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Quantification of environmental-economic trade-offs in nutrient management policies

Author

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  • Kaye-Blake, William
  • Schilling, Chris
  • Monaghan, Ross
  • Vibart, Ronaldo
  • Dennis, Samuel
  • Post, Elizabeth

Abstract

Nitrogen losses from agricultural are a key source of human impacts on the environment, and many countries have adopted policies to reduce nitrogen losses. Policy in New Zealand is being developed at the national and regional levels to address nitrogen losses and water quality. Several policy options were explored using a multi-agent simulation model of the Southland region of New Zealand in order to quantify the trade-off between the economic value of agricultural production and nitrogen losses from farming. It estimated the relative effectiveness and efficiency of alternative nitrogen mitigation policies while taking into account the heterogeneity of soil vulnerability to nitrogen leaching, land management options, and farmer behaviour. It used a hybrid modelling technique, assembling a multi-disciplinary model from outputs of other, specialised models, and using an agent-based approach to model land-use change. The policy options included uniform limits on nitrogen losses that applied across all farms, as well as differentiated policies that took into account either the propensity of a farm to leach nitrogen, past dairy conversion, or the type of land use. After 25 years, the impacts on dairy land area, nitrogen losses, agricultural production, and farm gross margin were compared with a baseline of no policy. The results suggested that policies worked better when they took account of the heterogeneity of agriculture practices and the environment. Those policies could be more effective at reducing nitrogen losses from farms, in term of the total mitigation in the region. They were also more efficient across the policies modelled: per kilogram of nitrogen mitigated, they produced the lowest economic costs. Choosing the right policy approach would be some combination of the absolute level of mitigation required, the historical patterns of land use, the variability of the absorptive capacity of the environment, the ability to spread the economic or environmental impacts across many farms and people, and the ability to specify required input or outputs. Most importantly, hybrid multi-agent simulation modelling provided a tool for examining the potential impacts of policies before they are implemented.

Suggested Citation

  • Kaye-Blake, William & Schilling, Chris & Monaghan, Ross & Vibart, Ronaldo & Dennis, Samuel & Post, Elizabeth, 2019. "Quantification of environmental-economic trade-offs in nutrient management policies," Agricultural Systems, Elsevier, vol. 173(C), pages 458-468.
  • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:458-468
    DOI: 10.1016/j.agsy.2019.03.013
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    References listed on IDEAS

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    1. Bill Kaye-Blake & Chris Schilling & Elizabeth Post, 2014. "Validation of an Agricultural MAS for Southland, New Zealand," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 17(4), pages 1-5.
    2. Adam Daigneault & Suzie Greenhalgh & Oshadhi Samarasinghe, 2018. "Economic Impacts of Multiple Agro-Environmental Policies on New Zealand Land Use," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(4), pages 763-785, April.
    3. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    4. Axelrod, Robert, 2006. "Agent-based Modeling as a Bridge Between Disciplines," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 33, pages 1565-1584, Elsevier.
    5. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    6. Berger, Thomas & Schreinemachers, Pepijn & Woelcke, Johannes, 2006. "Multi-agent simulation for the targeting of development policies in less-favored areas," Agricultural Systems, Elsevier, vol. 88(1), pages 28-43, April.
    7. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    8. Daigneault, Adam & Greenhalgh, Suzie & Samarasinghe, Oshadhi, 2017. "Equitably slicing the pie: Water policy and allocation," Ecological Economics, Elsevier, vol. 131(C), pages 449-459.
    9. Baillie, Sarah & Kaye-Blake, William & Smale, Paul & Dennis, Samuel, 2016. "Simulation modelling to investigate nutrient loss mitigation practices," Agricultural Water Management, Elsevier, vol. 177(C), pages 221-228.
    10. Emily M. Jin & Michelle Girvan & M. E. J. Newman, 2001. "The Structure of Growing Social Networks," Working Papers 01-06-032, Santa Fe Institute.
    11. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    12. Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 24(1), pages 85-108.
    13. Happe, Kathrin & Kellermann, Konrad & Balmann, Alfons, 2006. "Agent-based analysis of agricultural policies: An illustration of the agricultural policy simulator AgriPoliS, its adaptation and behavior," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(1).
    14. Kaye-Blake, Bill & Schilling, Chris & Nixon, Chris & Destremau, Killian, 2014. "Water management in New Zealand : A road map for understanding water value," NZIER Working Paper 2014/1, New Zealand Institute of Economic Research.
    15. Fraser J Morgan & Adam J Daigneault, 2015. "Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-20, May.
    16. Axelrod, Robert & Tesfatsion, Leigh, 2006. "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences," Staff General Research Papers Archive 12515, Iowa State University, Department of Economics.
    17. Dimitris Kremmydas, 2012. "Agent based modeling for agricultural policy evaluation: A review," Working Papers 2012-3, Agricultural University of Athens, Department Of Agricultural Economics.
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    1. Spicer, E. Anne & Swaffield, Simon & Moore, Kevin, 2021. "Agricultural land use management responses to a cap and trade regime for water quality in Lake Taupo catchment, New Zealand," Land Use Policy, Elsevier, vol. 102(C).

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