What is a Good Calibration Question?

Weighted aggregation of expert judgments based on their performance on calibration questions may improve mathematically aggregated judgments relative to equal weights. However, obtaining validated, relevant calibration questions can be difficult. If so, should analysts settle for equal weights? Or should they use calibration questions that are easier to obtain but less relevant? In this article, we examine what happens to the out-of-sample performance of weighted aggregations of the classical model (CM) compared to equal weighted aggregations when the set of calibration questions includes many so-called "irrelevant" questions, those that might ordinarily be considered to be outside the domain of the questions of interest. We find that performance weighted aggregations outperform equal weights on the combined CM score, but not on statistical accuracy (i.e., calibration). Importantly, there was no appreciable difference in performance when weights were developed on relevant versus irrelevant questions. Experts were unable to adapt their knowledge across vastly different domains, and in-sample validation did not accurately predict out-of-sample performance on irrelevant questions. We suggest that if relevant calibration questions cannot be found, then analysts should use equal weights, and draw on alternative techniques to improve judgments. Our study also indicates limits to the predictive accuracy of performance weighted aggregation, and the degree to which expertise can be adapted across domains. We note limitations in our study and urge further research into the effect of question type on the reliability of performance weighted aggregations.

Strengthening conservation science as a crisis discipline by addressing challenges of precaution, privilege, and individualism.

Conservation science deals with crises and supports policy interventions devised to mitigate highly uncertain threats that pose irreversible harm. When conventional policy tools, such as quantitative risk assessments, are insufficient, the precautionary principle provides a practical framework and range of robust heuristics. Yet, precaution is often resisted in many policy arenas, especially those involving powerful self-interests, and this resistance is compounded by structures of privilege and competitive individualism in science. We describe key drivers and effects of such resistance in conservation science. These include a loss of rigor under uncertainty, an erosion of crisis response capabilities, and a further reinforcement of privileged interests in conservation politics. We recommend open acknowledgement of the pressures exerted by power inside science; greater recognition for the value of the precautionary principle under uncertainty; deliberate measures to resist competitive individualism; support for blind review, open science, and data sharing; and a shift from hierarchical multidisciplinarity toward more egalitarian transdisciplinarity to accelerate advances in conservation science. Article impact statement: Precautionary principle, privilege structures among disciplines, and culture of individualism link to effective conservation policy making.

Fortalecimiento de las Ciencias de la Conservación como Disciplinas de Crisis Resumen Las ciencias de la conservación tratan con crisis y respaldan a muchas intervenciones políticas para mitigar las amenazas altamente inciertas que representan un daño irreversible. El principio de precaución proporciona un marco práctico y una gama de heurística sólida cuando son insuficientes las herramientas convencionales de políticas como las evaluaciones cuantitativas de riesgo. Aun así, con frecuencia se niega el uso de la precaución en muchas arenas políticas, especialmente en aquellas que involucran intereses propios de mucho poder, y esta negación se agrava con las estructuras de privilegio y el individualismo competitivo presentes en la ciencia. Describimos los factores y efectos clave de dicha resistencia en las ciencias de la conservación. Estos incluyen la pérdida del rigor bajo la incertidumbre, un desgaste de las capacidades de respuesta a la crisis y un reforzamiento más profundo de los intereses privilegiados en las políticas de conservación. Recomendamos que se realice una aceptación abierta de las presiones ejercidas por el poder dentro de la ciencia; un mayor reconocimiento del valor del principio de precaución bajo la incertidumbre; que se lleven a cabo medidas deliberadas para oponerse al individualismo competitivo; que se apoye a las revisiones a ciegas, la ciencia abierta y la difusión de datos; y que se realice un cambio de la multidisciplinariedad jerárquica a una transdisciplinariedad más igualitaria para acelerar los avances dentro de las ciencias de la conservación.

Weighting and aggregating expert ecological judgments.

Performance weighted aggregation of expert judgments, using calibration questions, has been advocated to improve pooled quantitative judgments for ecological questions. However, there is little discussion or practical advice in the ecological literature regarding the application, advantages or challenges of performance weighting. In this paper we (1) illustrate how the IDEA protocol with four-step question format can be extended to include performance weighted aggregation from the Classical Model, and (2) explore the extent to which this extension improves pooled judgments for a range of performance measures. Our case study demonstrates that performance weights can improve judgments derived from the IDEA protocol with four-step question format. However, there is no a-priori guarantee of improvement. We conclude that the merits of the method lie in demonstrating that the final aggregation of judgments provides the best representation of uncertainty (i.e., validation), whether that be via equally weighted or performance weighted aggregation. Whether the time and effort entailed in performance weights can be justified is a matter for decision-makers. Our case study outlines the rationale, challenges, and benefits of performance weighted aggregations. It will help to inform decisions about the deployment of performance weighting and avoid common pitfalls in its application.

Protecting biodiversity and economic returns in resource-rich tropical forests.

In pursuit of socioeconomic development, many countries are expanding oil and mineral extraction into tropical forests. These activities seed access to remote, biologically rich areas, thereby endangering global biodiversity. Here we demonstrate that conservation solutions that effectively balance the protection of biodiversity and economic revenues are possible in biologically valuable regions. Using spatial data on oil profits and predicted species and ecosystem extents, we optimise the protection of 741 terrestrial species and 20 ecosystems of the Ecuadorian Amazon, across a range of opportunity costs (i.e. sacrifices of extractive profit). For such an optimisation, giving up 5% of a year's oil profits (US$ 221 million) allows for a protected area network that retains of an average of 65% of the extent of each species/ecosystem. This performance far exceeds that of the network produced by simple land area optimisation which requires a sacrifice of approximately 40% of annual oil profits (US$ 1.7 billion), and uses only marginally less land, to achieve equivalent levels of ecological protection. Applying spatial statistics to remotely sensed, historic deforestation data, we further focus the optimisation to areas most threatened by imminent forest loss. We identify Emergency Conservation Targets: areas that are essential to a cost-effective conservation reserve network and at imminent risk of destruction, thus requiring urgent and effective protection. Governments should employ the methods presented here when considering extractive led development options, to responsibly manage the associated ecological-economic trade-offs and protect natural capital. Article Impact Statement: Governments controlling resource extraction from tropical forests can arrange production and conservation to retain biodiversity and profits. This article is protected by copyright. All rights reserved.

The Value of Performance Weights and Discussion in Aggregated Expert Judgments.

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.

Metaresearch for Evaluating Reproducibility in Ecology and Evolution.

Recent replication projects in other disciplines have uncovered disturbingly low levels of reproducibility, suggesting that those research literatures may contain unverifiable claims. The conditions contributing to irreproducibility in other disciplines are also present in ecology. These include a large discrepancy between the proportion of "positive" or "significant" results and the average statistical power of empirical research, incomplete reporting of sampling stopping rules and results, journal policies that discourage replication studies, and a prevailing publish-or-perish research culture that encourages questionable research practices. We argue that these conditions constitute sufficient reason to systematically evaluate the reproducibility of the evidence base in ecology and evolution. In some cases, the direct replication of ecological research is difficult because of strong temporal and spatial dependencies, so here, we propose metaresearch projects that will provide proxy measures of reproducibility.

Clarifying values, risk perceptions, and attitudes to resolve or avoid social conflicts in invasive species management.

Decision makers and researchers recognize the need to effectively confront the social dimensions and conflicts inherent to invasive species research and management. Yet, despite numerous contentious situations that have arisen, no systematic evaluation of the literature has examined the commonalities in the patterns and types of these emergent social issues. Using social and ecological keywords, we reviewed trends in the social dimensions of invasive species research and management and the sources and potential solutions to problems and conflicts that arise around invasive species. We integrated components of cognitive hierarchy theory and risk perceptions theory to provide a conceptual framework to identify, distinguish, and provide understanding of the driving factors underlying disputes associated with invasive species. In the ISI Web of Science database, we found 15,915 peer-reviewed publications on biological invasions, 124 of which included social dimensions of this phenomenon. Of these 124, 28 studies described specific contentious situations. Social approaches to biological invasions have emerged largely in the last decade and have focused on both environmental social sciences and resource management. Despite being distributed in a range of journals, these 124 articles were concentrated mostly in ecology and conservation-oriented outlets. We found that conflicts surrounding invasive species arose based largely on differences in value systems and to a lesser extent stakeholder and decision maker's risk perceptions. To confront or avoid such situations, we suggest integrating the plurality of environmental values into invasive species research and management via structured decision making techniques, which enhance effective risk communication that promotes trust and confidence between stakeholders and decision makers.

Voting systems for environmental decisions.

Voting systems aggregate preferences efficiently and are often used for deciding conservation priorities. Desirable characteristics of voting systems include transitivity, completeness, and Pareto optimality, among others. Voting systems that are common and potentially useful for environmental decision making include simple majority, approval, and preferential voting. Unfortunately, no voting system can guarantee an outcome, while also satisfying a range of very reasonable performance criteria. Furthermore, voting methods may be manipulated by decision makers and strategic voters if they have knowledge of the voting patterns and alliances of others in the voting populations. The difficult properties of voting systems arise in routine decision making when there are multiple criteria and management alternatives. Because each method has flaws, we do not endorse one method. Instead, we urge organizers to be transparent about the properties of proposed voting systems and to offer participants the opportunity to approve the voting system as part of the ground rules for operation of a group.

General rules for managing and surveying networks of pests, diseases, and endangered species.

The efficient management of diseases, pests, or endangered species is an important global issue faced by agencies constrained by limited resources. The management challenge is even greater when organisms are difficult to detect. We show how to prioritize management and survey effort across time and space for networks of susceptible-infected-susceptible subpopulations. We present simple and robust rules of thumb for protecting desirable, or eradicating undesirable, subpopulations connected in typical network patterns (motifs). We further demonstrate that these rules can be generalized to larger networks when motifs are combined in more complex formations. Results show that the best location to manage or survey a pest or a disease on a network is also the best location to protect or survey an endangered species. The optimal starting point in a network is the fastest motif to manage, where line, star, island, and cluster motifs range from fast to slow. Managing the most connected node at the right time and maintaining the same management direction provide advantages over previously recommended outside-in strategies. When a species or disease is not detected and our belief in persistence decreases, our results recommend shifting resources toward management or surveillance of the most connected nodes. Our analytic approximation provides guidance on how long we should manage or survey networks for hard-to-detect organisms. Our rules take into account management success, dispersal, economic cost, and imperfect detection and offer managers a practical basis for managing networks relevant to many significant environmental, biosecurity, and human health issues.

Addressing a critique of the TEASI framework for invasive species risk assessment.

We address criticism that the Transport, Establishment, Abundance, Spread, Impact (TEASI) framework does not facilitate objective mapping of risk assessment methods nor defines best practice. We explain why TEASI is appropriate for mapping, despite inherent challenges, and how TEASI offers considerations for best practices, rather than suggesting one best practice.

Predicting and reasoning about replicability using structured groups.

This paper explores judgements about the replicability of social and behavioural sciences research and what drives those judgements. Using a mixed methods approach, it draws on qualitative and quantitative data elicited from groups using a structured approach called the IDEA protocol ('investigate', 'discuss', 'estimate' and 'aggregate'). Five groups of five people with relevant domain expertise evaluated 25 research claims that were subject to at least one replication study. Participants assessed the probability that each of the 25 research claims would replicate (i.e. that a replication study would find a statistically significant result in the same direction as the original study) and described the reasoning behind those judgements. We quantitatively analysed possible correlates of predictive accuracy, including self-rated expertise and updating of judgements after feedback and discussion. We qualitatively analysed the reasoning data to explore the cues, heuristics and patterns of reasoning used by participants. Participants achieved 84% classification accuracy in predicting replicability. Those who engaged in a greater breadth of reasoning provided more accurate replicability judgements. Some reasons were more commonly invoked by more accurate participants, such as 'effect size' and 'reputation' (e.g. of the field of research). There was also some evidence of a relationship between statistical literacy and accuracy.

TEASIng apart alien species risk assessments: a framework for best practices.

Some alien species cause substantial impacts, yet most are innocuous. Given limited resources, forecasting risks from alien species will help prioritise management. Given that risk assessment (RA) approaches vary widely, a synthesis is timely to highlight best practices. We reviewed quantitative and scoring RAs, integrating > 300 publications into arguably the most rigorous quantitative RA framework currently existing, and mapping each study onto our framework, which combines Transport, Establishment, Abundance, Spread and Impact (TEASI). Quantitative models generally measured single risk components (78% of studies), often focusing on Establishment alone (79%). Although dominant in academia, quantitative RAs are underused in policy, and should be made more accessible. Accommodating heterogeneous limited data, combining across risk components, and developing generalised RAs across species, space and time without requiring new models for each species may increase attractiveness for policy applications. Comparatively, scoring approaches covered more risk components (50% examined > 3 components), with Impact being the most common component (87%), and have been widely applied in policy (> 57%), but primarily employed expert opinion. Our framework provides guidance for questions asked, combining scores and other improvements. Our risk framework need not be completely parameterised to be informative, but instead identifies opportunities for improvement in alien species RA.

Decision making in a human population living sustainably.

The Tiwi people of northern Australia have managed natural resources continuously for 6000-8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision-making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long-term sustainability of environmental use. We examined the Tiwi decision-making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes.

Eliciting expert knowledge in conservation science.

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Allocating surveillance resources to reduce ecological invasions: maximizing detections and information about the threat.

Allocating resources to detect invasive pests, diseases, and pathogens on exposure pathways requires a trade-off between the need to detect as many contaminated items as possible and the need to acquire knowledge about contamination rates. We develop a model and an algorithm that provide guidance for the allocation of inspection resources across multiple dynamic pathways in cases where not every item can be inspected. The model uses a null hypothesis that the contamination rate of a pathway is above a specified level: a risk cutoff. Pathways with a risk above the cutoff are fully inspected, and those with a risk below the cutoff level are monitored at a rate that would detect a change of the risk to being above the cutoff level with high probability. We base our decision on the 95% upper confidence limit for the contamination rate. We demonstrate via simulations and a data set that focusing inspection resources on specific pathways can result in substantially more effective intervention, and that the reduction in overall effectiveness of monitoring low-risk pathways need not be substantial. Use of the model demands the selection of the risk cutoff, and this limit can be set according to projected consequences.

Traits explain invasion of alien plants into tropical rainforests.

1. The establishment of new botanic gardens in tropical regions highlights a need for weed risk assessment tools suitable for tropical ecosystems. The relevance of plant traits for invasion into tropical rainforests has not been well studied.2. Working in and around four botanic gardens in Indonesia where 590 alien species have been planted, we estimated the effect of four plant traits, plus time since species introduction, on: (a) the naturalization probability and (b) abundance (density) of naturalized species in adjacent native tropical rainforests; and (c) the distance that naturalized alien plants have spread from the botanic gardens.3. We found that specific leaf area (SLA) strongly differentiated 23 naturalized from 78 non-naturalized alien species (randomly selected from 577 non-naturalized species) in our study. These trends may indicate that aliens with high SLA, which had a higher probability of naturalization, benefit from at least two factors when establishing in tropical forests: high growth rates and occupation of forest gaps. Naturalized aliens had high SLA and tended to be short. However, plant height was not significantly related to species' naturalization probability when considered alongside other traits.4. Alien species that were present in the gardens for over 30 years and those with small seeds also had higher probabilities of becoming naturalized, indicating that garden plants can invade the understorey of closed canopy tropical rainforests, especially when invading species are shade tolerant and have sufficient time to establish.5. On average, alien species that were not animal dispersed spread 78 m further into the forests and were more likely to naturalize than animal-dispersed species. We did not detect relationships between the measured traits and estimated density of naturalized aliens in the adjacent forests.6. Synthesis: Traits were able to differentiate alien species from botanic gardens that naturalized in native forest from those that did not; this is promising for developing trait-based risk assessment in the tropics. To limit the risk of invasion and spread into adjacent native forests, we suggest tropical botanic gardens avoid planting alien species with fast carbon capture strategies and those that are shade tolerant.

Resource allocation for efficient environmental management.

Environmental managers must decide how to invest available resources. Researchers have previously determined how to allocate conservation resources among regions, design nature reserves, allocate funding to species conservation programs, design biodiversity surveys and monitoring programs, manage species and invest in greenhouse gas mitigation schemes. However, these issues have not been addressed with a unified theory. Furthermore, uncertainty is prevalent in environmental management, and needs to be considered to manage risks. We present a theory for optimal environmental management, synthesizing previous approaches to the topic and incorporating uncertainty. We show that the theory solves a diverse range of important problems of resource allocation, including distributing conservation resources among the world's biodiversity hotspots; surveillance to detect the highly pathogenic avian influenza H5N1 virus in Thailand; and choosing survey methods for the insect order Hemiptera. Environmental management decisions are similar to decisions about financial investments, with trade-offs between risk and reward.