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-wallabies Petrogale penicillata

Murray, J.V., Goldizen, A.W., O'Leary, R.A., McAlpine, C.A., Possingham, H.P. and Low Choy, S. (2009) 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-wallabies Petrogale penicillata. Journal of Applied Ecology, 46 4: 842-851. doi:10.1111/j.1365-2664.2009.01671.x


Author Murray, J.V.
Goldizen, A.W.
O'Leary, R.A.
McAlpine, C.A.
Possingham, H.P.
Low Choy, S.
Title 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-wallabies Petrogale penicillata
Formatted title
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-wallabies Petrogale penicillata
Journal name Journal of Applied Ecology   Check publisher's open access policy
ISSN 0021-8901
1365-2664
Publication date 2009-08
Year available 2009
Sub-type Article (original research)
DOI 10.1111/j.1365-2664.2009.01671.x
Open Access Status DOI
Volume 46
Issue 4
Start page 842
End page 851
Total pages 10
Place of publication United Kingdom
Publisher Wiley-Blackwell Publishing Ltd.
Collection year 2010
Language eng
Subject C1
9699 Other Environment
050104 Landscape Ecology
0608 Zoology
1604 Human Geography
Formatted abstract
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.

Keyword Bayesian
Elicitation
Expert knowledge
Extrapolation
Model transferability
Spatial habitat modelling
Q-Index Code C1
Q-Index Status Confirmed Code

 
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Created: Wed, 09 Dec 2009, 11:23:05 EST by Hayley Ware on behalf of Faculty of Science