Demonstration of a spatially explicit, tag-integrated stock assessment model with application to three interconnected stocks of yellowtail flounder off of New England

Ignoring population structure and connectivity in stock assessment models can introduce bias into important management metrics. Tag-integrated assessment models can account for spatially explicit population dynamics by modelling multiple population components, each with unique demographics, and estimating movement among them. A tagging submodel is included to calculate predicted tag recaptures, and observed tagging data are incorporated in the objective function to inform estimates of movement and mortality. We describe the tag-integrated assessment framework and demonstrate its use through an application to three stocks of yellowtail flounder (Limanda ferruginea) off New England. Movement among the three yellowtail flounder stocks has been proposed as a potential source of uncertainty in the closed population assessments of each. A tagging study was conducted during 2003–2006 with over 45 000 tagged fish released in the region, and the tagging data were included in the tag-integrated model. Results indicated that movement among stocks was low, estimates of stock size and fishing mortality were similar to those from conventional stock assessments, and incorporating stock connectivity did not resolve residual patterns. Despite low movement estimates, new interpretations of regional stock dynamics may have important implications for regional fisheries management given the source-sink nature of movement estimates.