Agent-based models (ABMs) explicit handling of space and time and integration of nonlinear interactions between system components to create a system response could facilitate realistic risk assessment modeling. We used this approach to evaluate the impact of spatial dynamic factors on a theoretical risk assessment of an insecticide on a carabid beetle population (based on Bembidion lampros). Results indicated that both impacts and recovery were dependent on period of application, area treated, spatial distribution of stressor, beetle dispersal, and underlying habitat suitability. The impact of the stressor was detected far outside the area to which it was applied, and the extent of this impact was affected by beetle dispersal and landscape structure. The results call into question the validity of the recovery endpoint as assessed by field trials because model recovery was primarily influenced by reinvasion, depleting surrounding areas. Despite the simplicity of the acute stressor/Bembidion system modeled, the results obtained were highly variable dependent on the precise inputs used. Therefore, we suggest that application of modeling to risk assessment in the future will require a much more complete description of the risk assessment problem than has hitherto been the case.