Agrochemicals interact synergistically to increase bee mortality.

Global concern over widely documented declines in pollinators1-3 has led to the identification of anthropogenic stressors that, individually, are detrimental to bee populations4-7. Synergistic interactions between these stressors could substantially amplify the environmental effect of these stressors and could therefore have important implications for policy decisions that aim to improve the health of pollinators3,8,9. Here, to quantitatively assess the scale of this threat, we conducted a meta-analysis of 356 interaction effect sizes from 90 studies in which bees were exposed to combinations of agrochemicals, nutritional stressors and/or parasites. We found an overall synergistic effect between multiple stressors on bee mortality. Subgroup analysis of bee mortality revealed strong evidence for synergy when bees were exposed to multiple agrochemicals at field-realistic levels, but interactions were not greater than additive expectations when bees were exposed to parasites and/or nutritional stressors. All interactive effects on proxies of fitness, behaviour, parasite load and immune responses were either additive or antagonistic; therefore, the potential mechanisms that drive the observed synergistic interactions for bee mortality remain unclear. Environmental risk assessment schemes that assume additive effects of the risk of agrochemical exposure may underestimate the interactive effect of anthropogenic stressors on bee mortality and will fail to protect the pollinators that provide a key ecosystem service that underpins sustainable agriculture.

Coupled information networks drive honeybee (Apis mellifera) collective foraging.

Collective behaviour by eusocial insect colonies is typically achieved through multiple communication networks that produce complex behaviour at the group level but often appear to provide redundant or even competing information. A classic example occurs in honeybee (Apis mellifera) colonies, where both the dance communication system and robust scent-based mechanisms contribute to the allocation of a colony's workforce by regulating the flow of experienced foragers among known food sources. Here we analysed social connectivity patterns during the reactivation of experienced foragers to familiar feeding sites to show that these social information pathways are not simply multiple means to achieve the same end but intersect to play complementary roles in guiding forager behaviour. Using artificial feeding stations, we mimicked a natural scenario in which two forager groups were simultaneously collecting from distinct patches containing different flowering species. We then observed the reactivation of these groups at their familiar feeding sites after interrupting their foraging. Social network analysis revealed that temporarily unemployed individuals interacted more often and for longer with foragers that advertised a familiar versus unfamiliar foraging site. Due to such resource-based assortative mixing, network-based diffusion analysis estimated that reactivation events primarily resulted from interactions among bees that had been trained to the same feeding station and less so from different-feeder interactions. Both scent- and dance-based interactions strongly contributed to reactivation decisions. However, each bout of dance-following had an especially strong effect on a follower's likelihood of reactivation, particularly when dances indicated locations familiar to followers. Our findings illustrate how honeybee foragers can alter their social connectivity in ways that are likely to enhance collective outcomes by enabling foragers to rapidly access up-to-date information about familiar foraging sites. In addition, our results highlight how reliance on multiple communication mechanisms enables social insect workers to utilise flexible information-use strategies that are robust to variation in the availability of social information.

Sulfoxaflor exposure reduces bumblebee reproductive success.

Intensive agriculture currently relies on pesticides to maximize crop yield1,2. Neonicotinoids are the most widely used insecticides globally3, but increasing evidence of negative impacts on important pollinators4-9 and other non-target organisms10 has led to legislative reassessment and created demand for the development of alternative products. Sulfoximine-based insecticides are the most likely successor11, and are either licensed for use or under consideration for licensing in several worldwide markets3, including within the European Union12, where certain neonicotinoids (imidacloprid, clothianidin and thiamethoxam) are now banned from agricultural use outside of permanent greenhouse structures. There is an urgent need to pre-emptively evaluate the potential sub-lethal effects of sulfoximine-based pesticides on pollinators11, because such effects are rarely detected by standard ecotoxicological assessments, but can have major impacts at larger ecological scales13-15. Here we show that chronic exposure to the sulfoximine-based insecticide sulfoxaflor, at dosages consistent with potential post-spray field exposure, has severe sub-lethal effects on bumblebee (Bombus terrestris) colonies. Field-based colonies that were exposed to sulfoxaflor during the early growth phase produced significantly fewer workers than unexposed controls, and ultimately produced fewer reproductive offspring. Differences between the life-history trajectories of treated and control colonies first became apparent when individuals exposed as larvae began to emerge, suggesting that direct or indirect effects on a small cohort may have cumulative long-term consequences for colony fitness. Our results caution against the use of sulfoximines as a direct replacement for neonicotinoids. To avoid continuing cycles of novel pesticide release and removal, with concomitant impacts on the environment, a broad evidence base needs to be assessed prior to the development of policy and regulation.

Transcriptomic responses to location learning by honeybee dancers are partly mirrored in the brains of dance-followers.

The waggle dances of honeybees are a strikingly complex form of animal communication that underlie the collective foraging behaviour of colonies. The mechanisms by which bees assess the locations of forage sites that they have visited for representation on the dancefloor are now well-understood, but few studies have considered the remarkable backward translation of such information into flight vectors by dance-followers. Here, we explore whether the gene expression patterns that are induced through individual learning about foraging locations are mirrored when bees learn about those same locations from their nest-mates. We first confirmed that the mushroom bodies of honeybee dancers show a specific transcriptomic response to learning about distance, and then showed that approximately 5% of those genes were also differentially expressed by bees that follow dances for the same foraging sites, but had never visited them. A subset of these genes were also differentially expressed when we manipulated distance perception through an optic flow paradigm, and responses to learning about target direction were also in part mirrored in the brains of dance followers. Our findings show a molecular footprint of the transfer of learnt information from one animal to another through this extraordinary communication system, highlighting the dynamic role of the genome in mediating even very short-term behavioural changes.

'Inert' ingredients are understudied, potentially dangerous to bees and deserve more research attention.

Agrochemical formulations are composed of two broad groups of chemicals: active ingredients, which confer pest control action, and 'inert' ingredients, which facilitate the action of the active ingredient. Most research into the effects of agrochemicals focusses on the effects of active ingredients. This reflects the assumption that 'inert' ingredients are non-toxic. A review of relevant research shows that for bees, this assumption is without empirical foundation. After conducting a systematic literature search, we found just 19 studies that tested the effects of 'inert' ingredients on bee health. In these studies, 'inert' ingredients were found to cause mortality in bees through multiple exposure routes, act synergistically with other stressors and cause colony level effects. This lack of research is compounded by a lack of diversity in study organism used. We argue that 'inert' ingredients have distinct, and poorly understood, ecological persistency profiles and toxicities, making research into their individual effects necessary. We highlight the lack of mitigation in place to protect bees from 'inert' ingredients and argue that research efforts should be redistributed to address the knowledge gap identified here. If so-called 'inert' ingredients are, in fact, detrimental to bee health, their potential role in widespread bee declines needs urgent assessment.

Detecting and quantifying social transmission using network-based diffusion analysis.

Although social learning capabilities are taxonomically widespread, demonstrating that freely interacting animals (whether wild or captive) rely on social learning has proved remarkably challenging. Network-based diffusion analysis (NBDA) offers a means for detecting social learning using observational data on freely interacting groups. Its core assumption is that if a target behaviour is socially transmitted, then its spread should follow the connections in a social network that reflects social learning opportunities. Here, we provide a comprehensive guide for using NBDA. We first introduce its underlying mathematical framework and present the types of questions that NBDA can address. We then guide researchers through the process of selecting an appropriate social network for their research question; determining which NBDA variant should be used; and incorporating other variables that may impact asocial and social learning. Finally, we discuss how to interpret an NBDA model's output and provide practical recommendations for model selection. Throughout, we highlight extensions to the basic NBDA framework, including incorporation of dynamic networks to capture changes in social relationships during a diffusion and using a multi-network NBDA to estimate information flow across multiple types of social relationship. Alongside this information, we provide worked examples and tutorials demonstrating how to perform analyses using the newly developed nbda package written in the R programming language.

Individual and combined impacts of sulfoxaflor and Nosema bombi on bumblebee (Bombus terrestris) larval growth.

Sulfoxaflor is a globally important novel insecticide that can have negative impacts on the reproductive output of bumblebee (Bombus terrestris) colonies. However, it remains unclear as to which life-history stage is critically affected by exposure. One hypothesis is that sulfoxaflor exposure early in the colony's life cycle can impair larval development, reducing the number of workers produced and ultimately lowering colony reproductive output. Here we assess the influence of sulfoxaflor exposure on bumblebee larval mortality and growth both when tested in insolation and when in combination with the common fungal parasite Nosema bombi, following a pre-registered design. We found no significant impact of sulfoxaflor (5 ppb) or N. bombi exposure (50 000 spores) on larval mortality when tested in isolation but found an additive, negative effect when larvae received both stressors in combination. Individually, sulfoxaflor and N. bombi exposure each impaired larval growth, although the impact of combined exposure fell significantly short of the predicted sum of the individual effects (i.e. they interacted antagonistically). Ultimately, our results suggest that colony-level consequences of sulfoxaflor exposure for bumblebees may be mediated through direct effects on larvae. As sulfoxaflor is licensed for use globally, our findings highlight the need to understand how novel insecticides impact non-target insects at various stages of their development.

A social insect perspective on the evolution of social learning mechanisms.

The social world offers a wealth of opportunities to learn from others, and across the animal kingdom individuals capitalize on those opportunities. Here, we explore the role of natural selection in shaping the processes that underlie social information use, using a suite of experiments on social insects as case studies. We illustrate how an associative framework can encompass complex, context-specific social learning in the insect world and beyond, and based on the hypothesis that evolution acts to modify the associative process, suggest potential pathways by which social information use could evolve to become more efficient and effective. Social insects are distant relatives of vertebrate social learners, but the research we describe highlights routes by which natural selection could coopt similar cognitive raw material across the animal kingdom.

Lower bumblebee colony reproductive success in agricultural compared with urban environments.

Urbanization represents a rapidly growing driver of land-use change. While it is clear that urbanization impacts species abundance and diversity, direct effects of urban land use on animal reproductive success are rarely documented. Here, we show that urban land use is linked to long-term colony reproductive output in a key pollinator. We reared colonies from wild-caught bumblebee (Bombus terrestris) queens, placed them at sites characterized by varying degrees of urbanization from inner city to rural farmland and monitored the production of sexual offspring across the entire colony cycle. Our land-use cluster analysis identified three site categories, and this categorization was a strong predictor of colony performance. Crucially, colonies in the two clusters characterized by urban development produced more sexual offspring than those in the cluster dominated by agricultural land. These colonies also reached higher peak size, had more food stores, encountered fewer parasite invasions and survived for longer. Our results show a link between urbanization and bumblebee colony reproductive success, supporting the theory that urban areas provide a refuge for pollinator populations in an otherwise barren agricultural landscape.

Metabolic rate does not explain performance on a short-term memory task or personality traits in juvenile chickens (Gallus gallus domesticus).

Metabolic rate determines life processes and the physiological requirements of an individual, and has recently been implicated as a driver of inter-individual variation in behaviour, with positive correlations associated with boldness, exploration and aggressive behaviours being recorded. While the link between metabolism and personality has been explored, little is known about the influence of metabolism on cognitive abilities. Here we used juvenile female chickens (Gallus gallus domesticus) to investigate the relationships between metabolic rate at rest, short-term memory, personality, and dominance. Resting metabolic rates of the chicks were measured over a three-week period, concurrently with measures of short-term memory using an analogue of the radial arm maze. We also measured latency to leave the shelter (boldness), neophobia (fear of novel objects) and dominance within a group, both before and after short-term memory trials. We found that metabolic rate did not explain inter-individual differences in short-term memory, personality traits or dominance, suggesting that energy allocated to these traits is independent of individual metabolic rate, and providing evidence for the independent energy-management hypothesis. Differences in short-term memory were also not explained by boldness or neophobia. Variation in behaviour in chicks, therefore, appears to be driven by separate, currently unknown variables.

Social complexity, life-history and lineage influence the molecular basis of castes in vespid wasps.

A key mechanistic hypothesis for the evolution of division of labour in social insects is that a shared set of genes co-opted from a common solitary ancestral ground plan (a genetic toolkit for sociality) regulates caste differentiation across levels of social complexity. Using brain transcriptome data from nine species of vespid wasps, we test for overlap in differentially expressed caste genes and use machine learning models to predict castes using different gene sets. We find evidence of a shared genetic toolkit across species representing different levels of social complexity. We also find evidence of additional fine-scale differences in predictive gene sets, functional enrichment and rates of gene evolution that are related to level of social complexity, lineage and of colony founding. These results suggest that the concept of a shared genetic toolkit for sociality may be too simplistic to fully describe the process of the major transition to sociality.

Behavioural variation among workers promotes feed-forward loops in a simulated insect colony.

Coordinated responses in eusocial insect colonies arise from worker interaction networks that enable collective processing of ecologically relevant information. Previous studies have detected a structural motif in these networks known as the feed-forward loop, which functions to process information in other biological regulatory networks (e.g. transcriptional networks). However, the processes that generate feed-forward loops among workers and the consequences for information flow within the colony remain largely unexplored. We constructed an agent-based model to investigate how individual variation in activity and movement shaped the production of feed-forward loops in a simulated insect colony. We hypothesized that individual variation along these axes would generate feed-forward loops by driving variation in interaction frequency among workers. We found that among-individual variation in activity drove over-representation of feed-forward loops in the interaction networks by determining the directionality of interactions. However, despite previous work linking feed-forward loops with efficient information transfer, activity variation did not promote faster or more efficient information flow, thus providing no support for the hypothesis that feed-forward loops reflect selection for enhanced collective functioning. Conversely, individual variation in movement trajectory, despite playing no role in generating feed-forward loops, promoted fast and efficient information flow by linking together otherwise unconnected regions of the nest.

Machine learning models identify gene predictors of waggle dance behaviour in honeybees.

The molecular characterization of complex behaviours is a challenging task as a range of different factors are often involved to produce the observed phenotype. An established approach is to look at the overall levels of expression of brain genes-or 'neurogenomics'-to select the best candidates that associate with patterns of interest. However, traditional neurogenomic analyses have some well-known limitations: above all, the usually limited number of biological replicates compared to the number of genes tested-known as the "curse of dimensionality." In this study we implemented a machine learning (ML) approach that can be used as a complement to more established methods of transcriptomic analyses. We tested three supervised learning algorithms (Random Forests, Lasso and Elastic net Regularized Generalized Linear Model, and Support Vector Machine) for their performance in the characterization of transcriptomic patterns and identification of genes associated with honeybee waggle dance. We then matched the results of these analyses with traditional outputs of differential gene expression analyses and identified two promising candidates for the neural regulation of the waggle dance: boss and hnRNP A1. Overall, our study demonstrates the application of ML to analyse transcriptomics data and identify candidate genes underlying social behaviour. This approach has great potential for application to a wide range of different scenarios in evolutionary ecology, when investigating the genomic basis for complex phenotypic traits, and can present some clear advantages compared to the established tools of gene expression analysis, making it a valuable complement for future studies.

Ecology dictates the value of memory for foraging bees.

"Ecological intelligence" hypotheses posit that animal learning and memory evolve to meet the demands posed by foraging and, together with social intelligence and cognitive buffer hypotheses, provide a key framework for understanding cognitive evolution.1-5 However, identifying the critical environments where cognitive investment reaps significant benefits has proved challenging.6-8 Here, we capitalize upon seasonal variation in forage availability for a social insect model (Bombus terrestris audax) to establish how the benefits of short-term memory, assayed using a radial arm maze (RAM), vary with resource availability. Following a staggered design over 2 years, whereby bees from standardized colonies at identical life-history stages underwent cognitive testing before foraging in the wild, we found that RAM performance predicts foraging efficiency-a key determinant of colony fitness-in plentiful spring foraging conditions but that this relationship is reversed during the summer floral dearth. Our results suggest that the selection for enhanced cognitive abilities is unlikely to be limited to harsh environments where food is hard to find or extract,5,9-11 highlighting instead that the challenges of rich and plentiful environments, which present multiple options in short succession, could be a broad driver in the evolution of certain cognitive traits. VIDEO ABSTRACT.

Do inexperienced bumblebee foragers use scent marks as social information?

Bumblebees (Bombus spp.) foraging in the field typically reject flowers where they detect the olfactory footprints of previous visitors and hence avoid recently emptied inflorescences. A growing number of studies have begun to illustrate that associative learning shapes the development of this process, in both bumblebees and other bee species. This raises the question of what the default response to such marks is, but little is known about how inexperienced foragers use social information. Here, we offered flower-naive bees a choice between scent-marked flowers and unmarked alternatives and found that individuals neither avoided nor preferred marked flowers. Our findings provide no support for 'hard-wired' responses to scent marks in bumblebees and highlight the importance of associative learning in shaping social information use to match local circumstances.

Social learning in insects--from miniature brains to consensus building.

Communication and learning from each other are part of the success of insect societies. Here, we review a spectrum of social information usage in insects--from inadvertently provided cues to signals shaped by selection specifically for information transfer. We pinpoint the sensory modalities involved and, in some cases, quantify the adaptive benefits. Well substantiated cases of social learning among the insects include learning about predation threat and floral rewards, the transfer of route information using a symbolic 'language' (the honeybee dance) and the rapid spread of chemosensory preferences through honeybee colonies via classical conditioning procedures. More controversial examples include the acquisition of motor memories by observation, teaching in ants and behavioural traditions in honeybees. In many cases, simple mechanistic explanations can de identified for such complex behaviour patterns.

Urbanisation is associated with reduced Nosema sp. infection, higher colony strength and higher richness of foraged pollen in honeybees.

Bees are vital pollinators, but are faced with numerous threats that include loss of floral resources and emerging parasites amongst others. Urbanisation is a rapidly expanding driver of land-use change that may interact with these two major threats to bees. Here we investigated effects of urbanisation on food store quality and colony health in honeybees (Apis mellifera) by sampling 51 hives in four different land-use categories: urban, suburban, rural open and rural wooded during two seasons (spring and autumn). We found positive effects of urban land use on colony strength and richness of stored pollen morphotypes, alongside lower late-season Nosema sp. infection in urban and suburban colonies. Our results reveal that honeybees exhibit lower colony performance in strength in rural areas, adding to the growing evidence that modern agricultural landscapes can constitute poor habitat for insect pollinators.

Network-based diffusion analysis reveals context-specific dominance of dance communication in foraging honeybees.

The honeybee (Apis mellifera) dance communication system is a marvel of collective behaviour, but the added value it brings to colony foraging efficiency is poorly understood. In temperate environments, preventing communication of foraging locations rarely decreases colony food intake, potentially because simultaneous transmission of olfactory information also plays a major role in foraging. Here, we employ social network analyses that quantify information flow across multiple temporally varying networks (each representing a different interaction type) to evaluate the relative contributions of dance communication and hive-based olfactory information transfer to honeybee recruitment events. We show that virtually all successful recruits to novel locations rely upon dance information rather than olfactory cues that could otherwise guide them to the same resource. Conversely, during reactivation to known sites, dances are relatively less important, as foragers are primarily guided by olfactory information. By disentangling the contributions of multiple information networks, the contexts in which dance communication truly matters amid a complex system full of redundancy can now be identified.

Sulfoxaflor exposure reduces egg laying in bumblebees Bombus terrestris.

Sulfoximine-based insecticides, such as sulfoxaflor, are of increasing global importance and have been registered for use in 81 countries, offering a potential alternative to neonicotinoid insecticides.Previous studies have demonstrated that sulfoxaflor exposure can have a negative impact on the reproductive output of bumblebee colonies, but the specific life-history variables that underlie these effects remain unknown.Here, we used a microcolony-based protocol to assess the sub-lethal effects of chronic sulfoxaflor exposure on egg laying, larval production, ovary development, sucrose consumption, and mortality in bumblebees. Following a pre-registered design, we exposed colonies to sucrose solutions containing 0, 5, 10 and 250ppb of sulfoxaflor. Exposure at 5 ppb has been previously shown to negatively impact colony reproductive success.Our results showed that sulfoxaflor exposure at 5 ppb (lowest exposure tested) reduced the number of eggs found within the microcolonies (Hedge's d = -0.37), with exposed microcolonies also less likely to produce larvae (Hedge's d = -0.36). Despite this, we found no effect of sulfoxaflor exposure on ovarian development. Sulfoxaflor-exposed bumblebees consumed less sucrose solution, potentially driving the observed reduction in egg laying. Policy implications. Regulatory bodies such as the European Food Safety Authority (EFSA) are under increasing pressure to consider the potential impact of insecticides on wild bees, such as bumblebees, but sublethal effects can go undetected at lower-tier testing. In identifying just such an effect for bumblebees exposed to sulfoxaflor, this study highlights that microcolony-based protocols are a useful tool that could be implemented within an ecotoxicology framework. Furthermore, the results provide evidence for potentially negative consequences of pollinator exposure to an insecticide that is currently undergoing the licensing process in several EU member states.