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BACKGROUND
The proportionality principle has been broadly used for over 10 years in regulatory assessments of pesticide residues. It allows extrapolation of supervised field trial data conducted at lower or higher application rates compared to the use pattern under evaluation by adjustment of measured concentrations, assuming direct proportionality between the rates applied and the resulting residues. This work revisits the principle idea by using supervised residue trials sets conducted under identical conditions but with deviating application rates. Four different statistical methods were used to investigate the relationship between application rates and residue concentrations and to draw conclusions on the statistical significance of the direct proportionality assumed.RESULTS
Based on over 5000 individual trial results, the assumption of direct proportionality was not confirmed to be statistically significant (P > 0.05) using three models: direct comparison of application rates and residue concentrations ratios and two linear log-log regression models correlating application rate and residue concentration or only residue concentrations per se. In addition, a fourth model analysed deviations between expected concentrations following direct proportional adjustment and measured residue values from corresponding field trials. In 56% of all cases, the deviation was larger than ±25%, which represents the tolerance usually accepted for the selection of supervised field trials in regulatory assessments.CONCLUSION
Overall, the assumption of direct proportionality between application rates and resulting residue concentrations of pesticides was not statistically significant. Although the proportionality approach is highly pragmatic in regulatory practice, its use should be considered carefully on a case-by-case basis. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. 相似文献Landscape and local habitat traits moderate wild bee communities. However, whether landscape effects differ between local habitat types is largely unknown.
ObjectivesWe explored the way that wild bee communities in three distinct habitats are shaped by landscape composition and the availability of flowering plants by evaluating divergences in response patterns between habitats.
MethodsIn a large-scale monitoring project across 20 research areas, wild bee data were collected on three habitats: near-natural grassland, established flower plantings and residual habitats (e.g. field margins). Additionally, landscape composition was mapped around the research areas.
ResultsOur monitoring produced a dataset of 27,650 bees belonging to 324 species. Bee communities on all three habitats reacted similarly to local flower availability. Intensively managed grassland in the surrounding landscape had an overall negative effect on the studied habitats. Other landscape variables produced diverging response patterns that were particularly pronounced during early and late season. Bee communities in near-natural grassland showed a strong positive response to ruderal areas. Flower plantings and residual habitats such as field margins showed a pronounced positive response to extensively managed grassland and woodland edges. Response patterns regarding bee abundance were consistent with those found for species richness.
ConclusionWe advise the consideration of local habitat type and seasonality when assessing the effect of landscape context on bee communities. A reduction in the intensity of grassland management enhances bee diversity in a broad range of habitats. Moreover, wild bee communities are promoted by habitat types such as ruderal areas or woodland edges.
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