Social scientist Mike Downs from our project team will be making a presentation about Measuring the Effects of Catch Shares at the North American Association of Fisheries Economists 8th (2015) Biennial Forum on May 20th in Ketchikan, Alaska.
Measuring the Effects of Catch Shares: Identifying Indicators and Establishing Baselines along the West and Northeast Coasts
Michael A. Downs (AECOM), Marcus Hartley (Northern Economics), Stev Weidlich (AECOM), Don Schug (Northern Economics)
The Measuring the Effects of Catch Shares Project is a webportal-based effort that continues to compile and analyze data on ecological, economic, social, and administrative changes in groundfish catch share fisheries on the West Coast and in the Northeast. The purpose of the five-year project is to make the best available data and accompanying analyses readily accessible to the general public as well as to those with specific interests the fisheries, including fishery managers, fishermen, policymakers, legislators, and service business owners. Among other data, the project presents information on six key economic and social indicators across both fisheries. This presentation describes the overall project, its goals, and initial findings. Specifically described are methodological considerations used in determining how and why a much larger number of potential indicators considered during project planning and initial baseline data gathering processes were winnowed down to the final key economic and social indicators. These considerations included the public availability of data, data accuracy, confidentiality, geographic coverage, and replicability, among others. Specifically underlined by the project findings is the importance of extended baseline time series data in placing potentially catch share-related changes in the context of longer-term fishery fluctuations and trends of change. Another preliminary conclusion is related to the challenges of confidentiality that severely restrict the analysis of changes at the sub-regional and/or port level, which is requiring implementation of additional methodologies in later stages of the project to address data gaps.