Goater, Cameron

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https://opus.uleth.ca/handle/10133/4801

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    Living on the edge: comparative phylogeography and phylogenetics of Oreohelix land snails at their range edge in Western Canada
    (BioMed Central, 2020) Dempsey, Zach W.; Goater, Cameron P.; Burg, Theresa M.
    Background: The biodiversity and distributions of terrestrial snails at local and regional scales are influenced by their low vagility and microhabitat specificity. The accessibility of large-bodied species and their characteristically high levels of genetic polymorphism make them excellent ecological and evolutionary models for studies on the phylogeography, phylogenetics, and conservation of organisms in fragmented populations. This study aims to elucidate the biodiversity, systematics, and distributions of genetic lineages within the genus Oreohelix at the northern and western periphery of their range. Results: We found four mitochondrial clades, three of which are putative subspecies of Oreohelix subrudis. One clade was geographically widespread, occurring within numerous sites in Cypress Hills and in the Rocky Mountains, a second was geographically restricted to the Rocky Mountains in Alberta, and a third was restricted to the Cypress Hills region. A fourth clade was the small-bodied species, O. cooperi. ITS2 sequence and screening data revealed three genetic clusters, of which one was O. cooperi. Cluster 1 contained most individuals in COI clade X and some from clade B and cluster 2 was predominantly made up of individuals from COI clades B and B′ and a few from clade X. ITS2 alleles were shared in a narrow contact zone between two COI clades, suggestive of hybridization between the two. Conclusions: A sky island known as Cypress Hills, in southeastern Alberta, Canada, is a biodiversity hotspot for terrestrial land snails in the genus Oreohelix. The observed phylogeographic patterns likely reflect reproductive isolation during the Last Glacial Maximum, followed by secondary contact due to passive, long-range dispersal resulting from low vagility, local adaptation, and complex glacial history.
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    Where's the risk? : Landscape epidemiology of gastrointestinal parasitism in Alberta beef cattle
    (Biomed Central Ltd, 2015) Beck, Melissa A.; Colwell, Douglas D.; Goater, Cameron P.; Kienzle, Stefan W.
    Background: Gastrointenstinal nematodes (GIN) present a serious challenge to the health and productivity of grazing stock around the globe. However, the epidemiology of GIN transmission remains poorly understood in northern climates. Combining use of serological diagnostics, GIS mapping technology, and geospatial statistics, we evaluated ecological covariates of spatial and temporal variability in GIN transmission among bovine calves pastured in Alberta, Canada. Methods: Sera were collected from 1000 beef calves across Alberta, Canada over three consecutive years (2008–2010) and analyzed for presence of anti-GIN antibodies using the SVANOVIR Ostertagia osteragi-Ab ELISA kit. Using a GIS and Bayesian multivariate spatial statistics, we evaluated the degree to which variation in specific environmental covariates (e.g. moisture, humidity, temperature) was associated with variation in spatial and temporal heterogeneity in exposure to GIN (Nematodirus and other trichostrongyles, primarily Ostertagia and Cooperia). Results: Variation in growing degree days above a base temperature of 5 °C, humidity, air temperature, and accumulated precipitation were found to be significant predictors of broad–scale spatial and temporal variation in serum antibody concentrations. Risk model projections identified that while transmission in cattle from southeastern and northwestern Alberta was relatively low in all years, rate of GIN transmission was generally higher in the central region of Alberta. Conclusions: The spatial variability in risk is attributed to higher average humidity, precipitation and moderate temperatures in the central region of Alberta in comparison with the hot, dry southeastern corner of the province and the cool, dry northwestern corner. Although more targeted sampling is needed to improve model accuracy, our projections represent an important step towards tying treatment recommendations to actual risk of infection.