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Scale, context, and decision making in agricultural adaptation to climate variability and change

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Abstract

This work presents a framework for viewing agricultural adaptation, emphasizing the multiple spatial and temporal scales on which individuals and institutions process information on changes in their environment. The framework is offered as a means to gain perspective on the role of climate variability and change in agricultural adaptation, and developed for a case study of Australian agriculture. To study adaptation issues at the scale of individual farms we developed a simple modelling framework. The model highlights the decision making element of adaptation in light of uncertainty, and underscores the importance of decision information related to climate variability. Model results show that the assumption of perfect information for farmers systematically overpredicts adaptive performance. The results also suggest that farmers who make tactical planting decisions on the basis of historical climate information are outperformed by those who use even moderately successful seasonal forecast information. Analysis at continental scales highlights the prominent role of the decline in economic operating conditions on Australian agriculture. Examples from segments of the agricultural industry in Australia are given to illustrate the importance of appropriate scale attribution in adapting to environmental changes. In particular, adaptations oriented toward short time scale changes in the farming environment (droughts, market fluctuations) can be limited in their efficacy by constraints imposed by broad changes in the soil/water base and economic environment occuring over longer time scales. The case study also makes the point that adaptation must be defined in reference to some goal, which is ultimately a social and political exercise. Overall, this study highlights the importance of allowing more complexity (limited information, risk aversion, cross-scale interactions, mis-attribution of cause and effect, background context, identification of goals) in representing adaptation processes in climate change studies.

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References

  • ABARE: 1996, Australian Commodity Statistics. Australian Bureau of Agricultural and Resource Economics, Canberra.

    Google Scholar 

  • ABS: 1996a, Australian Agriculture and the Environment. Australian Bureau of Statistics, Canberra, Catalogue No. 4606.0.

    Google Scholar 

  • ABS: 1996b, Australians and the Environment. Australian Bureau of Statistics, Canberra, Catalogue No. 4601.0.

    Google Scholar 

  • Andresen, J. and Dale, R.: 1989, Prediction of county-level corn yield using an energy-crop growth index, J. Climate 2, 48–56.

    Google Scholar 

  • Bowler, I.: 1993, The Geography of Agriculture in Developed Market Economies, Longman, London.

    Google Scholar 

  • Conacher, J., Conacher, A. and Conacher, J. (eds.): 1995, Rural Land Degradation in Australia (Meridian: Australian Geographical Perspectives), Oxford Univ. Press, England, 170 pp.

    Google Scholar 

  • Curran, W., Gleeson, T. and Topp, V.: 1996, Broadacre farming today - forces for change, Outlook 97: Proceedings of the National Agricultural and Resources Outlook Conference 2, 53–66.

    Google Scholar 

  • Dowlatabadi, H.: 1998, Wheat Needs Rain to Grow!, Degrees of Change (in press).

  • EPA: 1995, New South Wales State of the Environment 1995, Environmental Protection Authority, Chatswood, New South Wales.

    Google Scholar 

  • Frank, B.: 1995a, Constraints limiting innovation adoption in the North Queensland beef industry 1. A socio-economic means of maintaining a balanced lifestyle, Agricultural Systems 47, 291–321.

    Google Scholar 

  • Frank, B. 1995b: Constraints limiting innovation adoption in the North Queensland beef industry 2. Non-adoption is an intelligent response to environmental circumstances, Agricultural Systems 47, 323-346.

    Google Scholar 

  • Gifford, R., Angus, J., Barrett, D., Passioura, J., Rawson, H., Richards, R., Stapper, M. and Wood, J.: 1998, Climate change and Australian wheat yield, Nature 391, 448–449.

    Google Scholar 

  • Graetz, D., Dowlatabadi. H., Risbey, J. and Kandlikar, M.: 1997, Applying Frameworks for Assessing Agricultural Adaptation to Climate Change in Australia, CSIRO Earth Observation Center report 97/1, 136 pp.

  • Hammer, G. and McCown, R.: 1995, Assessing the economic value to dryland crop production of seasonal rainfall forecasts, Queensland DPI Report.

  • Houghton, J.T., Meira Filko, L.G., Callander, B.A., Harris, N., Kattenberg, A. and Maskell, K. (Eds.) 1996.

  • Huda, A., Ghildyl, B. and Tomar, V.: 1976, Contribution of climatic variables in predicting maize yield under monsoon conditions, Agricultural Meteorology 29, 291–300.

    Google Scholar 

  • IPCC: 1995a, Climate Change 1995. The Science of Climate Change, Cambridge Univ. Press, Cambridge, 572 pp.

    Google Scholar 

  • IPCC: 1995b, Climate Change 1995. Impacts, Adaptations and Mitigation of Climate Change: Scientific-Technical Analyses, Cambridge Univ. Press, Cambridge, 879 pp.

    Google Scholar 

  • Jones, C. and Kiniry, J.: 1996, CERES Maize: A Simulation Model of Maize Growth and Development, Texas A & M Press, College Station, Texas.

    Google Scholar 

  • Katz, R. and Brown, B.: 1992, Extreme events in a changing climate: variability is more important than averages, Climatic Change 21, 289-302.

    Google Scholar 

  • Kauffman, R.: 1998, The impact of climate change on US agriculture: A response to Mendelsohn et al., 1994, Ecological Economics (in press).

  • Kaufmann, R. and Snell, S.: 1997, A biophysical model of corn yield: Integrating physical and economic determinants, American Journal of Agricultural Economics 79 (1), 178–180.

    Google Scholar 

  • Lavery, B., Joung, G. and Nicholls, N.: 1997, An extended high quality historical rainfall data set for Australia, Australian Meteorol. Mag. 46, 27–38.

    Google Scholar 

  • Mearns, L., Giorgi, F., McDaniel, L. and Shields, C.: 1995, Analysis of daily variability of precipitation in a nested regional climate model: comparison with observations and doubled CO2 results, Global and Planetary Change 10, 55–78.

    Google Scholar 

  • Mendelsohn, R., Nordhaus, W. and Shaw, D.: 1994, The impact of global warming on agriculture: A Ricardian analysis, American Economic Review 84 (4), 753–771.

    Google Scholar 

  • Nicholls, N., Lavery, B., Frederiksen, C., Drosdowsky, W. and Torok, S.: 1996, Recent apparent changes in relationships between the El Nino-Southern Oscillation and Australian rainfall and temperature, Geophysical Research Letters 23, 3357–3360.

    Google Scholar 

  • Nicholls, N.: 1997, Increased Australian wheat yield due to recent climate trends, Nature 387, 484–485.

    Google Scholar 

  • Pasour, E.: 1990, Agriculture and the State: Market Processes and Bureaucracy, Holmes and Meier, New York.

    Google Scholar 

  • Pittock, A.B.: 1975, Climatic change and patterns of variation in Australian rainfall, Search 6, 498–504.

    Google Scholar 

  • Rosenzweig, C. and Parry, M.: 1994, Potential impact of climate change on world food supply, Nature 367, 133–138.

    Google Scholar 

  • Rosenzweig, M. and Binswanger, H.: 1993, Wealth, weather risk and the composition and profitability of agricultural investments, The Economic Journal 103, 56–78.

    Google Scholar 

  • Runge, E.: 1968, Effects of rainfall and temperature interactions during the growing season on corn yield, Agronomy Journal 60, 503–507.

    Google Scholar 

  • Schneider, S.: 1997, Integrated assessment modeling of global climate change: tranparent rational tool for policy making or opaque screen hiding value-laden assumptions?, Env. Mod. Assessment 2, 229–249.

    Google Scholar 

  • SEAC: 1996, Australia State of the Environment 1996, State of the Environment Advisory Council, CSIRO Publishing, Collingwood, Australia, 500 pp.

    Google Scholar 

  • Smit, B., McNabb, D. and Smithers, J.: 1996, Agricultural adaptation to climatic variation, Climatic Change 33, 7–29.

    Google Scholar 

  • Stewart, T.: 1997, Forecast value: descriptive decision studies, in R. Katz and A. Murphy (eds.), Economic Value of Weather and Climate Forecasts, Cambridge Univ. Press, 222 pp.

  • The Long Paddock: 1998, The Long Paddock: Climate Information Highway, Queensland Dept. Nat. Resources. http://www.dnr.qld.gov.au/longpdk/.

  • UKMO: 1997, Climate Change and its Impacts: A Global Perspective. United Kingdom Meteorological Office report, December 1997, 16 pp.

  • Visvanathan, S.: 1997, A Carnival for Science. Essays on Science, Technology, and Development, Oxford Univ. Press, Oxford, England, 249 pp.

    Google Scholar 

  • Watson, R., Zinyowera, M. and Moss, R. (eds.): 1998, The Regional Impacts of Climate Change: An Assessment of Vulnerability, Cambridge Univ. Press, Cambridge, England.

    Google Scholar 

  • Weber, E.: 1994, Production and pricing decisions in cash-crop farming: effects of decision traits and climate change expectations, in B. Jacobsen, D. Pedersen, J. Christensen and S. Rasmussen (eds.), Farmers' Decision Making - A Descriptive Approach, Proceedings of the 38th EAAE seminar of the European Association of Agricultural Economists, October 3- 5, 1994, Copenhagen, Denmark, 203–218.

  • Weber, E.: 1996, Perception and Expectation of Climate Change: Precondition for Economic and Technological Adaptation. Accepted by Psychological Perspectives to Environmental and Ethical Issues in Management.

  • Whetton, P., Fowler, A., Haylock, M. and Pittock, A.: 1993, Implications of climate change due to the enhanced greenhouse effect on floods and droughts in Australia, Clim. Change 25 289–317.

    Google Scholar 

  • White, D.: 1997, Case Study - Drought and risk, Outlook 97, Proceedings of the National Agricultural and Resources Outlook Conference 1, 98–106.

    Google Scholar 

  • Williams, J.: 1995, Farming without harming: how Australia made rural industries sustainable, in R. Eckersley and K. Jeans (eds.), Challenge to Change. Australia in 2020, CSIRO Publishing, East Melbourne, Australia, 271 pp.

    Google Scholar 

  • Yohe, G.: 1992, Imbedding dynamic responses with imperfect information into static portraits of the regional impact of climate change, in J. Reilly and M. Anderson (eds.), Economic Issues in Global Climate Change, Westview Press, 200–214.

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Risbey, J., Kandlikar, M., Dowlatabadi, H. et al. Scale, context, and decision making in agricultural adaptation to climate variability and change. Mitigation and Adaptation Strategies for Global Change 4, 137–165 (1999). https://doi.org/10.1023/A:1009636607038

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