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Title: Disease and demography in the Woodchester Park badger population
Author: McDonald, Jennifer Leslie
ISNI:       0000 0004 5346 7376
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2014
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The topic of badgers in the UK is often a contentious one, dividing opinions and sparking political debate. On one hand, badgers represent an important part of the British ecosystem but on the other a wildlife reservoir of disease implicated in the transmission of bovine tuberculosis (TB) to livestock in the UK. This has prompted strong interest in their population dynamics and epidemiology. Using data from a long-term study of a naturally infected badger population in Woodchester Park, Gloucestershire, this thesis explores a range of capture-mark-recapture (CMR) models to further understand disease and demographic processes. The first section examines long term population dynamics, simultaneously estimating demographic rates alongside their drivers using integrated population models (IPMs). The findings provide new insight into badger demography, highlighting density-dependent mechanisms, vulnerabilities to changing climate and disease prevalence and subsequently how multi-factorial analyses are required to explain fluctuating badger populations. The following sections use multistate models to answer pertinent questions regarding individual disease dynamics, revealing rates of TB infection, progression and disease-induced mortality. A key finding was sex-differences in disease response, with males more susceptible to TB infection. After applying a survival trajectory analysis we suggest sex differences are due to male immune defence deficiencies. A comparative analysis demonstrated similarities between epidemiological processes at Woodchester Park to an unconnected population of badgers from a vaccine study, supporting its continued use as a model population. The final study in this thesis constructs an IPM to estimate disease and population dynamics and in doing so uncovers disease-state recruitment allocation rates, demographic and population estimates of badgers in varying health-states and predicts future dynamics. This model aims to encapsulate the more commonly held notion of populations as dynamic entities with numerous co-occurring processes, opening up avenues for future analyses within both the badger-TB system and possible extensions to other wildlife reservoir populations.
Supervisor: Hodgson, Dave Sponsor: NERC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Bovine tuberculosis ; European badger ; state-dependent modelling ; survival ; wildlife disease ; Sex-differences ; disease ; Bayesian ; survival analysis ; Capture-mark-recapture