Australian mammals are amongst the most threatened in the world. Predation by invasive cats and foxes has driven many species to extinction, and has caused rapid declines and extirpation among others. Many Australian mammals now only persist in a small number of refugial populations of few individuals with a high risk of extinction from demographic population failure and catastrophic events. The persistence of many Australian mammal species now depends on continuous management, and the creation of new populations through translocations into predator controlled areas. Predator exclusion fences have become pivotal for effectively abating the predation threat for remnant populations and translocations. However, translocations are notoriously costly and failure prone, making it particularly important to identify protocols that maximize the likelihood of success. Thorough assessments are therefore required to improve outcomes, but knowledge to make them is often lacking. In this thesis, I address key knowledge gaps associated with translocation and predator management for Australian mammals, with particular regard to conservation fences.
In Chapter 2 I address the issue of uncertainty of the accuracy of habitat models. Reintroductions often rely on models to identify suitable habitat, and such modelling requires occurrence data from a representative sample of a species’ niche. However, the historic distributions of species that have subsequently declined are often poorly sampled. Therefore, we need to know how thoroughly a species’ historic distribution was sampled before habitat suitability models can be trusted. I propose and test a method for determining whether a species’ niche is well sampled pre-decline for Australian marsupials, by comparing accumulation curves of niche volume when data are arranged in forward and reverse chronological order. I found that accumulation curves can be used to test if a species’ niche is poorly sampled, and that poor association between chronologically and randomly arranged data implies an under sampled niche.
A good understanding of how translocated animals use the space within a fence is crucial in making choices about its size. In Chapter 3, I investigate the spatial use of woylies (Bettongia penicillata) a species of acute conservation concern at the Australian Wildlife Conservancy’s Scotia Sanctuary in the arid extreme of their known historic distribution. Using GPS tracking devices, I measured the movements of woylies in two adjacent fenced populations. The higher density population occupied foraging ranges similar in size to those previously reported (37ha) while woylies at lower density had homes ranges 2.5 times greater in size (96 ha). The woylies in the lower density population increased the size of their foraging range by covering more unique ground each evening, and spending more time further away from their nest. While the differences between the two populations are most likely related to density, it remains uncertain whether intraspecific competition or environmental stochasticity is the main driver of population differences. The example of Scotia Sanctuary demonstrates that stochastic variability in spatial requirements needs to be incorporated into translocation feasibility assessments.
In Chapter 4 I set about developing a framework for prioritizing new fenced translocation projects. Instead of the standard representation problem often used in conservation prioritisations, sites were instead prioritised using a population viability approach. This approach is far more appropriate given the inconsistent nature of threat listing for Australian mammals, and the crisis circumstances of Australian mammal populations. The approach also considers the conservation community’s priorities, capacity to act, and limitations of a decentralised network while using a complementarity framework. I demonstrated that under this framework, similar outcomes could be achieved 17 times more efficiently than an ad hoc approach, highlighting the utility of prioritisation frameworks in conservation fencing.
To many, the ultimate conservation goal for Australian mammals is to re-establish fully wild and unfenced populations. To achieve this, predators need to be managed effectively in a broader landscape. In Chapter 5 I investigated whether taking advantage of underlying ecological cycles could allow managers to improve conservation outcomes for a predator-affected mammal through poison baiting programs. Over the long term, implementation can range from consistent, maintained baiting programs to ad hoc, spontaneous pulses. I wanted to test if dynamic baiting schedules which varied in intensity in harmony with the El Niño Southern Oscillation (ENSO) cycle could improve overall cost-effectiveness. I modeled populations of rabbits (Oryctolagus cuniculus), foxes (Vulpes vulpes) and bilbies (Macrotis lagotis) in a semi-arid community across the duration of the ENSO cycle. I found that the system’s intrinsic stochasticy overshadowed the potential benefit of dynamic baiting. While modest savings can be made by avoiding baiting when predator populations are naturally deminished, the majority of conservation benefit comes from the amount of baiting, not the time or sequence of its application.
In sum, my thesis demonstrates that improvements in cost-effectiveness for management of Australian mammals could be made through systematic planning. By treating fenced translocations as a portfolio rather than a set of individual units, we can achieve significant improvements in outcomes, however, more widespread reporting of project costs and outcomes could greatly improve estimates of future recovery projects. Yet from an ecological perspective, the effects of environmental stochasticity particularly in multispecies translocations within fences, reduces our ability to explain project outcomes. While significant improvements to current practices could still be made through systematic planning, in stochastic systems, increased ecological knowledge may not equate to a capacity to improve management effectiveness.