Stock assessment models rely on a realistic description of species’ biology and ecology to yield unbiased estimates of stock status.
Atlantic bluefin tuna (Thunnus thynnus) are highly migratory fish with a contemporary range spanning the North Atlantic Ocean. Bluefin tuna populations have undergone severe decline and the status of the fish within each population remains uncertain. Improved biological knowledge, particularly of natural mortality and rates of mixing of the western (GOM) and eastern (Mediterranean) populations, is key to resolving the current status of the Atlantic bluefin tuna. We evaluated the potential for acoustic tags to yield empirical estimates of mortality and migration rates for long-lived, highly migratory species such as Atlantic bluefin tuna. Bluefin tuna tagged in the Gulf of St. Lawrence (GSL) foraging ground (2009–2016) exhibited high detection rates post release, with 91% crossing receiver lines one year post tagging, 61% detected after year two at large, with detections up to ~1700 days post deployment. Acoustic detections per individual fish ranged from 3 to 4759 receptions. A spatially-structured Bayesian mark recapture model was applied to the acoustic detection data for Atlantic bluefin tuna electronically tagged in the GSL to estimate the rate of instantaneous annual natural mortality. We report a median estimate of 0.10 yr−1 for this experiment. Our results demonstrate that acoustic tags can provide vital fisheries independent estimates for life history parameters critical for improving stock assessment models.
Atlantic bluefin tuna (Thunnus thynnus) are highly migratory fish with a contemporary range spanning the North Atlantic Ocean. Bluefin tuna
