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Human Behavior and Adaptation

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The Food-Energy-Water Nexus

Abstract

The coupled nature of FEW systems means the human and natural systems are linked such that human behavior impacts natural processes, and the outcomes of these natural processes influence human behavior. Effectively managing FEW systems requires understanding how humans behave and interact with their natural and social environments, as well as understanding the environmental impacts of social changes (e.g., population growth and urbanization). We discuss the importance of including more sophisticated models of human behavior in the study of FEW systems and provide examples of how past research has incorporated complexity in human behavior into models of these systems. We do so from the perspectives of psychology, economics, and decision science—all social sciences with well-developed theories and models of human behavior that are useful in informing models and policies. We present two case studies as examples of how research can explicitly account for human behavior in these systems. Finally, we discuss challenges in incorporating human behavior and adaptation into models of these systems and identify future directions for work in this field.

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Notes

  1. 1.

    Utility maximization is a theoretical framework often used to model human behavior in economics. Utility maximization assumes people have a well-defined function that determines their utility (called a utility function). In economics, this function has certain properties that make it easy to model. For example, utility functions are assumed to be decreasing in the price of an object, so that an individual experiences less utility if the price of that object increases. These functions and their defined properties make them easy to incorporate into economic models, although some of the assumptions they make may not be accurate in describing someone’s well-being, and the behavioral predictions made by using such models have often found to be lacking in their ability to model people’s actual behavior.

  2. 2.

    See Irwin and Wrenn (2014) for a discussion of equilibrium-based and other modeling approaches, including agent-based models, in the context of land use decision-making and land change systems.

  3. 3.

    See Irwin et al. (2016b) for more discussion of these and other dynamic coupled models of human-natural systems.

  4. 4.

    Approximately $32 million per year is spent in the Lake Erie basin by the federal government on agricultural conservation.

References

  • Bailey, C., & Majumdar, M. (2014). Absentee forest and farmland ownership in Alabama. In Rural wealth creation (Vol. 134). London: Routledge.

    Google Scholar 

  • Bollinger, B., & Gillingham, K. (2012). Peer effects in the diffusion of solar photovoltaic panels. Marketing Science, 31(6), 900–912.

    Article  Google Scholar 

  • Bosch, N. S., Evans, M. A., Scavia, D., & Allan, J. D. (2014). Interacting effects of climate change and agricultural BMPs on nutrient runoff entering Lake Erie. Journal of Great Lakes Research, 40(3), 581–589.

    Google Scholar 

  • Dieter, C. A. (2018). Water Availability and Use Science Program: Estimated Use of Water in the United States In 2015. Geological Survey.

    Google Scholar 

  • EIA. (2018). 2015 Residential Energy Consumption Survey. https://www.eia.gov/consumption/residential/data/2015/index.php?view=consumption

    Google Scholar 

  • Flint, C. G., & Haynes, R. (2006). Managing forest disturbances and community responses: Lessons from the Kenai Peninsula, Alaska. Journal of Forestry, 104(5), 269–275.

    Google Scholar 

  • Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40(2), 351–401.

    Article  Google Scholar 

  • Hart, P. S., & Nisbet, E. C. (2012). Boomerang effects in science communication: How motivated reasoning and identity cues amplify opinion polarization about climate mitigation policies. Communication Research, 39(6), 701–723.

    Google Scholar 

  • Hunter, L. M., Murray, S., & Riosmena, F. (2013). Rainfall patterns and U.S. migration from rural Mexico. International Migration Review, 47(4), 874–909.

    Google Scholar 

  • Inglehart, R., Haerpfer, C., Moreno, A., Welzel, C., Kizilova, K., Diez-Medrano, J., Lagos, M., Norris, P., Ponarin, E., Puranen, B., et al. (2014). World values survey: Round Six - Country-pooled datafile version. Madrid: JD Systems Institute. Retrieved from http://www.worldvaluessurvey.org/WVSDocumentationWV6.jsp.

    Google Scholar 

  • Irwin, E., Campbell, J., Wilson, R., Faggian, A., Moore, R., & Irwin, N. (2016a). Human adaptations in food, energy, and water systems. Journal of Environmental Studies and Sciences, 6, 127–139.

    Article  Google Scholar 

  • Irwin, E., Gopalakrishnan, S., & Randall, A. (2016b). Welfare, wealth and sustainability. Annual Review of Resource Economics, 8, 77. https://doi.org/10.1146/annurev-resource-100815-095351.

    Article  Google Scholar 

  • Irwin, E. G., & Wrenn, D. (2014). An assessment of empirical methods for modeling land use. In J. M. Duke & J. Wu (Eds.), The Oxford handbook of land economics. London: Oxford University Press.

    Google Scholar 

  • Jager, W., Janssen, M. A., De Vries, H. J. M., De Greef, J., & Vlek, C. A. J. (2000). Behaviour in commons dilemmas: Homo economicus and Homo psychologicus in an ecological-economic model. Ecological economics, 35(3), 357–379.

    Google Scholar 

  • Krosnick, J. A. (1999). Survey research. Annual Review of Psychology, 50(1), 537–567.

    Article  CAS  Google Scholar 

  • Lauren, N., Fielding, K. S., Smith, L., & Louis, W. R. (2016). You did, so you can and you will: Self-efficacy as a mediator of spillover from easy to more difficult pro-environmental behaviour. Journal of Environmental Psychology, 48, 191–199.

    Google Scholar 

  • Lin, B.H., & Guthrie, J. (2012). Nutritional quality of food prepared at home and away from home, 1977-2008 Washington, DC US Department of Agriculture, Economic Research Service (Economic Information Bulletin Number 105.)

    Google Scholar 

  • Michalak, A. M., Anderson, E. J., Beletsky, D., Boland, S., Bosch, N. S., Bridgeman, T. B., ... & DePinto, J. V. (2013). Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions. Proceedings of the National Academy of Sciences, 110(16), 6448–6452.

    Google Scholar 

  • Pfeiffer, L., & Lin, C. Y. C. (2014). Does efficient irrigation technology lead to reduced groundwater extraction? Empirical evidence. Journal of Environmental Economics and Management, 67(2), 189–208.

    Google Scholar 

  • Robinson, D. T., Brown, D. G., Parker, D. C., Schreinemachers, P., Janssen, M. A., Huigen, M., Wittmer, H., Gotts, N., Promburom, P., Irwin, E., Berger, T., Gatzweiler, F., & Barnaud, C. (2007). Comparison of empirical methods for building agent-based models in land use science. Journal of Land Use Science, 2(1), 31–55.

    Article  CAS  Google Scholar 

  • Rust, J., & Golombok, S. (2014). Modern psychometrics: The science of psychological assessment. London: Routledge.

    Google Scholar 

  • Scavia, D., Kalcic, M., Muenich, R. L., Read, J., Aloysius, N., Bertani, I., Boles, C., Confesor, R., DePinto, J., Gildow, M., & Martin, J. (2017). Multiple models guide strategies for agricultural nutrient reductions. Frontiers in Ecology and the Environment, 15(3), 126–132.

    Article  Google Scholar 

  • Sintov, N., Geislar, S., & White, L. V. (2017). Cognitive accessibility as a new factor in proenvironmental spillover: Results from a field study of household food waste management. Environment and Behavior, 51, 50. https://doi.org/10.1177/0013916517735638.

    Article  Google Scholar 

  • The Ohio Legislature. (2014). To revise the law governing the abatement of agricultural pollution, to require a person that applies fertilizer for the purposes of agricultural production to be certified to do so by the Director of Agriculture, to make other changes to the Agricultural Additives, Lime, and Fertilizer Law. Ohio Senate Bill 150. 113th General Assembly.

    Google Scholar 

  • Thomas, G. O., Poortinga, W., & Sautkina, E. (2016). The Welsh single-use carrier bag charge and behavioural spillover. Journal of Environmental Psychology, 47, 126–135.

    Google Scholar 

  • van Duinen, R., Filatova, T., Jager, W., & van der Veen, A. (2015). Going beyond perfect rationality: Drought risk, economic choices and the influence of social networks. Annals of Regional Science, 57(2-3), 335–369.

    Article  Google Scholar 

  • Wilson, R. S., Beetstra, M., Reutter, J., Hesse, G., Fussell, K., Johnson, L., King, K., LaBarge, G., Martin, J., & Winslow, C. (2019). Commentary: Achieving phosphorus reduction targets for Lake Erie. Journal of Great Lakes Research, 45(1), 4–11.

    Article  CAS  Google Scholar 

  • Wilson, R. S., Hardisty, D. J., Epanchin‐Niell, R. S., Runge, M. C., Cottingham, K. L., Urban, D. L., Maguire, L. A., Hastings, A., Mumby, P. J., & Peters, D. P. (2016). A typology of time‐scale mismatches and behavioral interventions to diagnose and solve conservation problems. Conservation Biology, 30(1), 42–49.

    Article  Google Scholar 

  • Wilson, R. S., Howard, G., & Burnett, E. A. (2014). Improving nutrient management practices in agriculture: The role of risk‐based beliefs in understanding farmers’ attitudes toward taking additional action. Water Resources Research, 50(8), 6735–6746.

    Article  Google Scholar 

  • Zhang, W., Wilson, R. S., Burnett, E., Irwin, E. G., & Martin, J. F. (2016). What motivates farmers to apply phosphorus at the “right” time? Survey evidence from the Western Lake Erie Basin. Journal of Great Lakes Research, 42(6), 1343–1356.

    Article  Google Scholar 

Further Reading

  • Arneth, A., Brown, C., & Rounsevell, M. D. A. (2014). Global models of human decision-making for land-based mitigation and adaptation assessment. Nature Climate Change, 4(7), 550–557.

    Google Scholar 

  • Collins, S. L., Carpenter, S. R., Swinton, S. M., Orenstein, D. E., Childers, D. L., Gragson, T. L., Grimm, N. B., Grove, J. M., Harlan, S. L., Kaye, J. P., & Knapp, A. K. (2011). An integrated conceptual framework for long‐term social-ecological research. Frontiers in Ecology and the Environment, 9(6), 351–357.

    Google Scholar 

  • Irwin, E., Campbell, J., Wilson, R., Faggian, A., Moore, R., & Irwin, N. (2016). Human adaptations in food, energy, and water systems. Journal of Environmental Studies and Sciences, 6, 127–139.

    Article  Google Scholar 

  • Irwin, E. G., & Wrenn, D. (2014). An assessment of empirical methods for modeling land use. In J. M. Duke & J. Wu (Eds.), The Oxford handbook of land economics. London: Oxford University Press.

    Google Scholar 

  • Millner, A., & Ollivier, H. (2016). Beliefs, politics, and environmental policy. Review of Environmental Economics and Policy, 10(2), 226–244. https://doi.org/10.1093/reep/rew010.

    Article  Google Scholar 

  • Shogren, J. F., & Taylor, L. O. (2008). On behavioral-environmental economics. Review of Environmental Economics and Policy, 2(1), 26–44. https://doi.org/10.1093/reep/rem027.

    Article  Google Scholar 

  • Wilkinson, N., & Klaes, M. (2017). An introduction to behavioral economics. London: Macmillan International Higher Education.

    Google Scholar 

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Correspondence to Mary Doidge .

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Doidge, M., Irwin, E., Sintov, N., Wilson, R.S. (2020). Human Behavior and Adaptation. In: Saundry, P., Ruddell, B. (eds) The Food-Energy-Water Nexus. AESS Interdisciplinary Environmental Studies and Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-29914-9_4

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