Infectious diseases are increasingly being recognised as significant threatening processes in conservation biology. Developing strategies to effectively manage infectious diseases in wildlife is, therefore, of the utmost importance to the maintenance of global biodiversity. The effective management of infectious diseases relies on understanding the ecology of the host, the epidemiological characteristics of the pathogen and the impacts of the pathogen on the host population. However, for most wildlife-disease systems this information remains poorly understood. This is particularly true for endangered species threatened by novel infectious agents as opportunities to observe and assess disease impacts and host-pathogen dynamics in the wild are limited. The Tasmanian devil (Sarcophilus harrisii), the world’s largest carnivorous marsupial, is threatened with extinction as a result of an epidemic of an emerging disease, a fatal infectious cancer known as Devil Facial Tumour Disease (DFTD). In this thesis I capitalised on a unique dataset from a population of Tasmanian devils where disease arrived part-way through an intensive longitudinal study, and utilised existing genetic samples collected prior to DFTD outbreak, to determine the impact of DFTD on the demography, population dynamics, genetic diversity and population genetic structure of wild Tasmanian devils. I then used this knowledge of the impacts of DFTD impacts in an unmanaged population to evaluate the effectiveness of a disease management trial involving the selective culling of infected individuals. I employed mark-recapture models to investigate the impact of DFTD on age-specific and sex-specific apparent survival rates, to examine the pattern of variation in infection rates (force of infection), and to investigate the impact of DFTD on population growth rate. I investigated demography, life-history traits and morphometric parameters of infected and uninfected individuals to determine the impacts of DFTD on age-structure and sex-structure, female fecundity and individual growth rates. I used this information to assess the population’s ability to respond to low population densities and to compensate for the detrimental impacts of DFTD. To determine the genetic consequences of disease-induced population decline I used microsatellite DNA to compare genetic diversity, population genetic structure and dispersal patterns in three Tasmanian devil populations prior to and following DFTD outbreaks. Capture-mark-recapture analyses revealed that the arrival of DFTD triggered an immediate decline in apparent survival rates of devils, the rate of which was predicted well by the increase in disease prevalence in the population over time. Transition rates of healthy individuals to the diseased class (the force of infection) increased in relation to disease prevalence, while the arrival of DFTD coincided with a marked and ongoing decline in the population growth rate. There was a significant change to the age structure following the arrival of DFTD. This shift to a younger population was caused by the loss of older individuals as a direct consequence of DFTD-driven declines in adult survival rates. Evidence of reproductive compensation in response to these disease impacts was observed via a reduction in the age of sexual maturity of females over time. However, widespread precocial breeding in devils was precluded by physiological and ecological constraints that limited the ability of one year olds to breed. Using temporally-replicated spatial genetic data, I found evidence of increased inbreeding following DFTD arrival and greater population genetic differentiation in post-disease populations. These changes appeared to be driven by a combination of selection and altered dispersal patterns of females in DFTD-affected populations. Comparison of demographic and epidemiological parameters indicative of disease progression and impact between the managed and unmanaged populations revealed that selective culling of infected individuals neither slowed the rate of disease progression nor reduced the population level impacts of this debilitating disease; with culling mortality simply compensating for disease mortality. This thesis provides one of the few direct empirical evaluations of the impact of an emerging wildlife disease epidemic on a wild population. This thesis revealed that infectious diseases can result in major demographic and genetic changes in host populations over relatively few generations and short time-scales. Results showing dramatic and ongoing population declines and very limited population compensation in DFTD-affected populations indicate that DFTD poses a significant extinction risk for wild devil populations. Hence, this study confirms that host-specific pathogens can pose a significant extinction risk for wild species, even in the absence of alternate reservoir hosts, a finding critical to our understanding of host-pathogen dynamics. My thesis also highlights the potential negative interplay between disease susceptibility and host genetic variability, which is of utmost importance to the management of novel wildlife epizootics and the conservation of threatened wildlife in general. The thorough understanding of the ecology and impacts of DFTD in the wild obtained in this study has provided a solid base from which to both rigorously assess the outcome of management strategies and also formulate recommendations for the management of this disease in the wild. The lack of evidence for successful control of the DFTD epidemic in a wild population during the first phase of a selective culling experimental adaptive management approach, points to the need to implement a multi-faceted disease management program when attempting to control a novel infectious disease in the wild. By drawing on the lessons learnt in this case study I show that it is possible to establish a set of general guidelines for the future management of infectious diseases in threatened wildlife.
Identifer | oai:union.ndltd.org:ADTP/279350 |
Creators | Shelly Lachish |
Source Sets | Australiasian Digital Theses Program |
Detected Language | English |
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