design student, received training in iterative design to create a science content infographic to convey information to a non-technical audience.?? How have the results been disseminated to communities of interest? Engagementwith the ag-related community throughout Ohioon the climate resultsfrom this project were made to 6programs,~350participants.However, our Obj. 2 and 3 findingswerehighlightedthroughthe presentations mentioned above, as well as a series of other products (e.g., farmer adaptation infographic) and presentations (e.g.,webinar, podcast) highlighted in our products.Thesepresentations andproductsare also made publicly available throughour website(https://u.osu.edu/agroecosystemresilience).We have alsoidentifiedkey presentations that we will give to extension and policy audiences throughout the project. These activities are detailed in an extensiveGanttchartidentifyingthe timeline for each activity and the associated finding being shared. What do you plan to do during the next reporting period to accomplish the goals? Obj 1:We will continue to meet with our stakeholder advisory team monthly to update them on project progress and seek their input on various components. We are planningour next conference call in December2021, andafourthand finalin-person(or virtual if necessary)meeting in March 2022. Obj 2: The climate team will resubmit the climate model comparison resultstoWeather and Climate Extremes. Coordination with otherobjectiveleads for model integration will continue.Additionalclimate guidance will beprovidedbased on feedback from the Stakeholder Advisory group. The climate team will continue tofinalizeall educational materials/productsper the goalsstatedfor Obj. 7. Obj 3: We willcontinue toanalyze thesurveydata andfinalizeseveral papers inpreparationor review(C. Dale Shaffer-Morrison, a new post-doc, is receiving training in interdisciplinary collaboration, and working on several papers supplementing survey data with aggregated spatial data frompublicly availabledata sets).We arein the process of estimatinga series of land management models using the data from the farmer survey. We are estimating land management decisions regardingno till,tilingand conservation,as well as the decision to chooseno adaptationas a function of the following variables: changes in climate conditions, including precipitation and temperature, that alter the planting and harvesting dates and growing season rainfall; conservation payments; crop rotations; farm size; proportion of land in retirement or dedicated to conservation; soil characteristics, including proportion of highly erodible; farmer characteristics, including number of years in farming; historical land use patterns; and county population, population change, economic conditions. Once we havefinalizedthese estimated models, we will link the land use and management models using variables that the two models have in common, which include crop choices, county population, and historical land uses. This will allow us to project land use and management changes together as inputs into the ecosystem services models.Scenario development willbefinalized,and policies will be selected to assess what type of interventions may best promote sustainability and resilience in the agroecosystem. Obj 4: We willfinalize twopapers in preparationfor publication.We will keep developing models for addressinguncertainty andanalyzingthe impact of the scenarios developed in otherobjectives(changes in land management and ecosystem services as a function of climate and farmer adaptation). We will alsokeepworkingwith Obj 6 to develop the principal-agent models and simulate their results. Obj 5: We willfinalizeresearch manuscripts on crop-climate interaction and prediction of cropyields, andimplement thenew version of the agroecosystem model-EPIC-RPto simulate the effect of climate change and farmer adaptation on our proposed suite of ecosystem services.We will also finish integrating these projected changes in ecosystem services to the dynamic, regional integrated economic model. Obj6:We will design the principal-agent model to incorporatestate-of-the-artformulations of sustainability criteria and decision criteria that are robust to uncertainty,especiallyasymmetric risks. Optimization will be assessed through experiments with the model.Sustainability criteria will include weak sustainability adapted to the regional economy, and strong sustainability restrictions on critical resources and environmental services. We will explore the implications of scale (e.g.,farm, county, whole region) on achievement of sustainability.Simulations will address BAU and four alternativescenarios andexamine the implications of alternative policies. Obj 7: Research and model outputs will be used to share project findings with specific audiencesthrough both planned presentations to key audiences, and through dissemination of these products in newsletters, on our website,etc.(see dissemination plan).Project results to date will be delivered via the Ohio Grain Symposium (Dec2021) and the North Central Climate Collaborative (Feb2022).Additionalengagements will include FSR2022.In the next year, the team intends to createthreeadditionaloverview videosand develop a learning activity that will also gather embedded evaluation data. The intent of the learning activity is to improve comprehension and retention of climate information and promote dialogue about available actions through a blend of individual rankings, small group discussion, and whole group reporting/presenting. The team intends to user test the learning activity with some of the groups to whom A. Wilson is scheduled to present and revisions will bemade,as necessary. Embedded evaluation data will be collected at various points in the activity to measure participant change.We had hoped to be able to user test and refine the lesson over the past year, but the continued pandemic made such efforts impossible.Evaluation of educational presentations and related materials will continue throughout the next reporting period.All efforts will continue to bemonitoredby the project evaluator. ?The evaluator will attend all project team meetings, work closely with the PD and team members, seek input into evaluation measures asappropriate, and present evaluation findings. ? Evaluation:Theevaluator will continue to attend project team and advisory team meetings, examine implementation and objectives,and assess the impact of educational outreach activities.?

Impacts
What was accomplished under these goals? In line with Obj 1.1, we have been engagingthe Stakeholder Advisory Team (SAT)regularly (quarterly conference calls, with one of those being an annual in-person meeting, conducted virtually this year due to COVID). In line with Obj 1.2, weare alsoassessingthe impact of the stakeholder engagement processthroughthree(to date) annual assessments.Wesharedthese resultswith the SATandcontinuedtotalk about how we can make the project results more impactfulanduseful.During the meetings,SAT participants have contributedbeneficialideas for improving educational materialsand evaluation measures,clarifyingmodelsthat have been developed,and planningproject andoutreachactivities. To complete Objectives 2.1-2.4, the climate team'sinitialpaper titled "Contemporary (1980-2018) and future (2036-2099) changes in climate extremes across the Eastern Corn Belt Region of the U.S." was rejected from the journal AtmosphericResearch.Ultimately, thepaper did not fit well within the scope of this journal, but using guidance from the review, the paper has been restructured. It is being resubmitted to a different journal: Weatherand Climate Extremes.Based onourwork, guidance and data have been provided to an NSF-sponsoredFood-Energy-Waterproject, to which manyco-investigators on this project are a part of, to help guide their modeling decisions concerning waterquality andland usechanges in the Maumee River basin. Though fewer in number due to COVID,dissemination of resultscontinued through Ag-related events in Ohio and the Midwest (See Objective 7). In line with Obj 3.1,weare continuing theconceptualization of scenariosand policiesfor modeling and simulation.Ourscenariosarebased on the UN's Shared Socioeconomic Pathways, includingabusiness-as-usualscenarioand four alternative scenariosrepresentingthe possible combinations of high vs low sustainability, and rivalry vs cooperation among nations. We are well-along withestablishingtrajectories through 2050for agricultural best management practices, agricultural yield, energy technology capital cost reductions due to technological learning, state populations, CO2?emissions, etc.Thepolicieswe will model are mostly efforts by state and local governments to augment federal policy requirements and incentives and/or address issues that have not elicited a federal response. We received suggestionsregardingparticularpoliciesduring two SAT meetings.In line with Obj 3.2and3.3, wecontinuedto work on papers from our farmer decision making models.In line with Obj 3.4, integration of farmer adaptations into simulation modeling is ongoing, and wedeveloped a land use change model for our Great Lakes study region using spatially disaggregate remotely sensed data on land use.We estimated a series of land use transition modelsas a function of historical land use allocations and current land rents, economic activity, and land quality. The estimates of these models are used to project changes in these land uses over time. The projection of changes in wetlands andforestsin each county is based on historical trends.Net forest area increased from an estimated 22.5% to 24.7% from 2008-2018 in the 5-state regionand net pasture area decreased the most from 16.5% to 12%. There were slight net increases in urban, cropland, and wetlands during this period.The 5-state regionexhibitstwo distinct land use change regimes: the northernportionof the regionhasmore wetlands, forest, and less urban land than the southernportion. This northern area alsowitnessedmore land transitioning to and from cropland and pasture and more land transitioning from cropland to urban uses.The amount of land converted into urban land is negatively influenced by cropland rents, soil quality, and the baseline amount of county land in crops; it ispositivelyinfluenced by population, the baseline amount of urban land, and pasture rents. In line with Objective 4, we built a dynamic regional model integrating the multi-sector economic system and a health system modeling the COVID-19 spreading process in Ohio. We collected related data, calibrated parameters, estimated the damage from the pandemic, and provided economic policy analysis.Theresults indicate that theCOVID-19pandemicled to nearly 8% loss of outputandnearly 50% reduction in investment in Ohio in the worstmonth, but vaccinationseffectively reducedthe pandemic spread andeconomic loss. In line with Obj5.4, we finished a journal paper that explored the biophysical effects of forest loss on local land surface temperature (LST). Our analyses combined multiple long-term satellite products at 700 sites across major climate zones in the conterminous United States, using time-series trend and changepoint detection methods. Our method helped isolate the biophysical changes attributed to disturbances from those attributed to climate backgrounds and natural growth. We found that forest loss increased surface albedo, decreased evapotranspiration, and reduced leaf area index LAI. Net annual warming--an increase in LST--was observed after forest loss in the arid/semiarid, northern, tropical, and temperate regions, dominated by the warming from decreased ET and attenuated by the cooling from increased albedo. In line with Obj 6.1,development ofthe principal agent model is occurring.We have conceptualized and reported a framework that treatsWSas a default sustainability criterion while invokingSSor safety instruments to address specific acute challenges to sustainability.Two articles have been published. We have estimated an inclusive wealth index for the state of Ohio as a first step to implementing a measure of WS for the region.Initial applications of SS methods to atmospheric carbon accounting for the non-urban counties show that corn-producing counties tend to release carbonin excess oftheir downscaled planetary boundaries,whereasforested counties are more likely to be sustainable in that dimension.We have conceptualized, and are preparing to simulate, a carbon-trading scheme that, combined with aggressive carbonsequestrationefforts, can reduce the costs of reducing net carbon emissions in the region.In addition, uncertain future climate and agroecosystem conditions involve asymmetric risks, where worst-case losses maysubstantially exceedgains. In contrast to standard expected-value maximization, robust decision criteria include sustainability and safety (i.e.,strict avoidance of worst-case outcomes at (perhaps substantial) loss of expected value). For Obj.7.1,wedisseminatedclimaterelated results atvenues including private consultingand insurancefirms (e.g.,Aimpoint Research, Nationwide Insurance Board Council),Ag events (Conservation Tillage and Technology Conference, Agraria & Community Solutions Growing Green, andOhio Grain Symposium).We also presented talks atOSU Farm Science Reviewand through aNorth Central Climate Collaborative Webinar. Evaluation responsesindicated thatparticipants planned to share informationfrom the webinarwith othersandthat theinformation presented wouldbehelpful intheirworkwith farmers. For Obj. 7.2,wecreatedafarmer adaptationinfographicand asecondseries of educational videosfocusing on ecosystem services and the policy assessmentisbeing developed.The video page also includes interviews that the team conducts with media outlets.Evaluation measures have been developed fortheeducational presentations on climate and agriculture forstakeholder audiences.Participants have reported increases in theirknowledge of climate and agriculture, including awareness of changes that are happening, challenges farmers will face, and ways they can reduce negative impacts on their farming operations.The project evaluator monitored project implementationbyregularlyattending project and advisory team meetingsanddiscussingobjectiveswith the PI, co-PI's, and staff.The evaluator alsodevelopedevaluation measures for educational outreach programs.?

Publications

  • Type: Other Status: Other Year Published: 2020 Citation: Wilson, RS. 2020 (November). The role of climate-exacerbated hazards and adaptation in engaging rural audiences. Midwest Climate Summit Outreach & Engagement Workshop. The Science of Climate Communication: How to reach conservatives and moderates. Virtual.
  • Type: Other Status: Other Year Published: 2021 Citation: Wilson, RS and M. Doidge. 2021 (April). Understanding climate adaptation decisions in the eastern Corn Belt. Environmental Science Graduate Program Seminar. Columbus, OH.
  • Type: Other Status: Other Year Published: 2021 Citation: Wilson, RS. 2021 (May). Understanding climate adaptation decisions in large-scale agriculture. Stanford University Speaker Series. Approaching Sustainability: Conversations with Leading Scholars. Virtual.
  • Type: Journal Articles Status: Under Review Year Published: 2021 Citation: Walpole, H. and R.S. Wilson. In review. Identifying who engages in sustainable adaptations in large-scale commodity agriculture. Climatic Change. Preprint available at: https://www.researchsquare.com/article/rs-936827/v1
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Kien, ND, T Ancev, A Randall 2021. Farmers choices of climate-resilient strategies: Evidence from Vietnam, Journal of Cleaner Production, 317, p. 128399. https://doi.org/10.1016/j.jclepro.2021.128399.
  • Type: Journal Articles Status: Under Review Year Published: 2021 Citation: Wilson, A. B, A. J. Avila-Diaz, B. Mark, 2020: Contemporary (1980-2018) and future (2036-2099) changes in climate extremes across the Eastern Corn Belt Region of the U.S. Resubmission forthcoming
  • Type: Book Chapters Status: Published Year Published: 2021 Citation: Cai, Y. 2021. The Role of Uncertainty in Controlling Climate Change. Oxford Research Encyclopedia of Economics and Finance. Oxford University Press. https://doi.org/10.1093/acrefore/9780190625979.013.573
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Cai, Y (Presenter). A dynamic regional economic model to evaluate impacts of deglobalizing forces on food, energy and water systems and the sustainability of the Great Lakes region. AAEA Annual Meeting (virtual track session), August 2020.
  • Type: Book Chapters Status: Published Year Published: 2020 Citation: Doidge M., EG Irwin, N Sintov, RS Wilson (2020). Human Behavior and Adaptation. The Food-Energy-Water Nexus Saundry, Peter, Ruddell, Benjamin.
  • Type: Other Status: Other Year Published: 2020 Citation: Irwin, E.G. (invited panelist) (2020). Downscaling sustainability theory and measurement to subnational regional scales. National Academies Panel on Measuring Progress toward Sustainable Development. Virtual Session.
  • Type: Other Status: Other Year Published: 2020 Citation: Irwin, E.G. (Invited panelist) (2020). Gordon Rausser Keynote Panel on "Sustainability: the interface of food, agriculture, and the environment". AAEA Annual Meeting. Virtual Session.
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Li, Y., Liu, Y., Bohrer, G., Cai, Y., Wilson, A., Hu, T., Wang, Z. and Zhao, K., 2021. Impacts of forest loss on local climate across the conterminous United States: Evidence from satellite time-series observations. Science of The Total Environment, p.149651 (19 pages).
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Randall, A. 2021. Resource Scarcity and Sustainability  The Shapes have Shifted but the Stakes Keep Rising. Sustainability 13, 5751. https://doi.org/10.3390/su13063181
  • Type: Journal Articles Status: Published Year Published: 2021 Citation: Randall, A. 2021. Monitoring Sustainability and Targeting Interventions: Indicators, Planetary Boundaries, Benefits and Costs. Sustainability 2021, 13, 3181. https://doi.org/10.3390/su13105751
  • Type: Other Status: Other Year Published: 2021 Citation: Wilson, R.S. and A. Wilson. 2021 (February). Agroecosystem Resilience: Regional integrated modeling of farmer adaptations to guide management in a changing climate. NC3 Webinar. Virtual.


Progress 08/01/19 to 07/31/20

Outputs
Target Audience:Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs, insurance professionals, Extension Specialists and Educators, agricultural interest groups, conservation interest groups, and representatives of the agribusiness sector. We also provided experiential learning opportunities for student researchers. Changes/Problems:The COVID-19 pandemic created some challenges this past year, in particular having to move all of our meetings and outreach to virtual as of March 2020. We have been able to do fewer presentations to external audiences through normal extension activities, and those that we were able to do were conducted virtually. What opportunities for training and professional development has the project provided?This project provided an opportunity for an international scholar from Colombia, Alvaro Avila-Diaz, who was completing his doctorate degree with the Department of Agricultural Engineering, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil, to collaborate with our interdisciplinary team. Dr. Avila-Diaz assisted in analyzing climate extremes for the ECBR using techniques he utlized in his doctoral work and is co-authoring the manuscript. The project has provided Ziyu Guo (GRA) training on finding data for the regional model (particularly when direct data are missing), how to parameterize functions, and how to calibrate a model, and how to write GAMS code to solve dynamic general equilibrium problems. The project has provided an opportunity for MacKenzie Jones and Brian Cultice (GRAs) to develop expertise in analyzing geospatial land use data (USDA Cropland Data Layer) and estimating land use transitions (these individuals are funded on a complementary NSF project). The project provided interdisciplinary team training and survey design expertise to Mary Doidge, a post-doc who left the project in December 2019 to take a tenure track position. The project provided interdisciplinary team training and meta-analysis skills to Tongxi Hu, a PhD student who volunteered to assist with the efforts in Objective 5. Maria Burns, an undergraduate design student, received training in iterative design to create a science content infographic to convey information to a non-technical audience. How have the results been disseminated to communities of interest?Engagement utilizing results from Obj 2 with Ag-related community throughout Ohio has been weaker than 2019 due to COVID-19, with about 18 presentations made to ~800 participants during this reporting cycle. Our Obj. 2 and 3 findings have been highlighted through three videos that were created and released during OSU's 2020 Farm Science Review, which was held virtually this year due to the COVID-19 Pandemic. The videos providing a description of the project by Robyn Wilson, a summary of climate modeling by Aaron Wilson, and an overview of the farmer survey method and results by Mary Doidge. A talk given by Robyn Wilson titled Adapting to Changing Weather Patterns in the Eastern Corn Belt was also recorded. All four videos map be viewed at https://u.osu.edu/agroecosystemresilience/videos/. An infographic was created to convey the results of the climate modeling to the stakeholder communities. The graphic was developed by undergraduate design student Maria Burns in collaboration with Aaron Wilson. The Stakeholder Advisory Board offered suggestionsand feedback throughout the design process. Beyond the project team, the graphic has also been used by members of the State Climate Office of Ohio as it clearly conveys trends that they are trying communicate. The infographic may be viewed at go.osu.edu/climatecornbelt. These products have been disseminated to critical audiences through our website (https://u.osu.edu/agroecosystemresilience) and associated websites, webinars, stakeholder newsletters, and our College communications staff. We have also identified key presentations that we will give to extension and policy audiences throughout the project. These activities are detailed in an extensive gantt chart identifying the timeline for each activity and the associated finding being shared. What do you plan to do during the next reporting period to accomplish the goals?Obj 1: We will continue to meet with our stakeholder advisory team monthly to update them on project progress and seek their input on various components. We are planning our next conference call in December 2020, and a third in-person (or virtual if necessary) meeting in March 2021. Obj 2: The climate team will resubmit the climate model comparison results to a scientific journal. Coordination with other objective leads for model integration will continue. Additional climate guidance will be provided based on feedback from the Stakeholder Advisory group. The climate team will continue to finalize all educational materials/product per the goals stated for Obj. 7. Obj 3: We will continue to analyze the survey data, and finalizel the several papers in preparation. We will calculate land use change transitions and use these data to develop a predictive model of agricultural land use change. The likely adaptations will be integrated into this model to develop a combined model of land use/management to assess future changes in ecosystem services and regional economic conditions given likely farmer responses to climate change. Scenario development will continue and potential scenarios will be discussed with the SAT. Obj 4: We will complete a manuscript for publication on the economic model. We will keep developing models for addressing uncertainty, and analyze the impact of the scenarios developed in other objectives (changes in land management and ecosystem services as a function of climate and farmer adaptation). We will also work with Obj 6 to develop the principal-agent models and simulate their results. Obj 5: We will continue to collect and process watershed data of all sorts for preparing watershed-level model simulation. We will finish and submit two research manuscripts on crop-climate interaction and prediction of crop yields. We will implement the proposed new version of the agroecosystem model-EPIC-RP. Obj 6: We will design the principal-agent model to incorporate state-of-the-art formulations of sustainability criteria and decision criteria that are robust to uncertainty, expecially asymmetric risks. Optimization will be assessed through experiments with the model. Sustainability criteria will include weak sustainability adapted to the regional economy, and strong sustainability restrictions on critical resources and environmental services. We will explore the implications of scale (e.g. farm, county, whole region) on achievement of sustainability. Obj 7: Research and model outputs will be used to share project findings with specific audiences through both planned presentations to key audiences, and through dissemination of these products in newsletters, on our website, etc (see dissemination plan). Project results to date will be delivered via the Ohio Grain Symposium (Dec 20) and the North Central Climate Collaborative (Feb 21). Additional engagements will include FSR 2021. Efforts have begun to create an infographic to communicate farmer survey results to a non-technical. In the next year, the team intends to create one additional overview video and develop a learning activity that will also gather embedded evaluation data. The intent of the learning activity is to improve comprehension and retention of climate information and promote dialogue about available actions through a blend of individual rankings, small group discussion, and whole group reporting/presenting. The team intends to user test the learning activity with some of the groups to whom A. Wilson is scheduled to present and revisions will be made as necessary. Embedded evaluation data will be collected at various points in the activity to measure participant change. Due to the pandemic, at least some of these sessions will be virtual. Evaluation of educational presentations and related materials will continue throughout the next reporting period. All efforts will continue to be monitored by the project evaluator. The evaluator will attend all project team meetings, work closely with the PD and team members, seek input into evaluation measures as appropriate, and present evaluation findings.

Impacts
What was accomplished under these goals? In line with Obj 1.1, we have been engaging the Stakeholder Advisory Team (SAT) regularly (quarterly conference calls, with one of those being an annual in-person meeting, conducted virtually this year due to COVID). In line with Obj 1.2, we are also assessing the impact of the stakeholder engagement process through two (to date) annual assessments. We shared these results with the SAT, and continue to talk about how we can make the project results more impactful and useful. To complete Objectives 2.1-2.4, the climate team explored observed trends in climate extremes over the Eastern Corn Belt region between 1980 and 2018. We compared statistically downscaled CMIP5 models to assess how well the models perform. Based on this analysis, we constructed an optimal model ensemble to investigate future climate projections for mid and late 21st century under RCP4.5 and RCP8.5. We found significant observed climate trends that present many challenges to agriculture. We found a large range in the performance of various models and model ensembles compared to observed climate extremes, with variability even among sub-watershed regions and across different variables. Different models and ensembles of models lead to important differences in the degree of future projections and using models that perform well over the observed period does not necessarily limit the variability within future scenarios. While there is consensus in a future reality that is warmer and wetter, representation of climate extremes in models is an evolving process, and there are likely future changes in these climate extremes that we are not yet able to detect. This suggests that effective adaptation and mitigation measures for agriculture should be flexible and scalable across different regions. In line with Obj 3.1, we began the conceptualization of scenarios for modeling and simulation. Scenarios are coherent sets of trends and external drivers that will influence the future economy of the regional system and, for policy simulations, include policy drivers that potentially might be implemented in the region. Because our region is nested in the nation, which is nested in the world, scenarios will be expressed at all three levels: regional initiatives will overlay national trends and drivers, which will overlay international trends and drivers. We are well-along in developing the bottom two layers, international and national. In line with Obj 3.2, we have developed a model of farmer utility maximization that reflects both profit and non-profit motives. To specify this model, we have assembled data on land use, land use change, cropland and pasture rents, physical land characteristics, proximity to urban areas and other geographic features. We have estimated reduced form hedonic models of land values to examine how physical land characteristics, including soil type and slope, are capitalized into agricultural land values. In line with Obj 3.3, we analyzed the survey data to assess what climate impacts and behavioral factors are most likely to encourage particular adaptations. A report on the survey findings was completed and distributed to the SAT. In line with Obj 3.4, survey data analysis and integration of farmer adaptations into simulation modeling is ongoing. For example, we found that larger farms are more likely to adapt, as are those individuals with stronger reported experience with climate impacts. We can then simulate how farm sizes will change in the future, and how experience with climate impacts will change, allowing us to simulate how adaptation decisions will be made over time. In line with Obj 4.1, we have built a dynamic multi-sector regional economic model that consists of a representative household, crop farming firms, livestock firms, food production firms, manufacturing firms, and market clearing conditions. The model assumes that the household owns land and shares of all firms. At each period, the household receives profits from these firms, wages, rents of capital and land, and potential subsidies. At the same time, the household decides investment for the next period, and consumption of food and manufactured goods in the current period. The optimal land allocation, labor supply, wages, and prices are endogenously derived from equilibrium among the sectors. In line with Obj 4.2, we have calibrated all parameters of the model and successfully obtained a reasonable simulation solution under the baseline scenario. For Obj 4.3 and 4.4 we are working on addressing uncertainty and alternative scenarios. In line with Obj 5.1-5.3, we finished a review paper on statistical modeling for crop yield prediction, highlighting the lack of localized information on crop-climate interactions and the inherent model uncertainties rarely accounted for explicitly. We developed a state-of-the-art machine learning model to infer the statistical linkage between crop yield and major climatic variables. The implementation of the model is in Matlab and will be made publicly available once the relevant manuscripts are finalized. To address the research goals in Object 5.1 and 5.3, we applied the Bayesian modeling to the US corn belt region at the county level; the results show how crop responses to climate change vary from one region to another and offer new information about the current regime of climate-crop interactions. This work is drafted in a manuscript. In addition to statistical modeling, we conducted intensive evaluation of a mechanistic agroecosystem model "EPIC"; our initial finding is that EPIC has difficulties in simulating crop dynamics for C4 crops under a changing climate. We found the problem is largely attributed to the relatively simplistic parameterization of crop growth/photosynthesis. This limitation is not unique to EPIC but is a weakness of the majority of existing crop models used to support climate policies. We started an ambitious effort to replace the RUE scheme with a modern scheme; we have been and will incorporate a more realistic radiative transfer scheme (i.e., the two stream model) and a biochemical photosynthesis model (i.e., the Farquhar model) into EPIC. In line with Obj 6.1, development of the principal agent model is occurring simultaneously to Obj 4 model development. In regards to Obj 6.2, the standard concepts of sustainability were developed for national economies and are now being adapted for regional and sectoral economies. This work is well-advanced, with one article published and several manuscripts in preparation. A robust finding is that sustainability can be achieved more readily as economic scale increases, enabling more options to assign responsibility for solutions to those sectors and/or localities that can make progress at lower cost. In addition, uncertain future climate and agroecosystem conditions involve asymmetric risks, where worst-case losses may substantially exceed likely gains. In contrast to standard expected-value maximization, robust decision criteria include sustainability and safety (i.e. strict avoidance of worst-case outcomes at (perhaps substantial) loss of expected value). Conceptual work on the advantages and limitations of safety criteria has been presented to professional audiences, and one article published. For Obj. 7.2, we completed the climate projections infographic. A series of educational videos were developed and deployed via our project website. Evaluation measures have been developed for the educational presentations on climate and agriculture for stakeholder audiences. Participants have reported increases in their knowledge of climate and agriculture, including awareness of changes that are happening, challenges farmers will face, and ways they can reduce negative impacts on their farming operations.

Publications

  • Type: Journal Articles Status: Submitted Year Published: 2020 Citation: Wilson, A. B, A. J. Avila-Diaz, B. Mark, 2020: Contemporary (1980-2018) and future (2036-2099) changes in climate extremes across the Eastern Corn Belt Region of the U.S. Resubmission forthcoming.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Wilson, R.S. 2020. Understanding climate adaptation decisions in the eastern Corn Belt. Invited Seminar. Department of Geography, The Ohio State University. Virtual.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Wilson, R.S. 2020. Understanding climate adaptation decisions in the eastern Corn Belt. Farm Science Review, The Ohio State University. Virtual. https://u.osu.edu/agroecosystemresilience/videos/
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Wilson, R.S. 2020. Understanding climate adaptation decisions in the eastern Corn Belt. Soil and Water Conservation Society Annual Meeting. Virtual.
  • Type: Other Status: Published Year Published: 2020 Citation: Taber, S., Doidge, M., and Wilson, R. 2020. Farmer Adaptation to Changes in Extreme Weather: Survey Report. Columbus, OH: The Ohio State University, School of Environment & Natural Resources.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Doidge, M. 2020. The influence of subsidised crop insurance on farmers future climate change adaptation decisions. Canadian Agricultural Economics Society Annual Meeting. Virtual.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Doidge, M. 2020. Crowding out or crowding in? The influence of subsidised crop insurance on farmers on-farm climate change adaptation decisions. Agricultural and Applied Economics Association Annual Meeting. Virtual.
  • Type: Book Chapters Status: Awaiting Publication Year Published: 2020 Citation: Cai, Y. The Role of Uncertainty in Controlling Climate Change, In the Oxford Research Encyclopedia of Economics and Finance. Oxford University Press. doi: 10.1093/acrefore/9780190625979.013.573. Forthcoming.
  • Type: Conference Papers and Presentations Status: Other Year Published: 2020 Citation: Hu, T., & Zhao, K. Modeling nonlinear crop responses to climate variability in the US Using a Bayesian Approach. Fall Meeting, American Geophyiscal Union, December, 2019.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Randall A. 2020. On Intergenerational Commitment, Weak Sustainability, and Safety. Sustainability, 12 (13), 5381; doi:10.3390/su12135381
  • Type: Websites Status: Other Year Published: 2020 Citation: Wilson, R.S. et al. Agroecosystem Resilience Project is a website providing project information and copies of products created for the project, including slides, handouts, graphics, videos, and links to research publications. https://u.osu.edu/agroecosystemresilience


Progress 08/01/18 to 07/31/19

Outputs
Target Audience:Target audiences reached through extension and outreach, and through our advisory team engagement, include farmers in Ohio and across portions of the eastern cornbelt/Midwest, soil and water conservation districts, CCAs, insurance folks, Extension Specialists and Educators, agricultural interest groups, conservation interest groups, and representatives of the agribusiness sector.We also provided experiential learning opportunities for student researchers. Changes/Problems:Our typical survey vendor was unable to administer the survey, so we had to work with a new local vendor who was more expensive than expected.This may require us to use funds from elsewhere in the budget to support survey data collection, and/or we may adjust our administration and recruitment process to decrease costs. What opportunities for training and professional development has the project provided?This project supported a research associate position for female graduate student Emily Sambuco, who graduated with a Masters in Atmospheric Science in Spring 2019. This gave Emily an opportunity to gain knowledge on data optimization and working with large atmospheric data sets. Emily has taken a position in Boston, MA as a weather analyst for Liberty Mutual Insurance.The project has provided Brian Cultice and Ziyu Guo (GRAs) and training on finding data for the regional model (particularly when direct data are missing), how to parameterize functions, and how to calibrate a model.The project provided interdisciplinary team training and survey design expertise to Mary Doidge, a post-doc who will leave the project in December 2019 to take a tenure track position.The project provided interdisciplinary team training and meta-analysis skills to Tongxi Hu, a PhD student who volunteered to assist with the efforts in Objective 5. How have the results been disseminated to communities of interest?Engagement with Ag-related community throughout Ohio has been strong, including about 55 presentations made to ~2500 participants during this reporting cycle. A marquee event in July 2019 included an audience of 130 in London, Ohio and included the topics of weather and climate, price and production risk, soil health, lessons from other states throughout the region, and a farmer guided panel. Presentations were recorded to make the information available to a wider audience online following the event. Event materials including presentations and bios may be found athttps://u.osu.edu/climatesmart/july18/. Although dissemination was limited in year 1 as the research is initiated, we did develop an extensive dissemination plan focused on four key findings (climate trajectories, farmer profiles, agroecosystem impacts and policy scenarios). These findings will be highlighted in a series of products including an infographic, a 3 minute video, and fact sheets (one each for farmer and policy/decision makers). These products will then be disseminated to critical audiences through several designated means, including our website and associated websites, webinars, stakeholder newsletters, and our College communications staff. We have also identified key presentations that we will give to extension and policy audiences throughout the project. These activities are detailed in an extensive gantt chart identifying the timeline for each activity and the associated finding being shared. What do you plan to do during the next reporting period to accomplish the goals?Obj 1: We will continue to meet with our stakeholder advisory team monthly to update them on project progress and seek their input on various components.We are planning our next conference call in December 2019, and a second in-person meeting inMarch 2020. Obj 2: The climate team will complete the analysis of the LOCA and Daymet comparison across the ECBR. Results from this study will published in a scientific journal. Data will be finalized in the format necessary to complete Obj 5.The climate team will also finalize all educational materials/product per the goals stated for Obj. 7. Obj 3: We will complete survey data collection and analyze the data.The likely adaptations will then be integrated into the ecosystem services model to assess future changes in services given likely farmer responses to climate change. Obj 4: We plan to finish all data collection and cleaning and calibration of the regional economic model to match data. We will then analyze the impact of the scenarios developed in other objectives (changes in land management and ecosystem services as a function of climte and farmer adaptation), and start to write a paper for publication. Obj 5: We will be working with the climate team to incorporate the downlscaled climate data into our modeling framework. We will finish and submit the review paper on climatic impacts on crop yield. Our team will also prepare the inputs for two ecosystem service models, EPIC and SWAT. Obj 6: We will design the principal-agent model to incorporate state-of-the-art formulations of sustainability criteria and decision criteria that are robust to uncertainty, expecially asymmetric risks. Optimization will be assessed through experiments with the model. Obj 7: Research and model outputs will be used to create an inforgraphic, video, and extension fact sheet for four key project findings.These products will be used to share project findings with specific audiences through both planned presentations to key audiences, and through dissemination of these products in newsletters, on our website, etc (see dissemination plan).

Impacts
What was accomplished under these goals? In line withObj 1.1, we created our Stakeholder Advisory Team (SAT) and have been engaging them in quarterly video conference calls and an annual in-person meeting.In line withObj 1.2, we have begun to assess the impact of the stakeholder engagement process by collecting baseline information from our project and stakeholder advisory team about what they perceive to be the goals of the project and the potential benefits, as well as what they perceive their role to be. This baseline assessment indicates that the research team needs to improve the clarity of the advisory team's role and ensure that project decisions are transparent. We see severalareas for improvement, andwe hope that by the end of the project the stakeholders will believe more in the usefulness of the results for their own decision making. We will work in future advisory meetings to share these results, and talk about how we can make the project results more impactful, useful, etc. In line withObj. 2.1, the climate team has obtained robust scientifically-vetted future climate projections (i.e., Locally Constructed Analog (LOCA) statistically downscaled climate projections for North America based on the Coupled Model Intercomparion Project (CMIP5)). Analysis on this data is underway.To assist in the analysis forObjs. 2.2 - 2.4,we identified the climate record stations throughout the ECBR that have robust, nearly complete records to compare to the downscaled LOCA climate projections.Three of the chosen watersheds did not have long-term, complete records for comparison. So we decided to use another dataset for comparison, Daymet (https://daymet.ornl.gov/overview). The methodology for Daymet allows for the interpolation and extrapolation of data from available meteorological observations to produce estimates of daily weather where stations are scarce. This gridded product is also allowing us to analyze changes in temperature and precipitation extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). This will help assess the historical extremes (Obj. 2.2)and future projections (Objs. 2.3-2.4).In line withObjs. 2.3-2.4,we used the LOCA dataset present projected ranges in temperatures, growing degree days, precipitation, etc, to the SAT. Based on feedback from the SAT, the survey team constructed scenarios based on high/low extremes of precipitation paired with other qualitative data impacted by temperatures (e.g., planting & harvest date) for use in the survey. In line withObj 3.1, we worked with our advisory team to develop future climate scenarios and potential farmer adaptations. We used this input to design a survey assessing farmer climate adaptations. In line withObj 3.2, we have collected historical data, but have not yet started estimating the empirical models of past adaptation in response to climate shifts. In line withObj 3.3, we also launched the survey to assess what climate impacts are most likely to encourage particular adaptations. In line withObj 4.1, we have built a preliminary multi-sector regional economic model that consists of a representative household, farming firms, food production firms, manufacturing firms, and market clearing conditions. The model assumes that the household owns land and shares of all firms. At each period, the household receives profits from these firms, wages, rents of capital and land, and potential subsidies. At the same time, the household decides investment for the next period, and consumption of food and other goods and services in the current period. The optimal land allocation, labor supply, wages, and prices are endogenously derived from equilibrium among the sectors. In line withObj 4.2, we are collecting and cleaning data in the ECBR for parameterizing the production functions, and then we will run our model to calibrate other indirect parameters such that our simulated results match with those data. We expect it will be completed by Feburary 2020. We are starting to think aboutObj 4.3(which builds on Obj 4.1 & 4.2), and after we completeObj 4.2,we will start to work onObj 4.4(which is based on Obj 4.3). In line withObj 5.1 & 5.2,we have been collecting and compiling a suite of environmental variables that are known to be related to ecosystem services. These variables will serve as inputs for our model-based analyses.The majority of the data collected are spatially-explicit layers, representing various environmental covariates such as weather and climate, soil parameters, land use/land cover, crop types, and topography. These spatial layers are secondary data retrieved from a variety of sources. These data, however, can't be directly applied for our modeling and analyses, due to their disparate characteristics in terms of spatial and temporal resolutions. We are currently processing them into meaningful formats and statistics conducive to our modeling efforts and watershed-level analyses.ForObj 5.1, we also performed a comprehensive literature review on crop yield responses to climate change and variability. The evidence synthesized from this literature review will serve as a baseline to guide our modeling efforts, and will be drafted into a review paper.We have yet to begin work onObjs. 5.3and5.4, which are about quantifying changes in ecosystem services, as this component builds on results from prior objectives about potential climate change and farmer adaptations. In line withObj 6.1, the principal agent model will be an offspring of the Objective 4 model, so development is occurring simultaneously to model development in Obj 4.In regards toObj 6.2, work has begun ahead of the schedule on the optimal policy ensemble, which will, among other things, enhance the sustainability and resilience of the regional agroecosystem and be robust to uncertain future climate and agroecosystem conditions. Work in year 1 was mostly conceptual, developing a sound theoretical base for policy analysis. The standard concepts of sustainability were developed for national economies little affected by trade and human migration.An essential first step is to adapt these concepts for regional and sectoral economies.This work is well-advanced, with manuscripts in preparation.Uncertain future climate and agroecosystem conditions involve asymmetric risks, where worst-case losses may substantially exceed likely gains.In contrast to standard expected-value maximization, robust decision criteria include sustainability and safety (i.e. strict avoidance of worst-case outcomes at (perhaps substantial) loss of expected value.Conceptual work on the advantages and limitations of safety criteria is well advanced and papers have been presented to professional audiences. To prepare forObj. 7.1 (dissemination)and7.2 (product development), we developed a dissemination plan highlighting four key findings or outputs from the project that will disseminated through a variety of outlets at regular intervals. While our specific development of products and dissemination of results has been limited in year 1, the extension team presented on the changing climate and impacts on agriculture in Ohio and across the ECBR to 55 audiences, engaging ~ 2500 participants during the reporting year. Although these events were not unique to our project, they highlighted the work being done by PI A. Wilson.In line with our first planned set of products on the project and the climate trajectories, an undergraduate design student at the Byrd Center has started to design infographics to communicate the project work performed so far, including the climate projections (means and ranges) and the choice conditions that we be available to survey participants.

Publications

  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Randall, A. Validating Integrated Assessment Models  a methodological inquiry, Taiwan National Science Council distinguished lecture, National Chi-Nan University, Puli, TW, December 5, 2018.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Randall, A. Optimal, Sustainable and Safe  The Sweet Spot?, Keynote Address, Taiwan Association of Agricultural Economists, Taipei, TW, December 8, 2018.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2018 Citation: Randall, A. If we have Optimality and Sustainability, what does Safety add?, Taiwan National Science Council distinguished lecture, National Chung-Hsing University, Tai-Chung, TW, December 6, 2018.
  • Type: Websites Status: Published Year Published: 2018 Citation: Wilson, Robyn et al. Agroecosystem Resilience Project. Website providing project information and copies of products created for the project. https://u.osu.edu/agroecosystemresilience
  • Type: Websites Status: Published Year Published: 2019 Citation: Website from Climate Smart July event: https://u.osu.edu/climatesmart/july18/ with embedded videos of presenters.
  • Type: Other Status: Published Year Published: 2019 Citation: Wilson, A. 2019. Climate smart: Farming with extreme weather. Extension presentation. https://vimeo.com/354284653