The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation
Abstract
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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Cites
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Cited by
Bayesian networks in environmental modelling
Aguilera, P. A., Fernández, A., Fernández, R., Rumí, R., & Salmerón, A. (2011) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2011.06.004 · Cited by 666
Good practice in Bayesian network modelling
Chen, S. H., & Pollino, C. A. (2012) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2012.03.012 · Cited by 657
The Role of Expert Opinion in Environmental Modelling
Krueger, T., Page, T., Hubacek, K., Smith, L., & Hiscock, K. (2012) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2012.01.011 · Cited by 413
Metrics for evaluating performance and uncertainty of Bayesian network models
Marcot, B. G. (2012) · Ecological Modelling · doi:10.1016/j.ecolmodel.2012.01.013 · Cited by 380
Self-citationMantyka-Pringle, C. S., Jardine, T. D., Bradford, L., Bharadwaj, L., Kythreotis, A. P., Fresque-Baxter, J., Kelly, E., Somers, G., Doig, L. E., Jones, P. D., et al. (2017) · Environment International · doi:10.1016/j.envint.2017.02.008 · Cited by 150
“Our broad aimwas therefore to present a theoretical and preliminary BBN for understanding the cumulative environmental impacts of multiple stressors on the SRD ecosystem, including both social and ecological consequences.”
Influential
Metadata
- Authors
- Marcot, B. G., Steventon, J. D., Sutherland, G. D., & McCann, R. K.
- Venue
- Canadian Journal of Forest Research
- Publisher
- Canadian Science Publishing
- Published
- 2006-12-01
- Volume
- 36
- Issue
- 12
- Pages
- 3063-3074
- ISSN
- 0045-5067 (ISSN-L)
- 1208-6037
- OpenAlex
- W1973107043
- Cited by
- 667
- References
- 36
- FWCI
- 13.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Marcot, B. G., Steventon, J. D., Sutherland, G. D., & McCann, R. K. (2006). Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation. Canadian Journal of Forest Research. https://doi.org/10.1139/x06-135
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