Using pop-up satellite archival tags to inform selectivity in fisheries stock assessment models
Published online on 05. March 2015
Using pop-up satellite archival tags to inform selectivity in fisheries stock assessment models:
a case study for the blue shark in the South Atlantic Ocean
Felipe Carvalho, Robert Ahrens, Debra Murie, Keith Bigelow, Alexandre Aires-Da-Silva, Mark N. Maunder, Fábio Hazin
Selectivity has traditionally been well estimated internally in stock assessment models when length or age composition data are available. However, in stock assessment, temporal or spatial variation in fishery or stock structure can lead to misspecification of the selectivity pattern, which can contribute substantially to the uncertainty in stock assessment results. Consequently, generating auxiliary information to help stock assessment scientists avoid unrealistic specifications of selectivity patterns should be encouraged. Here, we combine data from pop-up satellite archival tags (PSATs) deployed on blue sharks in the South Atlantic Ocean, and information on maximum pelagic longline fishing depths, to introduce an alternative approach for estimating selectivity of fishing gear. Further, we present how this externally estimated tag-based selectivity can be used to inform the most appropriate form of selectivity curves (e.g. asymptotic or dome-shaped) in a spatially structured stock assessment model for the South Atlantic blue shark population. The estimated tag-based selectivity showed substantially different selectivity patterns within the area of the assessed stock, in one area the depth range of the longline gear is inhabited mostly by adults, which is consistent with an asymptotic selectivity. In another area, the overlap shifts to younger ages, with older sharks located in deeper waters, consequently the expected selectivity is more dome-shaped. To account for this variability in the stock assessment model, we assigned fishing fleets with different selectivity patterns. The form of the selectivity curve assigned for each fleet was based on the tag-based selectivity estimates for the area of where that fleet operates. The assessment model demonstrated relatively good fit to the data and that the estimated management quantities were robust. This study provides additional evidence that externally derived estimates of selectivity using PSATs data can assist implementing stock assessments that capture some of the spatial variability of pelagic fish species.
ICES J. Mar. Sci. (2015) doi: 10.1093/icesjms/fsv026