Adapting population models for application in pesticide risk assessment: A case study with Mead's milkweed. (29th June 2018) - Schmolke, Amelie; Roy, Colleen; Brain, Richard; Forbes, Valery
Abstract: Population models can facilitate assessment of potential impacts of pesticides on populations or species rather than individuals and have been identified as important tools for pesticide risk assessment of nontarget species including those listed under the Endangered Species Act. Few examples of population models developed for this specific purpose are available; however, population models are commonly used in conservation science as a tool to project the viability of populations and the long‐term outcomes of management actions. We present a population model for Mead's milkweed ( Asclepias meadii ), a species listed as threatened under the Endangered Species Act throughout its range across the Midwestern United States. We adapted a published population model based on demographic field data for application in pesticide risk assessment. Exposure and effects were modeled as reductions of sets of vital rates in the transition matrices, simulating both lethal and sublethal effects of herbicides. Two herbicides, atrazine and mesotrione, were used as case study examples to evaluate a range of assumptions about potential exposure–effects relationships. In addition, we assessed buffers (i.e., setback distances of herbicide spray applications from the simulated habitat) as hypothetical mitigation scenarios and evaluated their influence on population‐level effects in the model. The model results suggest that buffers can be effective at reducing risk from herbicide drift to plant populations. These case studies demonstrate that existing population models can be adopted and integrated with exposure and effects information for use in pesticide risk assessment. Environ Toxicol Chem 2018;37:2235–2245. © 2018 SETAC Abstract : A model based on demographic field data of a threatened milkweed is applied to assess potential long‐term population‐level effects of exposure to herbicide spray drift. Uncertainties in effects are addressed with multiple scenarios.