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Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides

Topping, C. J., Kjaer, L. J., Hommen, U., Høye, T. T., Preuss, T. G., Sibly, R. M. ORCID: and van Vliet, P. (2014) Recovery based on plot experiments is a poor predictor of landscape-level population impacts of agricultural pesticides. Environmental Toxicology and Chemistry, 33 (7). pp. 1499-1507. ISSN 0730-7268

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To link to this item DOI: 10.1002/etc.2388


Current European Union regulatory risk assessment allows application of pesticides provided that recovery of nontarget arthropods in-crop occurs within a year. Despite the long-established theory of source-sink dynamics, risk assessment ignores depletion of surrounding populations and typical field trials are restricted to plot-scale experiments. In the present study, the authors used agent-based modeling of 2 contrasting invertebrates, a spider and a beetle, to assess how the area of pesticide application and environmental half-life affect the assessment of recovery at the plot scale and impact the population at the landscape scale. Small-scale plot experiments were simulated for pesticides with different application rates and environmental half-lives. The same pesticides were then evaluated at the landscape scale (10 km × 10 km) assuming continuous year-on-year usage. The authors' results show that recovery time estimated from plot experiments is a poor indicator of long-term population impact at the landscape level and that the spatial scale of pesticide application strongly determines population-level impact. This raises serious doubts as to the utility of plot-recovery experiments in pesticide regulatory risk assessment for population-level protection. Predictions from the model are supported by empirical evidence from a series of studies carried out in the decade starting in 1988. The issues raised then can now be addressed using simulation. Prediction of impacts at landscape scales should be more widely used in assessing the risks posed by environmental stressors.

Item Type:Article
Divisions:Life Sciences > School of Biological Sciences > Ecology and Evolutionary Biology
ID Code:37866

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