Propranolol (PROP) is a β-blocker prescribed mainly to treat human cardiac diseases but with its wide usage it often makes its way into the aquatic environment. This study examined whether PROP alters developmental patterns and catecholamine (CA)-regulated processes in the zebrafish (Danio rerio) and if exposure during early life alters the stress response and behaviors of adults. The 48 h LC50 was 21.6 mg/L, well above environmental levels (0.00059 mg/L). Embryos/larvae continuously PROP-exposed had decreased and increased transcript levels of the β1-adrenoceptor at 1 dpf and 5 dpf, respectively. Stressed, PROP-exposed zebrafish had reduced testosterone and estradiol levels and exhibited less anxiety behaviours than control fish. Furthermore, adults previously PROP-exposed as embryos/larvae had decreased growth in terms of body length (0.0006 mg/L PROP) and mass (20 mg/L PROP). Changes in cholesterol and testosterone levels occurred in PROP-exposed fish. Thus PROP-exposure alters developmental patterns and CA-regulated process that are essential for normal behaviours and responses to stress, and at least some of these changes persist in the adult zebrafish.

Behaviour genetics deals with complex phenotypes which respond flexibly to environments animals experience. Change of phenotype in response to environment is phenotypic plasticity. A central question is how genes influence plasticity. I study plasticity and gene by environment interactions (GEI) relating to behaviours, metabolic, and genomic phenotypes of adults of the fruit fly Drosophila melanogaster. Chapters 1-3 study cuticular hydrocarbon (CH) levels of male flies. Chapter 1 shows male CH levels respond to time of day and light. Methods are developed to reduce high variability of CH. I show variation in CH parallels activity of two classes of CH synthesis hormones. Analysis of rate of variation gives estimates of turnover rates of CH and the metabolic cost of signaling. Chapter 2 studies mixed groups of genetically different flies, “hosts” and “visitors”. GEI of CH are found with both abiotic factors and with social mix. Social mix results in GEI as strong as abiotic factors. Indirect Genetic Effects (IGE) theory is used to show frequency-dependent IGE interactions. Chapter 3 shows that males in mixed social environments reduce expression of clock and CH synthesis genes, resulting in different signals. Females mate more often with males in a mixed group than with single-genotype males. Plasticity in male gene expression in response to social environment leads to different signals, mating levels, and potentially different fitness. Chapter 4 deals with behaviour, metabolite, and genomic phenotypes in flies differing in foraging gene alleles, as the food environment is changed. Strong GEI is found, structured by food type, chemical class of metabolite, and gene metabolic roles. A concept called “relative nutrient sensitivity” suggests an interaction between foraging and the insulin signaling pathway. I demonstrate epistasis between for and insulin with quantitative genetic methods and bioinformatics. These results lead to the conclusion that GEI are common in many fly phenotypes in response to well studied environments such as food and less studied ones such as social group. Some implications of this for maintenance of genetic variance are discussed.

This thesis addresses two central questions: How in the long run do Canadian citizens learn about politics? And how does long term experience with politics influence democratic political engagement? The theoretical framework employed in this study makes four basic assumptions about citizens: they are intendedly rational, they use cognitive shortcuts, they are adaptive, and they often face deep uncertainty about the political world. These core assumptions generate a broad set of expectations about how long term experience with politics systematically affects citizen behaviour. This evidence indicates that years of accumulated experience with Canadian politics fundamentally shapes the political outlooks and behaviours of Canadian citizens. Political experience affects whether citizens vote, whether they get the requisite political information that helps them to make reasoned political judgments, and how different considerations enter into their vote choices. Moreover, and despite their different backgrounds, long term experience with Canadian politics influences democratic political engagement among Canadian born citizens and immigrant Canadians in strikingly similar ways.

Self-regulation is a highly adaptive process that enables goal-directed behaviour; however, individuals often fail to self-regulate successfully. Failures of self-regulation in the domain of health may be particularly harmful especially for those with chronic diseases. The Energy Model articulated by Baumeister and colleagues proposes that all acts of self-regulation rely on a single, finite energy resource. Thus, one possible explanation for self-regulation failure is insufficient energy. In the current research, four studies examine the relationship between the construct of energy, which can manifest in state or trait form, and self-regulatory success. Past research has demonstrated that individuals who perform two sequential tasks requiring self-regulation perform worse on the second task (the self-regulatory fatigue effect). The Energy Model proposes that this performance decrement can be explained by energy depletion. If this is true, then state energy should mediate the self-regulatory fatigue effect. A series of three experimental studies (studies 1-3) were designed to test this hypothesis. In Study 1, participants were randomly assigned to a gaze regulation task or to a no-regulation control group (as in Schmeichel et. al, 2003) before they watched a brief video clip. Following this first task, all participants worked on a second self-regulatory task (solving anagrams). Persistence and performance on this second task were the dependent measures and energy was measured before and after the initial video task. Contrary to the predictions of the Energy Model, the self-regulatory fatigue effect was not replicated in this study and so the mediating potential of energy could not be tested. However, ratings of task difficulty and effort suggested that individuals in the gaze regulation condition did not find this task to be very challenging. Accordingly, a second study was designed that added an additional level of self-regulatory demand by asking participants to rehearse a 7-digit number during the video clip (memory regulation). When this was crossed with the gaze regulation manipulation, four conditions were created: no regulation, gaze regulation only, memory regulation only and memory + gaze regulation. Study 2 then followed the same approximate procedure as Study 1, with individuals randomly assigned to one of the four conditions. The results of this study were consistent with Study 1 in that the self-regulatory fatigue effect was not replicated. However, the manipulation check suggested that some of the participants in the gaze regulation conditions may not have adhered to experimental instructions and the conditions may have differed in the degree to which they were enjoyable and interesting to participants. Accordingly, a third study used an eye-tracker to assess self-regulation during the video task and evaluated aspects of task engagement. Study 3 followed the same procedures as Study 2. Eye-tracker data verified significant differences between the groups in terms of self-regulation during the initial video task; however, there were no other significant between group differences. Taken together, these 3 studies indicate that the self-regulatory fatigue effect may be less robust than previous research would suggest. An unexpected finding was the high degree of variability in the energy measures, which implied that individual differences in energy may be important to consider. Accordingly, Study 4 prospectively examined the role of dispositional energy in the self-regulation of diet and exercise behaviour by testing whether energy moderated intention-behaviour concordance in a sample of individuals newly diagnosed with Type 2 diabetes. This study demonstrated that energy predicted future exercise behaviour in this sample and provided some preliminary support for the hypothesis that individuals with higher levels of dispositional energy may show more intention-behaviour concordance than those with lower levels of dispositional energy. Overall, these 4 studies provide some tentative support for the role of dispositional energy in the implementation of health behaviour, but do not support the Energy Models predictions regarding self-regulatory fatigue.

Certain temperament traits that exist may be accurate predictors of the behaviour animals will exhibit towards stockpersons and their offspring after parturition. A total of 184 beef cattle in year 1 and 169 in year 2 (99 of these were also tested in year 1) were run through a chute complex and individually restrained before calving to see if their response predicted their behaviour after calving. Pre-calving measurements included exertion force applied against the headgate, a subjective temperament score, the response to a stockperson standing in front of the headgate and the exit speed from the chute. Within 2 d after calving, the cows response to her calf, stockpersons and a predator model were recorded during standardized testing. A blood sample from each calf was collected to measure total serum protein and the calfs adjusted 205 d weaning weight was recorded in year 1. A principal component analysis was used to reduce the number of variables. The components were then used to generate multiple regression trees. The results of this study indicated that many measures of maternal behaviour were not related to the temperament of the animal. The amount of time the cow spends greater than 3m from the calf when it is being handled was somewhat related to temperament; however, this variable may indicate fearfulness of people rather than maternal behaviour. It appears that a cows temperament is, in general, a poor predictor of maternal behaviour. A producer survey was also conducted on 168 cattle producers at 3 Saskatchewan cattle events. The cumulative number of cows owned by the respondents was 33,621, 5.7% of which were reported to be dangerous (cows the producer judged would hurt them after calving if given the chance). The majority of farms (76.2%) had at least one dangerous cow. Mis-mothering (i.e. the cow abandoned or did not care for her calf) had an incidence of 1.4% of cows, and occurred on 56.3% farms. Producers are more tolerant of aggressive cows and are less likely to cull them than cows which abandon or mis-mother their calves.

This study assessed which behaviour management techniques, BMTs, pediatric dentists are using, and find effective in treating patients with Autism Spectrum Disorders, ASD and identified influences which contributed to their use. Surveys were mailed and emailed to 1669 members of the American Academy of Pediatric Dentistry. Seven hundred eighty-nine (48.2%) completed surveys were returned. Nearly 60% of respondents treated children with ASD weekly or more frequently. Of the 23 listed BMTs, General Anaesthesia, Tell-Show-Do, Distraction, and Non-verbal Communication, were considered effective. Seventy percent of respondents were primarily users of classical BMTs. Pharmacological and classical techniques, are used frequently, but may not be effective. Time and costs limit the use of modern techniques. Cost efficiency and long-term patient management were the most influential factors in selecting a BMT; patient co-operation was the least influential. Pediatric dentists recognized a need for further education related to behaviour management of children with ASD.

This thesis develops econometric models of departure time and travel mode choice to evaluate dynamic transportation policies. Dynamic policies affect travel attributes differently throughout the day. Both departure time and mode choice are modelled with Random Utility Maximizing (RUM) Generalized Extreme Value (GEV) discrete choice models that capture systematic and random heterogeneity. Departure time is represented by a heteroskedastic generalized extreme value model (Het-GEV) with overlapping choice sets. Studying the Greater Toronto and Hamilton Area (GTHA), models are estimated using Revealed Preference (RP) household travel data from the 2006 Transportation Tomorrow Survey (TTS). Empirical models are used to evaluate dynamic transit and road pricing policies. Results indicate that the models are capable of capturing mode and time switching behaviour in response to peak pricing policies. To alleviate demand while maintaining transit mode share, a road charge and a moderate, flat, transit fare increase throughout the morning peak are recommended.

This study assessed which behaviour management techniques, BMTs, pediatric dentists are using, and find effective in treating patients with Autism Spectrum Disorders, ASD and identified influences which contributed to their use. Surveys were mailed and emailed to 1669 members of the American Academy of Pediatric Dentistry. Seven hundred eighty-nine (48.2%) completed surveys were returned. Nearly 60% of respondents treated children with ASD weekly or more frequently. Of the 23 listed BMTs, General Anaesthesia, Tell-Show-Do, Distraction, and Non-verbal Communication, were considered effective. Seventy percent of respondents were primarily users of classical BMTs. Pharmacological and classical techniques, are used frequently, but may not be effective. Time and costs limit the use of modern techniques. Cost efficiency and long-term patient management were the most influential factors in selecting a BMT; patient co-operation was the least influential. Pediatric dentists recognized a need for further education related to behaviour management of children with ASD.

This thesis develops econometric models of departure time and travel mode choice to evaluate dynamic transportation policies. Dynamic policies affect travel attributes differently throughout the day. Both departure time and mode choice are modelled with Random Utility Maximizing (RUM) Generalized Extreme Value (GEV) discrete choice models that capture systematic and random heterogeneity. Departure time is represented by a heteroskedastic generalized extreme value model (Het-GEV) with overlapping choice sets. Studying the Greater Toronto and Hamilton Area (GTHA), models are estimated using Revealed Preference (RP) household travel data from the 2006 Transportation Tomorrow Survey (TTS). Empirical models are used to evaluate dynamic transit and road pricing policies. Results indicate that the models are capable of capturing mode and time switching behaviour in response to peak pricing policies. To alleviate demand while maintaining transit mode share, a road charge and a moderate, flat, transit fare increase throughout the morning peak are recommended.

Computer algorithms are routinely used to aid in the identification of biological patterns not easily detected with standard statistics. Currently, observed changes in normal patterns of feeding behavior (FB) are used to identify morbid feedlot cattle. The objective of this study was to use pattern classification techniques to develop algorithms capable of identifying morbid (M) cattle earlier than traditional pen checking methods. In two separate studies, individual feeding behaviour was obtained from 384 feedlot steers (228 ± 22.7 kg, initial BW) in a 226 d trial (model dataset), and 384 feedlot heifers (322 ± 34.7 kg, initial BW) in a 142 d trial (naive dataset). Data was collected using an automated feed bunk monitoring system. FB variables calculated included feeding duration, inter-meal interval (min., max., avg., SD and total; min/d) and feeding frequency (visits/d). Animal health records including the number of times treated, d in the hospital and d on feed were also collected. Ninety-three and 53 morbid (M) animals were identified in each trial respectively, and were categorized into low, moderate and high groups, based on severity of sickness. FB data for 68 cattle from the model dataset (45 classified as Moderate and 25 classified as High) was analyzed to develop an algorithm which would aid in identifying morbid FB. This algorithm was later tested on 18 M animals (12 classified as Moderate and 6 as High) in the naive dataset. The pattern recognition procedure involved reducing data dimensionality via Principal Component Analysis, followed by K-means clustering and finally the development of a binary string to aid in the classification of M feeding behaviour. The developed procedure resulted in an overall classification accuracy of 84 % (82.5 and 85 % accuracy for H and M, respectively) for the model dataset, and 75 % overall (100 and 50 % accuracy for H and M, respectively) for the naive dataset. The model predicted morbidity on average 3.3 and 1.2 d earlier than pen checkers could for each trial respectively. The application of pattern recognition algorithms to FB shows value as a method of identifying morbid cattle in advance of overt physical signs of morbidity.