Modeling pesticide residues in nectar and pollen in support of pesticide exposure assessment for honeybees: A generic modeling approach

Pesticide residues in nectar and pollen of plants can damage honeybees; however, few modeling approaches have simulated residue levels in nectar and pollen in support of exposure assessment for honeybees. This study introduced a generic modeling approach based on plant uptake models and simple partitioning rules that specifies soil incorporation and foliar spray application scenarios of pesticides and is flexible for conducting variability analysis for various environmental conditions, pesticide application patterns, chemical individuals, and plant varieties. The results indicated that, in general, systemic or moderate lipophilicity (log K-OW of ~2.5) pesticides have relatively high simulated residue levels in nectar and pollen because of the enhanced residue uptake process from soil. For non-systemic or highly lipophilic pesticides, the residue uptake via leaf surface deposition pathway can be enhanced, and more residues will be bioaccumulated in pollen than nectar due to a relatively high lipid content of pollen (as compared to nectar), but the overall residue levels in nectar and pollen are lower than systemic or moderately lipophilic pesticides. The variability analysis showed that environmental conditions, pesticide application patterns, chemical properties, and plant varieties cause considerable variations in simulated residue levels in nectar and pollen, indicating that spatiotemporal, chemical, and plant-related factors must be considered in pesticide exposure assessment for honeybees. Moreover, the comparison between the simulated and measured data showed a high degree of consistency, indicating that the proposed model could be used to conduct a screening-level pesticide exposure assessment for honeybees.

Automated summary

The study found that different types of pesticides leave varying levels of residues in the nectar and pollen of plants, which in turn have different impacts on honeybees. The high consistency between simulated and measured data indicates that the proposed model can be used for screening-level pesticide exposure assessment for honeybees.