Marcot, B. G.  1999.  Use of Bayesian belief network models for evaluating Final EIS alternatives for wildlife viability.  Presented 10 March 1999 at Annual Northwest Section Conference, The Wildlife Society, Bozeman MT.
 

    The Terrestrial Staff of the Science Advisory Group has developed “causal web” models relating key environmental correlates (KECs) of wildlife species, to potential population response under several Final EIS alternatives for the Interior Columbia Basin Ecosystem Management Project.  The models involve use of Bayesian belief networks (BBNs), which represent conditional probabilities of population response given environmental conditions at two scales of spatial resolution.  The KECs were identified by use of literature and expert panels and formalized into a Species-Environment Relations database.  The probabilities and BBN model structures were derived from literature and, where needed, expert judgment.  The BBN models provide a consistent, testable framework by which to represent simple habitat relations of a wide array of species.  Sensitivity analyses using entropy-reduction metrics identify controlling KECs that may be worthy of further study or monitoring.  BBN species modeling represents a major step beyond using expert panels to evaluate population viability; it opens the “black box” of expert opinion by formally modeling the subjacent ecological relations.