PAH7 concentration reflects anthropization: A study using environmental biomonitoring with honeybees

Cochard, Précillia; Laurie, Myriam; Veyrand, Bruno; Bizec, Bruno Le; Poirot, Benjamin; Marchand, Philippe

doi:10.1016/j.scitotenv.2020.141831

Cited by 15 publications

(15 citation statements)

References 33 publications

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“…We found a high variety of studied pollutant(s) of interest, matrices, and sampling in the nineteen included studies. Of the nineteen studies included, thirteen reviewed contaminant levels in a single hive matrix, as shown in Table 2 [10,14,[34][35][36][37][39][40][41]44,46,47]. Note: BTEX = benzene, toluene, ethylbenzene, and xylenes, HM = heavy metal, PAH = polycyclic aromatic hydrocarbon, PM = particulate matter, n = number, ICP-MS = inductively coupled plasma-mass spectrometry, ICP-OES = inductively coupled plasma-optical emission spectroscopy, GC-MS = gas chromatography-mass spectrometry, EAS = electron absorption spectroscopy, FAS = flame absorption spectroscopy, and AAS = atomic absorption spectroscopy.…”

Section: Characteristics Of Reviewed Studiesmentioning

confidence: 99%

Elucidating the Role of Honey Bees as Biomonitors in Environmental Health Research

Mair,

Irrgeher,

Haluza

2023

Insects

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Recently, the One Health concept, which recognizes the interconnectedness of environmental, animal, and human health, has gained popularity. To collect data on environmental pollutants potentially harmful to human health over time, researchers often turn to natural organisms known as biomonitors. Honey bees, in particular, prove to be exceptionally valuable biomonitors due to their capacity to accumulate pollutants from the air, soil, and water within a specific radius during their foraging trips. This systematic literature review summarizes the previous application of the bee species Apis mellifera in pollutant monitoring in articles published during the period of 2010–2020. Nineteen studies were included in this systematic literature review. Of these studies, the majority (n = 15) focused on the detection of heavy metals in honey bees and beehive products, while 4 studies focused on air pollution by polycyclic aromatic hydrocarbons or particulate matter. The matrix most often applied was the whole honey bee. The included studies demonstrated that honey bees and hive products deliver quantitative and qualitative information about specific pollutants. In this regard, the whole honey bee was found to be the most reliable biomonitor. We found that the included studies differed in design and the methods used. Standardized studies could foster a more consistent interpretation of the levels detected in beehive matrices from an environmental health perspective.

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Section: Characteristics Of Reviewed Studiesmentioning

confidence: 99%

Elucidating the Role of Honey Bees as Biomonitors in Environmental Health Research

Mair,

Irrgeher,

Haluza

2023

Insects

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“…Systematic variations in compounds and trace element concentrations of honey from gathered from various colonies closely re ect anthropogenic land-use activities (Smith et al, 2019). Researchers monitored pesticides, heavy metals and volatile organic compounds in the environment by detecting the composition of substances in bees and honey (Balayiannis et al, 2008;Cochard et al, 2021;Sari et al, 2021). In addition, honeybees have extraordinary olfactory capabilities and are highly sensitive to toxic substances.…”

Section: Introductionmentioning

confidence: 99%

Beehive Sound: Can It Indicate The Response Of Honey Bees To Chemicals In Or Out Of The Beehive?

Xin-qiu

Sharif

et al. 2022

Preprint

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Honey bees (Apis spp.) are widely used as biological indicators of environmental changes. Recently, bees have been explored by researchers to monitor air contamination by listening to their hive sound. However, no study has determined whether beehive sound reflects the responses of bees to in-hive or out-hive chemicals. In this study, we conducted a feeding experiment to address this. First, we fed colonies with pure syrup (PS), syrup containing acetone (SA) or syrup containing ethyl acetate (SE) to collect beehive sound to establish multiple classifications using machine learning (ML) models. Then, we orderly fed colonies with PS, followed by SE, SA and PS. Next, we fed colonies in PS, SA, SE and PS order. Eventually, we evaluated the recall and precision of the model in detecting each syrup type. The result built on orderly feeding had a recall of 99%, 80%, 30%, 53% in detecting PS, SE, SA, PS, respectively. In the reverse feeding experiment, the ML model has a recall of 99%, 89%, 37% and 44% in detecting PS, SA, SE, and PS, respectively. Because the collected syrup in the two orderly feeding sessions was not removed from the frames during the experiment, the results indicate that beehive sound responds to chemicals in or out of the beehive.

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“…[2][3][4] France is among the countries affected. 5 Human activities, decreasing floral resources and pollution, [6][7][8][9] climate change, 10 and the emergence of new pathogens have been implicated in colony collapse disorder. 11,12 In particular, since the 1970s, a mite originating from Asia, Varroa destructor, has spread throughout the world and is now one of the principal pathogenic agents in bee hives.…”

Section: Introductionmentioning

confidence: 99%

Modelling the impact of Apivar treatment on a Varroa mite population and the influence of resistance

Almecija

Poirot²,

Ventelon

et al. 2021

Pest Management Science

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BACKGROUND Varroa destructor is a parasite of honeybees. It causes biological damage leading to the colony collapse in the absence of treatment. In recent years, acaricide resistance has emerged in Varroa mites, leading to a decrease in treatment efficacy. We modelled the action of Apivar (amitraz) treatment, using three input parameters: treatment duration, treatment period, and daily mortality due to the treatment. The output parameters were cumulative mite mortality during treatment, the residual number of Varroa mites, and treatment efficacy, expressed as a percentage. RESULTS The model was validated by monitoring efficacy in the field, in 36 treated hives. According to the model, treatment in the absence of brood is optimal. For a long period without egg laying during the winter, an initial infestation of 100 mites and a start date for treatment of August 7, a minimal treatment efficacy of 98.8% is required for stabilization of the mite population for year to year. More effective treatment is associated with lower cumulative numbers of dead Varroa mites over the entire treatment period. Thus, the total number of dead mites observed during the monitoring of field efficacy provides information about more than just the initial level of colony infestation. The proportion of resistant mites can be modelized by a decrease of daily mortality rate influencing treatment efficacy. Management of the initial Varroa mite infestation of the colony by the beekeeper can compensate for the decrease in treatment efficacy for resistance thresholds of up to 40% of resistant mites. CONCLUSION Treatment efficacy depends on several parameters, including initial level of infestation, treatment period and the presence of acaricide resistance. Amitraz resistance may lead to treatment failure, even if the beekeeper is able to keep initial infestation rates low. © 2021 Society of Chemical Industry.

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PAH7 concentration reflects anthropization: A study using environmental biomonitoring with honeybees

Cited by 15 publications

References 33 publications

Elucidating the Role of Honey Bees as Biomonitors in Environmental Health Research

Elucidating the Role of Honey Bees as Biomonitors in Environmental Health Research

Beehive Sound: Can It Indicate The Response Of Honey Bees To Chemicals In Or Out Of The Beehive?

Modelling the impact of Apivar treatment on a Varroa mite population and the influence of resistance

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