VespAI: a deep learning-based system for the detection of invasive hornets.

The invasive hornet Vespa velutina nigrithorax is a rapidly proliferating threat to pollinators in Europe and East Asia. To effectively limit its spread, colonies must be detected and destroyed early in the invasion curve, however the current reliance upon visual alerts by the public yields low accuracy. Advances in deep learning offer a potential solution to this, but the application of such technology remains challenging. Here we present VespAI, an automated system for the rapid detection of V. velutina. We leverage a hardware-assisted AI approach, combining a standardised monitoring station with deep YOLOv5s architecture and a ResNet backbone, trained on a bespoke end-to-end pipeline. This enables the system to detect hornets in real-time-achieving a mean precision-recall score of ≥0.99-and send associated image alerts via a compact remote processor. We demonstrate the successful operation of a prototype system in the field, and confirm its suitability for large-scale deployment in future use cases. As such, VespAI has the potential to transform the way that invasive hornets are managed, providing a robust early warning system to prevent ingressions into new regions.

Quantifying the impact of an invasive Hornet on Bombus terrestris Colonies.

The invasive hornet Vespa velutina nigrithorax is considered a proliferating threat to pollinators in Europe and Asia. While the impact of this species on managed honey bees is well-documented, effects upon other pollinator populations remain poorly understood. Nonetheless, dietary analyses indicate that the hornets consume a diversity of prey, fuelling concerns for at-risk taxa. Here, we quantify the impact of V. velutina upon standardised commercially-reared colonies of the European bumblebee, Bombus terrestris terrestris. Using a landscape-scale experimental design, we deploy colonies across a gradient of local V. velutina densities, utilising automated tracking to non-invasively observe bee and hornet behaviour, and quantify subsequent effects upon colony outcomes. Our results demonstrate that hornets frequently hunt at B. terrestris colonies, being preferentially attracted to those with high foraging traffic, and engaging in repeated-yet entirely unsuccessful-predation attempts at nest entrances. Notably however, we show that B. terrestris colony weights are negatively associated with local V. velutina densities, indicating potential indirect effects upon colony growth. Taken together, these findings provide the first empirical insight into impacts on bumblebees at the colony level, and inform future mitigation efforts for wild and managed pollinators.

Spatial extent of road pollution: A national analysis.

Roads form vast, pervasive and growing networks across the Earth, causing negative environmental impacts that spill out into a 'road-effect zone'. Previous research has estimated the regional and global extent of these zones using arbitrary distances, ignoring the spatial distribution and distance-dependent attenuation of different forms of road environmental impact. With Great Britain as a study area, we used mapping of roads and realistic estimates of how pollution levels decay with distance to project the spatial distribution of road pollution. We found that 25% of land was less than 79 m from a road, 50% of land was less than 216 m and 75% of land was less than 527 m. Roadless areas were scarce, and confined almost exclusively to the uplands (mean elevation 391 m), with only ca 12% of land in Great Britain more than 1 km from roads and <4% of land more than 2.5 km from roads. Using light, noise, heavy metals, NO2, and particulate matter PM2.5 and PM10 as examples, we estimate that roads have a zone of influence that extends across >70% of the land area. Potentially less than 6% of land escapes any impact, resulting in nearly ubiquitously elevated pollution levels. Generalising from this, we find that, whilst the greatest levels of road pollution are relatively localised around the busiest roads, low levels of road pollution (which may be ecologically significant) are pervasive. Our findings demonstrate the importance of incorporating greater realism into road-effect zones and considering the ubiquity of road pollution in global environmental issues. We used Great Britain as a study area, but the findings likely apply to other densely populated regions at present, and to many additional regions in the future due to the predicted rapid expansion of the global road network.

Honey bee colony performance affected by crop diversity and farmland structure: a modeling framework.

Forage availability has been suggested as one driver of the observed decline in honey bees. However, little is known about the effects of its spatiotemporal variation on colony success. We present a modeling framework for assessing honey bee colony viability in cropping systems. Based on two real farmland structures, we developed a landscape generator to design cropping systems varying in crop species identity, diversity, and relative abundance. The landscape scenarios generated were evaluated using the existing honey bee colony model BEEHAVE, which links foraging to in-hive dynamics. We thereby explored how different cropping systems determine spatiotemporal forage availability and, in turn, honey bee colony viability (e.g., time to extinction, TTE) and resilience (indicated by, e.g., brood mortality). To assess overall colony viability, we developed metrics, PH and PP, which quantified how much nectar and pollen provided by a cropping system per year was converted into a colony's adult worker population. Both crop species identity and diversity determined the temporal continuity in nectar and pollen supply and thus colony viability. Overall farmland structure and relative crop abundance were less important, but details mattered. For monocultures and for four-crop species systems composed of cereals, oilseed rape, maize, and sunflower, PH and PP were below the viability threshold. Such cropping systems showed frequent, badly timed, and prolonged forage gaps leading to detrimental cascading effects on life stages and in-hive work force, which critically reduced colony resilience. Four-crop systems composed of rye-grass-dandelion pasture, trefoil-grass pasture, sunflower, and phacelia ensured continuous nectar and pollen supply resulting in TTE > 5 yr, and PH (269.5 kg) and PP (108 kg) being above viability thresholds for 5 yr. Overall, trefoil-grass pasture, oilseed rape, buckwheat, and phacelia improved the temporal continuity in forage supply and colony's viability. Our results are hypothetical as they are obtained from simplified landscape settings, but they nevertheless match empirical observations, in particular the viability threshold. Our framework can be used to assess the effects of cropping systems on honey bee viability and to develop land-use strategies that help maintain pollination services by avoiding prolonged and badly timed forage gaps.

Quantifying the relative predation pressure on bumblebee nests by the European badger (Meles meles) using artificial nests.

Bumblebee populations are declining. Factors that impact the size and success of colonies act by either limiting resource availability (bottom-up regulation) or causing mortality, for example, pesticides, disease, and possibly predation (top-down regulation). The impact of predation has not been quantified, and so, the current study used novel artificial nests as a proxy for wild bumblebee nests to quantify the relative predation pressure from badgers in two habitats: woodland and grassland, and at two nesting depths: surface and underground. Badgers occur across most parts of the UK and are known to predate on bumblebee nests. We found that significantly more artificial nests (pots containing bumblebee nest material) were dug up compared with control pots (pots without bumblebee nest material). This shows that artificial nests have the potential to be used as a method to study the predation of bumblebee nests by badgers. In a location of high badger density, predation pressure was greater in woodland than grassland, whereas no difference was observed in relation to nest depth. Woodland and grassland are shared habitats between bumblebees and badgers, and we suggest that higher predation may relate to activity and foraging behavior of badgers in woodland compared with grassland. We discuss how badger predation in different habitats could impact different bumblebee species according to their nesting behaviors. Understanding the relative impact of badger predation on bumblebee colonies provides key information on how such top-down regulation affects bumblebee populations.

Bombus terrestris in a mass-flowering pollinator-dependent crop: A mutualistic relationship?

Bumblebees (Bombus spp.) rely on an abundant and diverse selection of floral resources to meet their nutritional requirements. In farmed landscapes, mass-flowering crops can provide an important forage resource for bumblebees, with increased visitation from bumblebees into mass-flowering crops having an additional benefit to growers who require pollination services. This study explores the mutualistic relationship between Bombus terrestris L. (buff-tailed bumblebee), a common species in European farmland, and the mass-flowering crop courgette (Cucurbita pepo L.) to see how effective B. terrestris is at pollinating courgette and in return how courgette may affect B. terrestris colony dynamics. By combining empirical data on nectar and pollen availability with model simulations using the novel bumblebee model Bumble-BEEHAVE, we were able to quantify and simulate for the first time, the importance of courgette as a mass-flowering forage resource for bumblebees. Courgette provides vast quantities of nectar to ensure a high visitation rate, which combined with abundant pollen grains, enables B. terrestris to have a high pollination potential. While B. terrestris showed a strong fidelity to courgette flowers for nectar, courgette pollen was not found in any pollen loads from returning foragers. Nonetheless, model simulations showed that early season courgette (nectar) increased the number of hibernating queens, colonies, and adult workers in the modeled landscapes. Synthesis and applications. Courgette has the potential to improve bumblebee population dynamics; however, the lack of evidence of the bees collecting courgette pollen in this study suggests that bees can only benefit from this transient nectar source if alternative floral resources, particularly pollen, are also available to fulfill bees' nutritional requirements in space and time. Therefore, providing additional forage resources could simultaneously improve pollination services and bumblebee populations.

Bumble-BEEHAVE: A systems model for exploring multifactorial causes of bumblebee decline at individual, colony, population and community level.

World-wide declines in pollinators, including bumblebees, are attributed to a multitude of stressors such as habitat loss, resource availability, emerging viruses and parasites, exposure to pesticides, and climate change, operating at various spatial and temporal scales. Disentangling individual and interacting effects of these stressors, and understanding their impact at the individual, colony and population level are a challenge for systems ecology. Empirical testing of all combinations and contexts is not feasible. A mechanistic multilevel systems model (individual-colony-population-community) is required to explore resilience mechanisms of populations and communities under stress.We present a model which can simulate the growth, behaviour and survival of six UK bumblebee species living in any mapped landscape. Bumble-BEEHAVE simulates, in an agent-based approach, the colony development of bumblebees in a realistic landscape to study how multiple stressors affect bee numbers and population dynamics. We provide extensive documentation, including sensitivity analysis and validation, based on data from literature. The model is freely available, has flexible settings and includes a user manual to ensure it can be used by researchers, farmers, policy-makers, NGOs or other interested parties.Model outcomes compare well with empirical data for individual foraging behaviour, colony growth and reproduction, and estimated nest densities.Simulating the impact of reproductive depression caused by pesticide exposure shows that the complex feedback mechanisms captured in this model predict higher colony resilience to stress than suggested by a previous, simpler model. Synthesis and applications. The Bumble-BEEHAVE model represents a significant step towards predicting bumblebee population dynamics in a spatially explicit way. It enables researchers to understand the individual and interacting effects of the multiple stressors affecting bumblebee survival and the feedback mechanisms that may buffer a colony against environmental stress, or indeed lead to spiralling colony collapse. The model can be used to aid the design of field experiments, for risk assessments, to inform conservation and farming decisions and for assigning bespoke management recommendations at a landscape scale.

Searching for nests of the invasive Asian hornet (Vespa velutina) using radio-telemetry.

Asian hornets (Vespa velutina) are voracious predators of bees, and are the latest emerging threat to managed and wild pollinator populations in Europe. To prevent establishment or reduce the rate of spread of V. velutina, early detection and destruction of nests is considered the only option. Detection is difficult as their nests are well hidden and flying hornets are difficult to follow over long distances. We address this challenge by tracking individual V. velutina workers flying back to their nests using radio telemetry for the first time, finding five previously undiscovered nests, up to 1.33 km from hornet release points. Hornets can fly with 0.28 g tags if the tag:hornet ratio is less than 0.8. This method offers a step-change in options to tackle the spread of this invader, providing an efficient means of finding V. velutina nests in complex environments to manage this emerging threat to pollinators.

Monitoring Neonicotinoid Exposure for Bees in Rural and Peri-urban Areas of the U.K. during the Transition from Pre- to Post-moratorium.

Concerns regarding the impact of neonicotinoid exposure on bee populations recently led to an EU-wide moratorium on the use of certain neonicotinoids on flowering crops. Currently, evidence regarding the impact, if any, the moratorium has had on bees' exposure is limited. We sampled pollen and nectar from bumblebee colonies in rural and peri-urban habitats in three U.K. regions: Stirlingshire, Hertfordshire, and Sussex. Colonies were sampled over three years: prior to the ban (2013), during the initial implementation when some seed-treated winter-sown oilseed rape was still grown (2014), and following the ban (2015). To compare species-level differences, in 2014 only, honeybee colonies in rural habitats were also sampled. Over half of all samples were found to be contaminated ( n = 408), with thiamethoxam being the compound detected at the highest concentrations in honeybee- (up to 2.29 ng/g in nectar in 2014, median ≤ 0.1 ng/g, n = 79) and bumblebee-collected pollen and nectar (up to 38.77 ng/g in pollen in 2013, median ≤ 0.12 ng/g, n = 76). Honeybees were exposed to higher concentrations of neonicotinoids than bumblebees in 2014. While neonicotinoid exposure for rural bumblebees declined post-ban (2015), suggesting a positive impact of the moratorium, the risk of neonicotinoid exposure for bumblebees in peri-urban habitats remained largely the same between 2013 and 2015.

Drought reduces floral resources for pollinators.

Climate change is predicted to result in increased occurrence and intensity of drought in many regions worldwide. By increasing plant physiological stress, drought is likely to affect the floral resources (flowers, nectar and pollen) that are available to pollinators. However, little is known about impacts of drought at the community level, nor whether plant community functional composition influences these impacts. To address these knowledge gaps, we investigated the impacts of drought on floral resources in calcareous grassland. Drought was simulated using rain shelters and the impacts were explored at multiple scales and on four different experimental plant communities varying in functional trait composition. First, we investigated the effects of drought on nectar production of three common wildflower species (Lathyrus pratensis, Onobrychis viciifolia and Prunella vulgaris). In the drought treatment, L. pratensis and P. vulgaris had a lower proportion of flowers containing nectar and O. viciifolia had fewer flowers per raceme. Second, we measured the effects of drought on the diversity and abundance of floral resources across plant communities. Drought reduced the abundance of floral units for all plant communities, irrespective of functional composition, and reduced floral species richness for two of the communities. Functional diversity did not confer greater resistance to drought in terms of maintaining floral resources, probably because the effects of drought were ubiquitous across component plant communities. The findings indicate that drought has a substantial impact on the availability of floral resources in calcareous grassland, which will have consequences for pollinator behaviour and populations.

Courgette Production: Pollination Demand, Supply, and Value.

Courgette (Cucurbita pepo L.) production in the United Kingdom is estimated to be worth £6.7 million. However, little is known about this crop's requirement for insect-mediated pollination (pollinator dependence) and if pollinator populations in a landscape are able to fulfil its pollination needs (pollination deficit). Consequently, pollination experiments were conducted over 2 yr to explore pollinator dependence and pollination deficit in field-grown courgette in the United Kingdom. Results showed that pollination increased yield by 39% and there was no evidence of pollination limitation on crop yield. This was evidenced by a surprisingly low pollination deficit (of just 3%) and no statistical difference in yield (length grown, circumference, and weight) between open- and hand-pollinated crops. Nonetheless, the high economic value of courgettes means that reducing even the small pollination deficit could still increase profit by ∼£166/ha. Interestingly, 56% of fruit was able to reach marketable size and shape without any pollination. Understanding a crop's requirement for pollinators can aid growers in their decision-making about what varieties and sites should be used. In doing so, they may increase their agricultural resilience and further their economic advantage.

Re-evaluating strategies for pollinator-dependent crops: How useful is parthenocarpy?

Whilst most studies reviewing the reliance of global agriculture on insect pollination advocate increasing the 'supply' of pollinators (wild or managed) to improve crop yields, there has been little focus on altering a crop's 'demand' for pollinators.Parthenocarpy (fruit set in the absence of fertilization) is a trait which can increase fruit quantity and quality from pollinator-dependent crops by removing the need for pollination.Here we present a meta-analysis of studies examining the extent and effectiveness of parthenocarpy-promoting techniques (genetic modification, hormone application and selective breeding) currently being used commercially, or experimentally, on pollinator-dependent crops in different test environments (no pollination, hand pollination, open pollination).All techniques significantly increased fruit quantity and quality in 18 pollinator-dependent crop species (not including seed and nut crops as parthenocarpy causes seedlessness). The degree to which plants experienced pollen limitation in the different test environments could not be ascertained, so the absolute effect of parthenocarpy relative to optimal pollination could not be determined. Synthesis and applications. Parthenocarpy has the potential to lower a crop's demand for pollinators, whilst extending current geographic and climatic ranges of production. Thus, growers may wish to use parthenocarpic crop plants, in combination with other environmentally considerate practices, to improve food security and their economic prospects.

Oilseed rape (Brassica napus) as a resource for farmland insect pollinators: quantifying floral traits in conventional varieties and breeding systems.

Oilseed rape (OSR; Brassica napus L.) is a major crop in temperate regions and provides an important source of nutrition to many of the yield-enhancing insect flower visitors that consume floral nectar. The manipulation of mechanisms that control various crop plant traits for the benefit of pollinators has been suggested in the bid to increase food security, but little is known about inherent floral trait expression in contemporary OSR varieties or the breeding systems used in OSR breeding programmes. We studied a range of floral traits in glasshouse-grown, certified conventional varieties of winter OSR to test for variation among and within breeding systems. We measured 24-h nectar secretion rate, amount, concentration and ratio of nectar sugars per flower, and sizes and number of flowers produced per plant from 24 varieties of OSR representing open-pollinated (OP), genic male sterility (GMS) hybrid and cytoplasmic male sterility (CMS) hybrid breeding systems. Sugar concentration was consistent among and within the breeding systems; however, GMS hybrids produced more nectar and more sugar per flower than CMS hybrid or OP varieties. With the exception of ratio of fructose/glucose in OP varieties, we found that nectar traits were consistent within all the breeding systems. When scaled, GMS hybrids produced 1.73 times more nectar resource per plant than OP varieties. Nectar production and amount of nectar sugar in OSR plants were independent of number and size of flowers. Our data show that floral traits of glasshouse-grown OSR differed among breeding systems, suggesting that manipulation and enhancement of nectar rewards for insect flower visitors, including pollinators, could be included in future OSR breeding programmes.

Modeling Effects of Honeybee Behaviors on the Distribution of Pesticide in Nectar within a Hive and Resultant in-Hive Exposure.

Recently, the causes of honeybee colony losses have been intensely studied, showing that there are multiple stressors implicated in colony declines, one stressor being the exposure to pesticides. Measuring exposure of individual bees within a hive to pesticide is at least as difficult as assessing the potential exposure of foraging bees to pesticide. We present a model to explore how heterogeneity of pesticide distribution on a comb in the hive can be driven by worker behaviors. The model contains simplified behaviors to capture the extremes of possible heterogeneity of pesticide location/deposition within the hive to compare with exposure levels estimated by averaging values across the comb. When adults feed on nectar containing the average concentration of all pesticide brought into the hive on that particular day, it is likely representative of the worst-case exposure scenario. However, for larvae, clustering of pesticide in the comb can lead to higher exposure levels than taking an average concentration in some circumstances. The potential for extrapolating the model to risk assessment is discussed.

Migratory flight behaviour of the pollen beetle Meligethes aeneus.

BACKGROUND: The field ecology of the pollen beetle Meligethes aeneus and its damaging effects on oilseed rape crops are well understood. However, the flight behaviour of M. aeneus, in particular the drivers for migratory movements across the landscape, is not well studied. We combined three established methodologies - suction traps, vertical-looking radar and high-altitude aerial netting - to demonstrate that M. aeneus flies at a range of altitudes at different points during its active season. RESULTS: By linking evidence of high-altitude mass migration with immigration of pollen beetles into oilseed rape fields, we were able to 'ground-truth' the results to characterise the seasonal movements of this pest across the landscape. CONCLUSION: We demonstrate that this novel combination of methodologies can advance our understanding of the population movements of pollen beetles and could provide an opportunity to develop predictive models to estimate the severity and timing of pest outbreaks. © 2017 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Optimal search patterns in honeybee orientation flights are robust against emerging infectious diseases.

Lévy flights are scale-free (fractal) search patterns found in a wide range of animals. They can be an advantageous strategy promoting high encounter rates with rare cues that may indicate prey items, mating partners or navigational landmarks. The robustness of this behavioural strategy to ubiquitous threats to animal performance, such as pathogens, remains poorly understood. Using honeybees radar-tracked during their orientation flights in a novel landscape, we assess for the first time how two emerging infectious diseases (Nosema sp. and the Varroa-associated Deformed wing virus (DWV)) affect bees' behavioural performance and search strategy. Nosema infection, unlike DWV, affected the spatial scale of orientation flights, causing significantly shorter and more compact flights. However, in stark contrast to disease-dependent temporal fractals, we find the same prevalence of optimal Lévy flight characteristics (µ ≈ 2) in both healthy and infected bees. We discuss the ecological and evolutionary implications of these surprising insights, arguing that Lévy search patterns are an emergent property of fundamental characteristics of neuronal and sensory components of the decision-making process, making them robust against diverse physiological effects of pathogen infection and possibly other stressors.

Flight performance of actively foraging honey bees is reduced by a common pathogen.

Sudden and severe declines in honey bee (Apis mellifera) colony health in the US and Europe have been attributed, in part, to emergent microbial pathogens, however, the mechanisms behind the impact are unclear. Using roundabout flight mills, we measured the flight distance and duration of actively foraging, healthy-looking honey bees sampled from standard colonies, before quantifying the level of infection by Nosema ceranae and Deformed Wing Virus complex (DWV) for each bee. Neither the presence nor the quantity of N. ceranae were at low, natural levels of infection had any effect on flight distance or duration, but presence of DWV reduced flight distance by two thirds and duration by one half. Quantity of DWV was shown to have a significant, but weakly positive relation with flight distance and duration, however, the low amount of variation that was accounted for suggests further investigation by dose-response assays is required. We conclude that widespread, naturally occurring levels of infection by DWV weaken the flight ability of honey bees and high levels of within-colony prevalence are likely to reduce efficiency and increase the cost of resource acquisition. Predictions of implications of pathogens on colony health and function should take account of sublethal effects on flight performance.

Predicting Honeybee Colony Failure: Using the BEEHAVE Model to Simulate Colony Responses to Pesticides.

To simulate effects of pesticides on different honeybee (Apis mellifera L.) life stages, we used the BEEHAVE model to explore how increased mortalities of larvae, in-hive workers, and foragers, as well as reduced egg-laying rate, could impact colony dynamics over multiple years. Stresses were applied for 30 days, both as multiples of the modeled control mortality and as set percentage daily mortalities to assess the sensitivity of the modeled colony both to small fluctuations in mortality and periods of low to very high daily mortality. These stresses simulate stylized exposure of the different life stages to nectar and pollen contaminated with pesticide for 30 days. Increasing adult bee mortality had a much greater impact on colony survival than mortality of bee larvae or reduction in egg laying rate. Importantly, the seasonal timing of the imposed mortality affected the magnitude of the impact at colony level. In line with the LD50, we propose a new index of "lethal imposed stress": the LIS50 which indicates the level of stress on individuals that results in 50% colony mortality. This (or any LISx) is a comparative index for exploring the effects of different stressors at colony level in model simulations. While colony failure is not an acceptable protection goal, this index could be used to inform the setting of future regulatory protection goals.

So near and yet so far: harmonic radar reveals reduced homing ability of Nosema infected honeybees.

Pathogens may gain a fitness advantage through manipulation of the behaviour of their hosts. Likewise, host behavioural changes can be a defence mechanism, counteracting the impact of pathogens on host fitness. We apply harmonic radar technology to characterize the impact of an emerging pathogen--Nosema ceranae (Microsporidia)--on honeybee (Apis mellifera) flight and orientation performance in the field. Honeybees are the most important commercial pollinators. Emerging diseases have been proposed to play a prominent role in colony decline, partly through sub-lethal behavioural manipulation of their hosts. We found that homing success was significantly reduced in diseased (65.8%) versus healthy foragers (92.5%). Although lost bees had significantly reduced continuous flight times and prolonged resting times, other flight characteristics and navigational abilities showed no significant difference between infected and non-infected bees. Our results suggest that infected bees express normal flight characteristics but are constrained in their homing ability, potentially compromising the colony by reducing its resource inputs, but also counteracting the intra-colony spread of infection. We provide the first high-resolution analysis of sub-lethal effects of an emerging disease on insect flight behaviour. The potential causes and the implications for both host and parasite are discussed.

BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure.

A notable increase in failure of managed European honeybee Apis mellifera L. colonies has been reported in various regions in recent years. Although the underlying causes remain unclear, it is likely that a combination of stressors act together, particularly varroa mites and other pathogens, forage availability and potentially pesticides. It is experimentally challenging to address causality at the colony scale when multiple factors interact. In silico experiments offer a fast and cost-effective way to begin to address these challenges and inform experiments. However, none of the published bee models combine colony dynamics with foraging patterns and varroa dynamics.We have developed a honeybee model, BEEHAVE, which integrates colony dynamics, population dynamics of the varroa mite, epidemiology of varroa-transmitted viruses and allows foragers in an agent-based foraging model to collect food from a representation of a spatially explicit landscape.We describe the model, which is freely available online (www.beehave-model.net). Extensive sensitivity analyses and tests illustrate the model's robustness and realism. Simulation experiments with various combinations of stressors demonstrate, in simplified landscape settings, the model's potential: predicting colony dynamics and potential losses with and without varroa mites under different foraging conditions and under pesticide application. We also show how mitigation measures can be tested.Synthesis and applications. BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.