Accounting for environmental and observer effects in estimating abundance of southern bluefin tuna from aerial survey data

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Abstract

Southern bluefin tuna (SBT) is a valuable species that has been subject to high exploitation rates since the 1950s. In 2011, the spawning stock biomass was estimated to be at a historically low level, at only 5% of pre-fished biomass. A key component for managing and rebuilding the stock is having reliable, fishery-independent estimates of juvenile abundance. This paper describes how such estimates have been constructed from aerial surveys of juvenile (age 2–4) SBT conducted annually in the Great Australian Bight from 1993–2000 and 2005–2009. During these surveys, observers flew along pre-set transect lines searching for surface schools of SBT. Data were collected on the location and biomass of SBT sightings, and on the environmental conditions present during the survey. Sea surface temperature (SST) was found to correlate with the size (biomass) of schools, and several environmental variables, SST and wind speed in particular, were found to correlate with the number of sightings (presumably by affecting the ability of observers to see surface schools as well as whether fish were present at the surface). In addition, observers changed over time and differed in their aptitude for spotting tuna. Thus, generalized linear mixed models (GLMMs) were used to standardize the sightings and biomass data to a common set of observers and environmental conditions in order to produce an annual time series of relative abundance estimates. These estimates, which form one of two key inputs to the management procedure used by the international Commission for the Conservation of Southern Bluefin Tuna to set the global catch quota, suggest juvenile abundance was highest in the first years of the survey (1993–1996), after which it declined and fluctuated around a level about four times lower.

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Paige Eveson, J., Bravington, M. V., & Farley, J. H. (2018, November 1). Accounting for environmental and observer effects in estimating abundance of southern bluefin tuna from aerial survey data. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0207790

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