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An Integrated Economic, Environmental and Social Approach to Agricultural Land-Use Planning

Author

Listed:
  • Sahar Shahpari

    (Institute for Regional Development, University of Tasmania, Tasmania 7320, Australia)

  • Janelle Allison

    (University College, Cradle Coast Campus, University of Tasmania, Tasmania 7320, Australia)

  • Matthew Tom Harrison

    (Tasmanian Institute of Agriculture, University of Tasmania, Tasmania 7320, Australia)

  • Roger Stanley

    (Tasmanian Institute of Agriculture, University of Tasmania, Tasmania 7320, Australia)

Abstract

Agricultural land-use change is a dynamic process that varies as a function of social, economic and environmental factors spanning from the local to the global scale. The cumulative regional impacts of these factors on land use adoption decisions by farmers are neither well accounted for nor reflected in agricultural land use planning. We present an innovative spatially explicit agent-based modelling approach (Crop GIS-ABM) that accounts for factors involved in farmer decision making on new irrigation adoption to enable land-use predictions and exploration. The model was designed using a participatory approach, capturing stakeholder insights in a conceptual model of farmer decisions. We demonstrate a case study of the factors influencing the uptake of new irrigation infrastructure and land use in Tasmania, Australia. The model demonstrates how irrigated land-use expansion promotes the diffusion of alternative crops in the region, as well as how coupled social, biophysical and environmental conditions play an important role in crop selection. Our study shows that agricultural land use reflected the evolution of multiple simultaneous interacting biophysical and socio-economic drivers, including soil and climate type, crop and commodity prices, and the accumulated effects of interactive decisions of farmers.

Suggested Citation

  • Sahar Shahpari & Janelle Allison & Matthew Tom Harrison & Roger Stanley, 2021. "An Integrated Economic, Environmental and Social Approach to Agricultural Land-Use Planning," Land, MDPI, vol. 10(4), pages 1-18, April.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:364-:d:528506
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    References listed on IDEAS

    as
    1. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    2. Ozge Dilaver, 2015. "From Participants to Agents: Grounded Simulation as a Mixed-Method Research Design," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(1), pages 1-15.
    3. Deng Ding & David Bennett & Silvia Secchi, 2015. "Investigating Impacts of Alternative Crop Market Scenarios on Land Use Change with an Agent-Based Model," Land, MDPI, vol. 4(4), pages 1-28, November.
    4. Harrison, Matthew T. & Cullen, Brendan R. & Rawnsley, Richard P., 2016. "Modelling the sensitivity of agricultural systems to climate change and extreme climatic events," Agricultural Systems, Elsevier, vol. 148(C), pages 135-148.
    5. Parker, Andrew M. & Srinivasan, Sinduja V. & Lempert, Robert J. & Berry, Sandra H., 2015. "Evaluating simulation-derived scenarios for effective decision support," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 64-77.
    6. Thomas Berger & Christian Troost, 2014. "Agent-based Modelling of Climate Adaptation and Mitigation Options in Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 323-348, June.
    7. Phelan, David C. & Harrison, Matthew T. & Kemmerer, Ernst P. & Parsons, David, 2015. "Management opportunities for boosting productivity of cool-temperate dairy farms under climate change," Agricultural Systems, Elsevier, vol. 138(C), pages 46-54.
    8. Phelan, David C. & Harrison, Matthew T. & McLean, Greg & Cox, Howard & Pembleton, Kieth G. & Dean, Geoff J. & Parsons, David & do Amaral Richter, Maria E. & Pengilley, Georgie & Hinton, Sue J. & Moham, 2018. "Advancing a farmer decision support tool for agronomic decisions on rainfed and irrigated wheat cropping in Tasmania," Agricultural Systems, Elsevier, vol. 167(C), pages 113-124.
    9. Veronique Beckers & Jeroen Beckers & Matthias Vanmaercke & Etienne Van Hecke & Anton Van Rompaey & Nicolas Dendoncker, 2018. "Modelling Farm Growth and Its Impact on Agricultural Land Use: A Country Scale Application of an Agent-Based Model," Land, MDPI, vol. 7(3), pages 1-19, September.
    10. Alcock, Douglas J. & Harrison, Matthew T. & Rawnsley, Richard P. & Eckard, Richard J., 2015. "Can animal genetics and flock management be used to reduce greenhouse gas emissions but also maintain productivity of wool-producing enterprises?," Agricultural Systems, Elsevier, vol. 132(C), pages 25-34.
    11. Christie, Karen M. & Smith, Andrew P. & Rawnsley, Richard P. & Harrison, Matthew T. & Eckard, Richard J., 2018. "Simulated seasonal responses of grazed dairy pastures to nitrogen fertilizer in SE Australia: Pasture production," Agricultural Systems, Elsevier, vol. 166(C), pages 36-47.
    12. Ge Song & Hongmei Zhang, 2021. "Cultivated Land Use Layout Adjustment Based on Crop Planting Suitability: A Case Study of Typical Counties in Northeast China," Land, MDPI, vol. 10(2), pages 1-19, January.
    13. Antoni Perello-Moragues & Pablo Noriega & Manel Poch, 2019. "Modelling Contingent Technology Adoption in Farming Irrigation Communities," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 22(4), pages 1-1.
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    2. Okura, Fumi & Budiasa, I Wayan & Kato, Tasuku, 2022. "Exploring a Balinese irrigation water management system using agent-based modeling and game theory," Agricultural Water Management, Elsevier, vol. 274(C).
    3. Franco Bilotto & Karen Michelle Christie-Whitehead & Bill Malcolm & Nicoli Barnes & Brendan Cullen & Margaret Ayre & Matthew Tom Harrison, 2025. "Costs of transitioning the livestock sector to net-zero emissions under future climates," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    4. Kotchakarn Nantasaksiri & Patcharawat Charoen-amornkitt & Takashi Machimura & Kiichiro Hayashi, 2021. "Multi-Disciplinary Assessment of Napier Grass Plantation on Local Energetic, Environmental and Socioeconomic Industries: A Watershed-Scale Study in Southern Thailand," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    5. Bushra Ahmed Alhammad & Mahmoud F. Seleiman & Matthew Tom Harrison, 2023. "Hydrogen Peroxide Mitigates Cu Stress in Wheat," Agriculture, MDPI, vol. 13(4), pages 1-15, April.
    6. Tianran Ding & Bernhard Steubing & Wouter Achten, 2022. "Coupling optimization with territorial LCA to support agricultural land-use planning," ULB Institutional Repository 2013/352783, ULB -- Universite Libre de Bruxelles.
    7. Mulya, Setyardi Pratika & Hudalah, Delik & Prilandita, Niken, 2024. "Developing a new methodology for determining typologies of peri-urban agriculture: A case study of the Jakarta Bandung Mega Urban Region Indonesia," Land Use Policy, Elsevier, vol. 146(C).

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