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An agent-based modelling approach to evaluation of multiple-use management strategies for coastal marine ecosystems

Author

Listed:
  • McDonald, A.D.
  • Little, L.R.
  • Gray, R.
  • Fulton, E.
  • Sainsbury, K.J.
  • Lyne, V.D.

Abstract

The general objective of the multiple-use management strategy evaluation (MSE) framework is to develop and demonstrate practical science-based methods that support, under existing statutory arrangements, integrated regional planning and management of coastal and marine ecosystems. In the present paper multiple-use MSE is focused on four sectors: oil and gas, conservation, fisheries, and urban and industrial development. A selection of cross-sectoral development scenarios, management strategies and computer representations, provided by the relevant interest groups, is represented. These include prospective future sectoral activities and their impacts, and the sectoral response to alternative management policies and strategies. The agent-based modelling software InVitro is well placed for analysing prospective social and ecological impacts of multiple-use management strategies in a risk-assessment framework such as MSE. An illustrative example is provided to demonstrate the tradeoffs that can be recognised and quantified using the MSE framework. The example explores the implications of a change in management strategy that not only has a direct impact on the targeted sectors, but also indirect impacts, not all of which are to be expected.

Suggested Citation

  • McDonald, A.D. & Little, L.R. & Gray, R. & Fulton, E. & Sainsbury, K.J. & Lyne, V.D., 2008. "An agent-based modelling approach to evaluation of multiple-use management strategies for coastal marine ecosystems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 401-411.
    • Handle: RePEc:eee:matcom:v:78:y:2008:i:2:p:401-411
    DOI: 10.1016/j.matcom.2008.01.039
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    Cited by:

    1. Jlenia Di Noia, 2022. "Agent-Based Models for Climate Change Adaptation in Coastal Zones. A Review," Working Papers 2022.20, Fondazione Eni Enrico Mattei.
    2. Burgess, Matthew G. & Carrella, Ernesto & Drexler, Michael & Axtell, Robert L. & Bailey, Richard M. & Watson, James R. & Cabral, Reniel B. & Clemence, Michaela & Costello, Christopher & Dorsett, Chris, 2018. "Opportunities for agent-based modeling in human dimensions of fisheries," SocArXiv gzhm5, Center for Open Science.
    3. Atakelty Hailu & Lei Gao, 2012. "Research Note: Recreational Trip Timing and Duration Prediction," Tourism Economics, , vol. 18(1), pages 243-251, February.
    4. Cooper, Rachel & Jarre, Astrid, 2017. "An Agent-based Model of the South African Offshore Hake Trawl Industry: Part I Model Description and Validation," Ecological Economics, Elsevier, vol. 142(C), pages 268-281.
    5. Di Noia, Jlenia, 2022. "Agent-Based Models for Climate Change Adaptation in Coastal Zones. A Review," FEEM Working Papers 322810, Fondazione Eni Enrico Mattei (FEEM).
    6. Perez, Liliana & Dragicevic, Suzana, 2012. "Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model," Ecological Modelling, Elsevier, vol. 231(C), pages 53-64.

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