Population models, in particular individual-based models, are becoming increasingly important in chemical risk assessment. They can be used to assess recovery of spatially structured populations, after chemical exposure that varies in time and space. We used an IBM and an unstructured, non-spatial, logistic growth model to assess recovery times for 4 aquatic organisms, after application of chlorpyrifos in 4 crops in Southern Europe. The species had different life history (e.g. voltinism, reproductive capacity, mobility). Exposure was derived from a pesticide fate model, following standard EU (FOCUS) scenarios. The full spatially-explicit time-varying exposure patterns were used when the IBM was coupled to a toxicokinetic-toxicodynamic model. A simplified exposure pattern, based on peak concentrations, was used when exposure was linked to effects by means of concentration-effect relationships (CE). We showed that under certain conditions, the logistic growth model approximated the dynamics of the IBMs. We compared the recovery dynamics and recovery times predicted by the three models (logistic equation, IBM-TDM and IBM-CE) for the 4 species, to obtain an understanding of (1) the role spatial processes play in recovery, (2) the conditions under which one needs the full time-varying exposure pattern instead of a simplified peak-based exposure pattern, and (3) the sensitivity of recovery times to the intensity of density dependence and the choice of spatial dimensions.

Recovery of four aquatic invertebrate species after insecticide exposure, using different models for population dynamics and to link exposure with effects

248th National Meeting (2014)

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