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Shoaling dynamics and abundance estimation : Atlantic bluefin tuna (Thunnus thynnus) Newlands, Nathaniel K.

Abstract

The Atlantic bluefin tuna (Thunnus thynnus) is a long-lived, highly migratory species that attains sizes of 2.20 m, and weights of 300 kg or more. Adults undertake cyclic migrations between coastal feeding zones, offshore wintering areas and spawning grounds. During June through October, bluefin tuna are common off the eastern United States and Canada, entering the Gulf of Maine, a semi-enclosed continental shelf area. The population is currently believed to have plummeted to 20% of 1970's levels, yet there is significant uncertainty in their population status and size. This thesis investigates bluefin tuna movement, aggregation and distribution, size and structure of bluefin shoals, and examines how these factors can affect the measurement bias and estimation uncertainty of population abundance. Data analysis methods applied include: interpolation of movement data, Lomb spectral analysis, statistical bootstrap simulation, Kalman filtering, and geostatistics. An automated digital image analysis system (SAIA) is developed for the three-dimensional analysis of fish shoal structure. A theoretical model is also formulated to describe the movement and behaviour of shoaling tuna leading to changes in shoal aggregation, distribution and abundance. The precision in abundance estimation of random, systematic, stratified, and spotter-search aerial survey sampling schemes are simulated under changes in the size, distribution and aggregation of shoals. Correlated and biased random walk models can predict lower and upper limits on displacement and spatial movement range over time. Bluefin tuna move by responding to changes in temperature gradients and to the local abundance of prey, preferring to be situated in the warmest water available, while also showing a weak response to flow and bathymetric gradients. The effect of aggregation on the distribution of shoals considerably reduces precision of population estimates under random transect sampling. Stratified sampling is shown to increase precision to within 5%, with adaptive stratification leading to further increases. Movement and shoal aggregation introduce relatively equal levels of bias and uncertainty in estimating abundance. Results indicate that reliable estimates of abundance can be attained under systematic and stratified survey schemes. However, further reductions in uncertainties associated with the shoal aggregation process are necessary to achieve acceptable precision in abundance estimation.

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