Application of decision analysis in the evaluation of recreational fishery management problems

• Main Author: Merritt, Margaret Faye
• Other Authors: Reynolds, James B., Criddle, Keith R.
• Format: Doctoral or Postdoctoral Thesis
• Language: unknown
• Published: 1995
• Subjects: Forestry; Operations research; Aquatic sciences; Recreation; Fairbanks; Coregonus pidschian; Humpback whitefish; pidschian; Alaska
• Online Access: http://hdl.handle.net/11122/9443

Dissertation (Ph.D.) University of Alaska Fairbanks, 1995 Fisheries management is a decision-making process, yet typically formal decision analysis techniques are not used in structuring problems, quantifying interactions, or arriving at a prioritized solution. Decision analysis tools are applied in the decision-making process for Alaska's recreational fisheries management as a means to reduce risk in management at the policy (Chapter 2) and field (Chapter 3) levels. In Chapter 2 the analytic hierarchy process is applied to the recreational fishery for chinook salmon (Oncorhynchus tshawytscha) in the Kenai River. Model structure is developed through an iterative interview process involving individuals asked to represent the perspectives of 15 different stakeholders. Individual stakeholder judgments are combined using a geometric mean, and maximax and maximin criteria. The sensitivity of the results to under-representation is explored through various models. Despise the contentious differences of perspective represented among stakeholders, the analytic hierarchy process identifies management options that enjoy broad support and limited opposition. In Chapter 3 decision analysis is applied to the recreational spear fishery for humpback whitefish (Coregonus pidschian) in the Chatanika River. A modified form of catch-age analysis is used to combine information derived from creel surveys and run age composition with auxiliary information in the form of mark-recapture estimates of abundance. Four systems are used in weighting annual observations: prior beliefs regarding their reliability, by the inverses of their variances, through a combination of these two weighting schemes, and equal (no) weights. The perception-weighted model generates the most reasonable estimates of abundance, which are relatively precise and associated with small bias. Forecasts of mature exploitable abundance are calculated based on various recruitment scenarios, maturity schedules, and exploitation rates. From these outcomes, the odds of ...