Adam McVeigh

Arable field margins provide important floral resources for insect foragers. This study assessed the significance of cultivated margins and floristically enhanced margins, both English agri-environment scheme (AES) options, to foraging bumble bees (Bombus species). We examined plant foraging preferences in each habitat according to species and caste. Additionally, detailed botanical surveys were carried out to determine vascular plant densities on the study margins. Overall, our results emphasised the importance of spontaneous (Asteraceae) species emerging from the seed bank in the provision of forage across Bombus species and castes, and highlighted that Bombus foraging preferences appeared to be only weakly related to floral species densities. Although found only occasionally in high densities, the popularity of these dicots was likely due to high nectar sugar mass. Bombus queens were recorded relatively infrequently, implying that these habitats are failing to provide the preferred floral resources of all Bombus spp. queens. Queens that were observed were found to favour earlier-flowering species (e.g. Anchusa arvensis) and species with longer corollas (e.g. Vicia sativa). Worker bees across Bombus spp. showed high overlap in plant preferences (e.g. Cirsium arvense, Ononis spinosa). However, some variability in preferences between castes within a species were noted, for example, only B. terrestris/lucorum drones were found to forage on Crepis vesicaria in cultivated margins. Additionally, bumble bee abundance was only found to increase as dicot cover increased. Overall, our findings highlight the importance of continuing to utilise multiple AES types in order to fully support Bombus and other pollinating insect populations on farmland.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies’ exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony’s health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project’s data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

In this work we aim to provide a quantitative method allowing the probing of the physiological status of honeybee colonies by providing them with a gentle, short, external artificial vibrational shockwave, and recording their response. The knock is provided by an external electromagnetic shaker attached to the outer wall of a hive, driven by a computer with a 0.1 s long, monochromatic vibration at 340Hz set to an amplitude that occasionally yields a mild response from the bees, recorded by an accelerometer placed in the middle of the central frame of the colony. To avoid habituation, the stimulus is supplied at randomised times, approximately every hour. The method is pioneered with a pilot study on a single colony hosted indoors, then extended onto eight outdoors colonies. The results show that we can quantitatively sense the colony's overall mobility, independently from another physiological aspect, which is phenomenologically explored. Using this, a colony that is queenless is easily discriminated from the others.

Sensor technologies have sufficiently advanced to provide low-cost devices that can quantify carbon dioxide levels in honeybee hives with high temporal resolution and in a small enough package for hive deployment. Recent publications have shown that summer carbon dioxide levels vary throughout the day and night over ranges that typically exceed 5000 ppm. Such dramatic changes in a measurable parameter associated with bee physiology are likely to convey information about the colony health. In this work, we present data from four UK-based hives collected through the winter of 2022/2023, with a focus on seeing if carbon dioxide can indicate when colonies are at risk of failure. These hives have been fitted with two Sensirion SCD41 photoacoustic non-dispersive infrared (NDIR) carbon dioxide sensors, one in the queen excluder, at the top of the brood box, and one in the crown board, at the top of the hive. Hive scales have been used to monitor the hive mass, and internal and external temperature sensors have been included. Embedded accelerometers in the central frame of the brood box have been used to measure vibrations. Data showed that the high daily variation in carbon dioxide continued throughout the coldest days of winter, and the vibrational data suggested that daily fanning may be responsible for restoring lower carbon dioxide levels. The process of fanning will draw in colder air to the hive at a time when the bees should be using their energy to maintain the colony temperature. Monitoring carbon dioxide may provide feedback, prompting human intervention when the colony is close to collapse, and a better understanding may contribute to discussions on future hive design.

Non-dispersive infra-red (NDIR) detectors have become the dominant method for measuring atmospheric CO2, which is thought to be an important gas for honeybee colony health. In this work we describe a microcontroller-based system used to collect data from Senserion SCD41 NDIR sensors placed in the crown boards and queen excluders of honeybee colonies. The same sensors also provide relative humidity and temperature data. Several months of data have been recorded from four different hives. The mass change measurements, from hive scales, when foragers leave the hive were compared with the data from the gas sensors. Our data suggest that it is possible to estimate the colony size from the change in measured CO2, however no such link with the humidity is observed. Data are presented showing the CO2 decreasing over many weeks as a colony dies.

We investigate the potential benefits to pollinators of two agri-environment scheme habitats, annually cultivated and floristically enhanced grass margins. The former encourages annual plant species whereas the latter targets the provision of perennial plants, both may benefit foraging pollinators, many of which have declined in the UK since the 1980s. We surveyed thirty cultivated margins and thirty floristically enhanced grass margins across the UK for pollinators, which included bumblebees Bombus spp., solitary bees and hoverflies Syrphidae. Pollinator abundance was then related to margin attributes such as age, width, soil fertility and adjacent habitat type. For cultivated margins we also investigated relationships with cultivation and rotation, and for floristically enhanced margins time cut. Plant preferences of foraging pollinators were recorded in 2019. On cultivated margins, target annual plants were frequently recorded on plots and were repeatedly visited by pollinators with management significantly influencing visitation rates. For example, plots which had been created with ploughing attracted fewer solitary bees and bees overall than those created with minimum tillage. Annually rotated cultivated margins were associated with lower flower abundance, broad leaved species cover and vegetation heights which resulted in lower total bee abundance. We therefore advise that cultivated margins be left in situ on farmland over longer periods. Older floristically enhanced grass margins became dominated by grass and contained fewer flowerheads to support foraging pollinators. Compared to those established via natural regeneration, sown margins were associated with increased bee and Syrphidae abundance, which is probably linked to the high flowerhead abundance and coverage of broad-leaved species on sown plots. Our pollinator foraging data from 2019 showed that tolerance of some agricultural weeds should be advocated. Our results highlight the complementary benefits of these agri-environment scheme habitats to pollinators. We suggest that where arable pollinator conservation is a priority both habitats be provided.

Honeybee colonies depend on suitable temperatures for successful development. We demonstrate the use of a spatially resolved temperature measurement system for a honeybee colony by producing ten custom frames which results into four hundred eighty sensors across the hive. A first prototype used four layers of wax to embed the sensors, however, the honeybees rejected these and removed the wax before building new, irregular honeycomb. A second system using a single sheet of wax onto which the sensors were laid was accepted by the colony, and normal honeycomb was built. We showcase some of the data collected from this system.

Two of the most relevant gasses correlating to honeybee colony health are likely carbon dioxide and humidity. Non-Dispersive Infra-Red (NDIR) detectors have become the dominant method for measuring atmospheric CO2. In this work, we describe a microcontroller-based system used to collect data from two models of these NDIR sensors that also provide humidity and temperature data. Placement in a frame in the brood box and in the crown board and queen excluder is investigated. With several thousands of hours of data for comparison, we demonstrate both the daily and long-term trends in these important gasses in multiple honeybee colonies.