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Summary1. Conservation decision-makers face a trade-off between spending limited funds on direct management action, or gaining new information in an attempt to improve management performance in the future. Value-of-information analysis can help to resolve this trade-off by evaluating how much management performance could improve if new information was gained. Value-of-information analysis has been used extensively in other disciplines, but there are only a few examples where it has informed conservation planning, none of which have used it to evaluate the financial value of gaining new information. 2. We address this gap by applying value-of-information analysis to the management of a declining koala Phascolarctos cinereus population. Decision-makers responsible for managing this population face uncertainty about survival and fecundity rates, and how habitat cover affects mortality threats. The value of gaining new information about these uncertainties was calculated using a deterministic matrix model of the koala population to find the expected population growth rate if koala mortality threats were optimally managed under alternative model hypotheses, which represented the uncertainties faced by koala managers. 3. Gaining new information about survival and fecundity rates and the effect of habitat cover on mortality threats will do little to improve koala management. Across a range of management budgets, no more than 1Á7% of the budget should be spent on resolving these uncertainties. 4. The value of information was low because optimal management decisions were not sensitive to the uncertainties we considered. Decisions were instead driven by a substantial difference in the cost efficiency of management actions. The value of information was up to forty times higher when the cost efficiencies of different koala management actions were similar. 5. Synthesis and applications. This study evaluates the ecological and financial benefits of gaining new information to inform a conservation problem. We also theoretically demonstrate that the value of reducing uncertainty is highest when it is not clear which management action is the most cost efficient. This study will help expand the use of value-of-information analyses in conservation by providing a cost efficiency metric by which to evaluate research or monitoring.

Finding cost-effective management strategies to recover species declining due to multiple threats is challenging, especially when there are limited resources. Recent studies offer insights into how costs and threats can influence the best choice of management actions. However, when implementing management actions in the real-world, a range of impediments to management success often exist that can be driven by social, technological and land-use factors. These impediments may limit the extent to which we can achieve recovery objectives and influence the optimal choice of management actions. Nonetheless, the implications of these impediments are not well understood, especially for recovery planning involving multiple actions. We used decision theory to assess the impact of these types of impediments for allocating resources among recovery actions to mitigate multiple threats. We applied this to a declining koala (Phascolarctos cinereus) population threatened by habitat loss, vehicle collisions, dog attacks and disease. We found that the unwillingness of dog owners to restrain their dogs at night (a social impediment), the effectiveness of wildlife crossings to reduce vehicle collisions (a technological impediment) and the unavailability of areas for restoration (a land-use impediment) significantly reduced the effectiveness of our actions. In the presence of these impediments, achieving successful recovery may be unlikely. Further, these impediments influenced the optimal choice of recovery actions, but the extent to which this was true depended on the target koala population growth rate. Given that species recovery is an important strategy for preserving biodiversity, it is critical that we consider how impediments to the success of recovery actions modify our choice of actions. In some cases, it may also be worth considering whether investing in reducing or removing impediments may be a cost-effective course of action.

Time is of the essence in conservation biology. To secure the persistence of a species, we need to understand how to balance time spent among different management actions. A new and simple method to test the efficacy of a range of conservation actions is required. Thus, we devised a general theoretical framework to help determine whether to test a new action and when to cease a trial and revert to an existing action if the new action did not perform well. The framework involves constructing a general population model under the different management actions and specifying a management objective. By maximizing the management objective, we could generate an analytical solution that identifies the optimal timing of when to change management action. We applied the analytical solution to the case of the Christmas Island pipistrelle bat (Pipistrelle murrayi), a species for which captive breeding might have prevented its extinction. For this case, we used our model to determine whether to start a captive breeding program and when to stop a captive breeding program and revert to managing the species in the wild, given that the management goal is to maximize the chance of reaching a target wild population size. For the pipistrelle bat, captive breeding was to start immediately and it was desirable to place the species in captivity for the entire management period. The optimal time to revert to managing the species in the wild was driven by several key parameters, including the management goal, management time frame, and the growth rates of the population under different management actions. Knowing when to change management actions can help conservation managers' act in a timely fashion to avoid species extinction.

Currently, there are insufficient resources available across the world to secure all threatened species. In the past decade there has been increasing research in the field of resource allocation for conservation actions. Deciding how to allocate resources optimally poses a challenging problem that is difficult to solve due to a multitude of complexities associated with each action. This requires us to solve the problem using a multidisciplinary framework. The research in this thesis is about addressing resource allocation problems using a decision theory framework. Specifically, we answer the general question about how much resource (time and money) we should allocate among multiple interacting management actions. In chapter 2, we address the question of how social, technological and habitat limitations affect the allocation of money among multiple management actions to mitigate multiple threats. We examine this question using an example of the koala inhabiting the Koala Coast that is limited by constraints: the unwillingness of owners to enclose their dogs a night (social limitations), the effectiveness of road crossing structures (technological limitations) and the amount of suitable koala habitat available for restoration (habitat limitations). Using numerical optimisation, we found the best management option for any budget but we also found that that these limitations significantly reduce the effectiveness of management. Thus, it reduces our ability to achieve a stable population growth rate. The only plausible alternative is to find ways to alleviate these limitations. In chapter 3, we addressed the question of how several key ecological variables influences the amount of resources (time and money) we spend on monitoring a population that we could be managing. Using a simulation model we examined how several demographic parameters influence the optimal monitoring strategy. We found that the amount of time one should spend on monitoring before translocating a population should increase as the unmanaged population growth rate or the initial population size increases. The optimal amount of money to invest in annual monitoring increases as the uncertainty associated with the wild or captive population growth rate, or the initial population size, increases. In chapter 4, we considered the question of whether or not we should abandon our current population management strategy with reliable outcomes, or if we try a new and uncertain strategy, for how long should we pursue that new strategy before reverting to the old strategy. To do this, we uncovered an analytical solution to help us decide when to cease a new action before reverting back to an existing action. We applied this theory to the conservation management of the Christmas 3 Island Pipistrelle, where existing actions appear to have failed and a new strategy, captive breeding, might have secured the species. Our model revealed the time at which we should stop captive breeding before releasing animals back into the wild. We found that the optimal switching ...