A guide to eliciting and using expert knowledge in Bayesian ecological models

A guide to eliciting and using expert knowledge in Bayesian ecological models Ecology Letters (2010) 13: 900–914 Expert knowledge in ecology is gaining momentum as a tool for conservation decision‐making where data are lacking. Yet, little information is available to help a researcher decide whether expert opinion is useful for their model, how an elicitation should be conducted, what the most relevant method for elicitation is and how this can be translated into prior distributions for analysis in a Bayesian model. In this study, we provide guidance in using expert knowledge in a transparent and credible manner to inform ecological models and ultimately natural resource and conservation decision‐making. We illustrate the decisions faced when considering the use of expert knowledge in a model with the help of two real ecological case studies. These examples are explored further to examine the impact of expert knowledge through ‘priors’ in Bayesian modeling and specifically how to minimize potential bias. Finally, we make recommendations on the use of expert opinion in ecology. We believe if expert knowledge is elicited and incorporated into ecological models with the same level of rigour provided in the collection and use of empirical data, expert knowledge can increase the precision of models and facilitate informed decision‐making in a cost‐effective manner. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ecology Letters Wiley

A guide to eliciting and using expert knowledge in Bayesian ecological models

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Abstract

Ecology Letters (2010) 13: 900–914 Expert knowledge in ecology is gaining momentum as a tool for conservation decision‐making where data are lacking. Yet, little information is available to help a researcher decide whether expert opinion is useful for their model, how an elicitation should be conducted, what the most relevant method for elicitation is and how this can be translated into prior distributions for analysis in a Bayesian model. In this study, we provide guidance in using expert knowledge in a transparent and credible manner to inform ecological models and ultimately natural resource and conservation decision‐making. We illustrate the decisions faced when considering the use of expert knowledge in a model with the help of two real ecological case studies. These examples are explored further to examine the impact of expert knowledge through ‘priors’ in Bayesian modeling and specifically how to minimize potential bias. Finally, we make recommendations on the use of expert opinion in ecology. We believe if expert knowledge is elicited and incorporated into ecological models with the same level of rigour provided in the collection and use of empirical data, expert knowledge can increase the precision of models and facilitate informed decision‐making in a cost‐effective manner.

Journal

Ecology LettersWiley

Published: Jul 1, 2010

References

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