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This thesis is presented as a collection of five papers and one report, each of which has been either published after peer review or submitted for publication. It covers a broad range of applied statistical methods, from deterministic modelling to integrated Bayesian modelling using MCMC, via bootstrapping and stochastic simulation. It also covers a broad range of subjects, from analysis of recreational fishing diaries, to genetic mark recapture for wombats. However, it focuses on practical applications of statistics to the management of wild populations. The first chapter (Hoyle and Jellyman 2002, published in Marine and Freshwater Research) applies a simple deterministic yield per recruit model to a fishery management problem: possible overexploitation of the New Zealand longfin eel. The chapter has significant implications for longfin eel fishery management. The second chapter (Hoyle and Cameron 2003, published in Fisheries Management and Ecology) focuses on uncertainty in the classical paradigm, by investigating the best way to estimate bootstrap confidence limits on recreational harvest and catch rate using catch diary data. The third chapter (Hoyle et al., in press with Molecular Ecology Notes) takes a different path by looking at genetic mark-recapture in a fisheries management context. Genetic mark-recapture was developed for wildlife abundance estimation but has not previously been applied to fish harvest rate estimation. The fourth chapter (Hoyle and Banks, submitted) addresses genetic mark-recapture, but in the wildlife context for estimates of abundance rather than harvest rate. Our approach uses individual-based modeling and Bayesian analysis to investigate the effect of shadows on abundance estimates and confidence intervals, and to provide guidelines for developing sets of loci for populations of different sizes and levels of relatedness. The fifth chapter (Hoyle and Maunder 2004, Animal Biodiversity and Conservation) applies integrated analysis techn