A User-Friendly Kinetic Model Incorporating Regression Models for Estimating Pesticide Accumulation in Diverse Earthworm Species Across Varied Soils

Existing models for estimating pesticide bioconcentration
in earthworms
exhibit limited applicability across different chemicals, soils and
species which restricts their potential as an alternative, intermediate
tier for risk assessment. We used experimental data from uptake and
elimination studies using three earthworm species (Lumbricus terrestris, Aporrectodea
caliginosa, Eisenia fetida), five pesticides (log Kow 1.69–6.63)
and five soils (organic matter content = 0.972–39.9 wt %) to
produce a first-order kinetic accumulation model. Model applicability
was evaluated against a data set of 402 internal earthworm concentrations
reported from the literature including chemical and soil properties
outside the data range used to produce the model. Our models accurately
predict body load using either porewater or bulk soil concentrations,
with at least 93.5 and 84.3% of body load predictions within a factor
of 10 and 5 of corresponding observed values, respectively. This suggests
that there is no need to distinguish between porewater and soil exposure
routes or to consider different uptake and elimination pathways when
predicting earthworm bioconcentration. Our new model not only outperformed
existing models in characterizing earthworm exposure to pesticides
in soil, but it could also be integrated with models that account
for earthworm movement and fluctuating soil pesticide concentrations
due to degradation and transport.