The document discusses a study that compared using expert knowledge versus field data for modeling the habitat of brush-tailed rock-wallabies, finding that combining the two through a Bayesian approach provided more accurate predictions by broadening the knowledge base and tightening the posterior distributions. Experts were interviewed using an interactive GIS tool to elicit their knowledge of rock-wallaby habitat preferences, which was then combined with field data from 466 surveyed sites to develop habitat models incorporating both sources of information.
![IS FIELD WORK REALLY NECESSARY?: INCORPORATING EXPERT KNOWLEDGE WITH FIELD DATA IN A BAYESIAN FRAMEWORK Justine V. Murray, Anne Goldizen, Clive McAlpine, Hugh Possingham, Rebecca O’Leary and Samantha Low Choy The Ecology Centre - University of Queensland - www.uq.edu.au/spatialecology Acknowledgements : thanks to the 9 rock-wallaby experts who participated in the expert elicitation; the landholders and land managers for assistance and access to 466 field sites; QUT for development and use of the tool, especially Allan James and Kerrie Mengersen, and Robert Denham for the original elicitation tool; funding bodies – Mary O’Carroll Animal Welfare Fund, The Foundation for National Parks and Wildlife and The Wildlife Preservation Society of Australia. contact: Justine Murray [email_address] Figure 1: Interactive elicitation expert tool within a GIS interface. The elicitation window shows the interactive boxplot and beta curve that the expert can alter according to his/her perception of the probability of the selected site being occupied by the species. Figure 2: An example of the feedback curves from the elicitation tool. These species response curves depict the probability of presence for each covariate as decided by the expert. The x-axis represents each covariate and the y-axis represents the probability of presence. The bars represent the elicited sites for the categorical covariates and the dots represent the elicited sites for the continuous variables. These plots give an expert a visualisation of their elicited decisions at each site creating a pattern, such as probability of presence increasing with increasing elevation. The boxplots represent the variability in the decisions by the experts for each categorical covariate. For example, a small boxplot represents consistency in the answers. ,[object Object],[object Object],We used an expert elicitation tool and GIS to collect expert opinions at the landscape-scale consistent with the scale used in conservation. Does expert knowledge give us the same results as an extensive data set collected in the field? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Table 1: Results from a logistic regression model run in WinBUGS Bayesian software comparing priors of expert knowledge only (solid grey line) combined with field data (solid black line) and non-informative priors (dashed grey line) combined with field data (dashed black line). (See also text below) Photo: P.Thomas Photo: J. Murray Photo: J. Murray The cost of collecting field data may substantially reduce the budget available for management. We found the expert priors enhanced the predictions based on the field data and focused experts to expressing opinions at scales consistent with those used by management agencies. This approach may be more suitable and more feasible within constraints of management budgets and be beneficial in improving knowledge of rare or elusive species and threatened species distributions. Methods: Sampled 466 sites for Presence/Absence and habitat variables at two scales across northeast New South Wales and southeast Queensland. Interviewed 9 rock-wallaby experts Used interactive GIS tool to elicit expert knowledge on rock-wallaby habitat (Fig. 1). Assessed species response curves from experts (Fig. 2) Developed Bayesian diagnostics Expert knowledge alone Expert knowledge as priors Field data alone Compared models](https://image.slidesharecdn.com/scb-2007-portrait1286/85/scb-2007-portrait-1-320.jpg)
