SolBeePop ecotox : A Population Model for Pesticide Risk Assessments of Solitary Bees

• Published in: Environmental toxicology and chemistry 2024-12, Vol.43 (12), p.2645
• Main Authors: Schmolke, Amelie, Galic, Nika, Roeben, Vanessa, Preuss, Thomas G, Miles, Mark, Hinarejos, Silvia
• Format: Article
• Language: English
• Subjects: Animals; Bees - drug effects; Models, Biological; Pesticides - toxicity; Risk Assessment
• ISSN: 0730-7268; 1552-8618
• DOI: 10.1002/etc.5990

In agricultural landscapes, solitary bees occur in a large diversity of species and are important for crop and wildflower pollination. They are distinguished from honey bees and bumble bees by their solitary lifestyle as well as different nesting strategies, phenologies, and floral preferences. Their ecological traits and presence in agricultural landscapes imply potential exposure to pesticides and suggest a need to conduct ecological risk assessments for solitary bees. However, assessing risks to the large diversity of managed and wild bees across landscapes and regions poses a formidable challenge. Population models provide tools to estimate potential population-level effects of pesticide exposures, can support field study design and interpretation, and can be applied to expand study data to untested conditions. We present a population model for solitary bees, SolBeePop , developed for use in the context of ecological risk assessments. The trait-based model extends a previous version with the explicit representation of exposures to pesticides from relevant routes. Effects are implemented in the model using a simplified toxicokinetic-toxicodynamic model, BeeGUTS (GUTS = generalized unified threshold model for survival), adapted specifically for bees. We evaluated the model with data from semifield studies conducted with the red mason bee, Osmia bicornis, in which bees were foraging in tunnels over control and insecticide-treated oilseed rape fields. We extended the simulations to capture hypothetical semifield studies with two soil-nesting species, Nomia melanderi and Eucera pruinosa, which are difficult to test in empirical studies. The model provides a versatile tool for higher-tier risk assessments, for instance, to estimate effects of potential exposures, expanding available study data to untested species, environmental conditions, or exposure scenarios. Environ Toxicol Chem 2024;43:2645-2661. © 2024 SETAC.