Counting and sizing Atlantic bluefin tuna schools using medium range sonars of baitboats in the Bay of Biscay

Abstract This study reports on the automated counting and sizing of Atlantic bluefin tuna (ABFT) schools using medium range sonar data extracted from a systematic acoustic sampling survey in the Bay of Biscay (BoB). An image analysis program is used to obtain the morphometric characteristics of any objects detected by the sonar. These objects are classified into “Tuna” or “Non-Tuna” using a morphometric classification model (MCM). Next, the vessel's operational data are also extracted using optical character recognition (OCR), and a novel methodology for counting and sizing ABFT schools is developed. Validation of the school counting methodology is carried out by comparing the number of observed and estimated schools, and the dimensions of the schools are standardised for the effect of sonar gain and range. Unlike existing baitboat catch per unit effort (CPUE)-based abundance indices, this methodology avoids bias that arises from inter-annual changes in food availability, stomach repletion and/or feeding behaviour. Thus, the estimated number of tuna schools and their relative size can provide more fisheries with independent abundance estimates. This methodology can be applied in two ways: i) for detecting schools on images recorded by the commercial baitboat fleet during their regular fishing operations, to replace the currently used CPUE index with a new standardised detection per unit effort (DPUE) index, or ii) for performing scientifically designed systematic acoustic surveys to monitor the abundance of this species in the BoB year after year.