The Laskeek Bay Conservation Society has been collecting data on the East Limestone Island population of Ancient Murrelets since 1990. For the first 15 years of this decades-long study, mark-recapture data was collected annually on the adult population using one method while chicks were captured and tagged each year soon after their birth using another method. We developed a Jolly-Seber type model that integrates the adult and chick data. Using a multi-state framework, our model separates the `alive' state of the JS model into several age-related states, allowing for different survival and capture parameters between states. In the Ancient Murrelet case study we found that a 6-state model with constant adult survival and capture parameters best fit the data. We determined that, since the detected chicks are rarely seen again, including these individuals in the model does not result in estimates which greatly differ from that of the standard Jolly-Seber model but in a population in which juveniles have high survival and re-capture probabilities, the MSJS model is able to reduce the bias in estimates of population parameters. / Graduate

Loggerhead sea turtles (Caretta caretta) are listed as threatened under the Endangered Species Act and are protected both on nesting beaches and in United States waters. Loggerhead sea turtles are long-lived species and are most easily studied on the beaches during the nesting season. Bald Head Island, North Carolina has one of the highest density nesting beaches of loggerhead sea turtles in the turtle's northern range on the East Coast of the United States. Key life history parameters were estimated and applied to a population model using 16 years of data from a mark-recapture study on the loggerhead sea turtle nesting population on Bald Head Island, North Carolina. The beach survey conducted on the island only allowed for the capture of adult female sea turtles during the breeding state even though females may spend multiple years in the unobservable non-breeding state. The majority of females captured over the last 16 years have never been recaptured at the original capture site. These transients in the data coupled with unobservable states violate the assumption of equal catchability in the available single state mark-recapture models. Therefore, a multistate mark- recapture model originally developed for leatherback sea turtles was applied to the Bald Head Island loggerhead population. Multistate modeling provides a new technique to estimate sea turtle demographic parameters in which all model assumptions can be met. The multistate model outputs female survival rates, capture probability, and transition probabilities between breeding and non-breeding states. A correction factor for trap-dependence and transients was included given that both factors tested significant in the global model goodness-of-fit tests. The estimates of annual adult survival rate and breeding transitions were then used to project population size for the northern subpopulation. For the first time, estimation error around estimates of benthic juvenile and adult survival rates was included in a loggerhead sea turtle model. I explored the effects of estimation error, three levels of clutch frequency, and larger TED openings on population growth rate and on the probability of reaching a nesting recovery threshold. The nesting recovery threshold was based upon recovery criteria from the Federal Recovery Plan and set as the probability of reaching 12,800 nests/season in the states of North Carolina, South Carolina, and Georgia within a 50 year time period. The results of this study provide important information to guide future management and research. / Master of Science

La surveillance des infections acquises en réanimation (IAR) représente un outil majeur dans la stratégie de lutte contre les infections nosocomiales. Nous avons enrichi la base de données de surveillance REA-RAISIN avec des données médico-administratives du PMSI afin de disposer d’informations sur l’hospitalisation complète et d’analyser des facteurs de risques supplémentaires. L’étude descriptive détaillée des 11 années de notre cohorte a permis de montrer des variations temporelles et les groupes les plus à risque. L’estimation de l’impact de ces IAR sur la mortalité et la durée de séjour nécessite des techniques statistiques multiples afin de prendre en compte les biais dont la durée d’apparition de l’IAR et le risque compétitif. Cet impact dépend du type d’IAR. La mortalité est très impactée par les bactériémies, peu par les pneumopathies et pas par les infections urinaires. L’augmentation de la durée de séjour est la plus importante pour les pneumopathies, suivie des infections urinaires et est modérée pour les bactériémies. L’étude du portage de S. aureus méticillino-résistant est parue insuffisante pour détecter des épidémies. / Monitoring the infection acquired in intensive care units (ICU-AI) is a strategic tool for the control of hospital-associated infections. We enhanced the national surveillance database REA-RAISIN with the local diagnosis-related group database. This allows us to have data on the whole hospitalization and assess additional risk factors. The assessment of the impact of these ICU-AI on mortality and length of stay needs appropriate and multiple statistical analysis to take in account various potential bias, including time-dependent bias and competitive risk. This impact is a function of the kind of IAR. Mortality is most affected by bacteremia, more lightly by pneumonia and stay equivalent for patients with or without urinary tract infections. On the other hand, excess of length of stay was the most important for patients with pneumonia and urinary tract infections but moderate for those with bacteremia.Finally, studying the carriage of methicillin-resistant S. aureus appeared insufficient to detect outbreaks and does not measure the risk associated with SASM carriage.

New analytical and technological tools have the potential to yield unprecedented insights into the life histories of migratory species. I used Bayesian population models and Global Positioning System-acceleration tracking devices to understand the demographic mechanism and likely drivers underpinning the Greenland White-fronted Goose (Anser albifrons flavirostris) population decline. I used a 27-year capture-mark-recapture dataset from the main wintering site for these birds (Wexford, Ireland) to construct multistate models that estimated age- and sex-specific survival and movement probabilities and found no sex-bias in emigration or ‘remigration’ rates (chapter 2). These formed the foundation for an integrated population model, which included population size and productivity data to assess source-sink dynamics through estimation of age-, site-, and year-specific survival and movement probabilities, the results of which suggest that Wexford is a large sink and that a reduction in productivity (measured as recruitment rate) is the proximate demographic mechanism behind the population decline (chapter 3). Low productivity may be due to environmental conditions on breeding areas in west Greenland, whereby birds bred at youngest ages when conditions were favourable during adulthood and the breeding year (chapter 4), and possibly mediated by links with the social system, as birds remained with parents into adulthood, forfeiting immediate reproductive success, although a cost-benefit model showed the ‘leave’ strategy was marginally favoured over the ‘stay’ strategy at all ages (chapter 5). Foraging during spring does not appear to limit breeding, as breeding and non-breeding birds did not differ in their proportion of time feeding or energy expenditure (chapter 6). Two successful breeding birds were the only tagged individuals (of 15) to even attempt to nest, suggesting low breeding propensity has contributed to low productivity. Although birds wintering in Ireland migrated further to breeding areas than those wintering in Scotland, there were no differences in feeding between groups during spring migration (chapter 7). These findings suggest that Greenland White-fronted Geese are not limited until arrival on breeding areas and the increasingly poor environmental conditions there (chapter 8). More broadly, these findings demonstrate the application of novel tools to diagnose the cause of population decline.