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,

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

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

The treatment of uncertainty and the structure of the IUCN threatened species categories

Abstract The classi®cation of species with respect to their conservation status using the IUCN criteria is an important process in many countries, providing a guide for setting conservation priorities. Recent advances have resulted in several approaches to dealing with uncertainty in data used to classify species. These methods demand an unambiguous and transparent logical structure for the criteria. We suggest some changes to the ways in which the criteria are represented that correct an unnecessary inconsistency and which may serve to avoid important errors when uncertainty in the data is considered explicitly.

Expert Status and Performance

Expert judgements are essential when time and resources are stretched or we face novel dilemmas requiring fast solutions. Good advice can save lives and large sums of money. Typically, experts are defined by their qualifications, track record and experience [1], [2]. The social expectation hypothesis argues that more highly regarded and more experienced experts will give better advice. We asked experts to predict how they will perform, and how their peers will perform, on sets of questions. The results indicate that the way experts regard each other is consistent, but unfortunately, ranks are a poor guide to actual performance. Expert advice will be more accurate if technical decisions routinely use broadly-defined expert groups, structured question protocols and feedback

Expertise in research integration and implementation for tackling complex problems: when is it needed, where can it be found and how can it be strengthened?

© 2020, The Author(s). Expertise in research integration and implementation is an essential but often overlooked component of tackling complex societal and environmental problems. We focus on expertise relevant to any complex problem, especially contributory expertise, divided into ‘knowing-that’ and ‘knowing-how.’ We also deal with interactional expertise and the fact that much expertise is tacit. We explore three questions. First, in examining ‘when is expertise in research integration and implementation required?,’ we review tasks essential (a) to developing more comprehensive understandings of complex problems, plus possible ways to address them, and (b) for supporting implementation of those understandings into government policy, community practice, business and social innovation, or other initiatives. Second, in considering ‘where can expertise in research integration and implementation currently be found?,’ we describe three realms: (a) specific approaches, including interdisciplinarity, transdisciplinarity, systems thinking and sustainability science; (b) case-based experience that is independent of these specific approaches; and (c) research examining elements of integration and implementation, specifically considering unknowns and fostering innovation. We highlight examples of expertise in each realm and demonstrate how fragmentation currently precludes clear identification of research integration and implementation expertise. Third, in exploring ‘what is required to strengthen expertise in research integration and implementation?,’ we propose building a knowledge bank. We delve into three key challenges: compiling existing expertise, indexing and organising the expertise to make it widely accessible, and understanding and overcoming the core reasons for the existing fragmentation. A growing knowledge bank of expertise in research integration and implementation on the one hand, and accumulating success in addressing complex societal and environmental problems on the other, will form a virtuous cycle so that each strengthens the other. Building a coalition of researchers and institutions will ensure this expertise and its application are valued and sustained

Avoiding Costly Conservation Mistakes: The Importance of Defining Actions and Costs in Spatial Priority Setting

Background: The typical mandate in conservation planning is to identify areas that represent biodiversity targets within the smallest possible area of land or sea, despite the fact that area may be a poor surrogate for the cost of many conservation actions. It is also common for priorities for conservation investment to be identified without regard to the particular conservation action that will be implemented. This demonstrates inadequate problem specification and may lead to inefficiency: the cost of alternative conservation actions can differ throughout a landscape, and may result in dissimilar conservation priorities