title: Deconstructing the surrogate species concept: a life history approach to the protection of ecosystem services.
abstract: The use of the surrogate species concept is widespread in environmental risk assessment and in efforts to protect species that provide ecosystem services, yet there are no standard protocols for the choice of surrogates. Surrogates are often chosen on the basis of convenience or vague resemblances in physiology or life history to species of concern. Furthermore, our ability to predict how species of concern will fare when subjected to disturbances such as environmental contaminants or toxicants is often based on woefully misleading comparisons of static toxicity tests. Here we present an alternative approach that features a simple mathematical model parameterized with life history data applied to an assemblage of species that provide an important ecosystem service: a suite of parasitoid wasps that provide biological control of agricultural pests. Our results indicate that these parasitoid wasp species have different population responses to toxic insult--that is, we cannot predict how all four species will react to pesticide exposure simply by extrapolating from the response of any one species. Furthermore, sensitivity analysis of survivorship and reproduction demonstrates that the life stage most sensitive to pesticide disturbance varies among species. Taken together, our results suggest that the ability to predict the fate of a suite of species using the response of just one species (the surrogate species concept) is widely variable and potentially misleading.
authors.forename: John E
authors.initials: JE
authors.lastname: Banks
authors.forename: John D
authors.initials: JD
authors.lastname: Stark
authors.forename: Roger I
authors.initials: RI
authors.lastname: Vargas
authors.forename: Azmy S
authors.initials: AS
authors.lastname: Ackleh
mesh_terms: D000818:Animals; D001181:Arthropods / Q000502:physiology*; D003247:Conservation of Natural Resources / Q000379:methods*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D008675:Metamorphosis, Biological; D008954:Models, Biological