A blood test to monitor bee health across a European network of agricultural sites of different land-use by MALDI BeeTyping mass spectrometry.

There are substantial concerns about impaired honey bee health and colony losses due to several poorly understood factors. We used MALDI profiling (MALDI BeeTyping®) analysis to investigate how some environmental and management factors under field conditions across Europe affected the honey bee haemolymph peptidome (all peptides in the circulatory fluid), as a profile of molecular markers representing the immune status of Apis mellifera. Honey bees were exposed to a range of environmental stressors in 128 agricultural sites across eight European countries in four biogeographic zones, with each country contributing eight sites each for two different cropping systems: oilseed rape (OSR) and apple (APP). The full haemolymph peptide profiles, including the presence and levels of three key immunity markers, namely the antimicrobial peptides (AMPs) Apidaecin, Abaecin and Defensin-1, allowed the honey bee responses to environmental variables to be discriminated by country, crop type and site. When considering just the AMPs, it was not possible to distinguish between countries by the prevalence of each AMP in the samples. However, it was possible to discriminate between countries on the amounts of the AMPs, with the Swedish samples in particular expressing high amounts of all AMPs. A machine learning model was developed to discriminate the haemolymphs of bees from APP and OSR sites. The model was 90.6 % accurate in identifying the crop type from the samples used to build the model. Overall, MALDI BeeTyping® of bee haemolymph represents a promising and cost-effective "blood test" for simultaneously monitoring dozens of peptide markers affected by environmental stressors at the landscape scale, thus providing policymakers with new diagnostic and regulatory tools for monitoring bee health.

Distribution of infectious and parasitic agents among three sentinel bee species across European agricultural landscapes.

Infectious and parasitic agents (IPAs) and their associated diseases are major environmental stressors that jeopardize bee health, both alone and in interaction with other stressors. Their impact on pollinator communities can be assessed by studying multiple sentinel bee species. Here, we analysed the field exposure of three sentinel managed bee species (Apis mellifera, Bombus terrestris and Osmia bicornis) to 11 IPAs (six RNA viruses, two bacteria, three microsporidia). The sentinel bees were deployed at 128 sites in eight European countries adjacent to either oilseed rape fields or apple orchards during crop bloom. Adult bees of each species were sampled before their placement and after crop bloom. The IPAs were detected and quantified using a harmonised, high-throughput and semi-automatized qPCR workflow. We describe differences among bee species in IPA profiles (richness, diversity, detection frequencies, loads and their change upon field exposure, and exposure risk), with no clear patterns related to the country or focal crop. Our results suggest that the most frequent IPAs in adult bees are more appropriate for assessing the bees' IPA exposure risk. We also report positive correlations of IPA loads supporting the potential IPA transmission among sentinels, suggesting careful consideration should be taken when introducing managed pollinators in ecologically sensitive environments.

Diverse pollen nutrition can improve the development of solitary bees but does not mitigate negative pesticide impacts.

Floral resource loss and pesticide exposure are major threats to bees in intensively managed agroecosystems, but interactions among these drivers remain poorly understood. Altered composition and lowered diversity of pollen nutrition may reinforce negative pesticide impacts on bees. Here we investigated the development and survival of the solitary bee Osmia bicornis provisioned with three different pollen types, as well as a mixture of these types representing a higher pollen diversity. We exposed bees of each nutritional treatment to five pesticides at different concentrations in the laboratory. Two field-realistic concentrations of three nicotinic acetylcholine receptor (nAChR) modulating insecticides (thiacloprid, sulfoxaflor and flupyradifurone), as well as of two fungicides (azoxystrobin and tebuconazole) were examined. We further measured the expression of two detoxification genes (CYP9BU1, CYP9BU2) under exposure to thiacloprid across different nutrition treatments as a potential mechanistic pathway driving pesticide-nutrition interactions. We found that more diverse pollen nutrition reduced development time, enhanced pollen efficacy (cocoon weight divided by consumed pollen weight) and pollen consumption, and increased weight of O. bicornis after larval development (cocoon weight). Contrary to fungicides, high field-realistic concentrations of all three insecticides negatively affected O. bicornis by extending development times. Moreover, sulfoxaflor and flupyradifurone also reduced pollen efficacy and cocoon weight, and sulfoxaflor reduced pollen consumption and increased mortality. The expression of detoxification genes differed across pollen nutrition types, but was not enhanced after exposure to thiacloprid. Our findings highlight that lowered diversity of pollen nutrition and high field-realistic exposure to nAChR modulating insecticides negatively affected the development of O. bicornis, but we found no mitigation of negative pesticide impacts through increased pollen diversity. These results have important implications for risk assessment for bee pollinators, indicating that negative effects of nAChR modulating insecticides to developing solitary bees are currently underestimated.

Nutritional stress exacerbates impact of a novel insecticide on solitary bees' behaviour, reproduction and survival.

Pesticide exposure and food stress are major threats to bees, but their potential synergistic impacts under field-realistic conditions remain poorly understood and are not considered in current pesticide risk assessments. We conducted a semi-field experiment to examine the single and interactive effects of the novel insecticide flupyradifurone (FPF) and nutritional stress on fitness proxies in the solitary bee Osmia bicornis. Individually marked bees were released into flight cages with monocultures of buckwheat, wild mustard or purple tansy, which were assigned to an insecticide treatment (FPF or control) in a crossed design. Nutritional stress, which was high in bees foraging on buckwheat, intermediate on wild mustard and low on purple tansy, modulated the impact of insecticide exposure. Within the first day after application of FPF, mortality of bees feeding on buckwheat was 29 times higher compared with control treatments, while mortality of FPF exposed and control bees was similar in the other two plant species. Moreover, we found negative synergistic impacts of FPF and nutritional stress on offspring production, flight activity, flight duration and flower visitation frequency. These results reveal that environmental policies and risk assessment schemes that ignore interactions among anthropogenic stressors will fail to adequately protect bees and the pollination services they provide.

Hyperbolic odorant mixtures as a basis for more efficient signaling between flowering plants and bees.

Animals use odors in many natural contexts, for example, for finding mates or food, or signaling danger. Most analyses of natural odors search for either the most meaningful components of a natural odor mixture, or they use linear metrics to analyze the mixture compositions. However, we have recently shown that the physical space for complex mixtures is 'hyperbolic', meaning that there are certain combinations of variables that have a disproportionately large impact on perception and that these variables have specific interpretations in terms of metabolic processes taking place inside the flower and fruit that produce the odors. Here we show that the statistics of odorants and odorant mixtures produced by inflorescences (Brassica rapa) are also better described with a hyperbolic rather than a linear metric, and that combinations of odorants in the hyperbolic space are better predictors of the nectar and pollen resources sought by bee pollinators than the standard Euclidian combinations. We also show that honey bee and bumble bee antennae can detect most components of the B. rapa odor space that we tested, and the strength of responses correlates with positions of odorants in the hyperbolic space. In sum, a hyperbolic representation can be used to guide investigation of how information is represented at different levels of processing in the CNS.

No evidence for impaired solitary bee fitness following pre-flowering sulfoxaflor application alone or in combination with a common fungicide in a semi-field experiment.

Pesticide exposure is considered a major driver of pollinator decline and the use of neonicotinoid insecticides has been restricted by regulatory authorities due to their risks for pollinators. Impacts of new alternative sulfoximine-based compounds on solitary bees and their potential interactive effects with other commonly applied pesticides in agriculture remain unclear. Here, we conducted a highly replicated full-factorial semi-field experiment with the solitary bee Osmia bicornis, an important pollinator of crops and wild plants in Europe, and Phacelia tanacetifolia as a model crop. We show that spray applications of the insecticide sulfoxaflor (product Closer) and the fungicide azoxystrobin (product Amistar), both alone and combined, had no significant negative impacts on adult female survival or the production, mortality, sex ratio and body size of offspring when sulfoxaflor was applied five days before crop flowering. Our results indicate that for O. bicornis (1) the risk of adverse impacts of sulfoxaflor (Closer) on fitness is small when applied at least five days before crop flowering and (2) that azoxystrobin (Amistar) has a low potential of exacerbating sulfoxaflor effects under field-realistic conditions.

Bee Tracker-an open-source machine learning-based video analysis software for the assessment of nesting and foraging performance of cavity-nesting solitary bees.

The foraging and nesting performance of bees can provide important information on bee health and is of interest for risk and impact assessment of environmental stressors. While radiofrequency identification (RFID) technology is an efficient tool increasingly used for the collection of behavioral data in social bee species such as honeybees, behavioral studies on solitary bees still largely depend on direct observations, which is very time-consuming. Here, we present a novel automated methodological approach of individually and simultaneously tracking and analyzing foraging and nesting behavior of numerous cavity-nesting solitary bees. The approach consists of monitoring nesting units by video recording and automated analysis of videos by machine learning-based software. This Bee Tracker software consists of four trained deep learning networks to detect bees that enter or leave their nest and to recognize individual IDs on the bees' thorax and the IDs of their nests according to their positions in the nesting unit. The software is able to identify each nest of each individual nesting bee, which permits to measure individual-based measures of reproductive success. Moreover, the software quantifies the number of cavities a female enters until it finds its nest as a proxy of nest recognition, and it provides information on the number and duration of foraging trips. By training the software on 8 videos recording 24 nesting females per video, the software achieved a precision of 96% correct measurements of these parameters. The software could be adapted to various experimental setups by training it according to a set of videos. The presented method allows to efficiently collect large amounts of data on cavity-nesting solitary bee species and represents a promising new tool for the monitoring and assessment of behavior and reproductive success under laboratory, semi-field, and field conditions.

Flowering resources modulate the sensitivity of bumblebees to a common fungicide.

Bees are exposed to various stressors, including pesticides and lack of flowering resources. Despite potential interactions between these stressors, the impacts of pesticides on bees are generally assumed to be consistent across bee-attractive crops, and regulatory risk assessments of pesticides neglect interactions with flowering resources. Furthermore, impacts of fungicides on bees are rarely examined in peer-reviewed studies, although these are often the pesticides that bees are most exposed to. In a full-factorial semi-field experiment with 39 large flight cages, we assessed the single and combined impacts of the globally used azoxystrobin-based fungicide Amistar® and three types of flowering resources (Phacelia, buckwheat, and a floral mix) on Bombus terrestris colonies. Although Amistar is classified as bee-safe, Amistar exposure through Phacelia monocultures reduced adult worker body mass and colony growth (including a 55% decline in workers and an 88% decline in males), while the fungicide had no impact on colonies in buckwheat or the floral mix cages. Furthermore, buckwheat monocultures hampered survival and fecundity irrespective of fungicide exposure. This shows that bumblebees require access to complementary flowering species to gain both fitness and fungicide tolerance and that Amistar impacts are flowering resource-dependent. Our findings call for further research on how different flowering plants affect bees and their pesticide tolerance to improve guidelines for regulatory pesticide risk assessments and inform the choice of plants that are cultivated to safeguard pollinators.

Crab spiders impact floral-signal evolution indirectly through removal of florivores.

The puzzling diversity of flowers is primarily shaped by selection and evolutionary change caused by the plant's interaction with animals. The contribution of individual animal species to net selection, however, may vary depending on the network of interacting organisms. Here we document that in the buckler mustard, Biscutella laevigata, the crab spider Thomisus onustus reduces bee visits to flowers but also benefits plants by feeding on florivores. Uninfested plants experience a trade-off between pollinator and spider attraction as both bees and crab spiders are attracted by the floral volatile ß-ocimene. This trade-off is reduced by the induced emission of ß-ocimene after florivore infestation, which is stronger in plant populations where crab spiders are present than where they are absent, suggesting that plants are locally adapted to the presence of crab spiders. Our study demonstrates the context-dependence of selection and shows how crab spiders impact on floral evolution.