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Assessing the Impacts of Local Knowledge and Technology on Climate Change Vulnerability in Remote Communities

Author

Listed:
  • Christopher Bone

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA)

  • Lilian Alessa

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA
    Authors contributed equally to this work.)

  • Mark Altaweel

    (Computation Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, IL 60637, USA
    Authors contributed equally to this work.)

  • Andrew Kliskey

    (Resilience and Adaptive Management Group, University of Alaska Anchorage, 3101 Science Circle, Anchorage, AK 99508, USA
    Authors contributed equally to this work.)

  • Richard Lammers

    (Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
    Authors contributed equally to this work.)

Abstract

The introduction of new technologies into small remote communities can alter how individuals acquire knowledge about their surrounding environment. This is especially true when technologies that satisfy basic needs, such as freshwater use, create a distance ( i.e. , diminishing exposure) between individuals and their environment. However, such distancing can potentially be countered by the transfer of local knowledge between community members and from one generation to the next. The objective of this study is to simulate by way of agent-based modeling the tensions between technology-induced distancing and local knowledge that are exerted on community vulnerability to climate change. A model is developed that simulates how a collection of individual perceptions about changes to climatic-related variables manifest into community perceptions, how perceptions are influenced by the movement away from traditional resource use, and how the transmission of knowledge mitigates the potentially adverse effects of technology-induced distancing. The model is implemented utilizing climate and social data for two remote communities located on the Seward Peninsula in western Alaska. The agent-based model simulates a set of scenarios that depict different ways in which these communities may potentially engage with their natural resources, utilize knowledge transfer, and develop perceptions of how the local climate is different from previous years. A loosely-coupled pan-arctic climate model simulates changes monthly changes to climatic variables. The discrepancy between the perceptions derived from the agent-based model and the projections simulated by the climate model represent community vulnerability. The results demonstrate how demographics, the communication of knowledge and the types of ‘knowledge-providers’ influence community perception about changes to their local climate.

Suggested Citation

  • Christopher Bone & Lilian Alessa & Mark Altaweel & Andrew Kliskey & Richard Lammers, 2011. "Assessing the Impacts of Local Knowledge and Technology on Climate Change Vulnerability in Remote Communities," IJERPH, MDPI, vol. 8(3), pages 1-29, March.
    • Handle: RePEc:gam:jijerp:v:8:y:2011:i:3:p:733-761:d:11568
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    References listed on IDEAS

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    1. Daniel James Klooster, 2002. "Toward Adaptive Community Forest Management: Integrating Local Forest Knowledge with Scientific Forestry," Economic Geography, Taylor & Francis Journals, vol. 78(1), pages 43-70, January.
    2. Mark Altaweel & Lilian N. Alessa & Andrew D. Kliskey, 2010. "Social Influence and Decision-Making: Evaluating Agent Networks in Village Responses to Change in Freshwater," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-15.
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    Cited by:

    1. Weifang Shi & Weihua Zeng, 2013. "Genetic k -Means Clustering Approach for Mapping Human Vulnerability to Chemical Hazards in the Industrialized City: A Case Study of Shanghai, China," IJERPH, MDPI, vol. 10(6), pages 1-18, June.

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