Increased growth in salmon farming in Arctic Norway is paralleled with the discovery of enhanced volumes of anthropogenic debris. Much of this debris originates from the seafood industry and an estimated 29,000 tons of plastic waste is generated from the aquaculture industry annually. Despite these estimates, there is limited research on the extent and type of aquaculture debris on the Norwegian coast. Visual technologies are increasingly being used in aquaculture benthic monitoring programs and provide the opportunity to assess levels of debris surrounding fish farms. In addition, recent development in optical technology and computer power facilitates advancements in the automation of seafloor surveys. This project will utilize existing datasets from around aquaculture installations in Finnmark from ongoing Institute of Marine Research projects to address whether high north salmon farms are a source of seafloor debris. Visual data will be combined with machine-learning assisted image annotation methods currently under development in ongoing projects led by Akvaplan-niva og TerraNor. These projects will generate a method for the accelerated and automated detection and quantification of seafloor debris. Data will be collected on the spatial distribution and primary types of debris in relation to farms to determine how sources can be managed more effectively. Communication to the users will involve educational videos created by high school students and presented at aquaculture visitors centers. The project brings together an early career lead working with visual benthic survey techniques in the aquaculture industry and researchers with experience in machine-learning assisted image annotation methods to identify debris.
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