AbstractThe performance and health of managed game species is important to remote and rural economies. Wild red deer (Cervus elaphus) in the Scottish Highlands have long been recognised as occupying a sub-optimal (i.e., limiting) environment in terms of nutrition and shelter. Despite this wide recognition, no studies regarding the population have extensively quantified geographic variation in parasite prevalence or nutritional essential and non-essential trace/macro and toxic element status. Given the well-recognised effects of sub-lethal parasitism and sub-optimal nutrition on performance of ruminants (from an agricultural perspective; e.g., milk yield, growth rates), it is desirable to be aware of wild deer health status. Here, I establish baseline expectations regarding the health of wild red deer in the Scottish Highlands; and, in so doing, present evidence of marked geographic variation in parasite prevalence and nutritional status of wild red deer inhabiting a wide range of habitat types. Specifically, I:
1. Demonstrate that the novel diagnostic test (the coproantigen ELISA), performs comparatively well to the established faecal egg count (FEC) method for quantification of liver fluke (Fasciola hepatica) prevalence in Scottish Highland red deer.
2. Reveal substantial geographic variation in the prevalence of F. hepatica in wild red deer in the Scottish Highlands, and that an individual’s probability of infection: i) associates with sex, ii) follows a temporal pattern and iii) is associated with home range topography.
3. Reveal marked geographic variation in essential trace, non-essential trace, macro and toxic-element status of wild red deer in the Scottish Highlands, and show this to be associated with sex. Furthermore, I identify soil parent material as a potentially important factor in the availability of elements to wild red deer.
4. Utilise computer image analysis tools to reveal subtle geographic variation in red deer mandible shape and size in the Scottish Highlands; and, investigate the potential of a novel method for improving estimates of red deer age.
|Date of Award||4 Mar 2016|
|Supervisor||Mark Taggart (Supervisor), Stuart Gibb (Supervisor) & David Shaw (Supervisor)|