In Melipona stingless bees, larvae develop in sealed, identically sized, mass-provisioned cells. This enables larvae to determine their own caste fate, causing 5–15% of females to develop as queens, a frequency approaching the individual optimum but exceeding colony requirements. Self-determination has been suggested to operate through a stochastic switch, whereby intrinsic noise or environmental cues trigger alternative caste trajectories. This “fair lottery” hypothesis predicts a spatially random distribution of queens, whereas localised maternal or worker control should induce clustering. We tested this prediction using a 25-year dataset comprising 593 brood-comb maps from nine Melipona species. Multiscale spatial analyses showed that gyne positions were indistinguishable from random, while collectively controlled male production was clustered. Gyne production varied primarily among colonies and months and increased with comb cell number – a proxy for cell-building rate. These results suggest that Melipona caste determination resembles a fair lottery but with dynamically adjustable odds: within a contemporaneous brood cohort, larvae have an equal chance of developing as queens, but the colony-level odds change over time. Such recalibration is consistent with evolutionarily stable strategy theory, where seasonal variation in worker mortality and cell-building rates alters the colony-level cost, and hence the stable level, of queen overproduction.

Learning, memory and brain plasticity are thought to play an important role in regulating behavioural roles in social insects, as workers perform different tasks as nurses, builders, foragers and defenders. However, it remains challenging to disentangle whether neural changes regulate behaviour or arise as a consequence of it. While cognition has been extensively studied, especially in honeybees, the variation of cognitive traits remains poorly understood in social wasps. Here, we investigated age-related changes in learning, memory and neuroanatomy in workers of the common wasp, Vespula vulgaris. We developed a Y-maze to test differential conditioning and memory of wasps and later visualised the brains using a high-resolution micro-computed tomography imaging. We found that younger individuals exhibited slower decision making yet made more accurate decisions compared with older individuals, revealing a pronounced speed-accuracy trade-off. Short-term memory showed only a slight decline with age. Neuroanatomical image analysis revealed that, despite a reduction in overall brain volume, key major neuropils involved in sensory processing and learning, such as mushroom bodies, optic lobes and antennal lobes, increased in relative volume with age. These findings corroborate with studies in bees and provide novel insights into how ageing influences cognitive function and brain structure in wasps.

AbstractSelf-medication is the selective consumption of compounds that reduce infection and is a widespread form of adaptive plasticity across animals. However, relevant medicinal floral compounds remain poorly tested in bees. Here, we used robotic flowers to test the hypothesis that bumblebees (Bombus terrestris) modify nectar choice after pathogen exposure, focusing on quercetin, a common nectar secondary compound with antimicrobial activity. Colonies were maintained as healthy controls or exposed to the fungus Ascosphaera apis or the bacterium Serratia marcescens. Colonies exposed to A. apis showed higher visitation rates and longer probing times on quercetin-supplemented flowers, whereas healthy colonies and those exposed to S. marcescens showed no significant preference. Healthy colonies also showed no significant avoidance of quercetin, despite altered solution colour and palatability, and potential detoxification costs. These contrasting responses probably reflect pathogen life history: although A. apis primarily affects brood, increased quercetin foraging may indicate social medication, whereas for S. marcescens, an opportunistic gut pathogen of adults, any colony-level benefit is likely to be more indirect. Overall, these results indicate that pathogen identity shapes behavioural plasticity in nectar foraging and demonstrate the value of robotic flowers for studying adaptive foraging responses to pathogens.

Juvenile hormone (JH) is a conserved endocrine regulator that coordinate reproduction, behaviour and chemical communication in social insects. We tested whether JH would regulate these effects in queenright colonies of the common wasp Vespula vulgaris. We experimentally manipulated JH signalling in newly emerged workers using methoprene (JH analogue) or precocene (anti-JH), and measured ovarian development, task performance and cuticular hydrocarbon (CHC) profiles. As expected, ovarian activation increased with age and was altered by methoprene treatment accelerating early oocyte development, but these treatment effects changed later in life. Task allocation showed the expected age-related shift from intranidal to extranidal activities, however, was only weakly affected by the treatment. By contrast, CHC profiles varied with age, task and hormonal manipulation. Age had the broadest chemical effect, task differences mainly separated intranidal from extranidal workers, and treatment affected several compounds previously associated with fertility signalling, including long-chain alkanes. These results indicate that the experimental manipulation of JH-related signalling affected reproductive physiology and chemical phenotype, while overt task allocation remains primarily age structured. Hormonal pleiotropy may therefore contribute to the partial coordination of fertility, maturation and chemical communication in workers of V. vulgaris, but its effects appear to be trait-specific rather than uniform across all aspects of the worker phenotype.

The evolution of eusociality, characterized by cooperative brood care, reproductive division of labor, and overlapping generations, represents a major evolutionary transition. A central paradox is that early models suggested diminishing returns to helping, making solitary reproduction seemingly more efficient. Here, we experimentally demonstrate increasing returns to scale from early-season helping in the primitively eusocial wasp Polistes gallicus. By manipulating the proportion of females allowed to remain as helpers, we show that while reproductive output scales linearly with worker numbers, total sexual productivity increases convexly with helper probability, thereby showing that early-season helping leads to compounding effects on reproductive output. Using these data, we parameterize a dynamic population genetic model and show that this convex relationship facilitates the spread of eusociality alleles more readily under monandry than polyandry, contrary to the conclusions of some prior models. Importantly, we show that compounding effects can cause eusociality to evolve even when helpers are no more efficient at rearing brood than solitary breeders. Our findings emphasize the value of integrating experimental data with mechanistically motivated theoretical models to study social evolution.

Deformed wing virus (DWV) is a major driver of honeybee colony losses, yet its sublethal effects on adult foraging behaviour remain underexplored. Building on evidence that covert DWV infections impair sucrose responsiveness and associative learning, we tested whether infection changes foraging success and specialization in worker bees. Using a controlled experiment, we marked 1,000 newly emerged workers that were either inoculated with DWV lysate or injected with an RNA-interference control that suppressed viral replication. Foraging activity, success, and specialization were recorded. Our results show that DWV-infected bees began foraging earlier (“precocious foraging”) and had higher mortality, reducing their lifespan as foragers. Furthermore, infected nectar foragers were significantly less likely to return with nectar, and when they did, it contained markedly lower sugar concentrations compared to control bees. Conversely, infected bees were slightly more likely to return with pollen and showed greater specialization in pollen foraging, although pollen load weights were similar between treatments. These findings indicate that DWV disrupts multiple aspects of foraging ecology by accelerating behavioural maturation, shortening forager lifespan, reducing nectar yield and quality, and shifting resource preference towards pollen. Such changes may reflect a compensatory response to impaired nectar collection, but nonetheless could compromise colony nutrition, particularly when high-quality nectar is scarce. Our results align with previous work linking DWV to impaired foraging efficiency, and altered foraging specialization, and reduced honeybee survival, underscoring DWV’s substantial sublethal costs. By reducing nectar foraging while leaving pollen loads unaffected, DWV may limit honey stores and brood rearing during high demand periods, contributing to seasonal losses. Even moderate declines in nectar-foraging can undermine colony resilience, highlighting the need to address DWV’s role in the pollinator crisis.

Social inequality among individuals is a common cause of conflict in the animal kingdom. In eusocial insects, such as ants, bees, wasps, and termites, for example, the large differences in reproductive potential between castes result in conflicts over caste fate during development. Here, we present the first comprehensive review on caste fate conflict, drawing on data from diverse taxa and recent theoretical advances. In many eusocial species, caste fate is determined by differential feeding, which results in caste fate being socially controlled, thereby aligning larval development with the collective needs of the colony. However, in some taxa, mechanisms of individual self-determination disrupt this balance, leading to overproduction of reproductive individuals at the expense of workers, with significant costs to colony fitness. Such conflicts are particularly pronounced in some stingless bees and lower termites, where larvae can bypass social control to determine their own caste fate. Indications of caste conflict can also be found in other groups, such as in some parasitic ants and in ant hybrid zones. Overall, the observed dynamics illustrate how conflicts in biological systems can be resolved in favour of either individual or collective interests, and how this affects the functioning of higher levels of organisation.

Nectar yeasts can significantly influence the scent of floral nectar and therefore the foraging behavior of flower-visiting insects. While these effects likely depend on nectar chemistry and yeast species, their joint impact on nectar volatile profiles and associated insect responses remain poorly understood. Here, we used four synthetic nectar types varying in sugar and amino acid concentration and two specialist nectar yeasts (Metschnikowia gruessii and Metschnikowia reukaufii) to investigate how nectar composition and yeast species affect volatile profiles and the olfactory responses of the generalist aphid parasitoid Aphidius ervi. Olfactometer assays showed that A. ervi females significantly preferred fermented nectars with high amino acid-low sugar content (HL) and low amino acid-high sugar (LH) content, regardless being fermented by M. gruessii or M. reukaufii, over non-inoculated nectars. This effect was not observed for nectars with low amino acid-low sugar (LL) and high amino acid-high sugar (HH) content. Moreover, LL nectar fermented with M. gruessii became even repellent to the parasitoids. GC–MS analysis of volatile organic compounds (VOCs) revealed that VOC profiles of fermented nectars depended significantly on nectar type (i.e., chemical composition), yeast species, and their interaction. Whereas propyl acetate, isobutyl acetate, styrene, α-guaiene and pentyl-octanoate were associated with the LH fermented nectars, ethyl acetate and E-methyl isoeugenol were mainly associated with the HL fermented nectars, suggesting possible involvement in A. ervi attraction to these nectars. In contrast, isopropyl-hexadecanoate was associated with the non-attractive or repellent LL fermented nectars. Altogether, our results indicate that nectar composition has a strong impact on nectar scent when fermented by specialist nectar yeasts and subsequently on insect foraging behavior.

Adult parasitoids are well known to feed on sugar-rich resources such as floral nectar. Recently, an increasing body of evidence has shown that nectar is ubiquitously colonized by microorganisms and, as a consequence, microbial metabolic activity can affect several traits of floral nectar. Yet, how the fermentation of nectar by yeasts impacts the olfactory responses and performance of parasitoids is largely understudied, especially in the case of egg parasitoids. In this study, we investigated whether fermentation by the nectar yeasts Metschnikowia gruessii and M. reukaufii affects the olfactory responses of Trissolcus basalis and Ooencyrtus telenomicida, two egg parasitoid species associated with the southern green stink bug Nezara viridula . We also investigated how yeast fermentation affects the longevity and survival of the egg parasitoids. Results of static four-chamber olfactometer tests showed that nectar fermented by M. gruessii (but not by M. reukaufii ) was attractive to both egg parasitoid species, whereas no significant yeast-mediated effects were found in terms of wasp longevity. Gas chromatography coupled with mass spectrometry (GC-MS) showed a clear separation of the volatile profiles among M. gruessii , M. reukaufii and non-fermented control nectar supporting the results of the insect bioassays. The results of our study highlight the need to consider the role of microbes when studying interactions between flower nectar and egg parasitoids and could have implications from a conservation biological control perspective.

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

Understanding the complex interactions between external and internal factors that influence pollinator foraging behaviour is essential to understand ecosystem functioning, design agricultural practices or develop effective conservation strategies. However, it remains challenging to collect large and reliable data sets with reasonable personnel and workload. In this study, we present a wireless and cost‐effective robotic flower equipped with internet of things (IoT) technology that automatically offers nectar to visiting insects while monitoring visitation time and duration. The robotic flower is easy to manipulate and settings such as nectar refill rates can be remotely altered, making it ideal for field settings. The system transmits data completely wirelessly and autonomously, is mobile and easy to clean. The prototype settings allow for approximately 2 weeks of uninterrupted data collection for each battery charge. As a proof‐of‐concept application, a foraging preference dual choice experiment with bumblebees was performed. On average, more than 7000 flower visits per colony were registered daily with a set‐up consisting of 16 robotic flowers. The data show a gradual preference shift away from the pre‐trained low concentration, confirming the hypothesis of favouring sugar water with higher concentration. The robotic flower provides accurate and reliable data on insect behaviour, significantly reducing the price and/or labour costs. Although primarily designed for (bumble)bees, the system could be easily adapted for other flower‐visiting insects. The robotic flower is user‐friendly and can be easily adapted to address a wide range of research questions in pollination ecology, conservation biology, biocontrol and ecotoxicology, and allows for detailed studies on how nectar traits, flower colour and shape or pollutants affect foraging behaviour.

The transmission of complex behavior and culture in humans has long been attributed to advanced forms of social learning,1,2 which play a crucial role in our technological advancement.3 While similar phenomena of behavioral traditions and cultural inheritance have been observed in animals,1,2,4,5,6 including in primates,7 whales,8 birds,9 and even insects,10 the underlying mechanisms enabling the persistence of such animal traditions, particularly in insects, are less well understood. This study introduces pioneering evidence of enduring architectural traditions in the stingless bee Scaptotrigona depilis, which are maintained without any evidence for social learning. We demonstrate that S. depilis exhibits two distinct nest architectures, comprising either helicoidal or flat, stacked horizontal combs, which are transmitted across generations through stigmergy11,12,13,14,15,16,17—an environmental feedback mechanism whereby the presence of the existing comb structures guides subsequent construction behaviors—thereby leading to a form of environmental inheritance.18,19,20 Cross-fostering experiments further show that genetic factors or prior experience does not drive the observed variation in nest architecture. Moreover, the experimental introduction of corkscrew dislocations within the combs prompted helicoidal building, confirming the use of stigmergic building rules. At a theoretical level, we establish that the long-term equilibrium of building in the helicoidal pattern fits with the expectations of a two-state Markov chain model. Overall, our findings provide compelling evidence for the persistence of behavioral traditions in an insect, based on a simple mechanism of environmental inheritance and stigmergic interactions, without requiring any sophisticated learning mechanism, thereby expanding our understanding of how traditions can be maintained in non-human species.

Volatile aroma compounds are important chemical cues for insects. Behavioral responses to specific odors differ strongly between insect species, and the exact causative molecules are often unknown. Beer is frequently used in insect traps because it combines hundreds of plant and microbial aromas that attract many insects. Here, we analyzed responses of the pest fruit fly Drosophila suzukii and benign Drosophila melanogaster to beers with different chemical compositions. Using extensive chemical and behavioral assays, we identified ecologically relevant chemicals that influence drosophilid behavior and that induce different odor-evoked activity patterns in the antennal lobe of the two species obtained by functional imaging. Specific mixes of compounds increased the species-specificity and sex-specificity of lures in both laboratory and greenhouse settings. Together, our study shows how examining insect responses to highly complex natural mixtures of aroma compounds provides insight into insect-specific behavioral responses and also opens avenues for improved pest control.

In the field of social evolution, inclusive fitness theory has been successful in making a wide range of qualitative predictions on expected patterns of cooperation and conflict. Nevertheless, outside of sex ratio theory, inclusive fitness models that make accurate quantitative predictions remain relatively rare. Past models dealing with caste fate conflict in insect societies, for example, successfully predicted that if female larvae can control their own caste fate, an excess should opt to selfishly develop as queens. Available models, however, were unable to accurately predict levels of queen production observed in Melipona bees—a genus of stingless bees where caste is self-determined—as empirically observed levels of queen production are approximately two times lower than the theoretically predicted ones. Here, we show that this discrepancy can be resolved by explicitly deriving the colony-level cost of queen overproduction from a dynamic model of colony growth, requiring the incorporation of parameters of colony growth and demography, such as the per-capita rate at which new brood cells are built and provisioned, the percentage of the queen’s eggs that are female, costs linked with worker reproduction and worker mortality. Our revised model predicts queen overproduction to more severely impact colony productivity, resulting in an evolutionarily stable strategy that is approximately half that of the original model, and is shown to accurately predict actual levels of queen overproduction observed in different Melipona species. Altogether, this shows how inclusive fitness models can provide accurate quantitative predictions, provided that costs and benefits are modeled in sufficient detail and are measured precisely.

Effective treatment of bacterial infections proves increasingly challenging due to the emergence of bacterial variants that endure antibiotic exposure. Antibiotic resistance and persistence have been identified as two major bacterial survival mechanisms, and several studies have shown a rapid and strong selection of resistance or persistence mutants under repeated drug treatment. Yet, little is known about the impact of the environmental conditions on resistance and persistence evolution and the potential interplay between both phenotypes. Based on the distinct growth and survival characteristics of resistance and persistence mutants, we hypothesized that the antibiotic dose and availability of nutrients during treatment might play a key role in the evolutionary adaptation to antibiotic stress. To test this hypothesis, we combined high-throughput experimental evolution with a mathematical model of bacterial evolution under intermittent antibiotic exposure. We show that high nutrient levels during antibiotic treatment promote selection of high-level resistance, but that resistance mainly emerges independently of persistence when the antibiotic concentration is sufficiently low. At higher doses, resistance evolution is facilitated by the preceding or concurrent selection of persistence mutants, which ensures survival of populations in harsh conditions. Collectively, our experimental data and mathematical model elucidate the evolutionary routes toward increased bacterial survival under different antibiotic treatment schedules, which is key to designing effective antibiotic therapies.

We investigate the emergence, mutation profile, and dissemination of SARS-CoV-2 lineage B.1.214.2, first identified in Belgium in January 2021. This variant, featuring a 3-amino acid insertion in the spike protein similar to the Omicron variant, was speculated to enhance transmissibility or immune evasion. Initially detected in international travelers, it substantially transmitted in Central Africa, Belgium, Switzerland, and France, peaking in April 2021. Our travel-aware phylogeographic analysis, incorporating travel history, estimated the origin to the Republic of the Congo, with primary European entry through France and Belgium, and multiple smaller introductions during the epidemic. We correlate its spread with human travel patterns and air passenger data. Further, upon reviewing national reports of SARS-CoV-2 outbreaks in Belgian nursing homes, we found this strain caused moderately severe outcomes (8.7% case fatality ratio). A distinct nasopharyngeal immune response was observed in elderly patients, characterized by 80% unique signatures, higher B- and T-cell activation, increased type I IFN signaling, and reduced NK, Th17, and complement system activation, compared to similar outbreaks. This unique immune response may explain the variant's epidemiological behavior and underscores the need for nasal vaccine strategies against emerging variants.

Insect communities consist of species from several trophic levels that have to forage for suitable resources among and within larger patches of nonresources. To locate their resources, insects use diverse stimuli, including olfactory, visual, acoustic, tactile and gustatory cues. While most research has focused on cues derived from plants and other insects, there is mounting evidence that insects also respond to volatile organic compounds (VOCs) emitted by microorganisms. However, to date little is known about how the olfactory response of insects within and across different trophic levels is affected by bacterial VOCs. In this study, we used Y-tube bioassays and chemical analysis of VOCs to assess how VOCs emitted by bacteria affect the olfactory response of insects of the same and different trophic levels. Experiments were performed using two aphid species (Amphorophora idaei Börner and Myzus persicae var. nicotianae Blackman), three primary parasitoid species (Aphidius colemani Viereck, A. ervi Haliday, and A. matricariae Viereck), and two hyperparasitoid species (Asaphes suspensus Nees and Dendrocerus aphidum Rondani). Olfactory responses were evaluated for three bacterial strains (Bacillus pumilus ST18.16/133, Curtobacterium sp. ST18.16/085, and Staphylococcus saprophyticus ST18.16/160) that were isolated from the habitat of the insects. Results revealed that insects from all trophic levels responded to bacterial volatiles, but olfactory responses varied between and within trophic levels. All bacteria produced the same set of volatile compounds, but often in different relative concentrations. For 11 of these volatiles we found contrasting correlations between their concentration and the behavior of the primary parasitoids and hyperparasitoids. Furthermore, olfactometer experiments on three of these compounds confirmed the contrasting olfactory responses of primary parasitoids and hyperparasitoids. The potential of these findings for the development of novel semiochemical-based strategies to improve biological aphid control has been discussed.

Cuticular hydrocarbons (CHCs) are often used in the chemical communication among social insects. CHCs can be used in nestmate recognition and as queen pheromones, the latter allows the regulation of the reproductive division of labor. In the common wasp Vespula vulgaris, CHCs and egg-marking hydrocarbons are caste-specific, being hydrocarbon queen pheromones and egg maternity signals. Whether these compounds are conserved among other Vespinae wasps remains unknown. Queens, virgin queens, reproductive workers, and workers belonging to four different wasp species, Dolichovespula media, Dolichovespula saxonica, Vespa crabro, and Vespula germanica, were collected and studied. The cuticular hydrocarbons, egg surface, and Dufour's gland composition were characterized and it was found that chemical compounds are caste-specific in the four species. Quantitative and qualitative differences were detected in the cuticle, eggs, and Dufour's gland. Some specific hydrocarbons that were shown to be overproduced in the cuticle of queens were also present in higher quantities in queen-laid eggs and in their Dufour's gland. These hydrocarbons can be indicated as putative fertility signals that regulate the division of reproductive labor in these Vespine societies. Our results are in line with the literature for V. vulgaris and D. saxonica, in which hydrocarbons were shown to be conserved queen signals. This work presents correlative evidence that queen chemical compounds are found not only over the body surface of females but also in other sources, such as the Dufour's gland and eggs.

Juvenile hormone (JH) regulates developmental and physiological processes in insects. In bumble bees, the hormone acts as a gonadotropin that mediates ovary development, but the exact physiological pathways involved in ovary activation and subsequent egg laying are poorly understood. In this study, we examine how queen hibernation state, caste, and species impact the gonadotropic effect of JH in bumble bee queens through methoprene (JH analogue) application. We extend previous research by assessing queen egg laying and colony initiation, alongside ovary development. Furthermore, we compared sensitivity of workers of both species to the juvenile hormone's gonadotropic effect. In both bumble bee species, the ovaries of hibernated queens were developed five to six days after breaking diapause, regardless of methoprene treatment. By contrast, methoprene did have a stimulatory effect on ovary development in non-hibernated queens. The dose needed to obtain this effect was higher in B. impatiens. Methoprene did not have gonadotropic effects in callow workers of both species. These results indicate that the physiological effect of exogenous methoprene application varies according to species, caste and hibernation status. Interestingly, despite gonadotropic effects in non-hibernated queens, oviposition was not accelerated by JH. This suggests that JH alone is insufficient to induce egg laying and that an additional stimulus, which is naturally present in hibernated queens, is required. Consequently, our findings indicate that other physiological processes, beyond a rise in JH alone, are required for oviposition and colony initiation.