Griffiths, Christopher A. (2018) Using electronic tagging data to investigate the individual-, population- and community-level consequences of movement in free-roaming marine fish. PhD thesis, University of Sheffield.
Abstract
Tagging studies are now commonplace in ecology. Technological advances in telemetry devices have revolutionised our ability to track the movements of individual animals over vast spatial scales. This is especially true in marine ecology, where animals move through a world that is otherwise unobservable. The aim of many tagging studies is that by understanding the movements of the few we might gain some meaningful inference about the movements of the many, with clear consequences for conservation and management. Achieving this aim requires the scaling of inferences from the individual- to the population- and community-levels. Concentrating on the movements of marine fish, this scaling process forms the rationale behind this thesis. I start at the individual-level by investigating how movement influences stock structure and patterns of space use, with important implications for stock recovery. At the population-level, I introduce a novel method for behavioural classification, which addresses issues surrounding individual variation by assuming that individuals of the same species share two broad behavioural modes. Application of this method to the movements of two commercially important species reveals clear spatio-temporal patterns, as fish switch their horizontal and vertical activity levels on a seasonal basis. I step towards the community-level by first scrutinising the scaling relationship between body size and movement in marine fish before applying the findings to a dynamic size-structured community model. I show how changes to the underlying assumptions surrounding movement have large emergent consequences for community structure, species coexistence and fisheries yield. Marine tagging studies are currently underutilised by conservation and management, owing to small sample sizes, variations in data quality and a lack of methods for the scaling up of inference. Here I provide a body of work that tackles these issues and more generally demonstrates the importance of movement to our understanding of fish populations and marine communities.
Metadata
Supervisors: | Blackwell, Paul and Blanchard, Julia and Pitchford, Jon and Righton, David |
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Keywords: | tagging data, marine fish, movement, allometric scaling, movement behaviour, body mass, size-based modelling, scaling-up, population and community dynamics |
Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > Animal and Plant Sciences (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.770199 |
Depositing User: | Mr Christopher Griffiths |
Date Deposited: | 01 Apr 2019 08:44 |
Last Modified: | 01 May 2022 09:53 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:23410 |
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