Grantee Research Project Results
2002 Progress Report: Close-coupling of Ecosystem and Economic Models: Adaptation of Central U.S. Agriculture to Climate Change
EPA Grant Number: R828745Title: Close-coupling of Ecosystem and Economic Models: Adaptation of Central U.S. Agriculture to Climate Change
Investigators: Antle, John M. , Capalbo, Susan M. , Elliot, Edward T. , Paustian, Keith , Mooney, Sian , Hunt, William
Current Investigators: Antle, John M. , Capalbo, Susan M. , Hunt, William , Paustian, Keith , Mooney, Sian , Hoagland, Kyle D.
Institution: Montana State University - Bozeman , University of Nebraska at Omaha , Colorado State University
Current Institution: Montana State University - Bozeman
EPA Project Officer: Packard, Benjamin H
Project Period: October 1, 2000 through September 1, 2003
Project Period Covered by this Report: October 1, 2001 through September 1, 2002
Project Amount: $1,420,860
RFA: Assessing the Consequences of Interactions between Human Activities and a Changing Climate (2000) RFA Text | Recipients Lists
Research Category: Climate Change , Air
Objective:
The main objective of this research project is to significantly advance the state-of-the-art in modeling impacts of climate change in agroecosystems by moving beyond the loose coupling of unrelated and independent disciplinary models. This research project focuses on the development of a conceptual framework for closer model coupling and the implementation of the close coupling of an ecological model with an economic decision model. This project is investigating how our ability to simulate behavior in response to climate change is affected by the temporal and spatial scales of analysis, the degree of coupling of the models, and the dynamic properties of the models. This is being done for one of the most important agroecosystems-the crop-based system of the Central United States.
The specific objectives of this research project are to: (1) develop methods to more closely couple existing ecological and economic models that can be used to assess the impacts of climate change in agricultural ecosystems, which involves linking processes in ecological models with land use and input use decisions in economic models, so that the type and strength of feedback between ecological and economic processes is suitably represented; (2) simulate the ecological and economic impacts of climate change on agriculture in the Central United States, using data at various scales (field/farm, county, and Major Land Resource Area [MLRA]) and using a range of climate change scenarios and sensitivity analyses; and (3) investigate the dynamic and spatial properties of agricultural ecosystems to assess how estimates of the impacts of climate change are affected by the choice of spatial scale, temporal scale, and degree of model coupling. These properties will be compared at the farm/field, county, and MLRA scales in the Central United States using primary data collected by the Principal Investigators, and secondary data collected by various state and federal agencies.
Progress Summary:
During the first year of the project, we: (1) continued work to assemble data for the estimation and testing of farm-scale and county-scale models; (2) completed the development of a county-scale econometric process simulation model for the Central United States; (3) began the development of procedures to closely link ecosystem and economic simulation models; (4) began the development of procedures for climate scenarios for sensitivity analysis; and (5) completed publications and draft manuscripts for Year -1 work..
Data Development for Model Estimation, Testing, and Validation. During Year 2 of the project, our efforts focused on finalizing data and models to be used in the sensitivity analysis and developing procedures to more closely couple biophysical and economic models. This work was described in detail in the 2001 Annual Report. The work involved the following activities: (1) the development of a field-scale econometric-process model for Nebraska for analysis of scale effects in conjunction with the county-level analysis; (2) the development of a county-scale and regional-scale econometric process model of agricultural production systems; (3) assembly of soils and climate data for the 21-state Central United States region (these data will be used to implement the Century model for this region); (3) compilation of detailed management data (crop rotation, tillage practices, fertilizer and manure application, and irrigation) for the 21-state region to support the Century model applications; and (4) examination of agricultural census data from years prior to 1982 (these data will be used to test and validate the county-level model).
Analysis of the Dynamic Properties of Coupled Ecosystem and Economic Models. Our work on the dynamical properties of agroecosystems includes studies of chaos and of multiple stable equilibria (MSA). We showed that an empirical method widely applied for detecting chaos in ecological time series is unreliable. However, an alternative approach (determining the dynamic properties of mechanistic models fitted to the data) holds promise, and we will apply this method to our agroecosystem models. We have mapped out an approach for detecting MSA in agroecosystem models (applying optimization to search for multiple sets of state variable values yielding zero rates of change), and will soon test the approach using an ecological model known to have MSA. In related work, we have explored how our coupled ecosystem and economic models could give rise to MSA, for example, because of biophysical and economic thresholds.
Development of a County-Scale Econometric-Process Simulation Model for the Central United States. We have developed and begun testing a county-scale econometric-process and simulation model for the Central United States. This model will follow the same principles as the field-scale econometric-process models that we have developed previously. A key challenge in doing this is to account for the effects of aggregation on the way the model can be specified and estimated.
The model we are developing is based on the hypothesis that farmers make long-term decisions to choose a production system and then allocate land and other resources within the system. Thus, the model consists of two nested systems of equations. The first system represents the choice of production system and the second system represents the allocation of land among crops that characterized that system.
An important issue to be addressed is how to establish linkages between the Century ecosystem model and the county-level economic simulation model. In the field-scale model, carbon data from the ecosystem model can be matched directly to the production system choice. However, with county-level data that have been aggregated across individual land units, this kind of matching of production system data cannot be completed. The proposed solution to this problem is to model two features of production systems at the county scale with the economic model, cropping intensity (proportion of land in fallow) and tillage intensity (proportion of land where reduced tillage is used). These proportions will then be used to aggregate data from the ecosystem model.
Development of Farm-Scale Simulation Model for Montana. The existing simulation model structure developed in Year 1 has been adapted to represent management decisions at the farm scale. Specifically, estimates of carbon sequestration rates for a range of cropping systems were developed from farm-specific climatic and soil conditions using the Century ecosystem model. The economic simulation model framework was adapted to reflect the net returns and cropping system choices expected using data at this scale. We currently are testing the model structure for errors and evaluating model results for consistency.
Development of Procedures for Closer Linking of Ecosystem and Economic Simulation Models. We continued our work to more closely couple ecosystem and economic models. Our first objective is to dynamically couple the outputs of the ecosystem model (crop yields and soil carbon changes), the economic simulation model, and outputs of the economic simulation model (land use and other management decisions) to the ecosystem model. An initial framework for the dynamic coupling of the ecosystem model and economic simulations has been developed and code development is underway. Our initial work indicates that the coupling can be accomplished in a fairly straightforward way by using an interprocess communication technique. Using the Trade-off Model software developed in other research (see http://www.tradeoffs.montana.edu Exit ) to coordinate the calculation and couple the results between the ecosystem and economic models, initial code development is limited to interface modules with the core models being used largely in their existing form. This will give us a highly flexible, fully coupled model that can be used to explore the techniques of coupling the models and the output from a coupled model without restricting development or improvements in the individual components.Discussion of the methods for coupling using the Tradeoff Model software is in Antle and Stoorvogel (2003). In addition, we have continued to investigate the sensitivity of our models to uncertainties in information that is passed from one model to another (Capalbo, et al., 2003)..
One concern with this approach is its scalability to large-scale regional simulations. Regional simulations typically require significant computer resources and the current approach may not be computationally efficient enough or fully compatible with existing computer resources to handle full regional simulations. However, issues such as interface efficiency, code portability, language compatibility, and multithreading can be investigated using the initial model and the results used to define requirements for a more capable interface and to determine whether modifications of the Century or econometric models will be required.
Development of Climate Scenarios for Sensitivity Analysis and Analysis of Climate Change. Working with David Yates, National Center for Atmospheric Research, Boulder, we have identified procedures for constructing climate scenarios for the Central United States that we can use to subject our models to sensitivity analysis, and to simulate impacts of climate change. Our objective is to represent the range of possible climate change scenarios that has been suggested by global circulation models. For this purpose, David Yates will construct sets of climate data for weather stations in the Central United States that correspond to different combinations of temperature and precipitation changes suggested by general circulation models. These weather station data will then be matched to the farm level, county level, and to the MLRA data that we will use in simulation experiments.
Journal Articles on this Report : 4 Displayed | Download in RIS Format
Other project views: | All 34 publications | 9 publications in selected types | All 8 journal articles |
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Type | Citation | ||
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Antle JM, Capalbo SM, Elliott ET, Hunt HW, Mooney S, Paustian KH. Research needs for understanding and predicting the behavior of managed ecosystems: Lessons from agroecosystems. Ecosystems 2001;4(8):723-735. |
R828745 (2002) |
not available |
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Antle J, Capalbo S, Mooney S, Elliott EH, Paustian KH. Sensitivity of carbon sequestration costs to soil carbon rates. Environmental Pollution 2002;116(3):413-422. |
R828745 (2002) |
not available |
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Antle J, Capalbo S, Mooney S, Elliott E, Paustian K. Spatial heterogeneity, contract design, and the efficiency of carbon sequestration policies for agriculture. Journal of Environmental Economics and Management 2003;46(2):231-250. |
R828745 (2002) R828745 (Final) |
not available |
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Hunt HW, Antle JM, Paustian K. False determinations of chaos in short noisy time series. Physica D: Nonlinear Phenomena 2003;180(1-2):115-127. |
R828745 (2002) R828745 (Final) |
not available |
Supplemental Keywords:
close-coupling, ecological models, economic models, climate change, agriculture, agroecosystems., RFA, Scientific Discipline, Air, Ecosystem Protection/Environmental Exposure & Risk, Ecology, Ecosystem/Assessment/Indicators, Ecosystem Protection, climate change, Ecological Effects - Environmental Exposure & Risk, Economics, Environmental Monitoring, Ecological Risk Assessment, Agronomy, Social Science, ecological exposure, anthropogenic stress, climate change impact, farming, human activities, meteorology, economic models, socioeconomic indicators, circulation model, agroeconomics, climate models, agriculture, environmental stressors, agro ecosystems, modeling ecological risk, ecological models, ecosystem sustainability, global warming, sensitivity, agriculture ecosystemsRelevant Websites:
http://www.climate.montana.edu Exit
http://www.tradeoffs.montana.edu Exit
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.