watervulnerability

Sawtooth National Forest Watershed Vulnerability Assessment, Intermountain Region (R4)
that depicts hypothesized causes, effects, and ecological interactions) can be readily modified to reflect
new information or differences in perceptions about key relationships (Figure 4). Outcomes also are
expressed as probabilities, so uncertainty is explicit.
Bayesian belief networks (BBN) were constructed through a series of meetings with Boise and Sawtooth
Forest biologists and the Rocky Mountain Research Station in 2004 to identify what baseline condition
we believed possible when
multiple indicators and
pathways had certain
functionality outcomes.
Conceptual models (boxand-arrow
diagrams) that
depicted the hypothesized
causal relationships were
developed to show how
each indicator resulted in
pathway determinations and
specific pathway outcomes
resulted in an overall
physical or biological
baseline condition. Each
BBN network variable or
“node” was described as a set of discrete states that represented possible conditions or values, given the
node’s definition. Arrows represent dependence or a cause-and-effect relationship between corresponding
nodes. Conditional dependencies among nodes were represented by conditional probability tables (CPTs)
that quantify the combined response of each node to its contributing nodes, along with the uncertainty in
that response. The BBN was implemented in the modeling shell Netica software (Norsys Software Corp).
Key model assumptions included:
Figure 4. Bayesian belief network for determining overall physical condition from the
six matrix pathways.
• All independent variables (Parent Nodes) in each model exert some influence on the dependent
variables (Daughter Nodes). There are no “inert” variables in the Bayesian belief networks and
influence diagrams.
• Some variables may exert greater influence than others. For example, large pools and substrate
embeddedness were “weighted” more heavily than four other WCIs in the belief network
developed for evaluating the Aquatic Habitat pathway functional rating. In other words, the
probabilities in the relation table reflect a belief that the functional ratings for large pools and
substrate embeddedness exert greater influence on the overall Aquatic Habitat pathway than any
of the other four WCIs.
• Where all independent variables (parent node are functioning appropriately, there is zero
probability that the overall pathway/threat (daughter node) will be functioning at risk.
Conversely, where all independent variables (parent nodes) are functioning at risk, there is zero
probability that the overall pathway/threat (daughter node) will be functioning appropriately.
• The probability that the overall pathway (daughter node) is functioning appropriately decreases
incrementally with departure from the FA condition in its parent nodes. Conversely, the
probability that the overall pathway or risk (daughter node) is functioning at unacceptable risk
(FUR) decreases incrementally with improvement from the FUR condition in its parent nodes.
162 Assessing the Vulnerability of Watersheds to Climate Change