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.

Deficiencies of scope statements in ITLET standardization

To execute good design one not only needs to know what to do and how to do it, but also why it should be done. For a standardization expert the rationale of a standardization project may be found in the proposal for a new work item or terms of reference, but rarely in the scope statement. However, it is also commonplace that the rationale of the project is not clearly stated in any of these parts. If the rationale is not surfaced in the early phases of a project, it is left to the design, sense-making and negotiation cycles of the design process to orient the project towards a goal. This paper explores how scope statements are used to position standardization projects in the IT for Learning, Education and Training (ITLET) domain, and how scope and rationale are understood in recent projects in European and international standardization. Based on two case-studies the paper suggests some actions for further research and improvement of the process.

Children's self-talk and academic self-concepts: The impact of teachers' statements

Data were collected from 269 Australian primary school children in grades 3 to 7. Self-report questionnaires measuring students' perceptions of the frequency of positive and negative statements directed to them by their teacher, their positive and negative self-talk; and their reading, mathematics and learning self-concepts were administered. Positive statements made by teachers were found to be directly related to positive self-talk and to maths and learning self-concepts. Teachers' positive statements were also indirectly related to reading self-concept through positive self-talk. Negative statements made by teachers were not predictive of self-talk or self-concepts for the total sample but were predictive of maths self-concept for girls and negative self-talk for boys. Implications for teachers and educational psychologists are discussed.

The relationship between significant others' positive and negative statements, self-talk and self-esteem

This study investigated the effect of self-talk in mediating between positive and negative statements made by significant others and self-esteem with children in grades 3 to 7. Students completed questionnaires on the frequency of positive and negative statements from parents, teachers, and peers. Findings suggest that self-talk does mediate between significant others' statements and children's self-esteem.

Gender and grade differences in upper elementary school children’s descriptive and evaluative self-statements and self-esteem

Gender and developmental differences in self-description, self-evaluation and self-esteem were investigated using 957 elementary school children in grades 3 to 7. Gender differences were found for six of the seven descriptive statements and for five of the seven evaluative statements. The major gender stereotypical findings from previous studies were replicated. Boys reported higher scores than girls on descriptive and evaluative statements about their physical abilities and mathematics, while girls reported higher scores on descriptive and evaluative statements about reading. Declines over time were noted for all self-evaluations except having good relations with peers and for global self-esteem, providing some support for the notion that the decline in self-concepts and self-esteem may be attributed to the children's perceptions of themselves becoming more accurate and less egocentric in line with their cognitive capacity to integrate external feedback realistically.

Children's self-talk and significant others' positive and negative statements

A sample of 675 elementary school children in Grades 3-7 were administered the Self-talk Inventory and the Significant Others' Statements Inventory. The psychometric properties of both scales were investigated and the relationships between positive and negative self-talk and significant others' (parents, teachers, siblings and peers) positive and negative statements were explored using correlational and multiple regression analyses. Sex and age differences were also examined. The significant relationships and differences are described.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

Elicitator : an expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.