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Thesis (M.Sc.)--Memorial University of Newfoundland. / Bibliography : leaves 55-60. Also available online.

Recreational hunters play an important role in managing white-tailed deer (Odocoileus virginianus); however, the potential for deer to alter behaviors to avoid hunters has not been addressed within the risk-allocation hypothesis. I evaluated magnitude (i.e., hunter density) and temporal variation (i.e., time of day and initial and prolonged exposure) in human predation risk on movements, resource selection, and observation rates of 37 adult male deer in southern Oklahoma. Deer recognized human predation risk by increasing diel path complexity and use of security cover with greater hunter density. Moreover, deer reduced movement rates and tortuosity while seeking out areas with security cover during prolonged exposure. However, tortuosity and use of security cover remained elevated with greater hunter density. These alterations in behaviors subsequently led to a decrease in observation rates during prolonged exposure. My results clearly support the predation risk-allocation hypothesis by the behavioral responses observed with greater hunter density.

This study investigates the effect of changes in map scale on the error in the development of areal map units and their associated erosion severity measurements of New Zealand’s (NZ) Land Use Capability (LUC) surveying system. A map scale of 1:50,000 was used in the underlying data (i.e., a LUC survey) of an Erosion Susceptibility Classification (ESC) system, which was developed by Bloomberg and others (2011) of the University of Canterbury for the Ministry for the Environment’s (MFE) 2010 proposed National Environmental Standard for Plantation Forestry. The ESC was intended for local erosion management decisions, yet most literature would classify the map scale of 1:50,000 as more appropriate for regional management issues. Thus, this study will test two finer 1:10,000 scale datasets against the current 1:50,000 national LUC areal map units and their erosion severity measurements of the underlying data for the ESC system, to quantify the level of agreement. This study first attempted to identify a unique discriminating parameter of high erosion severity. A case study was conducted in the Sherry River catchment, located in the Tasman District of the South Island, NZ. The Sherry River Case Study had two aims; the first was to investigate the correlation between the Melton ratio and LUC erosion severity. This was accomplished by calculating the Melton ratio, a tested morphometric factor that describes basin (watershed) ruggedness, using Irvine’s (2011) Geographic Information Systems (GIS) debris-flow model. The product of this GIS debris-flow model, a calculated Melton ratio ≥ 0.50 with the areal extent outlined by a River Environment Classification (REC) order one polygon, were designated the areas of interest (AOIs). The Melton ratio was then tested against LUC erosion severity using the Spearman’s Ranked Correlation Coefficient, within the designated AOIs. A field investigation was conducted to verify debris-flow in GIS identified AOIs. Only five of the thirteen AOIs identified showed evidence of debris-flow. Two were un-checked due to accessibility and the others had a high degree of fluvial activity, which indicates a high probability that surface evidence of alluvial erosion deposition was erased. Nominal association between the two measurements of erosion (Melton ratio and LUC erosion severity) was found at the map scales of 1:50,000 or 1:10,000. Therefore the Melton ratio was not recommended as an independent parameter of erosion severity. The second aim of the Sherry River Catchment study was to assess the sensitivity of empirically generalised LUC areal map units and their erosion severity measurements to spatial resolution, that is, what is the effect of agreement between the smallest measurable value when looking at LUC map units and their erosion severity measurements recorded at two different map scales. A hard classification accuracy assessment was chosen to accomplish this objective. An accuracy assessment is a statistical model, which provides a probability of error (uncertainty), in essence a goodness-of-fit measurement, and quantified the agreement between a sample and reference dataset. This was accomplished by the calculation of an Overall accuracy (i.e., overall thematic agreement), Producer’s accuracy, and a User’s accuracy analytical statistics. The Producer’s accuracy refers to the probability that an area of sampled erosion severity category in the sample map is classified as such according to the reference map, while the user’s accuracy refers to the probability that a point labelled as a certain erosion severity in the sample map has that severity rating in reality (i.e., according to the reference map). An accuracy assessment also includes a second goodness-of-fit test, the Kappa statistic (K ̂), which measures the agreement between the sample and references map as well as chance agreement. An accuracy assessment of the AOIs within the Sherry Catchment Study area using an 85% significance criterion was conducted. This accuracy assessment investigated a sample LUC survey measured at the map scale of 1:10,000, as compared to the referenced underlying data of the ESC (1:50,000 map scale). Overall accuracy was marginal (69%) with equally marginal levels of Producer’s and User’s accuracy. The Kappa statistic showed a marginal level of significance according to Landis and Koch (1977) (K ̂ = 44%). The disagreement seen between the two LUC surveys, which were empirically developed using different map scales, provides evidence of high spatial resolution sensitivity, when comparing areal map units and erosion severity measurements. To further investigate evidence of spatial resolution sensitivity in LUC surveying, a second case study was conducted using a LUC survey across a broad geographical area of the Manawatu-Wanganui Region of the North Island, NZ. A sample dataset from the LUC survey, empirically generalised at 1:10,000 map scale by the Horizons Regional Council, was compared to the referenced underlying data of the ESC. There was a moderately-strong consistency found between the assessors of each LUC survey using Spearman’s Ranked Correlation Coefficient. This provides evidence of limited surveyor bias, as each map was made using empirical judgment. The accuracy assessment’s overall agreement was 63% and as for the previous case study, had equally low Producer’s and User’s accuracy levels. The Kappa statistic for this case study was K ̂= 46%, a moderate chance agreement. This evidence, along with the evidence provided by the Sherry River Catchment Case study, suggested that the MFE’s ESC system is sensitive to changes in map scale and that any decision based on it will have different results when its underlying data is produced at different spatial resolutions. It is therefore recommended that MFE reassess the map scales and resolutions of its underlying data, given that the ESC’s purpose is for local level environmental management, before imposing the system as a regulatory requirement in the National Environmental Standards for Plantation Forestry.

Cancer represents a major cause of human morbidity and mortality. There is no scientific consensus regarding cancer causality or prevention. Occupational exposure potentially remains a major contributor to the incidence of this group of diseases, but the data to assess its impact continues to elude researchers and public health advocates. Among women in industrialised countries, breast cancer is the most prevalent cancer. The known or suspected risk factors, including family history and lifetime oestrogen load, can account for less than 50 percent of the cases. New hypotheses about the role of xenoestrogens and endocrine disrupting compounds are challenging the previous scientific precepts regarding cancer causality. Within this context, the extent to which a community-based occupational history data collection initiative can contribute to advancing our scientific understanding of associations between cancer and work is explored. The possibility that occupational histories data can find associations missed in conventional breast cancer research that ignore occupation is also explored. More specifically, the extent to which data derived from an occupational history questionnaire can provide insight into the potential association between breast cancer risk and farming is examined. Occupational histories of cancer patients contain data that could help to elucidate and inform our understanding of cancer aetiology and prevention. In the community of Windsor, Ontario, Canada a local cancer treatment centre responded to community concerns by cooperating in a collaborative research project to collect the occupational histories of cancer patients. 'Computerised Record of Occupation Made Easy' (CROME) was an innovative method that allowed individual patients to document their lifetime work histories. This data collection process represented the first time a local Canadian cancer treatment center had undertaken such an initiative. Based on the hypothesis generated by CROME, a new research study was launched - Lifetime Occupational History Record (LOHR). Over a two-and-a-half year period, all female patients at the Windsor Regional Cancer Centre with new incident breast cancer were invited to participate in a population-based case-control study along with an equivalent number of randomly selected community controls. A comprehensive lifetime history questionnaire was administered to subjects by interview. Data gathered included known or suspected risk factors along with a complete occupational history of all jobs ever worked. An occupational history of farming alone produced an Odds Ratio (OR) = 2.8 (Cl, 95%, 1.6-4.8). These findings are important for our understanding of cancer causality with implications for resolving the current scientific conflict regarding the role of occupationally caused carcinogenesis. Such collaborative, community-based studies also demonstrate the importance of community participation in the scientific research process.

Geoarchaeology has had a long history within archaeology around the world, but not so much so in Gotlandic archaeology. This study is aimed at drawing attention to this by using magnetic susceptibility (MS) and phosphate (P) analysis of an Iron Age site at Ytings, Gotland. This is where a small silver hoard was discovered in 1888, and in 2009 a geophysical survey was done, via metal detector, and concluded with the theory of there being a workshop in the southern field and a farmstead in the north (ArkeoDok, 2011). The first part of this study discussed predictive modeling and whether or not the information available at the time would be enough to generate a reliable model (Coleman, 2016). The first study concluded with not being able to do so since the only discrete data available was from the metal detecting survey, which when used alone is not the most reliable instrument for archaeological prospection (Coleman, 2016). This led to this current study, which is the second part of a two-part study of Ytings. This study is aimed at using geoarchaeological methods for archaeological prospection to illustrate the benefits and need for these types of studies on Gotland, by comparing the MS and P results with the 2015 excavation report.

The presence of turnip crinkle virus (TCV) in Arabidopsis thaliana plants has previously been shown to suppress the ability of these plants to produce a hypersensitive response (HR) upon inoculation with pathogens that would normally elicit this defense response. The ecotype Colombia-0 was examined using wildtype TCV and non-pathogenic strains of Pseudomonas syringae pv. glycinea Race 4 containing virulence genes avrRpt2, avrRpm1 and avrRps4. Transgenic lines of A. thaliana that express the TCV proteins p8, p9 or CP were also examined in an attempt to determine if these proteins play a role in suppression of the HR. Crosses of these transgenic lines were made in order to determine if binary combinations of these proteins were sufficient for HR suppression. In addition, assays were completed to determine if the inhibition of the HR correlated with suppression of resistance to the virulent Pseudomonas syringae pv. maculicola ES4236 avrRpt2 growth in the plant. Finally, PR-1 protein expression was inspected by visual and quantitative GUS reporter gene assays to determine if TCV also played a role in inhibition of the plants ability to develop systemic acquired resistance (SAR).