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.

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.

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.

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.

Radar tracking and motion-sensitive cameras on flowers reveal the development of pollinator multi-destination routes over large spatial scales.

Central place foragers, such as pollinating bees, typically develop circuits (traplines) to visit multiple foraging sites in a manner that minimizes overall travel distance. Despite being taxonomically widespread, these routing behaviours remain poorly understood due to the difficulty of tracking the foraging history of animals in the wild. Here we examine how bumblebees (Bombus terrestris) develop and optimise traplines over large spatial scales by setting up an array of five artificial flowers arranged in a regular pentagon (50 m side length) and fitted with motion-sensitive video cameras to determine the sequence of visitation. Stable traplines that linked together all the flowers in an optimal sequence were typically established after a bee made 26 foraging bouts, during which time only about 20 of the 120 possible routes were tried. Radar tracking of selected flights revealed a dramatic decrease by 80% (ca. 1500 m) of the total travel distance between the first and the last foraging bout. When a flower was removed and replaced by a more distant one, bees engaged in localised search flights, a strategy that can facilitate the discovery of a new flower and its integration into a novel optimal trapline. Based on these observations, we developed and tested an iterative improvement heuristic to capture how bees could learn and refine their routes each time a shorter route is found. Our findings suggest that complex dynamic routing problems can be solved by small-brained animals using simple learning heuristics, without the need for a cognitive map.

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.

A strong immune response in young adult honeybees masks their increased susceptibility to infection compared to older bees.

Honeybees, Apis mellifera, show age-related division of labor in which young adults perform maintenance ("housekeeping") tasks inside the colony before switching to outside foraging at approximately 23 days old. Disease resistance is an important feature of honeybee biology, but little is known about the interaction of pathogens and age-related division of labor. We tested a hypothesis that older forager bees and younger "house" bees differ in susceptibility to infection. We coupled an infection bioassay with a functional analysis of gene expression in individual bees using a whole genome microarray. Forager bees treated with the entomopathogenic fungus Metarhizium anisopliae s.l. survived for significantly longer than house bees. This was concomitant with substantial differences in gene expression including genes associated with immune function. In house bees, infection was associated with differential expression of 35 candidate immune genes contrasted with differential expression of only two candidate immune genes in forager bees. For control bees (i.e. not treated with M. anisopliae) the development from the house to the forager stage was associated with differential expression of 49 candidate immune genes, including up-regulation of the antimicrobial peptide gene abaecin, plus major components of the Toll pathway, serine proteases, and serpins. We infer that reduced pathogen susceptibility in forager bees was associated with age-related activation of specific immune system pathways. Our findings contrast with the view that the immunocompetence in social insects declines with the onset of foraging as a result of a trade-off in the allocation of resources for foraging. The up-regulation of immune-related genes in young adult bees in response to M. anisopliae infection was an indicator of disease susceptibility; this also challenges previous research in social insects, in which an elevated immune status has been used as a marker of increased disease resistance and fitness without considering the effects of age-related development.

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.

Tracking butterfly movements with harmonic radar reveals an effect of population age on movement distance.

We used harmonic radar to track freely flying Glanville fritillary butterfly (Melitaea cinxia) females within an area of 30 ha. Butterflies originated from large and continuous populations in China and Estonia, and from newly established or old (> 5 years) small local populations in a highly fragmented landscape in Finland. Caterpillars were raised under common garden conditions and unmated females were tested soon after eclosion. The reconstructed flight paths for 66 individuals comprised a total distance of 51 km with high spatial resolution. Butterflies originating from large continuous populations and from old local populations in Finland exhibited similar movement behaviors, whereas butterflies originating from newly established local populations in the fragmented landscape in Finland moved significantly more than the others. There was no difference in the lengths of individual flight bouts, but the new-population females flew more frequently, resulting in longer daily movement tracks. The flight activity of all individuals was affected by environmental conditions, peaking at 19-23 degrees C (depending on population type), in the early afternoon, and during calm weather. Butterflies from all population types showed a strong tendency to follow habitat edges between the open study area and the neighboring woodlands.

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.

Estimation of bumblebee queen dispersal distances using sibship reconstruction method.

Dispersal ability is a key determinant of the propensity of an organism to cope with habitat fragmentation and climate change. Here we quantify queen dispersal in two common bumblebee species in an arable landscape. Dispersal was measured by taking DNA samples from workers in the spring and summer, and from queens in the following spring, at 14 sites across a landscape. The queens captured in the spring must be full sisters of workers that were foraging in the previous year. A range of sibship reconstruction methods were compared using simulated data sets including or no genotyping errors. The program Colony gave the most accurate reconstruction and was used for our analysis of queen dispersal. Comparison of queen dispersion with worker foraging distances was used to take into account an expected low level of false identification of sister pairs which might otherwise lead to overestimates of dispersal. Our data show that Bombus pascuorum and B. lapidarius queens can disperse by at least 3 and 5 km, respectively. These estimates are consistent with inferences drawn from studies of population structuring in common and rare bumblebee species, and suggest that regular gene flow over several kilometres due to queen dispersal are likely to be sufficient to maintain genetic cohesion of ubiquitous species over large spatial scales whereas rare bumblebee species appear unable to regularly disperse over distances greater than 10 km. Our results have clear implications for conservation strategies for this important pollinator group, particularly when attempting to conserve fragmented populations.

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.

Flight metabolic rate and Pgi genotype influence butterfly dispersal rate in the field.

Dispersal is a key life-history trait, especially in species inhabiting fragmented landscapes. The process of dispersal is affected by a suite of morphological, physiological, and behavioral traits, all of which have a more or less complex genetic basis and are affected by the prevailing environmental conditions. To be able to identify genetic and phenotypic effects on dispersal, movements have to be recorded over relevant spatial and temporal scales. We used harmonic radar to track free-flying Glanville fritillary butterflies (Melitaea cinxia) released in the field and reconstructed their flight tracks for several hours. Flight track lengths for individual butterflies ranged from tens of meters to several kilometers. Butterflies were most mobile at midday and in intermediate temperatures. Flight metabolic rate (MR), measured prior to the tracking, explained variation in mobility at all scales studied. One-third of the variation in the distance moved in one hour could be attributed to variation in flight MR. Heterozygous individuals at a single nucleotide polymorphism in the phosphoglucose isomerase (Pgi) gene moved longer distances in the morning and at lower ambient temperatures than homozygous individuals. A similar genotype x temperature interaction was found to affect the metabolic rate. Our results establish connections from molecular variation in a single gene to flight physiology and movement behavior at the landscape level. These results indicate a fitness advantage to the heterozygous genotype in low temperatures and suggest a mechanism by which varying environmental conditions maintain genetic polymorphism in populations.

Pollination biology of fruit-bearing hedgerow plants and the role of flower-visiting insects in fruit-set.

BACKGROUND AND AIMS: In the UK, the flowers of fruit-bearing hedgerow plants provide a succession of pollen and nectar for flower-visiting insects for much of the year. The fruits of hedgerow plants are a source of winter food for frugivorous birds on farmland. It is unclear whether recent declines in pollinator populations are likely to threaten fruit-set and hence food supply for birds. The present study investigates the pollination biology of five common hedgerow plants: blackthorn (Prunus spinosa), hawthorn (Crataegus monogyna), dog rose (Rosa canina), bramble (Rubus fruticosus) and ivy (Hedera helix). METHODS: The requirement for insect pollination was investigated initially by excluding insects from flowers by using mesh bags and comparing immature and mature fruit-set with those of open-pollinated flowers. Those plants that showed a requirement for insect pollination were then tested to compare fruit-set under two additional pollination service scenarios: (1) reduced pollination, with insects excluded from flowers bagged for part of the flowering period, and (2) supplemental pollination, with flowers hand cross-pollinated to test for pollen limitation. KEY RESULTS: The proportions of flowers setting fruit in blackthorn, hawthorn and ivy were significantly reduced when insects were excluded from flowers by using mesh bags, whereas fruit-set in bramble and dog rose were unaffected. Restricting the exposure of flowers to pollinators had no significant effect on fruit-set. However, blackthorn and hawthorn were found to be pollen-limited, suggesting that the pollination service was inadequate in the study area. CONCLUSIONS: Ensuring strong populations of insect pollinators may be essential to guarantee a winter fruit supply for birds in UK hedgerows.

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.

Bumblebee flight distances in relation to the forage landscape.

1. Foraging range is a key aspect of the ecology of 'central place foragers'. Estimating how far bees fly under different circumstances is essential for predicting colony success, and for estimating bee-mediated gene flow between plant populations. It is likely to be strongly influenced by forage distribution, something that is hard to quantify in all but the simplest landscapes; and theories of foraging distance tend to assume a homogeneous forage distribution. 2. We quantified the distribution of bumblebee Bombus terrestris L. foragers away from experimentally positioned colonies, in an agricultural landscape, using two methods. We mass-marked foragers as they left the colony, and analysed pollen from foragers returning to the colonies. The data were set within the context of the 'forage landscape': a map of the spatial distribution of forage as determined from remote-sensed data. To our knowledge, this is the first time that empirical data on foraging distances and forage availability, at this resolution and scale, have been collected and combined for bumblebees. 3. The bees foraged at least 1.5 km from their colonies, and the proportion of foragers flying to one field declined, approximately linearly, with radial distance. In this landscape there was great variation in forage availability within 500 m of colonies but little variation beyond 1 km, regardless of colony location. 4. The scale of B. terrestris foraging was large enough to buffer against effects of forage patch and flowering crop heterogeneity, but bee species with shorter foraging ranges may experience highly variable colony success according to location.

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.

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.