Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation
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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…
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Topics
Keywords
- Bayesian network
- Credibility
- Computer science
- Spurious relationship
- Process (computing)
- Machine learning
- Resource (disambiguation)
- Data mining
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