From Lab to Landscape: Assessing the Impact of Pesticides on Pollinator Populations Based on Laboratory Data by Combining ALMaSS and BufferGUTS

Pesticides are designed to eradicate pests from crops, fulfilling an important role in the current agricultural system.

However, nature conservation requires that pesticide applications are protective for non-target organisms, which provide ecosystem services on the other hand.

Environmental risk assessment (ERA) is supposed to strike this balance, but the current use of laboratory derived toxicity thresholds in the landscape context, without consideration of population and landscape dynamics might be too coarse to achieve this task.

Here, we propose to overcome this limitation by coupling the Animal, Landscape, and Man Simulation System with the BufferGUTS model for non-target arthropods.

We conducted a case study of the solitary bee Osmia bicornis exposed to the pesticide formulation Closer (a.i. sulfoxaflor) to assess the integration.

Laboratory survival data of topical and oral exposure to Closer were used to calibrate BufferGUTS models.

The resulting parameters were used to parametrise model organisms in ALMaSS simulations to extrapolate the effects of sulfoxaflor at different exposure levels on population dynamics.

The integration of BufferGUTS into ALMaSS landscape simulation was achieved with high numerical precision, allowing for the calculation of daily survival probabilities for model organisms in the ALMaSS framework.

We found that even extreme application rates only led to negligible population effects in ALMaSS simulations, but an exploratory analysis of pesticide-driven larval mortality showed that effects might be more severe when all life stages are considered.

The work demonstrates how mechanistic modelling embedded into individual based modelling frameworks can support ERA by combining exposure and effect in systems-based ERA tools, bridging the gap between controlled laboratory experiments and realistic landscape-scale risk assessments for next generation ERA.