DOI: 10.5061/dryad.kwh70rzhh
title: Data from: Innovative airborne DNA approach for monitoring honey bee foraging and health

description: Environmental DNA (eDNA) refers to genetic material collected from the
 environment and not directly from an organism. eDNA is best known as a
 tool in aquatic ecology but has been found associated with almost every
 substrate examined including soils, surfaces, and riding around on other
 animals. The collection of eDNA from air is one of the most recent
 advances and has been used to monitor a variety of organisms, including
 plants, animals, and microorganisms. Current evidence suggests a high
 turnover rate providing a recent signal for the presence of DNA associated
 with an organism. Here, we test whether material carried in air can be
 collected from honey bee hives to evaluate recent foraging behavior and
 colony health. We sampled air using purpose-built “bee safe” air filters
 operating for 5-6 hours at each colony. We successfully recovered plant,
 fungal and microbial DNA from the air within hives over a 3-week pilot
 period. From these data we identified the core honey bee microbiome and
 plant interaction data representing foraging behaviour. We calculated beta
 diversity to estimate the effects of apiary sites and sampling date on
 data recovery. We observed that variance in ITS data was influenced by
 sampling date. Given that honey bees are generalist pollinators our
 ability to detect temporal signals in associated plant sequence data
 suggest this method opens new avenues into the ecological analysis of
 short-term foraging behavior at the colony level. In comparison variance
 in microbial 16S sequencing data was more influenced by sampling location.
 As the assessment of colony health needs to be localized, spatial variance
 in these data indicate this may be an important tool in detecting
 infection. This pilot study demonstrates that colony air filtration has
 strong potential for the rapid screening of honey bee health and for the
 study of bee behaviour.
description: # Data from: Innovative airborne DNA approach for monitoring honey bee
 foraging and health Dataset DOI:
 [10.5061/dryad.kwh70rzhh](10.5061/dryad.kwh70rzhh) ## Description of the
 data and file structure This is an eDNA analysis of filtered air from bee
 hives. All methods are described in detail in the manuscript. ### Files
 and variables #### File: 16SV4 **Description:** Files associated with all
 data and correspond with Figure 2 Files are coded with "MP" in
 the file name after the gene name (16s). This MP code corresponds with
 samples from Figure 2 as follows MP08 Fergus F01 MP09 Fergus F02 MP10
 Fergus F03 MP11 Fergus F04 MP12 Fergus F05 MP13 Mono Week1 M06 MP14 Mono
 Week1 M07 MP15 Mono Week1 M08 MP16 Mono Week1 M09 MP17 Mono Week1 M10 MP18
 Mono Week1 M11 MP19 Mono Week2 M12 MP20 Mono Week2 M13 MP21 Mono Week2 M14
 MP22 Mono Week2 M15 MP23 Mono Week2 M16 MP24 Mono Week2 M17 MPCon Positive
 Control MPNeg Negative Control #### File: ITS **Description:** Files are
 numbered to correspond with Samples from Figure 2 as follows Files are
 coded with "MP" in the file name after the gene name (ITS). This
 MP code corresponds with samples from Figure 2 as follows MP08 Fergus F01
 MP09 Fergus F02 MP10 Fergus F03 MP11 Fergus F04 MP12 Fergus F05 MP13 Mono
 Week1 M06 MP14 Mono Week1 M07 MP15 Mono Week1 M08 MP16 Mono Week1 M09 MP17
 Mono Week1 M10 MP18 Mono Week1 M11 MP19 Mono Week2 M12 MP20 Mono Week2 M13
 MP21 Mono Week2 M14 MP22 Mono Week2 M15 MP23 Mono Week2 M16 MP24 Mono
 Week2 M17 MPCon Positive Control MPNeg Negative Control ## Code/software
 These files can be analysed with any pipeline for NGS metabarcoding data.
 In our manuscript we use the QIIME2 v. 2019l10 pipeline. No extra coded
 scripts are used. We describe the subsequent steps and which reference
 databases we used in our methods. ## Access information Data was derived
 from the following sources: * All data were generated new for this
 manuscript using the methods described in the manuscript.