Application of an acoustic–trawl survey design to improve estimates of rockfish biomass

• Main Authors: Hanselman, Dana H., Spencer , Paul D., McKelvey, Denise R., Martin , Michael H.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2012
• Subjects: Biology; Ecology; Fisheries; Pacific; Yakutat; Alaska
• Online Access: http://aquaticcommons.org/14482/; http://fishbull.noaa.gov/1104/hanselman.pdf; http://aquaticcommons.org/14482/1/hanselman.pdf

Biomass estimates of several species of Alaskan rockfishes exhibit large interannual variations. Because rockfishes are long lived and relatively slow growing, large, short-term shifts in population abundance are not likely. We attribute the variations in biomass estimates to the high variability in the spatial distribution of rockfishes that is not well accounted for by the survey design currently used. We evaluated the performance of an experimental survey design, the Trawl and Acoustic Presence/Absence Survey (TAPAS), to reduce the variability in estimated biomass for Pacific ocean perch (Sebastes alutus). Analysis of archived acoustic backscatter data produced an acoustic threshold for delineating potential areas of high (“patch”) and low (“background”) catch per unit of effort (CPUE) in real time. In 2009, we conducted a 12-day TAPAS near Yakutat, Alaska. We completed 59 trawls at 19 patch stations and 40 background stations. The design performed well logistically, and Pacific ocean perch (POP) accounted for 55% of the 31 metric tons (t) of the catch from this survey. The resulting estimates of rockfish biomass were slightly less precise than estimates from simple random sampling. This difference in precision was due to the weak relationship of CPUE to mean volume backscattering and the relatively low variability of POP CPUE encountered. When the data were re-analyzed with a higher acoustic threshold than the one used in the field study, performance was slightly better with this revised design than with the original field design. The TAPAS design could be made more effective by establishing a stronger link between acoustic backscatter and CPUE and by deriving an acoustic threshold that allows better identification of backscatter as that from the target species.