What is an expert? A systems perspective on expertise

Expert knowledge is a valuable source of information with a wide range of research applications. Despite the recent advances in defining expert knowledge, little attention has been given to how to view expertise as a system of interacting contributory factors for quantifying an individual's expertise. We present a systems approach to expertise that accounts for many contributing factors and their inter‐relationships and allows quantification of an individual's expertise. A Bayesian network (BN) was chosen for this purpose. For illustration, we focused on taxonomic expertise. The model structure was developed in consultation with taxonomists. The relative importance of the factors within the network was determined by a second set of taxonomists (supra‐experts) who also provided validation of the model structure. Model performance was assessed by applying the model to hypothetical career states of taxonomists designed to incorporate known differences in career states for model testing. The resulting BN model consisted of 18 primary nodes feeding through one to three higher‐order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra‐experts for some nodes, but not others. The higher‐order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite the differences in the node weights provided by our supra‐experts, there was good agreement among assessments of our hypothetical experts that accurately reflected differences we had specified. This systems approach provides a way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.     

What Sources Are Natural Resource Managers Using to Make Decisions?

Natural resource management is more effective when it includes collaboration among numerous stakeholders who bring multiple perspectives to the decision-making process. In particular, many individuals and organizations (e.g., The Wildlife Society) have advocated for decisions to be science-based as a means for improving management outcomes. But there has been little research evaluating the sources, science-based or otherwise, used by natural resource agencies to support decision-making at the state-level within the United States. We surveyed state natural resource agency personnel in all 50 states to assess the sources of information used to make management decisions and the factors that influenced selection of the sources. Approximately 60% of respondents reported using ≥3 different source types when making recommendations. Existing management plans, the peer-reviewed scientific literature, and expert opinion were the most frequently used sources. Perception of source relevance was the most frequent predictor of source use, and the number of management plans a manager had previously written positively predicted the use of management plans, expert opinion, and personal experiences. Ninety percent of respondents reported that increased use of the peer-reviewed literature would or might improve management recommendations. Aspects of academic and agency cultures influenced which articles or journals were used to make recommendations. Our findings indicate managers support the use of peer-reviewed literature as an important component of management decision-making; however, if the goal is to improve the flow of information between scientists and managers, researchers should publish in journals that are readily accessible to managers and present results in a way that clearly articulates relevance to management decisions. © 2021 The Wildlife Society.     

Development of an expert system for the integration of biomarker responses in mussels into an animal health index

Biomarkers on sentinel organisms are utilised worldwide in biomonitoring programs. However, the lack of effective interpretational capacity has hampered their uptake for use for assessment of risk in environmental management. The aim of the present study was to develop and test an objective decision-support or expert system capable of integrating biomarker results into a five-level health-status index. The expert system is based on a set of rules derived from available data on responses to natural and contaminant-induced stress of marine mussels. Integration of parameters includes: level of biological organization; biological significance; mutual inter-relationship; and qualitative trends in a stress gradient. The system was tested on a set of biomarker data obtained from the field and subsequently validated with data from previous studies. The results demonstrate that the expert system can effectively quantify the biological effects of different levels of pollution. The system represents a simple tool for risk assessment of the harmful impact of contaminants by providing a clear indication of the degree of stress syndrome induced by pollutants in mussels.     

Woody vegetation dynamics in the tropical and subtropical Andes from 2001 to 2014: Satellite image interpretation and expert validation

The interactions between climate and land‐use change are dictating the distribution of flora and fauna and reshuffling biotic community composition around the world. Tropical mountains are particularly sensitive because they often have a high human population density, a long history of agriculture, range‐restricted species, and high‐beta diversity due to a steep elevation gradient. Here we evaluated the change in distribution of woody vegetation in the tropical Andes of South America for the period 2001–2014. For the analyses we created annual land‐cover/land‐use maps using MODIS satellite data at 250 m pixel resolution, calculated the cover of woody vegetation (trees and shrubs) in 9,274 hexagons of 115.47 km², and then determined if there was a statistically significant (p < 0.05) 14 year linear trend (positive—forest gain, negative—forest loss) within each hexagon. Of the 1,308 hexagons with significant trends, 36.6% (n = 479) lost forests and 63.4% (n = 829) gained forests. We estimated an overall net gain of ~500,000 ha in woody vegetation. Forest loss dominated the 1,000–1,499 m elevation zone and forest gain dominated above 1,500 m. The most important transitions were forest loss at lower elevations for pastures and croplands, forest gain in abandoned pastures and cropland in mid‐elevation areas, and shrub encroachment into highland grasslands. Expert validation confirmed the observed trends, but some areas of apparent forest gain were associated with new shade coffee, pine, or eucalypt plantations. In addition, after controlling for elevation and country, forest gain was associated with a decline in the rural population. Although we document an overall gain in forest cover, the recent reversal of forest gains in Colombia demonstrates that these coupled natural‐human systems are highly dynamic and there is an urgent need of a regional real‐time land‐use, biodiversity, and ecosystem services monitoring network.     

Validating indicators of sheep welfare through a consensus of expert opinion

A consensus of expert opinion was used to provide both face and consensual validity to a list of potential indicators of sheep welfare. This approach was used as a first step in the identification of valid welfare indicators for sheep. The consensus methodology of the National Institute of Health, using pre-meeting consultation and focus group discussions, was used to ascertain the consensus opinion of a panel of sheep welfare experts. The Farm Animal Welfare Council's five freedoms were used as a framework to organise a list of current on-farm welfare issues for sheep. The five freedoms were also the welfare criterion used to identify potential on-farm welfare indicators for sheep. As a result, experts identified 193 welfare issues for sheep and lambs managed on farms across England and Wales. Subsequently, a combination of animal- (n = 26), resource- (n = 13) and management- (n = 22) based indicators was suggested for (i) adult rams, (ii) adult ewes (male and female sheep, over 1 year old), (iii) growing lambs (male and female sheep, over 6 weeks to 1 year old) and (iv) young lambs (male and female lambs, 6 weeks old and under). The results from this study could therefore be used to inform the further development of valid methods of assessing the on-farm welfare of sheep.     

Using expert knowledge to incorporate uncertainty in cause‐of‐death assignments for modeling of cause‐specific mortality

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause‐specific mortality provide an example of implicit use of expert knowledge when causes‐of‐death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause‐specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause‐of‐death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event‐time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause‐of‐death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause‐of‐death assignment in modeling of cause‐specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause‐specific survival data for white‐tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause‐of‐death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.     

Expert systems in the control of animal cell culture processes: Potentials,functions, and perspectives

In recent years, the development of advanced systems for bioprocess monitoring and control has become an area of intensive research. Along with traditional techniques, there are several new approaches which are increasingly being applied to bioprocess operations. Among these, of special note is expert system technology, which provides possibilities for the design of efficient bioprocess control systems with new functional capabilities. This technology has been successfully applied to variety of microbial processes at laboratory and industrial scale. The present paper analyzes the possibility for application of expert systems to animal cell cultures processes whose high complexity is well suited to expert control. The discussion focuses on the organization and the functionality of the intelligent control systems, and covers some practical aspects of their design.