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Original Articles

Arctic observing network social indicators and northern commercial fisheries

Pages 87-105 | Published online: 22 Jul 2011
 

Abstract

This article presents issues and challenges associated with collecting social indicator data in the context of northern commercial fisheries. The Arctic Observing Network Social Indicators Project (AON-SIP) fisheries domain database consists of geo-coded social indicator datasets from Alaska, Iceland, Norway, and Chukotka, of place/year catch, landings, employment, and permit data from 1980-present for commercially important species above 60°N and in the Bering Sea. Comparability of indicator data across regions will be important for the future monitoring and modeling of the effects of changes in the arctic environment such as those influenced by diminishing sea ice cover and increasing ocean acidification which will impact fisheries production and distribution. Equally important, the collection and analysis of time-series social indicator data could aid in understanding how arctic residents experience the processes of globalization as they participate in industries such as fisheries that are increasingly dominated by non-local corporations. Because of this extrinsic control of resources, social indicator data reflecting local ownership in fisheries rights and revenues could be functional in understanding how changes in fisheries impact arctic livelihoods. It is also necessary to understand how changes in fisheries fit within a broader resource use and arctic development context, for example, in conjunction with the oil and gas industry. Finally, planning for arctic fisheries of the future will be dependent upon data collection and analysis activities that can inform management plans and governance structures accommodating international boundary conflicts, rights-based management regimes, indigenous access, and organization/oversight of arctic marine science initiatives.

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. NSF OPP0638408.

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