catchment: catchment Bayesian Network

In bnRep: A Repository of Bayesian Networks from the Academic Literature

catchment Bayesian Network

Description

A framework to diagnose the causes of river ecosystem deterioration using biological symptoms.

Format

A discrete Bayesian network to estimate the probability of individual stressors being causal for biological degradation at the scale of individual riverine ecosystems (Catchment BN). The network was available from an associated repository. The vertices are:

Arable

(Low, Enhanced, Intermediate, High);

N

(Low, Intermediate, High);

Urban

(None, Enhanced, High);

Fines

(Normal, Enhanced);

Nitrate

(Low, Enhanced);

Grazer

(Low, Medium, High);

oPO4

(Low, High);

BufForest

(Low, High);

BOD5

(Low, Enhanced, High);

WaterQ

(Low, Fair, Good);

OrgMatter

(Low, High);

Stagnant

(No, Yes);

HabitatQ

(Low, Fair, Good);

Straight

(No, Yes);

FlowQ

(Low, High);

EPT

(Low, Medium, High);

ASPT

(Low, Medium, High);

SI

(Low, Medium, High);

Shredder

(Low, Medium, High);

Value

An object of class bn.fit. Refer to the documentation of bnlearn for details.

References

Feld, C. K., Saeedghalati, M., & Hering, D. (2020). A framework to diagnose the causes of river ecosystem deterioration using biological symptoms. Journal of Applied Ecology, 57(11), 2271-2284.

bnRep documentation built on April 12, 2025, 1:13 a.m.