Managing offshore multi-use settings: Use of conceptual mapping to reduce uncertainty of co-locating seaweed aquaculture and wind farms

The offshore Multi-use Setting (MUS) is a concept that aims to co-locate marine industrial activities, including wind farms and aquaculture. MUS is considered an innovative approach to promoting efficiency in space and resource use whilst contributing global policy priorities. However, the impacts of MUS development across social, economic, and environmental domains are uncertain, hindering the commercialisation of the concept. In this study, we initially demonstrate the potential consequences of co-locating seaweed aquaculture and a wind farm as a step towards MUS. Using a hypothetical case study and modified Delphi methodology, 14 subject matter experts predicted potential outcomes across social and environmental objectives. Five Cognitive maps and impact tables of 58 potential consequences were generated based on experts' perspective on co-locating seaweed aquaculture and a wind farm. The findings highlight the potential to exasperate pressures in the area, including those already attributed to wind farm operations, such as species mortality and stakeholder conflict. However, it may also enhance social-ecological conditions, such as resource provisioning and promoting habitat functionality in the region, through the addition of seaweed aquaculture. The cognitive maps demonstrate the complexity of managing MUS implementation, where high degree of variability and uncertainty about the outcomes is present. The findings of this study provide the vital entry point to performing further integrative assessment and modelling approaches, such as probabilistic analysis and simulations, in support of MUS decision-making. The research also strongly recommends alternative strategies in the pursuit of combining seaweed production and wind farms to avoid significant financial (among many other) trade-offs and risks. More broadly, we have found that our approach's ability to visually represent a complex situation while considering multiple objectives could be immensely valuable for other bioeconomy innovations or nature-based solutions. It helps mitigate the potential for expensive investments without a comprehensive evaluation of the associated risks and negative impacts, as necessitated by the principles of sustainability in decision-making.

Comparing wildlife habitat suitability models based on expert opinion with camera trap detections

Expert knowledge is used in the development of wildlife habitat suitability models (HSMs) for management and conservation decisions. However, the consistency of such models has been questioned. Focusing on 1 method for elicitation, the analytic hierarchy process, we generated expert-based HSMs for 4 felid species: 2 forest specialists (ocelot [Leopardus pardalis] and margay [Leopardus wiedii]) and 2 habitat generalist species (Pampas cat [Leopardus colocola] and puma [Puma concolor]). Using these HSMs, species detections from camera-trap surveys, and generalized linear models, we assessed the effect of study species and expert attributes on the correspondence between expert models and camera-trap detections. We also examined whether aggregation of participant responses and iterative feedback improved model performance. We ran 160 HSMs and found that models for specialist species showed higher correspondence with camera-trap detections (AUC [area under the receiver operating characteristic curve] >0.7) than those for generalists (AUC < 0.7). Model correspondence increased as participant years of experience in the study area increased, but only for the understudied generalist species, Pampas cat (β = 0.024 [SE 0.007]). No other participant attribute was associated with model correspondence. Feedback and revision of models improved model correspondence, and aggregating judgments across multiple participants improved correspondence only for specialist species. The average correspondence of aggregated judgments increased as group size increased but leveled off after 5 experts for all species. Our results suggest that correspondence between expert models and empirical surveys increases as habitat specialization increases. We encourage inclusion of participants knowledgeable of the study area and model validation for expert-based modeling of understudied and generalist species.

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.

Reimagining peer review as an expert elicitation process

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.

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.

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.

Uncertainty Quantification with Experts: Present Status and Research Needs

Expert elicitation is deployed when data are absent or uninformative and critical decisions must be made. In designing an expert elicitation, most practitioners seek to achieve best practice while balancing practical constraints. The choices made influence the required time and effort investment, the quality of the elicited data, experts' engagement, the defensibility of results, and the acceptability of resulting decisions. This piece outlines some of the common choices practitioners encounter when designing and conducting an elicitation. We discuss the evidence supporting these decisions and identify research gaps. This will hopefully allow practitioners to better navigate the literature, and will inspire the expert judgment research community to conduct well powered, replicable experiments that properly address the research gaps identified.

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.

Prospective cohort study of procalcitonin levels in children with cancer presenting with febrile neutropenia

Background

Febrile neutropenia (FNP) causes significant morbidity and mortality in children undergoing treatment for cancer. The development of clinical decision rules to help stratify risks in paediatric FNP patients and the use of inflammatory biomarkers to identify high risk patients is an area of recent research. This study aimed to assess if procalcitonin (PCT) levels could be used to help diagnose or exclude severe infection in children with cancer who present with febrile neutropenia, both as a single measurement and in addition to previously developed clinical decision rules.

Methods

This prospective cohort study of a diagnostic test included patients between birth and 18 years old admitted with febrile neutropenia to the Paediatric Oncology and Haematology Ward in Leeds between 1^st October 2012 and 30^th September 2013. Each admission with FNP was treated as a separate episode. Blood was taken for a procalcitonin level at admission with routine investigations. ‘R’ was used for statistical analysis. Likelihood ratios were calculated and multivariable logistic regression.

Results

Forty-eight episodes from 27 patients were included. PCT >2 ng/dL was strongly associated with increased risk of severe infection (likelihood ratio of 26 [95% CI 3.5, 190]). The data suggests that the clinical decision rules are largely ineffective at risk stratification, frequently over-stating the risk of individual episodes. High procalcitonin levels on admission are correlated with a greatly increased risk of severe infection.

Conclusions

This study does not show a definitive benefit in using PCT in FNP though it supports further research on its use. The benefit of novel biomarkers has not been proven and before introducing new tests for patients it is important their benefit above existing features is proven, particularly due to the increasing importance of health economics.

Electronic supplementary material

The online version of this article (doi:10.1186/s12887-016-0766-8) contains supplementary material, which is available to authorized users.

Small intestinal atresia in a defined population: occurrence, prenatal diagnosis and survival

OBJECTIVE

To describe the prevalence, associated anomalies, prenatal diagnosis, and survival of cases of congenital small intestinal atresia (SIA).

METHOD

Data were extracted from the Northern Congenital Abnormality Survey (NorCAS) for cases delivered during 1991 to 2001.

RESULTS

A total of 99 cases of SIA were notified from 372 717 registered births. Twenty-five (25.8%) SIA cases were associated with a chromosomal anomaly. Of the 72 SIA cases with normal karyotype, 18 (25%) were associated with other structural anomalies. The total prevalence for all SIA cases over the 11 years was 2.66 per 10 000 registered births (95% CI 2.13, 3.18), and the livebirth prevalence was 2.37 per 10 000 livebirths (95% CI 1.88, 2.87). For jejunoileal atresia, the total prevalence increased from 0.54 per 10 000 births during 1991-1995 to 1.11 per 10 000 births during 1996-2001, and livebirth prevalence increased from 0.49 to 1.06 per 10 000 livebirths. The more proximal the lesion the prenatal diagnosis sensitivity was slightly better with 19 (44.2%) cases of duodenal atresia and 3 (42.8%) cases of jejunal atresia diagnosed prenatally by routine ultrasonography.

CONCLUSION

This population-based study of SIA has confirmed several previous findings but, by considering subtypes separately, it also suggests a trend towards an increase in the prevalence of jejunoileal atresia (JIA).

Respiratory syncytial virus replication is prolonged by a concomitant allergic response

Epidemiological studies show an association between early exposure to respiratory syncytial virus (RSV) and the development or exacerbation of asthma. This idea is supported by studies in mice that demonstrate worsened airway hyper-reactivity (AHR) when RSV-infected animals are exposed to allergen. The effect of allergen on RSV disease, however, has not been reported. Cotton rats (Sigmodon hispidus) that have been used as a model to study RSV pathogenesis were sensitized to extracts of Aspergillus fumigatus (Af), a common household mould. The allergic response to Af included eosinophilia, formation of granulomas and induction of Th2 type cytokines. RSV infection prior to allergen challenge resulted in exacerbation of the inflammatory response as well as increased airway responsiveness to methacholine. The exacerbated response was indeed dependent on virus replication. Virus replication in turn was influenced by the allergic response, with persistence in the noses for 2 days longer in animals challenged with allergen. This diminished clearance corresponded to decreased induction of mRNA for IFN-gamma, a Th1-type cytokine that is characteristic of viral infection. Treatment of RSV-infected Af-challenged animals with recombinant IFN-gamma reduced the allergic inflammatory response as well as the relative levels of Th1 and Th2 cytokine mRNA. However, this treatment did not reduce airway reactivity, showing that these pathologic and physiologic measures of exacerbated disease are independent. We speculate that the reciprocal effect of the allergic response on viral immunity may benefit the host by limiting exacerbation of physiologic responses that are IFN-gamma-dependent.

Respiratory syncytial virus immune globulin treatment of RSV lower respiratory tract infection in previously healthy children

OBJECTIVE

To evaluate the efficacy of high titer respiratory syncytial virus (RSV) immune globulin (RSVIG) in the treatment of previously healthy children hospitalized with proven RSV lower tract infection (LRI).

METHOD

Infants and young children </=2 years of age with RSV LRI of </=4 days duration, and respiratory scores >/=2. 5 were enrolled.

RESULTS

One hundred and one previously healthy children hospitalized with RSV LRI received either 1500 mg/kg of RSVIG (RespiGam, MedImmune Inc, Gaithersburg, MD) or albumin placebo in a randomized, double-blind, placebo-controlled trial. Forty-six RSVIG and 52 recipients of placebo met all eligibility criteria. Demographic characteristics of the two groups were similar. More RSVIG recipients (46% vs 29%) had an SaO2 </=85% at entry than did placebo recipients, but a higher proportion of placebo recipients required intensive care unit (ICU) care and mechanical ventilation at study entry. The mean RSV hospital stay was 5.52 +/- 0.69 days (SE) for placebo and 4.58 +/- 0.40 days for RSVIG. Additionally, there was an interaction between treatment group and entry respiratory score, which led to subgroup analysis. Children with modest respiratory illness did not receive any benefit from RSVIG therapy. RSVIG recipients with more severe illness (entry respiratory scores >/=3.0) had 1.6 fewer hospital days and 2.7 days less ICU stays.

CONCLUSION

RSVIG infusions seemed safe and generally well tolerated. Although some beneficial effect trends were seen for those with more severe disease who were treated there was no evidence that treatment with RSVIG resulted in reduced hospitalization and reduced ICU stays in all children with RSV disease.