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A risk assessment example for soil invertebrates using spatially explicit agent-based models.

Melissa Reed1, Tania Alvarez2, Sónia Chelinho3

  • 1Chemicals Regulation Directorate, HSE, Mallard House, Kings Pool, York, UK.

Integrated Environmental Assessment and Management
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Summary
This summary is machine-generated.

New agent-based models (ABMs) refine plant protection product risk assessment for soil invertebrates like earthworms. These models predict population recovery within a year, regardless of pesticide application method.

Keywords:
CollembolanEarthwormsPesticide risk assessmentPopulation modelingSoil ecotoxicology

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Area of Science:

  • Environmental toxicology
  • Ecotoxicology
  • Soil ecology

Background:

  • Current plant protection product (PPP) risk assessment relies on lab tests for acute toxicity and reproduction effects on soil invertebrates.
  • Higher-tier assessments use costly field trials due to a lack of modeling for extrapolating lower-tier data to population effects.
  • Existing methods struggle with landscape variability and extrapolation to population-level impacts.

Purpose of the Study:

  • To introduce and demonstrate two spatially explicit agent-based models (ABMs) for collembolans and earthworms as refinement tools in PPP risk assessment.
  • To provide refined risk assessments for various pesticide application scenarios in potato crops.
  • To explore the potential of mechanistic modeling for ecologically informed extrapolation of toxicity data.

Main Methods:

  • Development and application of two spatially explicit agent-based models (ABMs) for earthworms and collembolans.
  • Simulation of pesticide effects under different application scenarios (overall, in-furrow, soil-incorporated) on potato crops.
  • Incorporation of individual and landscape variability into the population models.

Main Results:

  • Population models suggest soil invertebrate populations are likely to recover within one year post-pesticide application, irrespective of the application method.
  • Lower predicted environmental concentrations (PECsoil) could result in greater population-level effects, depending on pesticide spatial heterogeneity and organism behavior.
  • Agent-based models elucidated population-level effects of spatial-temporal exposure variations, providing outputs aligned with protection goals.

Conclusions:

  • Agent-based models offer a valuable refinement for current plant protection product risk assessment, improving ecological relevance and extrapolation capabilities.
  • The choice of model outputs should align with specific protection goals, utilizing existing toxicity and fate data for parameterization.
  • Further evaluation and documentation of these models are recommended following established guidance to minimize data requirements and enhance reliability.