A systematic review of transparency in the methods of expert knowledge use

Abstract

1. The use of expert knowledge (EK) as an alternative to empirical data is increasing in the ecological disciplines in response to the growing need for rapid decisions that are embraced by local communities and implemented under strong resource constraints. Despite this increasing use, the validity of EK as a data source is still questioned by some who label it as biased or unreliable. Transparency in the methods applied in the use of EK allows confirmation of methodological rigour and study repeatability; key steps towards promoting the acceptance of EK as a valid data source. However, the practiced levels of methodological transparency in EK use are currently unknown in the ecological disciplines.2. To fill this knowledge gap, we performed a systematic review of transparency in methods applied in the use of EK, focusing on research in forest ecology and management as a case study. Covering the period from 1990 to 2016, we identified 296 publications that employed EK, which were assessed for their reporting on 15 methodological criteria of EK use. 3.Our results indicate that transparency in the use of EK is generally very low, with only three out of 15 methodological criteria addressed in more than 50% of publications. Nevertheless, overall reporting on EK methods, and the reporting of four individual methodological criteria, were positively affected by publicationyear, suggesting that researchers increasingly recognize the importance of transparency in the use of EK methods. Synthesis and applications.Given the growing use of expert knowledge (EK) in the ecological disciplines, there is an urgent need to further its acceptance as a valid data source. To achieve this goal, researchers need to be more diligent in following best practices and reporting on EK methods. We therefore present a proposed set of guidelines for the reporting of EK methods. However, journal editors and reviewers also can play an important role in reaching this goal by requiring authors to transparently report on EK methods, just as they would expect for the use of empirical data. K E Y W O R D Selicitation, expert judgement, expert knowledge, forest, methodology, reliability, reporting methods, transparency

Participatory mapping of invasive species: A demonstration in a coastal lagoon

“…These conditions are common in conservation sciences, which have recently witnessed an outburst of participatory mapping initiatives throughout the world, in both developing and developed countries [2][3] [4] . In fact, information extracted from the knowledge of people living in close relationship with the natural environment can complement, or even surrogate, ecological sampling, at various spatial and temporal scales [5][6] [7] . This expert knowledge, often reported as 'Local Ecological Knowledge' (LEK) is currently accessed to estimate a variety of biological and ecological parameters [8][9] [10] in both terrestrial and aquatic systems, where ecological monitoring is particularly demanding [11] .…”

Reference state and benchmark concepts for better biodiversity conservation in contemporary ecosystems

“…However, these opinions can be uncertain, value‐laden, subjective and prone to counter‐perspective and discrepancy (Burgman et al., 2011). The bias, validity and reliability of expert judgement are especially problematic when it is difficult to assess the transparency and repeatability of the methods (Drescher & Edwards, 2019). Consequently, reproducing benchmarks generated by expert opinion may lead to discrepant results, wide variations in estimates or contested debate.…”

Untapped potential of collective intelligence in conservation and environmental decision making

“…), and estimating population trends (Adams‐Hosking et al. ), most researchers do not use a structured approach (Drescher & Edwards ). Expert‐elicitation protocols require testing in a wider range of environmental decision making (Hemming et al.…”

“…The use of structured elicitation methods may increase the rigor with which decisions are made, aid the management of uncertainty, and mitigate prevalent and persistent biases that undermine judgment. Despite successful applications in, for example, threatened species assessments (McBride et al 2012b), prioritizing management strategies (e.g., Carwardine et al 2019), risk assessments (Smith et al 2015), and estimating population trends (Adams-Hosking et al 2016), most researchers do not use a structured approach (Drescher & Edwards 2019). Expert-elicitation protocols require testing in a wider range of environmental decision making (Hemming et al 2017), including in the harnessing of collective local ecological knowledge in groups without a strong numerical background or with different knowledge systems (Mantyka-Pringle et al 2017).…”