School of Botany - Theses
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ItemDecision analysis for threatened species management across the captive-wild spectrum( 2015)Programs for the recovery of threatened species increasingly involve active management of variable intensity, such as captive breeding, reintroduction and translocation. Managers of such programs thus need to make decisions about whether and how to implement a given type of management, usually in the face of uncertainty and constraints. Structured decision making provides decision makers with a theoretical framework and practical methods to make rational decisions under uncertainty. In this thesis, I investigate how different principles and tools of structured decision making can assist decisions in threatened species management. The fundamental decision problems in threatened species management concern whether and how to implement a given type of management for the target species. In Chapter 2, I examine the case of whether the conservation of a species should incorporate ex-situ management, using the recovery plan for an endangered frog species in south-eastern Australia as an example. I demonstrate that this question can only be answered rationally after determining how the ex-situ component will benefit the overarching objectives of the recovery plan. This logical sequence of decisions (how before whether) is however followed only infrequently in real-world conservation. I illustrate how managers can implement it with the aid of decision trees and multi-criteria decision analysis. Since decisions are aimed at achieving objectives, they necessarily reflect the values and preferences of stakeholders. Using value functions, in Chapter 2 I demonstrate how the optimal decision depends on the relative importance attributed to different objectives (for example, maximising the probability of persistence of the target species and meeting budget limitations). In Chapter 3, I expand this analysis to demonstrate how to account for the attitude of decision makers towards the risk of negative outcomes. I use two case studies of recovery plans for threatened frog species to illustrate the application of stochastic dominance, a useful method to rank alternative actions in the face of uncertainty and risk. Structured decision making provides methods to make decisions under uncertainty. However, in some instances reducing the existing uncertainty by collecting additional information can allow more robust decisions. As a result, managers of threatened species programs almost always advocate further research, in the expectation that it will improve the outcomes of management. In Chapter 4, I apply a formal method to calculate the expected benefit of additional information to two examples in threatened species management. I demonstrate how the value of information is a function of the current knowledge, by the potential to react to new information, and by the effectiveness of the learning process. Value of information analysis can help managers determine whether and how to implement experiments and monitoring programs to improve the ultimate outcomes of management. For several threatened species programs, the scale and speed of the threatening processes often require decisions to be made immediately, leaving no time for formal experimental learning. Adaptive management describes a specific case of structured decision making in which managers learn by monitoring the outcomes of management and adjust actions accordingly. In Chapter 5, I analyse the conditions and challenges that exist to the application of adaptive management in threatened species programs. The temporal scale of such programs is often sufficient to allow managers to collect information and react by updating actions in subsequent time steps. Particularly for programs toward the captive end of the management spectrum, controlled conditions are also favourable for effective learning. Adaptive management requires the ability to clearly structure uncertainty into formal hypotheses, to allow effective and focused monitoring that addresses the most important sources of uncertainty. Most importantly, institutions and stakeholders must be committed and capable of implementing learning. For clearly defined decision problems, structured decision making can draw upon a range of technical approaches to determine optimal management strategies. In Chapter 6, I consider a reintroduction program in which management decisions are complicated by the complex life history of the target species and budget constraints. I combine demographic modelling and cost-effectiveness analysis to identify the optimal rates of translocation between captive and wild populations. This thesis illustrates how the iterative cycle of structured decision making can benefit all stages of the design of management strategies for threatened species conservation. First, it can help managers in thinking clearly about the decision problem, allowing a transparent assessment of subjective preferences and value. It can then ensure an objective evaluation of the available management alternatives, using qualitative or quantitative predictive approaches that explicitly recognise uncertainty. Finally, it can assist in finding solutions to trade-offs and incorporating additional knowledge to allow better decisions.