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| Close-coupling of Ecosystem and Economic Models: Adaptationof Central U.S. Agriculture to Climate Change | |
| 项目编号 | R828745 |
| John M. Antle | |
| 项目主持机构 | University of Washington,Washington State University |
| 开始日期 | 2000-10-01 |
| 结束日期 | 2003-09-01 |
| 英文摘要 | Project Research Results Final Report 2002 Progress Report 2001 Progress Report 34 publications for this project 8 journal articles for this project Related Information Research Grants P3: Student Design Competition Research Fellowships Small Business Innovation Research (SBIR) Grantee Research Project Results Search Close-coupling of Ecosystem and Economic Models: Adaptationof Central U.S. Agriculture to Climate Change EPA Grant Number: R828745 Title: Close-coupling of Ecosystem and Economic Models: Adaptationof Central U.S. Agriculture to Climate Change Investigators: Antle, John M. , Capalbo, Susan M. , Elliot, Edward T. , Hunt, William , Mooney, Sian , Paustian, Keith Current Investigators: Antle, John M. , Capalbo, Susan M. , Hoagland, Kyle D. , Hunt, William , Mooney, Sian , Paustian, Keith Institution:Montana State University - Bozeman , Colorado State University , University of Nebraska at Omaha Current Institution:Montana State University - Bozeman EPA Project Officer: Packard, Benjamin H Project Period: October 1, 2000 through September 1, 2003 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:Global Climate Change ,Climate Change ,Air Description: The overall objective of our research is to significantly advance the stateof the art in modeling impacts of climate change in agroecosystems, by movingbeyond the loose coupling of unrelated and independent disciplinary models.Specific objectives are: Develop methods to more closely couple existing ecological and economicmodels that can be used to assess the impacts of climate change in agriculturalecosystems. Simulate the ecological and economic impacts of climate change onagriculture in the central U.S., using data at various scales (field/farm,county and Major Land Resource Area (MLRA)), and using a range of climate changescenarios and sensitivity analyses. Investigate the dynamic and spatial properties of agricultural ecosystems toassess how estimates of the impacts of climate change are affected by the choiceof spatial scale, temporal scale, and degree of model coupling.In this research we will develop a conceptual framework for closer modelcoupling, and implement the close coupling of an ecological model with aneconomic decision model. The research will investigate how our ability tosimulate behavior in response to climate change is affected by the temporal andspatial scales of analysis, the degree of coupling of the models, and thedynamic properties of the models. We will to do this for one of the mostimportant agroecosystems, the crop-based system of the central United States. To meet our first objective, we ill link processes in ecological models withland use and input use decisions in economic models, so that the type andstrength of feedback between ecological and economic processes is suitablyrepresented. To meet our second objective, to simulate the ecological and economic models,we will derive climate scenarios from historical climate data and from theresults of global circulation models (GCMs) that have been appropriatelydown-scaled. Climate data sets will be developed to conduct analysis ofsensitivity to changes in mean temperature and precipitation changes, andchanges in variability. Our third objective is to investigate the dynamic and spatial properties ofagricultural ecosystems and to assess how they are affected by spatial scale,temporal scale, and degree of model coupling. These properties will be comparedat the farm/field, county and MLRA scales in the central United States usingprimary data collected by the PIs, and secondary data collected by various stateand federal agencies.We expect that the possibility of successfully coupling ecosystem andeconomic models will depend on the level of data aggregation and spatial scale.Such coupling is expected to be most successful on a site-specific basis, andless successful as data are spatially and temporally aggregated. We hypothesize that coupling ecosystem and economic models will, at least insome important cases, lead to significantly different estimates of climatechange impacts on agriculture than is obtained from uncoupled models. Likewise,we expect to find significant effects of spatial and temporal aggregation onimpacts of climate change. |
| 英文关键词 | close coupling;ecological models;economic models;climate change;agriculture;agroecosystems. |
| 学科分类 | 0805 - 大气科学;;08 - 地球科学;09 - 环境科学 |
| 资助机构 | US-EPA |
| 项目经费 | 1420860 |
| 国家 | US |
| 语种 | 英语 |
| 文献类型 | 项目 |
| 条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/73028 |
| 推荐引用方式 GB/T 7714 | John M. Antle.Close-coupling of Ecosystem and Economic Models: Adaptationof Central U.S. Agriculture to Climate Change.2000. |
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