Fisheries Research 155 (2014) 168–176 Contents lists available at ScienceDirect Fisheries Research j ourna l ho me pa ge: www.elsevier.com/locate/fishres Accounting for vessel effects when standardizing catch rates from cooperative surveys James T. Thorson a,∗ , Eric J. Ward b a Fisheries Resource Assessment and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, United States b Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, United States a r t i c l e i n f o Article history: Received 20 November 2013 Received in revised form 24 February 2014 Accepted 26 February 2014 Handling Editor A.E. Punt Available online 1 April 2014 Keywords: Index standardization Index of abundance Cooperative research Vessel effect Time-varying catchability Delta-generalized linear model a b s t r a c t Interpretation of fishery-dependent and independent-survey data requires accounting for changes in the proportion of local individuals that are caught by fishing gear (“catchability”). Catchability may be influenced by measured characteristics of fishing gear, and even standardized fishing techniques may experience changing catchability over time due to changes in fishing vessel characteristics and person- nel. The importance of vessel power has long been recognized in the analysis of fishery dependent catch per unit effort data, but less-studied in the analysis of fishery independent data collected by research vessel surveys. Here we demonstrate how differences in catchability among vessels (“vessel effects”), as well as random variation in vessel-specific catchability over time (“vessel-year effects”) can be incorpo- rated into generalized linear mixed models through their treatment as random effects. We apply these methods to data for 28 groundfish species caught in a standardized survey using contracted fishery ves- sels and personnel in the Northeast Pacific. Model selection shows that vessel, vessel-year, and both effects simultaneously are supported by available data for at least a few species. However, vessel-year effects generally have a larger effect on catch rates than vessel-effects and hence abundance indices estimated using both vessel- and vessel-year effects are generally similar to estimates when using just vessel-year effects. Additionally, models indicate little support for the hypothesis that characteristics such as length and displacement of the contracted vessels used in this survey have a substantial impact on catch rates. Finally, inclusion of vessel- or vessel-year effects generally results in wider estimates of credible intervals for resulting indices of abundance. This increased credible interval width is consistent with statistical theory, because vessel effects will result in non-independence of different sampling occa- sions, thus decreasing effective sample sizes. For this reason, we advocate that future analyses include vessel- and/or vessel-year effects when standardizing survey data from cooperative research programs. Published by Elsevier B.V. 1. Introduction Population dynamics and stock assessment models are central to the scientific approach to managing fisheries in the United States and elsewhere (Cardinale et al., 2013; Methot et al., 2014). Assess- ment models ideally incorporate information regarding the age and length-composition of the population, as well as trends in popula- tion abundance that are informed by survey data collection efforts using a randomized design. However, scientific sampling of fish ∗ Corresponding author. Tel.: +1 2063021772. E-mail addresses: james.thorson@noaa.gov, JamesT.esq@gmail.com (J.T. Thorson). populations is complicated due to large spatial ranges of fish popu- lations, variable fish densities throughout their range and from year to year, and difficulties in accessing fish habitats (Walters and Martell, 2004). To obtain data for estimating abundance trends and age/length- composition of marine populations, fisheries scientists and managers will sometimes conduct cooperative research in which fishery vessels are contracted to conduct randomized sampling of a region or population following a pre-determined design. Coop- erative research may improve stakeholder confidence for resulting information and increase communication between researchers and fishers. Also, it may in some cases be significantly more cost- efficient that other sampling designs, e.g., by using existing fishing vessels and expertise. However, using fishing vessels for scientific http://dx.doi.org/10.1016/j.fishres.2014.02.036 0165-7836/Published by Elsevier B.V.