title: Influence diagrams as decision-making tools for pesticide risk management.
abstract: The pesticide policy arena is filled with discussion of probabilistic approaches to assess ecological risk, however, similar discussions about implementing formal probabilistic methods in pesticide risk decision making are less common. An influence diagram approach is proposed for ecological risk-based decisions about pesticide usage. Aside from technical data, pesticide risk management relies on diverse sources, such as stakeholder opinions, to make decisions about what, how, where, and when to spray. Bayesian influence diagrams allow multiple lines of evidence, including process related information from existing data and expert judgment, in 1 inclusive decision model. In ecological risk assessments, data informally incorporated for pesticide usage decisions, such as field and laboratory effect studies along with chemical monitoring and modeling data, can be formally incorporated and expressed in linked causal diagrams. A case study is presented from the perspective of an environmental manager wishing to efficiently control pests while minimizing risk to local aquatic receptors. Exposure modeling results and toxicity studies were incorporated, and an ecological risk assessment was carried out but combined with hypothetical information on spraying efficacy and valuation of outcomes that would be necessary for making risk management decisions. The variables and their links in the influence diagram are ones that are important to a manager and can be manipulated to optimally control pests while protecting nontarget resources.
authors.affiliation: College of William and Mary-VIMS, Gloucester Point, VA 23062, USA. carriger.john@epa.gov
authors.forename: John F
authors.initials: JF
authors.lastname: Carriger
authors.forename: Michael C
authors.initials: MC
authors.lastname: Newman
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D009033:Culicidae; D003657:Decision Making; D004781:Environmental Exposure / Q000517:prevention & control*; D007300:Insect Control; D008954:Models, Biological; D010575:Pesticides / Q000032:analysis / Q000633:toxicity*; D018570:Risk Assessment / Q000379:methods*
chemical_list: D010575:Pesticides