Assessing and mitigating simulated population-level effects of 3 herbicides to a threatened plant: Application of a species-specific population model of Boltonia decurrens

Amelie Schmolke, Richard Brain, Pernille Thorbek, Daniel Perkins, Valery Forbes

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Extrapolating from organism-level endpoints, as generated from standard pesticide toxicity tests, to populations is an important step in threatened and endangered species risk assessments. We apply a population model for a threatened herbaceous plant species, Boltonia decurrens, to estimate the potential population-level impacts of 3 herbicides. We combine conservative exposure scenarios with dose–response relationships for growth and survival of standard test species and apply those in the species-specific model. Exposure profiles applied in the B. decurrens model were estimated using exposure modeling approaches. Spray buffer zones were simulated by using corresponding exposure profiles, and their effectiveness at mitigating simulated effects on the plant populations was assessed with the model. From simulated exposure effects scenarios that affect plant populations, the present results suggest that B. decurrens populations may be more sensitive to exposures from herbicide spray drift affecting vegetative stages than from runoff affecting early seedling survival and growth. Spray application buffer zones were shown to be effective at reducing effects on simulated populations. Our case study demonstrates how species-specific population models can be applied in pesticide risk assessment to bring organism-level endpoints, exposure assumptions, and species characteristics together in an ecologically relevant context. Environ Toxicol Chem 2018;37:1545–1555.

Original languageEnglish (US)
Pages (from-to)1545-1555
Number of pages11
JournalEnvironmental Toxicology and Chemistry
Volume37
Issue number6
DOIs
StatePublished - Jun 2018

Bibliographical note

Funding Information:
Acknowledgment—The present study was funded by Syngenta Crop Protection. We thank F. Abi-Akar for helping with the data analysis and plotting, D. Desmarteau for providing runoff exposure estimates from exposure models, and G. Sarda for help with model coding. Thanks to 2 reviewers for helpful comments on an earlier version of the manuscript and to J. Gates for manuscript formatting.

Publisher Copyright:
© 2018 SETAC

Keywords

  • Drift
  • Endangered Species Act
  • Individual-based model
  • Pesticide risk assessment
  • Population modeling
  • Runoff

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