Abstract
Future climate change directly impacts crop agriculture by altering temperature and precipitation regimes, crop yields, crop enterprise net returns, and net farm income. Most previous studies assess the potential impacts of agricultural adaptation to climate change on crop yields. This study attempts to evaluate the potential impacts of crop producers’ adaptation to future climate change on crop yield, crop enterprise net returns, and net farm income in Flathead Valley, Montana, USA. Crop enterprises refer to the combinations of inputs (e.g., land, labor, and capital) and field operations used to produce a crop. Two crop enterprise adaptations are evaluated: flexible scheduling of field operations; and crop irrigation. All crop yields are simulated using the Environmental Policy Integrated Climate (EPIC) model. Net farm income is assessed for small and large representative farms and two soils in the study area. Results show that average crop yields in the future period (2006–2050) without adaptation are between 7% and 48% lower than in the historical period (1960–2005). Flexible scheduling of the operations used in crop enterprises does not appear to be an economically efficient form of crop enterprise adaptation because it does not improve crop yields and crop enterprise net returns in the future period. With irrigation, crop yields are generally higher for all crop enterprises and crop enterprise net returns increase for the canola and alfalfa enterprises but decrease for all other assessed crop enterprises relative to no adaptation. Overall, average crop enterprise net return in the future period is 45% lower with than without irrigation. Net farm income decreases for both the large and small representative farms with both flexible scheduling and irrigation. Results indicate that flexible scheduling and irrigation adaptation are unlikely to reduce the potential adverse economic impacts of climate change on crop producers in Montana’s Flathead Valley.



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Antle JM, Capalbo S, Elliott E, Paustian KH (2004) Adaptation, spatial heterogeneity, and the vulnerability of agricultural systems to climate change and CO2 fertilization: an integrated assessment approach. Clim Chang 64:289–315
Antle JM, Capalbo SM, Hewitt J (1999) Testing hypotheses in integrated impact assessments: climate variability and economic adaptation in Great Plains agriculture. National Institute for Global Environmental Change, Nebraska Earth Science Education Network, University of Nebraska, Lincoln, NE, pp. T5–4 and 21.
Bradshaw B, Dolan H, Smit B (2004) Farm-level adaptation to climatic variability and change: crop diversification in the Canadian prairies. Clim Chang 67:119–141
Brassard JP, Singh B (2008) Impacts of climate change and CO2 increase on agricultural production and adaptation options for Southern Quebec, Canada. Mitig Adapt Strateg Glob Chang 13:241–265
Brown RA, Rosenberg NJ (1997) Sensitivity of crop yield and water use to change in a range of climatic factors and CO2 concentrations: a simulation study applying EPIC to the central USA. Agric For Meteorol 83:171–203
Easterling WE III, Hurd BH, Smith JB (2004) Coping with global climate change: The role of adaptation in the United States. Pew Center on Global Climate Change, Arlington
Hogan R, Stiles S, Tacker P, Vories E, Bryant KJ (2007) Estimating irrigation costs. Report FSA28, University of Arkansas, Division of Agriculture
Hungerford RD, Nemani RR, Running SW, Coughlan JC (1989) MTCLIM a mountain microclimate simulation model, USDA Forest Service, Research Paper INT-414
Inkley DB, Anderson MG, Blaustein AR, Burkett VR, Felzer B, Griffith B, Price J, Root TL (2004) Global climate change and wildlife in North America. Technical review 04–2. The Wildlife Society, Bethesda, MD
Intergovernmental Panel on Climate Change (2007) Climate Change 2007: Synthesis report. Cambridge University Press, UK
Intergovernmental Panel on Climate Change (2007b) Summary for Policymakers. In: Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Parry ML, Canziani OF, Palutiko JP, van der Linden PJ, Hanson CE (Eds), Cambridge University Press, Cambridge, UK
Izaurralde RC, Rosenberg NJ, Brown RA, Allison JR, Thomson AM (2003) Integrated assessment of Hadley Centre (HadCM2) climate-change impacts on agricultural productivity and irrigation water supply in the conterminous United States. Part II. Regional agricultural production in 030 and 095. Agric For Meteorol 117:97–122
Izaurralde RC, Williams JR, McGill WB, Rosenberg NJ, Quiroga Jakas MC (2006) Simulating soil C dynamics with EPIC: model description and testing against long-term data. Ecol Model 192:362–384
Kaiser HM, Riha SJ, Wilks DS, Rossiter DG, Sampath F (1993) A farm-level analysis of economic and agronomic impacts of gradual climate warming. American Journal of Agricultural Economics 75:387–398.
Kimball JS, Running SW, Nemani R (1997) An improved method for estimating surface humidity from daily minimum temperature. Agric For Meteorol 85:87–98
McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS (2001) Climate Change 2001: Impacts, Adaptation, and Vulnerability. Intergovernmental Panel On Climate Change. Cambridge University Press, UK
McGinn SM, Toure A, Akinremi OO, Major DJ, Barr AG (1999) Agroclimate and crop response to climate change in Alberta, Canada. Outlook Agr 28:19–28
Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer FJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Am Meteorol Soc 88:1383–1394
Prato T, Qiu Z, Fagre D, Pederson G, Bengtson L, Williams J (2010) Potential economic benefits of adapting agricultural production systems to future climate change. Environ Manag 45:577–589
Raupach MR, Marland G, Ciais P, Le Quéré C, Canadell JG, Klepper G, Field CB (2007) Global and regional drivers of accelerating CO2 emissions. Proc Natl Acad Sci 104:10288–10293
Reilly JM (2002) Agriculture: the potential consequences of climate variability and change. A report of the National Agriculture Assessment Group for the U.S. Global Change Research Program. Cambridge University Press, UK
Rosenzweig C, Tubiello FN (2007) Adaptation and mitigation strategies in agriculture: an analysis of potential synergies. Mitig Adapt Strateg Glob Chang 12:855–873
Smit B, Skinner M (2002) Adaptation options in agriculture to climate change: a typology. Mitig Adapt Strateg Glob Chang 7:85–114
Smit B, Burton I, Klein R, Wandel J (2000) An anatomy of adaptation to climate change and variability. Clim Chang 45:223–251
Spittlehouse DL, Stewart RB (2003) Adaptation to climate change in forest management. BC J Ecosyst Manag 4:7–17
Stewart RB, Wheaton E, Spittlehouse DL (1998) Climate change: implications for the boreal forest. In: Legge AH, Jones LL (eds) Emerging air issues for the 21st century: the need for multidisciplinary management. Air and Waste Management Association, Pittsburg, pp 86–101
Tingem M, Rivington M (2009) Adaptation for crop agriculture to climate change in Cameroon: turning on the heat. Mitig Adapt Strateg Glob Chang 14:153–168
Tubiello FN, Jagtap S, Rosenzweig C, Goldberg R, Jones JW (2002) Effects of climate change on US crop production from the National Assessment. Simulation results using two different GCM scenarios. Part I: wheat, potato, corn, and citrus. Clim Res 20(3):259–270
US Department of Agriculture, National Agricultural Statistics Service (USDA NASS) (2007) Census of Agriculture. http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp. Cited 2011 May 2
US Department of Agriculture, National Agricultural Statistics Service (USDA NASS) (2008) 2008 Farm and Ranch Irrigation Survey. http://www.agcensus.usda.gov/Publications/2002/FRIS/index.asp. Cited 2011 March 15
US Department of Labor, Bureau of Labor Statistics (USDL BLS) (2011) Producer Price Indexes. http://data.bls.gov/pdq/SurveyOutputServlet?request_action=wh&graph_name=WP_ppibrief. Cited 2011 April 2
Walther G-R, Post E, Convey P, Menzel A, Parmesan C, Beebee TJC, Fromentin J-M, Hoegh-Guldberg O, Bairlein F (2002) Ecological responses to recent climate change. Nature 416:389–395
Wilbanks TJ, Leiby P, Perlack R, Ensminger JT, Wright SB (2007) Toward an integrated analysis of mitigation and adaptation: some preliminary findings. Mitig Adapt Strateg Glob Chang 12:713–725
Williams JR, Jones CA, Kiniry JR, Spanel DA (1989) The EPIC crop growth model. Trans ASAE 32:497–511
Williams JR, Wang E, Harman WL, Seimers M, Atwood, JD (2006) EPIC users guide v. 0509. Blackland Research and Extension Center, Temple, Texas
Acknowledgements
The research reported here was supported in part by the National Research Initiative of the United States Department of Agriculture Cooperative State Research, Education and Extension Service, grant number 2006-55101-17129. We acknowledge Dr. Jimmy Williams for providing the most recent version of the EPIC model, which was used in this study.
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Qiu, Z., Prato, T. Economic feasibility of adapting crop enterprises to future climate change: a case study of flexible scheduling and irrigation for representative farms in Flathead Valley, Montana, USA. Mitig Adapt Strateg Glob Change 17, 223–242 (2012). https://doi.org/10.1007/s11027-011-9322-x
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DOI: https://doi.org/10.1007/s11027-011-9322-x

