Population links between an insectivorous bird and moths disentangled through national-scale monitoring data.

Insects are key components of food chains, and monitoring data provides new opportunities to identify trophic relationships at broad spatial and temporal scales. Here, combining two monitoring datasets from Great Britain, we reveal how the population dynamics of the blue tit Cyanistes caeruleus are influenced by the abundance of moths - a core component of their breeding diet. We find that years with increased population growth for blue tits correlate strongly with high moth abundance, but population growth in moths and birds is less well correlated; suggesting moth abundance directly affects bird population change. Next, we identify moths that are important components of blue tit diet, recovering associations to species previously identified as key food sources such as the winter moth Operoptera brumata. Our work provides new evidence that insect abundance impacts bird population dynamics in natural communities and provides insight into spatial diet turnover at a national-scale.

New citizen science initiative enhances flowering onset predictions for fruit trees in Great Britain.

Accurately predicting flowering phenology in fruit tree orchards is crucial for timely pest and pathogen treatments and for the introduction of managed pollinators. Making predictions requires large datasets of flowering dates, which are often limited to single locations. Consequently, the resulting phenology predictions are not representative across larger geographic areas. Citizen science may offer a solution to this data gap, with millions of biological records across a wide range of taxa recorded annually. Here, a new citizen science platform called 'FruitWatch' is introduced, monitoring the flowering dates of fruit trees in Great Britain. The objectives of this study are to assess the suitability of FruitWatch submissions to (i) detect latitudinal variation in flowering onset dates, (ii) parameterize existing phenology modelling frameworks, and (iii) make predictions of flowering onset dates across Great Britain for a single year. Using data for four cultivars from 2022, linear models reveal significant latitudinal delays in flowering onset of as much as 1.49 ± 0.63 days per degree latitude further north (Pear 'Conference'), with significant delays also seen in Cherry 'Stella' (1.39 ± 0.48 days) and Plum 'Victoria' (1.22 ± 0.18 days). FruitWatch informed phenology modelling frameworks performed well for predicting flowering onset, with root mean square error values of predictions from validation datasets ranging between 4.6 ('Victoria') and 8.0 ('Conference') days. The parameterized models also provided realistic flowering onset predictions across Great Britain in 2022, with earlier flowering dates predicted in warmer areas. These findings demonstrate the potential of citizen science data to offer growers cultivar- and location-specific phenology predictions to help inform orchard management.

Novel indices reveal that pollinator exposure to pesticides varies across biological compartments and crop surroundings.

Declines in insect pollinators have been linked to a range of causative factors such as disease, loss of habitats, the quality and availability of food, and exposure to pesticides. Here, we analysed an extensive dataset generated from pesticide screening of foraging insects, pollen-nectar stores/beebread, pollen and ingested nectar across three species of bees collected at 128 European sites set in two types of crop. In this paper, we aimed to (i) derive a new index to summarise key aspects of complex pesticide exposure data and (ii) understand the links between pesticide exposures depicted by the different matrices, bee species and apple orchards versus oilseed rape crops. We found that summary indices were highly correlated with the number of pesticides detected in the related matrix but not with which pesticides were present. Matrices collected from apple orchards generally contained a higher number of pesticides (7.6 pesticides per site) than matrices from sites collected from oilseed rape crops (3.5 pesticides), with fungicides being highly represented in apple crops. A greater number of pesticides were found in pollen-nectar stores/beebread and pollen matrices compared with nectar and bee body matrices. Our results show that for a complete assessment of pollinator pesticide exposure, it is necessary to consider several different exposure routes and multiple species of bees across different agricultural systems.

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.