Simulating Honey Bee Large‐Scale Colony Feeding Studies Using the BEEHAVE Model—Part II: Analysis of Overwintering Outcomes

Abstract

Large-scale colony feeding studies (LSCFSs) aim to assess potential pesticide exposure to and effects on honey bees at the colony level. However, these studies are sometimes affected by high losses of control colonies, indicating that other stressors may impact colonies and confound the analysis of potential pesticide impacts. We assessed the study design and environmental conditions experienced by the untreated control colonies across 7 LSCFSs conducted in North Carolina (USA). Overwintering success differed considerably among the studies, as did their initial colony conditions, amount and timing of sugar feeding, landscape composition, and weather. To assess the effects of these drivers on control colonies' overwintering success, we applied the mechanistic colony model BEEHAVE. Sugar feedings and initial status of the simulated colonies were more important for fall colony condition than were landscape and weather. Colonies that had larger colony sizes and honey stores in the fall were those that began with larger honey stores, were provided more sugar, and had supplemental feedings before the fall. This information can be used to inform the standardization of a study design, which can increase the likelihood of overwintering survival of controls and help ensure that LSCFSs are comparable. Our study demonstrates how a mechanistic model can be used to inform study designs for higher tier effects studies.

Simulating Honey Bee Large‐Scale Colony Feeding Studies Using the BEEHAVE Model—Part I: Model Validation

“…These 2 endpoints were identified as most indicative of colony health (e.g., Genersch et al 2010; Austin 2014; Döke et al 2015) and had the lowest uncertainty in data reported from the studies. Fall was identified as a particularly important time of the year because colony condition prior to overwintering is related to subsequent overwinter survival (Abi‐Akar et al 2020, this issue). The parameter combination that resulted in the best match between apiary‐specific simulations and CCA data with the uncertainty range applied is summarized in Table 3.…”

“…The remaining variabilities between colonies experiencing very similar conditions and management point to factors influencing colony dynamics that are beyond what can be reasonably controlled in a field‐based study. Large variability in outcomes of overwintering success (Abi‐Akar et al 2020, this issue) further suggests that factors may be influencing colony dynamics and overwintering success in LSCFSs that are currently not well understood. Such factors and processes are not captured in BEEHAVE because the model is based on current knowledge about honey bee colonies, and on initial conditions and other factors reported in the studies.…”

“…In that respect, the model can be used to estimate the relative impact of the different conditions on colony outcomes at different times of the first year. For instance, conditions and colony managements from the different studies can be addressed systematically, and recommendations for study designs resulting in defined outcomes (e.g., prior to overwintering) can be derived (Abi‐Akar et al 2020, this issue).…”

Research on the usefulness of computer model in assessing the G-force impact on honeybees (Apis mellifera) – current stage of the BeeGs project

“…As the process of full model creation is long and complicated and the most developed model nowadays, BEEHAVE (Becher et al 2014), is available on the project's website and can be freely downloaded and used (BEEHAVE -The Model 2013), the author decided to expand it and create dedicated modules describing "G-forced" specimens. Predictions correctness of the BEEHAVE has been confirmed multiple times by different scientific groups (Horn et al 2016, Agatz et al 2019, Abi-Akar et al 2020). The model is based on the NetLogo software, making it simple to use while keeping high development possibilities (Tisue and Wilensky 2004).…”

A systems‐based approach to the environmental risk assessment of multiple stressors in honey bees

“…The original BEEHAVE model (Becher et al., 2013, 2014) was used to simulate the impacts of foraging stress (Horn et al., 2015), pesticides and pharmaceuticals (Rumkee et al., 2015; Carter et al., 2020), the Asian hornet, Vespa velutina (Requier et al., 2020), sublethal effects (Thorbek et al., 2017a, Schmolke et al., 2019) and to evaluate overwintering success (Abi‐Akar et al., 2020) and pesticide protection goals (Thorbek et al., 2017b). There has been development of BEEHAVE relating to foraging (BEESCOUT; Becher et al., 2016), a pollen exposure‐effects module (explicitly linking exposure to pesticide residues in pollen with colony effects, Schmolke et al., 2019) and model evaluation using field data (Agatz et al., 2019; Schmolke et al., 2020), which addresses some of the issues raised previously (EFSA PPR Panel, 2015).…”