Linking mechanistic toxicology to population models in forecasting recovery from chemical stress: A case study from Jackfish Bay, Ontario, Canada.
Recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating remediation success. Unfortunately, effectively monitoring population status on a routine basis can be difficult and costly. In the present study, the authors describe a framework that can be applied in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) to link chemically induced alterations in molecular and biochemical endpoints to adverse outcomes in whole organisms and populations. The approach employs a simple density-dependent logistic matrix model linked to adverse outcome pathways (AOPs) for reproductive effects in fish. Application of this framework requires a life table for the organism of interest, a measure of carrying capacity for the population of interest, and estimation of the effect of stressors on vital rates of organisms within the study population. The authors demonstrate the framework using linked AOPs and population models parameterized with long-term monitoring data for white sucker (Catostomus commersoni) collected from a study site at Jackfish Bay, Lake Superior, Canada. Individual responses of fish exposed to pulp mill effluent were used to demonstrate the framework's capability to project alterations in population status, both in terms of ongoing impact and subsequent recovery after stressor mitigation associated with process changes at the mill. The general approach demonstrated at the Jackfish Bay site can be applied to characterize population statuses of other species at a variety of impacted sites and can account for effects of multiple stressors (both chemical and nonchemical) and dynamics within complex landscapes (i.e., meta-populations including emigration and immigration processes).
Mid-Continent Ecology Division, US Environmental Protection Agency, Grosse Ile, Michigan, USA.
David H
DH
Miller
Mid-Continent Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Joseph E
JE
Tietge
Aquatic Contaminants Research Division, Environment Canada, Burlington, Ontario, Canada.
Mark E
ME
McMaster
University of New Brunswick, Saint John, New Brunswick, Canada.
Kelly R
KR
Munkittrick
Computer Sciences Corporation (CSC), Grosse Ile, Michigan, USA.
Xiangsheng
X
Xia
Computer Sciences Corporation (CSC), Grosse Ile, Michigan, USA.
David A
DA
Griesmer
Mid-Continent Ecology Division, US Environmental Protection Agency, Duluth, Minnesota, USA.
Gerald T
GT
Ankley
D000818:Animals; D061006:Bays; D003531:Cypriniformes / Q000254:growth & development*; D004781:Environmental Exposure; D005298:Fertility / Q000187:drug effects*; D016015:Logistic Models; D008297:Male; D008954:Models, Biological; D009864:Ontario; D013739:Testosterone / Q000032:analysis; D014865:Waste Disposal, Fluid; D014874:Water Pollutants, Chemical / Q000633:toxicity*
D014874:Water Pollutants, Chemical; D013739:Testosterone
Adverse outcome pathway; Population model; Pulp mill effluent; White sucker