Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation

Canadian Journal of Forest Research - Tập 36 Số 12 - Trang 3063-3074 - 2006
Bruce G. Marcot, J. Douglas Steventon, Glenn D. Sutherland, Robert K McCann

Tóm tắt

Bayesian belief networks (BBNs) are useful tools for modeling ecological predictions and aiding resource-management decision-making. We provide practical guidelines for developing, testing, and revising BBNs. Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model after expert review; testing and calibrating the model with case files to create a beta-level model; and updating the model structure and conditional probabilities with new validation data, creating the final-application gamma-level model. We illustrate and discuss these steps with an empirically based BBN model of factors influencing probability of capture of northern flying squirrels (Glaucomys sabrinus (Shaw)). Testing and updating BBNs, especially with peer review and calibration, are essential to ensure their credibility and reduce bias. Our guidelines provide modelers with insights that allow them to avoid potentially spurious or unreliable models.

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Canadian Journal of Forest Research

Tập 36 Số 12

3063-3074

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