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dc.contributor.authorFøre, Martinnb_NO
dc.date.accessioned2014-12-19T14:05:36Z
dc.date.available2014-12-19T14:05:36Z
dc.date.created2012-08-24nb_NO
dc.date.issued2011nb_NO
dc.identifier546673nb_NO
dc.identifier.isbn978-82-471-3224-1, hnb_NO
dc.identifier.urihttp://hdl.handle.net/11250/260580
dc.description.abstractTo develop safe and efficient cage management strategies for marine Atlantic salmon farming it is of paramount importance to understand how the fish behave in response to the culture environment. Most behavioural information available on farmed salmon has been assembled by using methods that target sub-volumes of the cage rather than observing the individual animals (e.g. submerged cameras and echo sounders). To obtain a more thorough understanding of salmon behaviour in sea-cages, it is necessary to also study the behaviours of individual fish within the population. The main contributions from the present thesis is the development and testing of two novel technological tools for observing and estimating the individual behaviours of farmed salmon. The first of these tools is a mathematical model of salmon behaviour in marine sea-cages. This model was built using an individual-based state-space oriented modelling approach, and is solved by numerical simulation. The individual fish were programmed to respond to a realistic cage environment containing factors that vary in time and space, and the main model outputs are the positions and swimming velocities of all simulated fish. Comparisons between model output and published data indicated that the model is able to replicate most of the behavioural dynamics behind vertical distribution patterns of Atlantic salmon populations in sea-cages. Furthermore, simulation results demonstrated that the combined effects of the individual fish responses toward the cage structure and other individuals in the cage resulted in the formation of school-like group structures similar to those commonly observed in commercial salmon cages. This suggests that schooling in caged salmon may be a behavioural expression emerging as a result of the fish being confined to within the boundaries of the cage and the density of fish within the cage. The second tool developed in this thesis was based on acoustic telemetry and aimed to produce information on the feeding behaviours of individual salmon. Based on preliminary literature studies and camera observations of feeding salmon, vertical movement, increased swimming activity and inertial suction (expansion of the gill lids to produce an underpressure within the oral cavity) were identified as behavioural expressions which typically accompany feeding activity. Three acoustic transmitter tag types containing different sensor technologies were developed with the intent of detecting these behavioural characteristics. The transmitters were tested in two sequential experiments, the first of which was performed in a small sea-cage stocked with a low fish density and equipped with submerged cameras that enabled validation of the outputs from the transmitter tags through visual observations. In the second experiment, the fish were moved to a larger cage holding a commercial density of fish, to test how the transmitters would perform under conditions more similar to those encountered in industrial salmon production. Based on the results from these studies, the transmitters sensitive to vertical movements and increased swimming activity were found to be better able to distinguish feeding activity from other behaviours than the tag type that was sensitive to inertial suction.nb_NO
dc.languageengnb_NO
dc.publisherNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikknb_NO
dc.relation.ispartofseriesDoktoravhandlinger ved NTNU, 1503-8181; 2011:322nb_NO
dc.titleIndividual based modelling and observation of Atlantic salmon (Salmo salar L.) behaviour in sea cagesnb_NO
dc.typeDoctoral thesisnb_NO
dc.contributor.departmentNorges teknisk-naturvitenskapelige universitet, Fakultet for informasjonsteknologi, matematikk og elektroteknikk, Institutt for teknisk kybernetikknb_NO
dc.description.degreePhD i teknisk kybernetikknb_NO
dc.description.degreePhD in Engineering Cyberneticsen_GB


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