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Fig. 2. Centre figure: graphical representation of the full Bayesian network for Neuse estuary eutrophication. Variables are indicated with rounded nodes, and causal relationships are indicated with arrows. Surrounding insets: networks representing submodels of the main network. Shaded nodes indicate model parameters. Double-headed, dashed arrows indicate a correlation between marginal variables that may be the result of exogenous factors, rather than causal influence.

Figure 2 Centre figure: graphical representation of the full Bayesian network for Neuse estuary eutrophication. Variables are indicated with rounded nodes, and causal relationships are indicated with arrows. Surrounding insets: networks representing submodels of the main network. Shaded nodes indicate model parameters. Double-headed, dashed arrows indicate a correlation between marginal variables that may be the result of exogenous factors, rather than causal influence.

Related Figures (4)

Fig. 1. The Neuse River estuary, North Carolina, indicating the region of concern in the present study.
Fig. 1. The Neuse River estuary, North Carolina, indicating the region of concern in the present study.
Fig. 3. Predictive probability distributions of policy-relevant ecosystem attributes. The baseline (no nitrogen reduction) scenario is shown as a solid curve, and the management scenario, corresponding to a 50% reduction in total nitrogen inputs, is shown as a dashed curve o1 diagonally striped bar.
Fig. 3. Predictive probability distributions of policy-relevant ecosystem attributes. The baseline (no nitrogen reduction) scenario is shown as a solid curve, and the management scenario, corresponding to a 50% reduction in total nitrogen inputs, is shown as a dashed curve o1 diagonally striped bar.
Fig. 4. Predictive probability distributions of intermediate diagnostic variables in the network. The baseline scenario is shown as a solid curve, and the management scenario is shown as a dashed curve.
Fig. 4. Predictive probability distributions of intermediate diagnostic variables in the network. The baseline scenario is shown as a solid curve, and the management scenario is shown as a dashed curve.
Related topics:
Decision MakingRisk AnalysisProbability Distribution & ApplicationsNutrient ManagementComplex Adaptive SystemBayesian NetworkUncertainty analysisGraphical Model
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