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Modeling the integration of stakeholder knowledge in social–ecological decision-making: Benefits and limitations to knowledge diversity

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  • Gray, Steven
  • Chan, Alex
  • Clark, Dan
  • Jordan, Rebecca

Abstract

Integrating stakeholder knowledge into natural resource governance is considered to add flexibility to social–ecological systems (SES) because knowledge diversity reduces rigidity, represents multiple perspectives, and promotes adaptability in decision-making. Characterizing the differences between knowledge systems, however, is not easily accomplished. There are few metrics readily available to compare one knowledge system to another. This paper characterizes knowledge about a model SES, the summer flounder fishery in the mid-Atlantic, to evaluate differences and similarities in the structural and functional characteristics of stakeholder mental models. To measure these differences, we collected Fuzzy-Logic Cognitive Maps (FCM) from several stakeholder groups (managers, scientists, harvesters, pre and post harvest sectors, and environmental NGOs) which comprise social agents within the SES. We then compared stakeholder groups’ maps using graph theory indices to characterize the structure and function of the model system. We then combined stakeholder FCM to generate a community map which represents a theoretical model of the combination of stakeholder knowledge. Our study indicates that while there may be benefits to integrating knowledge in resource decision-making, it also has costs associated with it. Although integrating knowledge may increase structural knowledge, it may also decrease precision in understanding of how a system functions and be overly focused on driving components which would reduce the ability of decision-makers to predict system reaction to a decision or policy plan.

Suggested Citation

  • Gray, Steven & Chan, Alex & Clark, Dan & Jordan, Rebecca, 2012. "Modeling the integration of stakeholder knowledge in social–ecological decision-making: Benefits and limitations to knowledge diversity," Ecological Modelling, Elsevier, vol. 229(C), pages 88-96.
  • Handle: RePEc:eee:ecomod:v:229:y:2012:i:c:p:88-96
    DOI: 10.1016/j.ecolmodel.2011.09.011
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    11. Ziv, Guy & Watson, Elizabeth & Young, Dylan & Howard, David C. & Larcom, Shaun T. & Tanentzap, Andrew J., 2018. "The potential impact of Brexit on the energy, water and food nexus in the UK: A fuzzy cognitive mapping approach," Applied Energy, Elsevier, vol. 210(C), pages 487-498.
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    14. Micha, Evgenia & Fenton, Owen & Daly, Karen & Kakonyi, Gabriella & Ezzati, Golnaz & Moloney, Thomas & Thornton, Steven F, 2019. "Mapping the pathways towards farm-level sustainable intensification of agriculture: an exploratory network 3 analysis of stakeholders’ views," SocArXiv 2rqjd, Center for Open Science.
    15. Cecilia Lundholm & Christian Stöhr, 2014. "Stakeholder Dialogues and Shared Understanding: The Case of Co-Managing Fisheries in Sweden," Sustainability, MDPI, vol. 6(7), pages 1-12, July.
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    17. Amanda E. Sorensen & Jeffrey Brown & Ashley Alred & Joseph J. Fontaine & Jenny M. Dauer, 2021. "Student representations and conceptions of ecological versus social sciences in a conservation course," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 11(1), pages 139-149, March.
    18. Meyer, Spencer R. & Johnson, Michelle L. & Lilieholm, Robert J. & Cronan, Christopher S., 2014. "Development of a stakeholder-driven spatial modeling framework for strategic landscape planning using Bayesian networks across two urban-rural gradients in Maine, USA," Ecological Modelling, Elsevier, vol. 291(C), pages 42-57.
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