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Bibliography: leaves 132-153. / viii, 153 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Spatially explicit models and computer intensive analysis were employed to explore how processes acting at the individual level scale up to population dynamics when processes are variable in space as well as the consequences of sampling spatially complex variability for drawing conclusions from limited ecological data. Dispersal and variation in marsupial mortality and development in relation to habitat selection and quality were studied, while evaluating spatially explicit models. The study of dynamics models of tick populations on sleepy lizards considered the effect of spatial and temporal variability, and demonstrated that counting ticks is a poor indicator of tick abundance. The "virtual ecologist" model is a useful method for linking the output of spatially explicit population models to reality, and will be a valuable approach for improving the design of ecological field research on spatially complex landscapes. / Thesis (Ph.D.)--University of Adelaide, Dept. of Environmental Science and Management, 1999?

Bibliography: leaves 132-153. Spatially explicit models and computer intensive analysis were employed to explore how processes acting at the individual level scale up to population dynamics when processes are variable in space as well as the consequences of sampling spatially complex variability for drawing conclusions from limited ecological data. Dispersal and variation in marsupial mortality and development in relation to habitat selection and quality were studied, while evaluating spatially explicit models. The study of dynamics models of tick populations on sleepy lizards considered the effect of spatial and temporal variability, and demonstrated that counting ticks is a poor indicator of tick abundance. The "virtual ecologist" model is a useful method for linking the output of spatially explicit population models to reality, and will be a valuable approach for improving the design of ecological field research on spatially complex landscapes.

Bibliography: leaves 132-153. / viii, 153 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Spatially explicit models and computer intensive analysis were employed to explore how processes acting at the individual level scale up to population dynamics when processes are variable in space as well as the consequences of sampling spatially complex variability for drawing conclusions from limited ecological data. Dispersal and variation in marsupial mortality and development in relation to habitat selection and quality were studied, while evaluating spatially explicit models. The study of dynamics models of tick populations on sleepy lizards considered the effect of spatial and temporal variability, and demonstrated that counting ticks is a poor indicator of tick abundance. The "virtual ecologist" model is a useful method for linking the output of spatially explicit population models to reality, and will be a valuable approach for improving the design of ecological field research on spatially complex landscapes. / Thesis (Ph.D.)--University of Adelaide, Dept. of Environmental Science and Management, 1999?

Incidental catch, or bycatch, of harbour porpoise (Phocoena phocoena) in fishing operations is an international conservation issue. The main objective of this thesis was to develop methods for determining the impact of bycatch on the state and dynamics of porpoise populations and for calculating bycatch limits that will achieve conservation objectives in the future. I applied these methods to the North Sea as a case study. First, I analysed sighting rates of harbour porpoise on seabird surveys in the North Sea during 1980-2003 to determine whether these data could provide informative time-series of relative abundance. Some general patterns and trends in sighting rates were consistent with previous studies. However, the standardised indices of abundance were relatively imprecise and thus have limited value for a monitoring framework that relies on statistical detection of trends. Second, I used a population model to integrate available data on harbour porpoise in the North Sea and to assess the dynamics of the population during 1987-2005. There was a high probability that bycatch resulted in a decrease in abundance. The estimated life history parameters suggested a limited scope for population growth even in the absence of bycatch. The model and data were not informative about maximum population growth rate or carrying capacity. The model suggested that dispersal was the most plausible explanation for observed changes in distribution within the North Sea. Third, I considered management procedures for calculating bycatch limits. I performed simulations to compare the behaviour of the procedures, to tune the procedures to specific conservation objectives and to test the robustness of the procedures to a range of uncertainties regarding population dynamics and structure, the environment, observation and implementation. Preliminary annual bycatch limits for harbour porpoise in the North Sea ranged from 187-1685 depending on the procedure, tuning and management areas used.

Integrated data analyses are becoming increasingly popular in studies of wild animal populations where two or more separate sources of data contain information about common parameters. Here we develop an integrated population model using abundance and demographic data from a study of common guillemots (Uria aalge) on the Isle of May, southeast Scotland. A state-space model for the count data is supplemented by three demographic time series (productivity and two mark-recapture-recovery (MRR)), enabling the estimation of prebreeder emigration rate - a parameter for which there is no direct observational data, and which is unidentifiable in the separate analysis of MRR data. A Bayesian approach using MCMC provides a flexible and powerful analysis framework. This model is extended to provide predictions of future population trajectories. Adopting random effects models for the survival and productivity parameters, we implement the MCMC algorithm to obtain a posterior sample of the underlying process means and variances (and population sizes) within the study period. Given this sample, we predict future demographic parameters, which in turn allows us to predict future population sizes and obtain the corresponding posterior distribution. Under the assumption that recent, unfavourable conditions persist in the future, we obtain a posterior probability of 70% that there is a population decline of >25% over a 10-year period. Lastly, using MRR data we test for spatial, temporal and age-related correlations in guillemot survival among three widely separated Scottish colonies that have varying overlap in nonbreeding distribution. We show that survival is highly correlated over time for colonies/age classes sharing wintering areas, and essentially uncorrelated for those with separate wintering areas. These results strongly suggest that one or more aspects of winter environment are responsible for spatiotemporal variation in survival of British guillemots, and provide insight into the factors driving multi-population dynamics of the species.