Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/17021
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dc.contributor.advisorNorman, Rachel-
dc.contributor.advisorShinn, Andrew-
dc.contributor.advisorHoyle, Andrew-
dc.contributor.advisorTaylor, Nicholas G H-
dc.contributor.authorDenholm, Scott J.-
dc.date.accessioned2013-10-21T08:16:25Z-
dc.date.available2013-10-21T08:16:25Z-
dc.date.issued2013-
dc.identifier.urihttp://hdl.handle.net/1893/17021-
dc.description.abstractGyrodactylus salaris Malmberg, 1957, is a notifiable freshwater ecto-parasite that infects both wild and farmed populations of Atlantic salmon (Salmo salar, L.). It has caused catastrophic damage to wild salmon stocks in Norway since its accidental introduction in 1975, reducing salmon density in some rivers by 98% over a period of five years. It is estimated that G. salaris has cost the Norwegian salmon industry more than 500 million EUR. Currently the UK has G. salaris free status under EU law, however, it is believed that if G. salaris emerged in the UK the impact would be similar to that witnessed in Norway. The aim of this thesis is to develop mathematical models that describe the salmon-G. salaris system in order to gain a greater understanding of the possible long-term impact the parasite may have on wild populations of Atlantic salmon in G. salaris-free territories such as the UK. Mathematical models, including deterministic, Leslie matrix and individual based models, were used to investigate the impact of G. salaris on Atlantic salmon at the individual and population level. It is known that the Atlantic strain of Atlantic salmon, examples of which occur naturally in Norway and the UK, does not have any resistance to G. salaris infections and the parasite population is able to quickly grow to epidemic levels. In contrast, the Baltic strain of Atlantic salmon, examples of which occur naturally in Sweden and Russia, exhibits some form of resistance and the parasite is unable to persist. Thus, baseline models were extended to include immunity to infection, a trade-off on salmon reproductive rate, and finally, to consider interactions between populations of G. salaris and multiple strains of salmon exhibiting varying levels of immunity from fully susceptible to resistant. The models proposed predict that in the absence of host resistance or an immune response infections by G. salaris will result in an epidemic followed by the extinction of the salmon host population. Models also predict that if salmon are able to increase their resistance to G. salaris infections through mutations, salmon population recovery after the epidemic is indeed possible within 10-15 years post introduction with low level parasite coexistence. Finally, models also highlight areas where additional information is needed in order to improve predictions and enable the estimation of important parameter values. Model predictions will ultimately be used to assist in future contingency planning against G. salaris outbreaks in the UK and possibly as a basis for future models describing other fish/ecto-parasite systems.en_GB
dc.language.isoenen_GB
dc.publisherUniversity of Stirlingen_GB
dc.subjectMathematical modellingen_GB
dc.subjectGyrodactylus salarisen_GB
dc.subjectAtlantic salmonen_GB
dc.subjectmultiple strainsen_GB
dc.subjectparasiteen_GB
dc.subjectpathogenen_GB
dc.subject.lcshEpidemiology Mathematical modelsen_GB
dc.subject.lcshFishes Diseasesen_GB
dc.subject.lcshHost-parasite relationshipen_GB
dc.subject.lcshAtlantic salmonen_GB
dc.titleMathematical models for investigating the long-term impact of Gyrodactylus salaris infections on Atlantic salmon populationsen_GB
dc.typeThesis or Dissertationen_GB
dc.type.qualificationlevelDoctoralen_GB
dc.type.qualificationnameDoctor of Philosophyen_GB
dc.rights.embargodate2014-12-31-
dc.rights.embargoreasonI require time to write articles for publication from my thesis.en_GB
dc.contributor.funderThis research was supported by the Department for Environment, Food and Rural Affairs (Defra, project no. FC1197) and the Centre for Environment, Fisheries and Aquaculture Science (Cefas).en_GB
dc.author.emailscott.j.denholm@gmail.comen_GB
dc.contributor.affiliationSchool of Natural Sciencesen_GB
dc.contributor.affiliationComputing Science and Mathematicsen_GB
Appears in Collections:Computing Science and Mathematics eTheses

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