Terry Walshe

A Framework for Assessing and Managing Risks Posed by Emerging Diseases

Frameworks for analyzing the risks of emerging diseases and invasive species often have relied on unstructured estimates of likelihoods and consequences. We suggest a flexible alternative that offers more transparent analysis without need for additional data. Its strength lies in explicit and complementary treatment of technical and social judgments. We describe a system in which cognitive maps, Bayes nets, and multicriteria analysis can be used in tandem to structure a problem, identify exposure pathways, combine data and expert judgement to estimate the likelihoods, and assess consequences of alternative decisions. These tools may be employed in participatory settings or as part of standard regulatory practice. We illustrate this approach with an assessment of the management of an emerging disease that poses a hazard to Australia.

A dynamic hydrological Monte Carlo simulation model to inform decision-making at Lake Toolibin, Western Australia

Lake Toolibin, an ephemeral lake in the agricultural zone of Western Australia, is under threat from secondary salinity due to land clearance throughout the catchment. The lake is extensively covered with native vegetation and is a Ramsar listed wetland, being one of the few remaining significant migratory bird habitats in the region. Currently, inflow with salinity greater than 1000 mg/L TDS is diverted from the lake in an effort to protect sensitive lakebed vegetation. However, this conservative threshold compromises the frequency and extent of lake inundation, which is essential for bird breeding. It is speculated that relaxing the threshold to 5000 mg/L may pose negligible additional risk to the condition of lakebed vegetation. To characterise the magnitude of improvement in the provision of bird breeding habitat that might be generated by relaxing the threshold, a dynamic water and salt balance model of the lake was developed and implemented using Monte Carlo simulation. Results from best estimate model inputs indicate that relaxation of the threshold increases the likelihood of satisfying habitat requirements by a factor of 9.7. A second-order Monte Carlo analysis incorporating incertitude generated plausible bounds of [2.6, 37.5] around the best estimate for the relative likelihood of satisfying habitat requirements. Parameter-specific sensitivity analyses suggest the availability of habitat is most sensitive to pan evaporation, lower than expected inflow volume, and higher than expected inflow salt concentration. The characterisation of uncertainty associated with environmental variation and incertitude allows managers to make informed risk-weighted decisions.

Minimizing the cost of keeping options open for conservation in a changing climate

Policy documents advocate that managers should keep their options open while planning to protect coastal ecosystems from climate-change impacts. However, the actual costs and benefits of maintaining flexibility remain largely unexplored, and alternative approaches for decision making under uncertainty may lead to better joint outcomes for conservation and other societal goals. For example, keeping options open for coastal ecosystems incurs opportunity costs for developers. We devised a decision framework that integrates these costs and benefits with probabilistic forecasts for the extent of sea-level rise to find a balance between coastal ecosystem protection and moderate coastal development. Here, we suggest that instead of keeping their options open managers should incorporate uncertain sea-level rise predictions into a decision-making framework that evaluates the benefits and costs of conservation and development. In our example, based on plausible scenarios for sea-level rise and assuming a risk-neutral decision maker, we found that substantial development could be accommodated with negligible loss of environmental assets. Characterization of the Pareto efficiency of conservation and development outcomes provides valuable insight into the intensity of trade-offs between development and conservation. However, additional work is required to improve understanding of the consequences of alternative spatial plans and the value judgments and risk preferences of decision makers and stakeholders.

Identifying Objectives and Alternative Actions to Frame a Decision Problem

In this chapter, we discuss the role of objectives and alternative actions in framing a natural resource management decision problem, with particular attention to thresholds. We outline a number of considerations in developing objectives and measurable attributes, including when utility thresholds may be needed to express the decision-makers’ values. We also discuss the development of a set of alternative actions, and how these might give rise to decision thresholds, particularly when the predictive models contain ecological thresholds. Framing of a decision problem plays a central role in decision analysis because it helps determine the needs for a predictive ecological model, the type of solution method required, and the value and structure of a monitoring system.

Rewarding excellence and promoting improvement in higher education teaching in Australia

Current implementation of Australias Learning and Teaching Performance Fund rewards universities that demonstrate outstanding performance. This paper critically evaluates the capacity of the fund to promote improvement in learning and teaching. Analysis of past data describing institutional performance clearly shows that the rank order of universities has varied little over time. It is argued that this stability implies that incentive for investment in improved teaching and learning will be restricted to those universities that tend to score close to the funding threshold. An alternative approach to funding is advocated, involving graphical communication of trends in performance using control charts. The approach seeks to broaden incentives for better teaching and learning by explicitly, (a) acknowledging excellence in any one funding round, and (b) rewarding improvement in performance over time.

The National Marine Science Plan: informing Australia’s future ocean policy*

In 1998 the Australian Government released ‘Australia’s Ocean Policy: Caring, Understanding, Using Wisely’ (Environment Australia 1998a). The policy, released in the International Year of Oceans, recognised that our oceans contain resources of enormous past, present and future benefit to us all – resources that must be managed carefully to ensure economic benefit exists side by side with sensitive environmental care. This pioneering policy attempted to set a framework for integrated and ecosystem-based planning and management for all of Australia’s marine jurisdictions but lacked input and therefore buy-in from state and territory jurisdictions.

Accounting for environmental uncertainty in the management of dredging impacts using probabilistic dose–response relationships and thresholds

Summary 1.Dredging and related activities are common across nearshore marine environments, potentially threatening nearby ecosystems. Regulatory frameworks are essential for minimising environmental impacts, yet rely heavily on a sound understanding of how ecosystems will respond to environmental stressors, and the thresholds that delineate benign and harmful conditions. 2.Here we use novel statistical approaches and mathematical tools to account for uncertainty in deriving in-situ dose-response relationships and thresholds for the environmental management of dredging, based on estimates of the probability of non-zero mortality of corals during a dredging campaign at Barrow Island, Western Australia. Using modified receiver operating characteristic curves we derive thresholds with explicit Type I and Type II errors rates, across the full range of primary stress pathways and exposure dimensions (intensity, frequency and duration). 3.Monitoring coral health and mortality can be expensive and water quality indicators are often used to supplement direct receptor monitoring during dredging management. We found strong relationships between coral mortality and a range of water quality exposure metrics, lending support to the use of water quality metrics as management tools for protecting corals during dredging. Metrics based on sediment deposition were more statistically powerful than those based on either light or turbidity, but may be more difficult to implement in practice. Thresholds reflecting aversion to a false sense of security in environmental protection or aversion to the costs of false alarms varied substantially for all exposure metrics examined. 4.Synthesis and applications. Strategies for managing environmental harm under uncertainty are critical to achieving an informed risk-weighted balance between environmental protection outcomes and development costs. Our study demonstrates the complexities of how communities respond to variable environmental exposure across a range of pressures in time and space, and the value of integrating probabilistic approaches in environmental management to account for that complexity and its associated uncertainty. Coral mortality was strongly related to a range of water quality exposure metrics associated with dredging activities and regulatory thresholds based on water quality can provide a solid and cost-effective foundation for protecting corals during dredging. The probabilistic dose-response relationships and thresholds presented here are the first to be derived from in situ data using dredging related coral mortality and represent a step forward in integrating formal decision science approaches into environmental management. This article is protected by copyright. All rights reserved.

Eliciting improved quantitative judgements using the IDEA protocol: A case study in natural resource management

Introduction Natural resource management uses expert judgement to estimate facts that inform important decisions. Unfortunately, expert judgement is often derived by informal and largely untested protocols, despite evidence that the quality of judgements can be improved with structured approaches. We attribute the lack of uptake of structured protocols to the dearth of illustrative examples that demonstrate how they can be applied within pressing time and resource constraints, while also improving judgements. Aims and methods In this paper, we demonstrate how the IDEA protocol for structured expert elicitation may be deployed to overcome operational challenges while improving the quality of judgements. The protocol was applied to the estimation of 14 future abiotic and biotic events on the Great Barrier Reef, Australia. Seventy-six participants with varying levels of expertise related to the Great Barrier Reef were recruited and allocated randomly to eight groups. Each participant provided their judgements using the four-step question format of the IDEA protocol (‘Investigate’, ‘Discuss’, ‘Estimate’, ‘Aggregate’) through remote elicitation. When the events were realised, the participant judgements were scored in terms of accuracy, calibration and informativeness. Results and conclusions The results demonstrate that the IDEA protocol provides a practical, cost-effective, and repeatable approach to the elicitation of quantitative estimates and uncertainty via remote elicitation. We emphasise that i) the aggregation of diverse individual judgements into pooled group judgments almost always outperformed individuals, and ii) use of a modified Delphi approach helped to remove linguistic ambiguity, and further improved individual and group judgements. Importantly, the protocol encourages review, critical appraisal and replication, each of which is required if judgements are to be used in place of data in a scientific context. The results add to the growing body of literature that demonstrates the merit of using structured elicitation protocols. We urge decision-makers and analysts to use insights and examples to improve the evidence base of expert judgement in natural resource management.

Accounting for Uncertainty in Value Judgements when Applying Multi-Attribute Value Theory

In environmental decisions, analysts commonly face substantial uncertainties around stakeholders’ values judgments. Multi-Attribute Value Theory (MAVT), a family of multi-criteria decision analysis techniques, is applied in participative settings to articulate stakeholders’ values in decision-making. In MAVT, value judgments represent the intensity of individuals’ preferences in a set of objectives, which are operationalized as scaling factors or weights. Different sets of weights may express variation in people’s preferences or value judgments. Unfortunately, there are still important methodological gaps regarding how to incorporate uncertainty and the substantial variation commonly encountered in stakeholders’ preferences. This article presents a model of uncertainty that encompasses the dispersion of value judgments in MAVT. To achieve this goal, we draw on info-gap theory, which provides a mathematically grounded method for exploring sensitivity to preference weights when there are relatively high levels of uncertainties. We experimentally tested the uncertainty model in an environmental decision problem. We found that MAVT can use info-gap analysis to deal with multiple value judgments, avoiding exclusive reliance on nominal expected values to inform decisions. We explored a mechanism to explicitly consider the trade-offs between the performance of alternatives and the level of uncertainty that in any specified context a decision maker is willing to accept. Findings emphasize the potential of MAVT to support environmental management decisions, particularly in situations where multiple stakeholders and their contested value judgments have to be considered simultaneously to explore uncertainties around value trade-offs.

Declaring Eradication of an Invasive Species

Imperfect detection methods mean that it is difficult to tell whether a species is absent from a site or remains undetected. For this reason, the decision to conclude an eradication program and declare a species successfully eradicated is fraught with uncertainty (Morrison et al., 2007). There are two errors that can be made (Regan et al., 2006). First, if the species is declared eradicated when it is still present, its population could grow undetected, causing large economic and environmental damages. There are costs associated with reinitiating the eradication campaign and reducing the species’ population to a low level. Second, monitoring cannot continue indefinitely, and continuing to survey when a species has already been eradicated uses resources that could be better deployed elsewhere. This chapter reviews statistical models that can be used to quantify the certainty that a species has been successfully eradicated from a site. It then describes how to analyse logically the decision to declare eradication, considering the risks and consequences of getting it wrong.