Influence diagrams are a conceptual modeling tool that graphically represents the causal relationships between decisions, external factors, uncertainties and outcomes. They are useful for:

• building a common understanding of “how things work”;
• facilitating communication among technical experts, decision makers and stakeholders;
• integrating knowledge from different sources in decision making (e.g., science, TEK, etc.);
• encouraging disciplined thinking about cause and effect relationships;
• being explicit about uncertainty, in particular, emphasizing the existence of competing hypotheses and facilitating informed debate about them;
• defining evaluation criteria;
• determining modeling and information needs directly related to the evaluation criteria;
• structuring subsequent quantitative modeling (especially when constructed under more formalized rules to describe inter-related conditional probabilities);
• documenting the basis for and improving the transparency of expert judgments

On the Bridge River Water Use Plan in British Columbia, fisheries scientists developed an influence diagram to document hypotheses about the major factors limiting fish populations.

(Click image to enlarge)

In the absence of a reliable model to estimate fish biomass directly, the boxes in bold were selected as proxy or indirect indicators of fish impacts. Interestingly, it was aboriginal participants who identified a need to include tributary spawning success.

An attribute defined as a “spawning success utility index” combined estimates of spawning success in each tributary (a function of water elevations associated with each proposed management alternative) and a tributary weighting (a judgment of the contribution of each tributary to overall juvenile recruitment in the reservoir). The estimate of spawning success as a function of water levels was provided partly by scientific insights and analysis (how long and at what depth can eggs survive inundation) and partly by aboriginal knowledge (how flexible are fish in their spawn timing). A tributary weighting was provided by aboriginal knowledge holders, based on their knowledge of the relative utilization of the tributaries.

This application provides an example of how different sources of knowledge can be combined to define hypotheses and estimate impacts, resulting in the use of that knowledge in a decision-relevant way.

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