Atlantic Bluefin Tuna in the Gulf of Maine, I: Estimation of Seasonal Abundance Accounting for Movement, School and School-Aggregation Behaviour

Direct assessment of the abundance of highly migratory pelagic species, such as tuna, is rarely available and most indices are based on catch information. We estimate the seasonal abundance of North Atlantic bluefin tuna, Thunnus thynnus, in the Gulf of Maine (GOM) from a 3-year aerial survey conducted with commercial spotter pilots, while also utilizing findings from analyses of tracking and tagging data. We apply statistical correction and calibration to seasonal abundance estimates accounting for measured changes in horizontal and vertical movement behaviour, size, shape and aggregation of bluefin tuna schools. Our approach relies on ecological knowledge of bluefin tuna to extrapolate survey observations across areas not sampled by correcting survey abundance estimates based on range of movement search pattern and depth preference. We demonstrate how separate findings obtained through the analysis of data collected across different spatial and temporal scales can be integrated to correct and calibrate estimates of population abundance. We obtain fitted estimates of seasonal abundance of bluefin tuna in the GOM during 1994–1996 in the range of 45,000–51,000 individuals. If tuna behaviour is not accounted for, we estimate that the base or residual survey precision would be 4–7% determined from analysis of recent spotter survey data in the study region. We estimate the precision in estimating seasonal abundance accounting for tuna behaviour to lie within a range of 1,301–3,302%. Under hypothetical future improvements in survey design that achieve a precision of 20% in transect length and placement, we calculate net-precision to lie within a range of 82–93%. This calculation assumes reducible uncertainty in school size estimation and irreducible uncertainty in movement and school-aggregation behaviour. We infer that survey precision could be further reduced by 43–32% to attain 10–50% in which a 3–8 years adaptive survey design may reliably detect a seasonal abundance trend.