Publications
202 results found
Wintle BC, Smith ET, Bush M, et al., 2023, Predicting and reasoning about replicability using structured groups, ROYAL SOCIETY OPEN SCIENCE, Vol: 10, ISSN: 2054-5703
Fraser H, Bush M, Wintle BC, et al., 2023, Predicting reliability through structured expert elicitation with repliCATS (Collaborative Assessments for Trustworthy Science) process, PLoS One, Vol: 18, ISSN: 1932-6203
As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences. The utility of processes to predict replicability is their capacity to test scientific claims without the costs of full replication. Experimental data supports the validity of this process, with a validation study producing a classification accuracy of 84% and an Area Under the Curve of 0.94, meeting or exceeding the accuracy of other techniques used to predict replicability. The repliCATS process provides other benefits. It is highly scalable, able to be deployed for both rapid assessment of small numbers of claims, and assessment of high volumes of claims over an extended period through an online elicitation platform, having been used to assess 3000 research claims over an 18 month period. It is available to be implemented in a range of ways and we describe one such implementation. An important advantage of the repliCATS process is that it collects qualitative data that has the potential to provide insight in understanding the limits of generalizability of scientific claims. The primary limitation of the repliCATS process is its reliance on human-derived predictions with consequent costs in terms of participant fatigue although careful design can minimise these costs. The repliCATS process has potential applications in alternative peer review and in the allocation of effort for replication studies.
Burgman M, Chiaravalloti R, Fidler F, et al., 2023, A toolkit for open and pluralistic conservation science, Conservation Letters, Vol: 16, ISSN: 1755-263X
Conservation science practitioners seek to pre-empt irreversible impacts on species, ecosystems, and social-ecological systems, requiring efficient and timely action even when data and understanding are unavailable, incomplete, dated, or biased. These challenges are exacerbated by the scientific community's capacity to consistently distinguish between reliable and unreliable evidence, including the recognition of questionable research practices (QRPs, or ‘questionable practices’), which may threaten the credibility of research, including harming trust in well-designed and reliable scientific research. In this paper, we propose a ‘toolkit’ for open and pluralistic conservation science, highlighting common questionable practices and sources of bias and indicating where remedies for these problems may be found. The toolkit provides an accessible resource for anyone conducting, reviewing, or using conservation research, to identify sources of false claims or misleading evidence that arise unintentionally, or through misunderstandings or carelessness in the application of scientific methods and analyses. We aim to influence editorial and review practices and hopefully to remedy problems before they are published or deployed in policy or conservation practice.
Huan Y, Wang L, Burgman M, et al., 2022, A multi‐perspective composite assessment framework for prioritizing targets of sustainable development goals, Sustainable Development, Vol: 30, Pages: 833-847, ISSN: 0968-0802
The 17 Sustainable Development Goals (SDGs) and 169 targets proposed in 2015 are wide ranging and achieving them before 2030 may require extraordinarily high costs. Prioritizing a more manageable and logical sequence of SDGs targets based on national conditions is critical to reduce the complexity of SDGs, lower costs, ensure transitions are efficient, and accelerate implementation. Researchers have proposed a range of methods to rank the prioritizations of SDGs from different perspectives. Unfortunately, prioritizations of SDGs arising from different methods are not entirely consistent due to the limitations of each method. Therefore, an integrated methodological framework is required to reconcile these inconsistencies. To fill this research gap, we synthesized several methods to create a new composite assessment framework to prioritize SDGs targets. The framework consists of assessment models from three perspectives, including the impact of targets in a network composed of the interactions between targets, the gap between the targets' current and ideal performances, and the urgency of improving participation by government and society in achieving the targets. We then tested the effectiveness of this assessment framework empirically by ranking prioritizations for six targets of SDG 6 (clean water and sanitation) in Southeast Asia. Empirical results show that target 6.5 has the highest priority, followed by targets 6.4 and 6.6, while the lowest ranking target is 6.1. Finally, we outlined the advantages and limitations of each assessment method to assist stakeholders in using and broadening this composite assessment framework in the future.
Tiernan H, Friedman S, Clube RKM, et al., 2022, Implementation of a structured decision-making framework to evaluate and advance understanding of airborne microplastics, Environmental Science and Policy, Vol: 135, Pages: 169-181, ISSN: 1462-9011
Microplastic pollution is increasingly recognised as a global environmental challenge which stems from the rapid growth of the use of petrochemical-derived plastic. As researchers and practitioners face a myriad of environmental challenges, oceanic microplastic pollution has so far dominated interest. However, airborne microplastics present an increasing environmental and public health concern. There is currently a need for research addressing this emerging challenge, and at the same time, the lack of knowledge and consensus regarding airborne microplastics presents an obstacle to action. The purpose of this study is to utilise a participatory Structured Decision-Making (SDM) approach to understand the perspectives of a range of stakeholders involved in the microplastics landscape, and subsequently refine common research priorities and knowledge gaps to advance the field. Through two participatory workshops, we first defined shared objectives of stakeholders and then negotiated best courses of action to achieve these objectives based on discussion between stakeholders and facilitators. The qualitative approach taken has enabled the full, complex and multidisciplinary aspects of the research into airborne microplastic pollution to be considered. Our findings highlight some important potential consequences of airborne microplastic pollution, including impacts on human health, and the need for more interdisciplinary research, and collaborative, integrated approaches in this area. As a result of the first workshop, five fundamental objectives on the theme of airborne microplastics were identified. As a direct consequence of this, participants identified 84 actions split across eight themes, which are outlined later in this paper.
Smith W, Hanea A, Burgman M, 2022, Can groups improve expert economic and financial forecasts?, Forecasting, Vol: 4, Pages: 699-716, ISSN: 2571-9394
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.
Burgman M, Layman H, French S, 2022, Eliciting model structures for multivariate probabilistic risk analysis, Frontiers in Applied Mathematics and Statistics, Vol: 7, Pages: 1-10, ISSN: 2297-4687
Notionally objective probabilistic risk models, built around ideas of cause and effect, are used to predict impacts and evaluate trade-offs. In this paper, we focus on the use of expert judgement to fill gaps left by insufficient data and understanding. Psychological and contextual phenomena such as anchoring, availability bias, confirmation bias and overconfidence are pervasive and have powerful effects on individual judgements. Research across a range of fields has found that groups have access to more diverse information and ways of thinking about problems, and routinely outperform credentialled individuals on judgement and prediction tasks. In structured group elicitation, individuals make initial independent judgements, opinions are respected, participants consider the judgements made by others, and they may have the opportunity to reconsider and revise their initial estimates. Estimates may be aggregated using behavioural, mathematical or combined approaches. In contrast, mathematical modelers have been slower to accept that the host of psychological frailties and contextual biases that afflict judgements about parameters and events may also influence model assumptions and structures. Few, if any, quantitative risk analyses embrace sources of uncertainty comprehensively. However, several recent innovations aim to anticipate behavioural and social biases in model construction and to mitigate their effects. In this paper, we outline approaches to eliciting and combining alternative ideas of cause and effect. We discuss the translation of ideas into equations and assumptions, assessing the potential for psychological and social factors to affect the construction of models. We outline the strengths and weaknesses of recent advances in structured, group-based model construction that may accommodate a variety of understandings about cause and effect.
Marcoci A, Vercammen A, Bush M, et al., 2022, Reimagining peer review as an expert elicitation process, BMC Research Notes, Vol: 15, ISSN: 1756-0500
Journal peer review regulates the flow of ideas through an academic discipline and thus has the power to shape what a research community knows, actively investigates, and recommends to policymakers and the wider public. We might assume that editors can identify the ‘best’ experts and rely on them for peer review. But decades of research on both expert decision-making and peer review suggests they cannot. In the absence of a clear criterion for demarcating reliable, insightful, and accurate expert assessors of research quality, the best safeguard against unwanted biases and uneven power distributions is to introduce greater transparency and structure into the process. This paper argues that peer review would therefore benefit from applying a series of evidence-based recommendations from the empirical literature on structured expert elicitation. We highlight individual and group characteristics that contribute to higher quality judgements, and elements of elicitation protocols that reduce bias, promote constructive discussion, and enable opinions to be objectively and transparently aggregated.
Swallow B, Birrell P, Blake J, et al., 2022, Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling, Epidemics: the journal of infectious disease dynamics, Vol: 38, Pages: 1-12, ISSN: 1755-4365
The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics.
Hemming V, Hanea A, Burgman M, 2022, What is a Good Calibration Question?, Risk Analysis: an international journal, Vol: 42, Pages: 264-278, ISSN: 0272-4332
Weighted aggregation of expert judgements based on their performance on calibration questions may improve mathematically aggregated judgements 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 paper, we examine what happens to the out-of-sample performance of weighted aggregations of the Classical Model 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 Classical Model (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 judgements. 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.
Roura-Pascual N, Leung B, Rabitsch W, et al., 2021, Alternative futures for global biological invasions, Sustainability Science, Vol: 16, Pages: 1637-1650, ISSN: 1862-4057
Scenario analysis has emerged as a key tool to analyze complex and uncertain future socio-ecological developments. However, currently existing global scenarios (narratives of how the world may develop) have neglected biological invasions, a major threat to biodiversity and the economy. Here, we use a novel participatory process to develop a diverse set of global biological invasion scenarios spanning a wide range of plausible global futures through to 2050. We adapted the widely used “two axes” scenario analysis approach to develop four families of four scenarios each, resulting in 16 scenarios that were later clustered into four contrasting sets of futures. Our analysis highlights that socioeconomic developments and technological innovation have the potential to shape biological invasions, in addition to well-known drivers, such as climate and human land use change and global trade. Our scenarios partially align with the shared socioeconomic pathways created by the climate change research community. Several factors that drive differences in biological invasions were underrepresented in the shared socioeconomic pathways; in particular, the implementation of biosecurity policies. We argue that including factors related to public environmental awareness and technological and trade development in global scenarios and models is essential to adequately consider biological invasions in global environmental assessments and thereby obtain a more integrative picture of future social–ecological developments.
Stirling A, Burgman MA, 2021, Strengthening conservation science as a crisis discipline by addressing challenges of precaution, privilege, and individualism, Conservation Biology, Vol: 35, Pages: 1738-1746, ISSN: 0888-8892
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.
Junaedi DI, Guillera-Arroita G, Vesk PA, et al., 2021, Traits explain invasion of alien plants into tropical rainforests, Ecology and Evolution, Vol: 11, Pages: 3808-3819, ISSN: 2045-7758
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
Vercammen A, Marcoci A, Burgman M, 2021, Pre-screening workers to overcome bias amplification in online labour markets, PLoS One, Vol: 16, ISSN: 1932-6203
Groups have access to more diverse information and typically outperform individuals on problem solving tasks. Crowdsolving utilises this principle to generate novel and/or superior solutions to intellective tasks by pooling the inputs from a distributed online crowd. However, it is unclear whether this particular instance of “wisdom of the crowd” can overcome the influence of potent cognitive biases that habitually lead individuals to commit reasoning errors. We empirically test the prevalence of cognitive bias on a popular crowdsourcing platform, examining susceptibility to bias of online panels at the individual and aggregate levels. We then investigate the use of the Cognitive Reflection Test, notable for its predictive validity for both susceptibility to cognitive biases in test settings and real-life reasoning, as a screening tool to improve collective performance. We find that systematic biases in crowdsourced answers are not as prevalent as anticipated, but when they occur, biases are amplified with increasing group size, as predicted by the Condorcet Jury Theorem. The results further suggest that pre-screening individuals with the Cognitive Reflection Test can substantially enhance collective judgement and improve crowdsolving performance.
Ball JCG, Burgman M, Goldman ED, et al., 2021, Protecting biodiversity and economic returns in resource rich tropical forests, Conservation Biology, Vol: 35, Pages: 263-273, ISSN: 0888-8892
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.
Bolam FC, Mair L, Angelico M, et al., 2021, How many bird and mammal extinctions has recent conservation action prevented?, Conservation Letters, Vol: 14, Pages: 1-11, ISSN: 1755-263X
Aichi Target 12 of the Convention on Biological Diversity (CBD) contains the aim to ‘prevent extinctions of known threatened species’. To measure the degree to which this was achieved, we used expert elicitation to estimate the number of bird and mammal species whose extinctions were prevented by conservation action in 1993–2020 (the lifetime of the CBD) and 2010–2020 (the timing of Aichi Target 12). We found that conservation action prevented 21–32 bird and 7–16 mammal extinctions since 1993, and 9–18 bird and two to seven mammal extinctions since 2010. Many remain highly threatened and may still become extinct. Considering that 10 bird and five mammal species did go extinct (or are strongly suspected to) since 1993, extinction rates would have been 2.9–4.2 times greater without conservation action. While policy commitments have fostered significant conservation achievements, future biodiversity action needs to be scaled up to avert additional extinctions.
Conway G, Burgman M, Makuch Z, et al., 2021, Beter diets, better health: Costs of Healthy Diets, Better diets, better health: Costs of Healthy Diets, 2
Conway G, Burgman M, Makuch Z, et al., 2021, Better diets, better health: Costs of Healthy Diets
Burgman M, Addison PFE, Stephenson PJ, et al., 2020, Bringing sustainability to life: A framework to guide biodiversity indicator development for business performance management, Business Strategy and the Environment, Vol: 29, Pages: 3303-3313, ISSN: 0964-4733
Biodiversity loss is a critical sustainability issue, and companies are beginning to seek ways to assess their biodiversity performance. Initiatives to date have developed biodiversity indicators for specific business contexts (e.g., spatial scales—from site, to product, to regional, or corporate scales); however, many are not widely translatable across different contexts making it challenging for businesses seeking indicators to manage their biodiversity performance. By synthesising the steps of common conservation and business decision‐making systems, we propose a framework to support more comprehensive development of quantitative biodiversity indicators, for a range of business contexts. The framework integrates experience from existing tried‐and‐tested conservation frameworks. We illustrate how our framework offers a pathway for businesses to assess their biodiversity performance and demonstrate responsible management by mitigating and reversing their biodiversity impacts and sustaining their dependencies, enabling them to demonstrate their contribution to emerging global biodiversity targets (e.g., Convention on Biological Diversity post‐2020 targets).
van Gelder T, Kruger A, Thomman S, et al., 2020, Improving analytic reasoning via crowdsourcing and structured analytic techniques, Journal of Cognitive Engineering and Decision Making, Vol: 14, Pages: 195-217, ISSN: 1555-3434
How might analytic reasoning in intelligence reports be substantially improved? One conjecture is that this can be achieved through a combination of crowdsourcing and structured analytic techniques (SATs). To explore this conjecture, we developed a new crowdsourcing platform supporting groups in collaborative reasoning and intelligence report drafting using a novel SAT we call “Contending Analyses.” In this paper we present findings from a large study designed to assess whether groups of professional analysts working on the platform produce better-reasoned reports than those analysts produce when using methods and tools normally used in their organizations. Secondary questions were whether professional analysts working on the platform produce better reasoning than the general public working on the platform; and how usable the platform is. Our main finding is a large effect size (Cohen’s d = 1.37) in favor of working on platform. This provides early support for the general conjecture. We discuss limitations of our study, implications for intelligence organizations, and future directions for the work as a whole.
Sutherland WJ, Alvarez-Castaneda ST, Amano T, et al., 2020, Ensuring tests of conservation interventions build on existing literature, Conservation Biology, Vol: 34, Pages: 781-783, ISSN: 0888-8892
Hemming V, Hanea A, Walshe T, et al., 2020, Weighting and aggregating expert ecological judgments, Ecological Applications, Vol: 30, Pages: 1-17, ISSN: 1051-0761
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.
Hemming V, Armstrong N, Burgman M, et al., 2020, Improving expert forecasts in reliability. Application and evidence for structured elicitation protocols, Quality and Reliability Engineering International, Vol: 36, Pages: 623-641, ISSN: 0748-8017
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.
Bammer G, O'Rourke M, O'Connell D, et al., 2020, 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?, Palgrave Communications, Vol: 6, Pages: 1-16, ISSN: 2055-1045
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 com
Vercammen A, Burgman M, 2019, Untapped potential of collective intelligence in conservation and environmental decision making., Conserv Biol, Vol: 33, Pages: 1247-1255
Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade-offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small-group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision-making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective-intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision-making research and practice.
Thompson CJ, Kodikara S, Burgman MA, et al., 2019, Using survival theory models to quantify extinctions, Biological Conservation, Vol: 241, Pages: 1-5, ISSN: 0006-3207
Extinctions are difficult to observe and typically are inferred from the timing and reliability of field observations and collections. Recent advances in approaches to estimating extinction probability consider the type, timing and certainty of records, the timing, scope and severity of threats, and the timing, extent and reliability of surveys. Here we describe a new approach to inference of extinction that uses survival theory, an approach that has a long history of effective use in other disciplines that confront similar problems. The model takes into account uncertainties in input parameter estimates and provides bounds on estimates of the extinction probability for the case in which a species has not been detected following some specified time. We illustrate application of the model using information for dodos and Aldabra snails. This approach provides an alternative perspective on the models underlying the techniques for inferring extinction. It should provide reliable estimates of recent extinction rates.
Rowland JA, Bland LM, Keith DA, et al., 2019, Ecosystem indices to support global biodiversity conservation, Conservation Letters, Vol: 13, ISSN: 1755-263X
Governments have committed to global targets to slow biodiversity loss and sustain ecosystem services. Biodiversity state indicators that measure progress towards these targets mostly focus on species, while indicators synthesizing ecosystem change are largely lacking. We fill this gap with three indices quantifying past and projected changes in ecosystems using data from the International Union for Conservation of Nature (IUCN) Red List of Ecosystems. Our indices quantify changes in risk of ecosystem collapse, ecosystem area, and ecological processes and capture variation in underlying patterns among ecosystems. We apply the indices to three case studies of regional and national assessments (American/Caribbean forests, terrestrial ecosystems of Colombia, and terrestrial ecosystems of South Africa) to illustrate the indices’ complementarity and versatility in revealing patterns of interest for users across sectors. Our indices have the potential to fill the recognized need for ecosystem indicators to inform conservation targets, guide policy, and prioritize management actions.
McCarthy MA, Burgman MA, Wei F, et al., 2019, Plan S and publishing: reply to Lehtomäki et al. 2019., Conservation Biology, Vol: 33, Pages: 1203-1204, ISSN: 0888-8892
Voulvoulis N, Burgman M, 2019, The contrasting roles of science and technology in environmental challenges, Critical Reviews in Environmental Science and Technology, Vol: 49, Pages: 1079-1106, ISSN: 1064-3389
Sustainable development is widely recognised as an existential challenge. To address it, humanity needs to change its ways. However, people seem slow to act, not always understanding and often denying environmental imperatives, creating substantial social and psychological barriers. Social inertia and denial have been allegedly amplified by a public discourse increasingly distrustful of science. But is this discourse a rejection of science or an erosion of trust in how science is applied? The paper examines the main differences between environmental science and technology, reviews how the wider science- technology convergence has affected them and evaluates potential implications for sustainability challenges. We question whether the ‘convergence’ between environmental science and technology, could be behind the growing public dissatisfaction and distrust of environmental science and policies. Although environmental science plays a role in enabling understanding and communicating complexity, technology requires political, social and economic skills, beyond conventional disciplinary expertise. To avoid putting academic freedom at risk, environmental technologists, a new breed of professionals, should have a clear understanding of scientific capacity and uncertainty and be able to engage with stakeholders, policy makers and the public to design integrated, interdisciplinary and holistic solutions, and also better define the many environmental problems we face.
Fidler F, Chee YE, Wintle BC, et al., 2019, Metaresearch for evaluating reproducibility in ecology and evolution, Bioscience, Vol: 67, Pages: 282-289, ISSN: 0006-3568
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.
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