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Title: When fish are not poisson : modelling the migration of Atlantic salmon (Salmo salar) and sea trout (Salmo trutta) at multiple time scales
Author: Van Der Waal, Zelda
ISNI:       0000 0004 5360 7439
Awarding Body: University of Newcastle Upon Tyne
Current Institution: University of Newcastle upon Tyne
Date of Award: 2014
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Migratory species undertake prolonged seasonal journeys; monitoring these movements is challenging but can sometimes be achieved by observations that taken locally and, ideally, using remote methods. Amongst the best known examples of migrating fish in Europe, are Atlantic salmon (Salmo salar) and sea trout (Salmo trutta) that migrate between river and seawater. Characteristics of habitat suitability, feeding opportunities, predation, as well as salmonid sensitivity and needs, vary throughout successive stages of their anadromous life cycle. Since the marine stage is the longest but is also challenging to monitor, in-river fish counters are of increasing importance in understanding salmonid patterns in abundance. The original contribution of this thesis lies in the use of modelling techniques to investigate salmonid migration, based on temporal observations produced by an electronic fish counter triggered by salmonid passage, as they return to spawn in the River Tyne. Small scale observation revealed seasonal differences; aggregation behaviour intensified during the middle of the migration season, and explanatory covariates varied in both their effect size and relevance to salmonid abundance. At the population scale, migration was highly driven by annual periodicity, abundance increased with river temperature and there was an NAO effect with a four year lag, underlining the importance of marine conditions to parent population and/or post-smolts. Differences between distinct populations of S. salar and S. trutta appeared related to a species-specific annual periodicity and oceanic conditions as salmonids return (more so for S. salar). State-space models suggested a complex demographic structure for the two species. There was a species identification learning curve that affected the data by 2007. A classification algorithm determined that observations are more likely to be S. salar for larger signal amplitude, within a higher river flow and earlier in the year; characteristics were too similar between the two species to reach a useful classification success rate (69%). The project overall suggests specificities relating to both species and age-class that cannot be addressed in depth with the collected data; emerging limitations and recommendations are discussed.
Supervisor: Not available Sponsor: Environment Agency
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available