IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i4p364-d528506.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/4/364/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/4/364/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Tianran Ding & Bernhard Steubing & Wouter Achten, 2022. "Coupling optimization with territorial LCA to support agricultural land-use planning," ULB Institutional Repository 2013/359529, ULB -- Universite Libre de Bruxelles.
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ara, Iffat & Turner, Lydia & Harrison, Matthew Tom & Monjardino, Marta & deVoil, Peter & Rodriguez, Daniel, 2021. "Application, adoption and opportunities for improving decision support systems in irrigated agriculture: A review," Agricultural Water Management, Elsevier, vol. 257(C).
    2. Smith, Andrew P. & Christie, Karen M. & Rawnsley, Richard P. & Eckard, Richard J., 2018. "Fertiliser strategies for improving nitrogen use efficiency in grazed dairy pastures," Agricultural Systems, Elsevier, vol. 165(C), pages 274-282.
    3. Ran Sun & James Nolan & Suren Kulshreshtha, 2022. "Agent-based modeling of policy induced agri-environmental technology adoption," SN Business & Economics, Springer, vol. 2(8), pages 1-26, August.
    4. Monjardino, Marta & Harrison, Matthew T. & DeVoil, Peter & Rodriguez, Daniel & Sadras, Victor O., 2022. "Agronomic and on-farm infrastructure adaptations to manage economic risk in Australian irrigated broadacre systems: A case study," Agricultural Water Management, Elsevier, vol. 269(C).
    5. He, Liuyue & Xu, Zhenci & Wang, Sufen & Bao, Jianxia & Fan, Yunfei & Daccache, Andre, 2022. "Optimal crop planting pattern can be harmful to reach carbon neutrality: Evidence from food-energy-water-carbon nexus perspective," Applied Energy, Elsevier, vol. 308(C).
    6. Menale Kassie & Zewdu Abro & Tesfamicheal Wossen & Samuel T. Ledermann & Gracious Diiro & Shifa Ballo & Lulseged Belayhun, 2020. "Integrated Health Interventions for Improved Livelihoods: A Case Study in Ethiopia," Sustainability, MDPI, vol. 12(6), pages 1-21, March.
    7. Harrison, Matthew T. & McSweeney, Chris & Tomkins, Nigel W. & Eckard, Richard J., 2015. "Improving greenhouse gas emissions intensities of subtropical and tropical beef farming systems using Leucaena leucocephala," Agricultural Systems, Elsevier, vol. 136(C), pages 138-146.
    8. Cheng, M.N. & Wong, Jane W.K. & Cheung, C.F. & Leung, K.H., 2016. "A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 44-62.
    9. Mössinger, Johannes & Troost, Christian & Berger, Thomas, 2022. "Bridging the gap between models and users: A lightweight mobile interface for optimized farming decisions in interactive modeling sessions," Agricultural Systems, Elsevier, vol. 195(C).
    10. Mathias Eistrup & Ana Rita Sanches & José Muñoz-Rojas & Teresa Pinto Correia, 2019. "A “Young Farmer Problem”? Opportunities and Constraints for Generational Renewal in Farm Management: An Example from Southern Europe," Land, MDPI, vol. 8(4), pages 1-13, April.
    11. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    12. Smith, Andrew P. & Beale, Peter & Fulkerson, Bill J. & Eckard, Richard J., 2019. "Managing the nitrogen status of subtropical dairy pastures for production, efficiency and profit," Agricultural Systems, Elsevier, vol. 176(C).
    13. Troost, Christian & Berger, Thomas, 2015. "Process-based simulation of regional agricultural supply functions in Southwestern Germany using farm-level and agent-based models," 2015 Conference, August 9-14, 2015, Milan, Italy 211929, International Association of Agricultural Economists.
    14. Alina Evelyn Badillo-Márquez & Alberto Alfonso Aguilar-Lasserre & Marco Augusto Miranda-Ackerman & Oscar Osvaldo Sandoval-González & Daniel Villanueva-Vásquez & Rubén Posada-Gómez, 2021. "An Agent-Based Model-Driven Decision Support System for Assessment of Agricultural Vulnerability of Sugarcane Facing Climatic Change," Mathematics, MDPI, vol. 9(23), pages 1-32, November.
    15. Meyer, Rachelle S. & Cullen, Brendan R. & Whetton, Penny H. & Robertson, Fiona A. & Eckard, Richard J., 2018. "Potential impacts of climate change on soil organic carbon and productivity in pastures of south eastern Australia," Agricultural Systems, Elsevier, vol. 167(C), pages 34-46.
    16. Gawith, David & Hodge, Ian & Morgan, Fraser & Daigneault, Adam, 2020. "Climate change costs more than we think because people adapt less than we assume," Ecological Economics, Elsevier, vol. 173(C).
    17. Zhao, Jiongchao & Wang, Chong & Shi, Xiaoyu & Bo, Xiaozhi & Li, Shuo & Shang, Mengfei & Chen, Fu & Chu, Qingquan, 2021. "Modeling climatically suitable areas for soybean and their shifts across China," Agricultural Systems, Elsevier, vol. 192(C).
    18. Shang, Linmei & Heckelei, Thomas & Börner, Jan & Rasch, Sebastian, 2020. "Adoption and Diffusion of Digital Farming Technologies – Integrating Farm-Level Evidence and System-Level Interaction," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305586, German Association of Agricultural Economists (GEWISOLA).
    19. Pengnan Xiao & Jie Xu & Zupeng Yu & Peng Qian & Mengyao Lu & Chao Ma, 2022. "Spatiotemporal Pattern Differentiation and Influencing Factors of Cultivated Land Use Efficiency in Hubei Province under Carbon Emission Constraints," Sustainability, MDPI, vol. 14(12), pages 1-24, June.
    20. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:10:y:2021:i:4:p:364-:d:528506. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.