Gypsy moths (Lymantria dispar) in the Niagara Region : population density variation, introduction of an entomopathogenic fungus (Entomophaga maimaiga) and occurrence of nuclear polyhedrosis virus

The gypsy moth, Lymantria dispar, a major defoliator of broad leaf trees, was accidentally introduced into North America in 1869. Much interest has been generated regarding the potential of using natural pathogens for biological control of this insect. One of these pathogens, a highly specific fungus, Entomophaga maimaiga, was accredited with causing major epizootics in populations of gypsy moth across the north-eastern United States in 1989 and 1990 and is thought to be spreading northwards into Canada. This study examined gypsy moth population densities in the Niagara Region. The fungus, .E.. maimaiga, was artificially introduced into one site and the resulting mortality in host populations was noted over two years. The relationship between fungal mortality, host population density and occurrence of another pathogen, the nuclear polyhedrosis virus (NPV), was assessed. Gypsy moth population density was assessed by counting egg masses in 0.01 hectare (ha) study plots in six areas, namely Louth, Queenston, Niagara-on-the-Lake, Shorthills Provincial Park, Chippawa Creek and Willoughby Marsh. High variability in density was seen among sites. Willoughby Marsh and Chippawa Creek, the sites with the greatest variability, were selected for more intensive study. The pathogenicity of E. maimaiga was established in laboratory trials. Fungal-infected gypsy moth larvae were then released into experimental plots of varying host density in Willoughby Marsh in 1992. These larvae served as the inoculum to infect field larvae. Other larvae were injected with culture medium only and released into control plots also of varying host density. Later, field larvae were collected and assessed for the presence of .E.. maimaiga and NPV. A greater proportion of larvae were infected from experimental plots than from control plots indicating that the experimental augmentation had been successful. There was no relationship between host density and the proportion of infected larvae in either experimental or control plots. In 1992, 86% of larvae were positive for NPV. Presence and intensity of NPV infection was independent of fungal presence, plot type or interaction of these two factors. Sampling was carried out in the summer of 1993, the year after the introduction, to evaluate the persistence of the pathogen in the environment. Almost 50% of all larvae were infected with the fungus. There was no difference between control and experimental plots. Data collected from Willoughby Marsh indicated that there was no correlation between the proportion of larvae infected with the fungus and host population density in either experimental or control plots. About 10% of larvae collected from a nearby site, Chippawa Creek, were also positive for .E.. maimaiga suggesting that low levels of .E.. maimaiga probably occurred naturally in the area. In 1993, 9.6% of larvae were positive for NPV. Again, presence or absence of NPV infection was independent of fungal presence plot type or interaction of these two factors. In conclusion, gypsy moth population densities were highly variable between and within sites in the Niagara Region. The introduction of the pathogenic fungus, .E.. maimaiga, into Willoughby Marsh in 1992 was successful and the fungus was again evident in 1993. There was no evidence for existence of a relationship between fungal mortality and gypsy moth density or occurrence of NPV. The results from this study are discussed with respect to the use of .E.. maimaiga in gypsy moth management programs.

Top-down and Bottom-up influences on ACC activation: Evaluation of a proposed model of the feedback-related negativity

The Feedback-Related Negativity (FRN) is thought to reflect the dopaminergic prediction error signal from the subcortical areas to the ACC (i.e., a bottom-up signal). Two studies were conducted in order to test a new model of FRN generation, which includes direct modulating influences of medial PFC (i.e., top-down signals) on the ACC at the time of the FRN. Study 1 examined the effects of one’s sense of control (top-down) and of informative cues (bottom-up) on the FRN measures. In Study 2, sense of control and instruction-based (top-down) and probability-based expectations (bottom-up) were manipulated to test the proposed model. The results suggest that any influences of medial PFC on the activity of the ACC that occur in the context of incentive tasks are not direct. The FRN was shown to be sensitive to salient stimulus characteristics. The results of this dissertation partially support the reinforcement learning theory, in that the FRN is a marker for prediction error signal from subcortical areas. However, the pattern of results outlined here suggests that prediction errors are based on salient stimulus characteristics and are not reward specific. A second goal of this dissertation was to examine whether ACC activity, measured through the FRN, is altered in individuals at-risk for problem-gambling behaviour (PG). Individuals in this group were more sensitive to the valence of the outcome in a gambling task compared to not at-risk individuals, suggesting that gambling contexts increase the sensitivity of the reward system to valence of the outcome in individuals at risk for PG. Furthermore, at-risk participants showed an increased sensitivity to reward characteristics and a decreased response to loss outcomes. This contrasts with those not at risk whose FRNs were sensitive to losses. As the results did not replicate previous research showing attenuated FRNs in pathological gamblers, it is likely that the size and time of the FRN does not change gradually with increasing risk of maladaptive behaviour. Instead, changes in ACC activity reflected by the FRN in general can be observed only after behaviour becomes clinically maladaptive or through comparison between different types of gain/loss outcomes.

Volume-Synchronized Probability of Informed Trading (VPIN), Market Volatility, and High-Frequency Liquidity

We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.