A short exposure to a semi-natural habitat alleviates the honey bee hive microbial imbalance caused by agricultural stress.

Honeybee health and the species' gut microbiota are interconnected. Also noteworthy are the multiple niches present within hives, each with distinct microbiotas and all coexisting, which we termed "apibiome". External stressors (e.g. anthropization) can compromise microbial balance and bee resilience. We hypothesised that (1) the bacterial communities of hives located in areas with different degrees of anthropization differ in composition, and (2) due to interactions between the multiple microbiomes within the apibiome, changes in the community of a niche would impact the bacteria present in other hive sections. We characterised the bacterial consortia of different niches (bee gut, bee bread, hive entrance and internal hive air) of 43 hives from 3 different environments (agricultural, semi-natural and natural) through 16S rRNA amplicon sequencing. Agricultural samples presented lower community evenness, depletion of beneficial bacteria, and increased recruitment of stress related pathways (predicted via PICRUSt2). The taxonomic and functional composition of gut and hive entrance followed an environmental gradient. Arsenophonus emerged as a possible indicator of anthropization, gradually decreasing in abundance from agriculture to the natural environment in multiple niches. Importantly, after 16 days of exposure to a semi-natural landscape hives showed intermediate profiles, suggesting alleviation of microbial dysbiosis through reduction of anthropization.

Honeybee-based biohybrid system for landmine detection.

Legacy landmines in post-conflict areas are a non-discriminatory lethal hazard and can still be triggered decades after the conflict has ended. Efforts to detect these explosive devices are expensive, time-consuming, and dangerous to humans and animals involved. While methods such as metal detectors and sniffer dogs have successfully been used in humanitarian demining, more tools are required for both site surveying and accurate mine detection. Honeybees have emerged in recent years as efficient bioaccumulation and biomonitoring animals. The system reported here uses two complementary landmine detection methods: passive sampling and active search. Passive sampling aims to confirm the presence of explosive materials in a mine-suspected area by the analysis of explosive material brought back to the colony on honeybee bodies returning from foraging trips. Analysis is performed by light-emitting chemical sensors detecting explosives thermally desorbed from a preconcentrator strip. The active search is intended to be able to pinpoint the place where individual landmines are most likely to be present. Used together, both methods are anticipated to be useful in an end-to-end process for area surveying, suspected hazardous area reduction, and post-clearing internal and external quality control in humanitarian demining.

Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs.

BACKGROUND: With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. RESULTS: Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. CONCLUSIONS: The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

Biomonitoring for wide area surveying in landmine detection using honeybees and optical sensing.

Humanitarian demining is a worldwide effort and the range of climates and environments prevent any one detection method being suitable for all sites, so more tools are required for safe and efficient explosives sensing. Landmines emit a chemical flux over time, and honeybees can collect the trace residues of explosives (as particles or as vapour) on their body hairs. This capability was exploited using a passive method allowing the honeybees to freely forage in a mined area, where trace explosives present in the environment stuck to the honeybee body, which were subsequently transferred onto an adsorbent material for analysis by a fluorescent polymer sensor. Potential false positive sources were investigated, namely common bee pheromones, the anti-varroa pesticide Amitraz, and the environment around a clean apiary, and no significant response was found to any from the sensor. The mined site gave a substantial response in the optical sensor films, with quenching efficiencies of up to 38%. A model was adapted to estimate the mass of explosives returned to the colony, which may be useful for estimating the number of mines in a given area.

Preconcentration techniques for trace explosive sensing.

Trace sensing of explosive vapours is a method in humanitarian demining and Improvised Explosive Device (IED) detection that has received increasing attention recently, since accurate, fast, and reliable chemical detection is highly important for threat identification. However, trace molecule sampling in the field can be extremely difficult due to factors including weather, locale, and very low vapour pressure of the explosive. Preconcentration of target molecules onto a substrate can provide a method to collect higher amounts of analyte for analysis. We used the commercial fluoropolymer Aflas as a preconcentrator material to sorb explosive molecules to the surface, allowing subsequent detection of the explosives via the luminescence quenching response from the organic polymer Super Yellow. The preconcentration effect of Aflas was confirmed and characterised with 2,4-DNT, prior to field sampling being conducted at a test minefield in Croatia by placing preconcentration strips in the entrance of beehives, where honeybees have collected explosive materials during free-flying. In this work we show for the first time a method for confirmation of landmines combining honeybee colonies containing a preconcentration material and subsequent monitoring of luminescence quenching.

Estimating the density of honeybee colonies across their natural range to fill the gap in pollinator decline censuses.

Although pollinator declines are a global biodiversity threat, the demography of the western honeybee (Apis mellifera) has not been considered by conservationists because it is biased by the activity of beekeepers. To fill this gap in pollinator decline censuses and to provide a broad picture of the current status of honeybees across their natural range, we used microsatellite genetic markers to estimate colony densities and genetic diversity at different locations in Europe, Africa, and central Asia that had different patterns of land use. Genetic diversity and colony densities were highest in South Africa and lowest in Northern Europe and were correlated with mean annual temperature. Confounding factors not related to climate, however, are also likely to influence genetic diversity and colony densities in honeybee populations. Land use showed a significantly negative influence over genetic diversity and the density of honeybee colonies over all sampling locations. In Europe honeybees sampled in nature reserves had genetic diversity and colony densities similar to those sampled in agricultural landscapes, which suggests that the former are not wild but may have come from managed hives. Other results also support this idea: putative wild bees were rare in our European samples, and the mean estimated density of honeybee colonies on the continent closely resembled the reported mean number of managed hives. Current densities of European honeybee populations are in the same range as those found in the adverse climatic conditions of the Kalahari and Saharan deserts, which suggests that beekeeping activities do not compensate for the loss of wild colonies. Our findings highlight the importance of reconsidering the conservation status of honeybees in Europe and of regarding beekeeping not only as a profitable business for producing honey, but also as an essential component of biodiversity conservation.