Incorporating collateral information using an adaptive management framework for the regulation of transgenic crops:

"A lack of data often makes biological management decisions difficult and has been an area of contention in the debate over the approval of transgenic crops. Our knowledge of agricultural and natural systems is limited and our ability to gain additional information, quickly and effectively, is often handicapped by statistical complexity. To adequately cope with this requires new approaches and models that integrate decision-making and management. This paper describes one possible approach to the integration of decision-making and management, which may have application for the regulatory approval of transgenic crops. In many situations countries wishing to approve transgenic crops will have limited data on the environmental performance of the crop. The approach outlined in this paper looks at how related information, possibly collected from other countries, might be used to help inform decisions about the approval of transgenic crops. This is done within an integrated decision-making and management framework." Authors' AbstractTransgenic plants, Collateral data, Bayesian theory, Inference,

Can groups improve expert economic and financial forecasts?

Economic and financial forecasts are important for business planning and government policy but are notoriously challenging. We take advantage of recent advances in individual and group judgement, and a data set of economic and financial forecasts compiled over 25 years, consisting of multiple individual and institutional estimates, to test the claim that nominal groups will make more accurate economic and financial forecast than individuals. We validate the forecasts using the subsequent published (real) outcomes, explore the performance of nominal groups against institutions, identify potential superforecasters and discuss the benefits of implementing structured judgment techniques to improve economic and financial forecasts

Improving expert forecasts in reliability. Application and evidence for structured elicitation protocols

Quantitative expert judgementsare used in reliability assessmentsto informcritically important decisions. Structured elicitation protocols have been advocated to improveexpert judgements, yet their application in reliability ischallenged by a lack of examples or evidence that they improve judgements. This paper aims to overcome these barriers. We present a case study where two world-leading protocols, the IDEA protocol and the Classical Model were combined and applied by the Australian Department of Defence for a reliability assessment. We assess the practicality of the methods, and the extent to which they improve judgements. The average expert was extremely overconfident, with 90% credible intervals containing the true realisation 36% of the time. However,steps contained inthe protocols substantially improvedjudgements. In particular, an equal weighted aggregation of individual judgements, and the inclusion ofa discussion phase and revised estimate helped to improve calibration, statistical accuracy and the Classical Model score. Further improvements in precision and information were made via performance weighted aggregation. This paper provides useful insights into the application of structured elicitation protocols for reliability andthe extent to which judgements are improved. The findings raise concerns about existing practices for utilising experts in reliability assessments and suggest greater adoption of structured protocols is warranted. We encourage the reliability community to further develop examples and insights

The value of performance weights and discussion in aggregated expert judgements

In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance‐based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics

Limits To The Use Of Threatened Species Lists

Threatened species lists are designed primarily to provide an easily understood qualitative estimate of risk of extinction. Although these estimates of risk can be accurate, the lists have inevitably become linked to several decision-making processes. There are four ways in which such lists are commonly used: to set priorities for resource allocation for species recovery; to inform reserve system design; to constrain development and exploitation; and to report on the state of the environment. The lists were not designed for any one of these purposes, and consequently perform some of them poorly. We discuss why, if and how they should be used to achieve these purposes

Treatment of uncertainty in conservation under climate change

Climate change is an important threat to biodiversity globally, but there are major uncertainties associated with its magnitude and ecological consequences. Here, we investigate how three major classes of uncertainty, linguistic uncertainty, epistemic uncertainty (uncertainty about facts) and human decision uncertainty, have been accounted for in scientific literature about climate change. Some sources of uncertainty are poorly characterized and epistemic uncertainty is much more commonly treated than linguistic or human decision uncertainty. Furthermore, we show that linguistic and human decision uncertainties are relatively better treated in the literature on socio-politics or economics than in natural sciences, which often overlook communication between stakeholders and socio-economic consequences. As uncertainty can significantly influence implementation of conservation, we discuss uncertainties associated with some commonly proposed conservation adaptation actions to mitigate climate change. There may be major differences between strategies, with implications on how they should be viewed in conservation planning. We conclude that evaluating conservation strategies in terms of different types of uncertainty will facilitate communication between disciplines and stakeholders. While accounting for uncertainties in a quantitative manner is difficult and data-demanding, even qualitative appreciation about the uncertainties inherent in conservation strategies can facilitate and improve decision making.Peer reviewe