Maintaining the Continuity and Information in a Fisheries-Dependent Relative Index of Abundance

Wednesday, August 20, 2014: 11:30 AM
301A (Centre des congrès de Québec // Québec City Convention Centre)
Daniel Hoenig , Marine Biology and Fisheries, Rosenstiel School of Marine and Atmospheric Science, Miami, FL
Meaghan Bryan , NOAA Fisheries, Southeast Fisheries Science Center, Miami, FL
John F. Walter III , Sustainable Fisheries Division, NOAA Fisheries, Southeast Fisheries Science Center, Miami, FL
David J. Die , Marine Biology and Fisheries, University of Miami, RSMAS, Miami, FL
Many stock assessments rely upon fishery dependent catch rate information to track relative abundance of the stock. Regulatory actions that alter fisher behavior can substantially change catchability. This can perturb the signal in catch per unit effort data, potentially changing assessment results or introducing substantial uncertainty and bias in the assessment results. In the absence of empirical data on how management actions have affected the interpretation of CPUE, an analyst has several modeling options for CPUE data; either truncate the index at the change in regulation, estimate time-varying catchability or keep the index intact and assume that the bias will be minimal. Time-varying catchability was estimated in two ways.  The first approach was to separate the index representing the pre-IFQ and IFQ time periods where a constant catchability parameter was estimated for each. Our second approach was to estimate catchability as a random-walk process. Through simulations we evaluate the performance of the outlined CPUE treatments relative to the tradeoff between a between bias versus variance and the relative to strength of auxiliary information in the form of survey CPUE. We hope to provide robust and practical solutions to analysts confronted with a myriad of regulatory impacts upon fishery-dependent CPUE data.