DOI: 10.5061/dryad.gf1vhhmw2
title: Nontarget impacts of neonicotinoids on nectar-inhabiting microbes

description: Plant-systemic neonicotinoid (NN) insecticides can exert non-target
 impacts on organisms like beneficial insects and soil microbes. NNs can
 affect plant microbiomes, but we know little about their effects on
 microbial communities that mediate plant-insect interactions, including
 nectar-inhabiting microbes (NIMs). Here we employed two approaches to
 assess impacts of NN exposure on several NIM taxa. First, we assayed in
 vitro effects of six NN compounds on NIM growth using plate assays.
 Second, we inoculated a standardized NIM community into nectar of
 NN-treated canola (Brassica napus) and assessed survival and growth after
 24 hours. With few exceptions, in vitro NN exposure tended to decrease
 bacterial growth metrics. However, the magnitude of decrease and the NN
 concentrations at which effects were observed varied substantially across
 bacteria. Yeasts showed no consistent in vitro response to NNs. In nectar,
 we saw no effects of NN treatment on NIM community metrics. Rather, NIM
 abundance and diversity responded to inherent plant qualities like nectar
 volume. In conclusion, we found no evidence NIMs respond to field-relevant
 NN levels in nectar within 24 h, but our study suggests that context,
 specifically assay methods, time, and plant traits, is important in
 assaying effects of NN on microbial communities.
description: <strong>EXPERIMENTAL PROCEDURES </strong>
 <strong>Overview of experiments</strong>
 To determine if and how exposure to NN residues affects the
 growth and abundance of NIMs, we conducted two separate experiments.
 First, we grew seven microbes as pure (single-species) cultures in
 artificial broths spiked to contain one of four concentrations of each of
 six NN compounds. We monitored microbial growth over 72 h and calculated
 maximum growth rate (r) and carrying capacity (K). Second, we inoculated a
 standardized community of four microbe taxa (a subset of those from the
 first experiment) into floral nectar of greenhouse-grown, potted canola
 plants. Plants had been treated with either low or high doses of two
 commercial NN formulations. Plants were also irrigated at either a low or
 high rate to monitor for any effect of water availability on nectar
 characteristics, NN translocation, or microbe community metrics.
 <strong>In vitro plate reader
 experiment</strong> We selected seven microbe
 species to assay growth in the presence of set concentrations of six major
 NN compounds. The selected species occur in floral nectar, are relatively
 well-studied, and in some cases have been found to influence behaviors of
 flower-visiting animals or plant reproduction (Vannette, 2020) (Table 1).
 All microbe strains were sourced from suspensions in glycerol and sucrose
 stocks at -80 °C. Prior to each plate reader run, we streaked stock on
 agar media and incubated plates at 25 °C for 72 h. Yeasts were streaked on
 yeast media (YM) agar and bacteria on tryptic soy (TS) agar, except for
 <em>Apilactobacillus micheneri</em>, which was streaked on de
 Man, Rogosa and Sharpe (MRS) agar + 2% m/v fructose (Vuong and
 McFrederick, 2019). We also prepared liquid broth analogs of each media
 type (omitting agarose) for use in well plates. All agar and broth media
 contained 0.1% v/v of a solution of either chloramphenicol (antibacterial;
 in yeast media) or cycloheximide (antifungal; in bacterial media) in
 methanol (10% m/v). We acquired
 PESTANAL<sup>®</sup> analytical standards (Millipore Sigma,
 St. Louis, MO) for each of six major NN compounds (Table 2). We created a
 separate stock solution for each compound in sterile distilled water by
 adding 2 mg of the respective compound to 100 mL of sterile distilled
 water, yielding a concentration of 2 x 10<sup>4</sup> ppb or
 µg L<sup>-1</sup>. Stock solution bottles were wrapped in foil
 and kept in a container at 5 °C to prevent photodegradation of NNs
 (Borsuah <em>et al.</em>, 2020). These six stock solutions
 were used as spikes (as in Meikle <em>et al.</em>,
 2022) to achieve specific concentrations of each compound in the
 corresponding broth for each microbe assay (see below; see also
 Supplementary Material). To determine if NN type and
 concentration influence the growth of microbes <em>in
 vitro</em>, we conducted successive runs using two spectrophotometer
 microplate readers (models SYNERGY HTX and 800 TS; Agilent, Santa Clara,
 CA) simultaneously, using a consistent plate layout for all runs (Fig.
 S1). We grew each microbe strain in pure culture in two 96-well plates,
 run at the same time in the two readers, with each run comprising one
 microbe. Prior to a run, we prepared separate solutions of the appropriate
 broth for the focal microbe spiked to contain either 1000 ppb, 100 ppb, 10
 ppb, or a no-NN control of each of the six NN compounds (see Table 2 for
 the ecological context of these concentrations). This resulted in a total
 of eight replicate wells for each of these 24 treatments per experimental
 run. For the inoculum, we prepared a suspension of the focal microbe by
 scraping a 2-mm bolus from agar into 3.5 mL of the appropriate broth and
 vortexing. Per treatment, we inoculated six of the eight wells containing
 180 µL of sterile broth with 20 µL of inoculum. In the remaining wells, we
 prepared 200 µL of non-inoculated broth to monitor for contamination
 across treatments. Immediately after inoculation, plates were sealed with
 a lid and wax film to minimize evaporation, then loaded into readers and
 incubated continuously at 25 °C (30 °C for
 <em>Apilactobacillus</em>; McFrederick <em>et
 al.</em>, 2017) for 72 hours. To estimate changes in cell
 concentration over time, readers recorded the optical density at λ=600 nm
 (OD<sub>600</sub>) of all wells after shaking (6-mm diameter
 at 6 Hz) every 15 min for 72h.
 <strong>Statistical analysis</strong>
 We performed all statistical analyses in R (R Core Team, 2023).
 We analyzed microbial growth using the function ‘SummarizeGrowthByPlate’
 in the package <em>growthcurver</em> (Sprouffske, 2020), which
 fits a logistic growth equation to OD vs. time, and estimates maximum
 growth rate (<em>r</em>) and maximum OD
 (<em>K</em>) for each well over the 72-h period. OD<sub>
 </sub>values for inoculated wells were blank-corrected by
 subtracting the mean OD of all non-inoculated wells at each time point.
 Using the package <em>lme4</em> (Bates <em>et
 al.</em>, 2015), we performed linear mixed-effect models (LMMs) for
 each microbe taxon, with either <em>r</em> or
 <em>K</em> as dependent variables, and NN type, concentration,
 and their interaction as independent variables, and plate reader as a
 random intercept effect. We obtained type III sums of squares and
 Kenward-Roger degrees of freedom using the ‘Anova’ function in the package
 <em>car </em>and checked all mixed models for
 multicollinearity (VIF &gt; 2.0) and normality of residuals.
 <strong>In planta greenhouse
 experiment</strong> To assess how NN application
 and plant water availability impact a microbe community in floral nectar,
 we conducted an experiment in a glass greenhouse on the University of
 California, Davis campus (USA: California: Yolo County; 38.5361 °N,
 -121.7475 °W). We obtained seeds of spring canola, <em>Brassica
 napus</em> L. ‘CP930RR’ (Land O’Lakes, Inc., Arden Hills, MN, USA),
 not previously treated with any chemicals. We sowed seeds in 60 2.5-gallon
 pots (25.7 cm x 23.2 cm) of “UC Mix C” soil (1:1 peat and sand) in three
 cohorts (18 February, 4 March, and 18 March 2022). After germination, we
 culled plants to six per pot. We applied commercial NN
 formulations to pots according to label specifications once the first buds
 were produced in a cohort, around 14-18 days before inoculations. Pots
 were treated with either a high dose (25 mg active ingredient per pot, or
 4.2 mg per plant), a low dose (2.5 mg AI per pot, 0.42 mg per plant), or a
 no-dose control of the respective formulation. For reference, a
 commercially treated seed typically contains from 0.2 to 1.3 mg of AI
 (Goulson, 2013; Wood and Goulson, 2017). We included two different NNs in
 the experiment, applied singly: imidacloprid, as
 Marathon<sup>®</sup> 1% Granular (OHP, Bluffton, SC, USA), and
 dinotefuran, as Safari<sup>®</sup> 20 SG (Valent U.S.A. LLC,
 San Ramon, CA, USA). We selected these two formulations based on multiple
 factors, including usage in agricultural settings, differences in
 solubility and leaching potential (Bonmatin <em>et al.</em>,
 2015), and approved usage in potting media and greenhouse
 settings. Each pot was additionally assigned in a
 crossed fashion to one of two irrigation treatments. Irrigation rate was
 controlled by inserting one high- or low-flow irrigation spike (Primerus
 Products, Encinitas, CA, USA) per pot, each connected to one central
 irrigation line (as in Cecala and Wilson Rankin, 2021).
 A high-flow spike emitted 2.7 times the water (0.61 L/min) as a low-flow
 spike (0.23 L/min). All pots were automatically irrigated simultaneously
 over the soil surface at 07:00 h daily for 60 s, or up to 120 s on hotter
 days to prevent wilting. Experimental flowers were
 selected and inoculated with a standardized microbe community containing
 10<sup>4</sup> cells µL<sup>-1 </sup>of each of a
 subset of four species from the plate reader experiment (Table 1) in a 20%
 v/v glycerol, 20% m/v sucrose stock (4 x 10<sup>4</sup> total
 cells µL<sup>-1</sup>). Microbes were stored in pure culture
 aliquots at -80 °C that were thawed and mixed the morning of each day of
 inoculations. All four microbes in the inoculum were confirmed to be
 successfully culturable on agar media prior to inoculations. Using a
 micropipette, we delivered 0.5 µL of inoculum into each lateral nectary
 (total 1 µL per flower) of newly opened canola flowers and tagged
 them. After 24 h, we excised all inoculated flowers
 using sterilized forceps and transported them to the laboratory. Inside a
 laminar flow hood, we used 10-µL microcapillary tubes to remove all nectar
 from each inoculated flower, estimated nectar volume from length of the
 fluid column, and expelled it into individual strip tubes. We also
 measured whole flower mass after nectar removal. We added 50 µL of
 Dulbecco’s phosphate-buffered saline (DPBS 1x) to each nectar sample,
 vortexed tubes, then plated a 15 µL aliquot of the solution onto each of
 YM, TS, and MRS agar in 100 x 15 mm Petri dishes using plating beads. We
 then incubated plates for 7 days at 25 °C and stored them at 5 °C. We
 tallied CFUs per plate and classified them into morphotypes. A
 representative CFU of each morphotype was sequenced by single-gene PCR and
 barcoded using NCBI Nucleotide BLAST (“blastn”;
 blast.ncbi.nlm.nih.gov). To determine the concentration
 of NN residues in canola nectar, we collected separate samples of nectar
 from newly opened, uninoculated flowers. To obtain sufficient volumes for
 residue analysis, we pooled up to 12 flowers from plants in the same pot.
 Samples were kept at -20 °C until analysis, at which point we diluted them
 in ultrapure water and analyzed them via electrospray ionization (ESI)
 LC-MS (Martel <em>et al.</em>, 2013) on an Orbitrap machine.
 For LC-MS analysis, 5µL of samples were injected onto a Thermo C18
 Accucore column (2.1 mm x 50 mm). A standard reverse phase gradient
 (solvent: Optima grade water and acetonitrile (Fisher, MS grade), plus
 0.1% formic acid) was run over 12 minutes at a flow rate of 250 µL
 min<sup>-1</sup> and the eluent was monitored for positive
 ions by a Thermo Scientific Q-Exactive HF operated in profile mode. Source
 parameters were 4kV spray voltage, capillary temperature of 275 °C and
 sheath gas setting of 20. Spectral data were acquired at a resolution
 setting of 60,000 FWHM with the lockmass feature, which typically results
 in a mass accuracy &lt; 2 ppm. Analytical standards of imidaclpoprid
 and dinetofuran (5 ppm in Milli-Q<sup>®</sup> ultrapure water)
 were dissolved in methanol and diluted into mobile phase for quantitation.
 Standard curves were run for every set of samples, from which we
 back-calculated sample residue concentrations. Extracted Ion Chromatograms
 (XICs) utilizing a 10 ppm mass window for each of the compounds were used
 for quantitation. <strong>Statistical
 analysis</strong> To determine how irrigation
 level and NN application impacted our model floral microbe community, we
 constructed linear mixed models in <em>lme4</em> with nectar
 volume, flower mass, CFU abundance (summed across the three media types),
 CFU density (per µL nectar), and CFU Shannon diversity per flower as
 dependent variables. As independent variables, we included irrigation
 rate, NN dose, their interaction, and NN type (nested within dose). To
 test if differences in microbial community composition (as Bray–Curtis
 dissimilarity) were related to treatments, we also performed a
 permutational multivariate analysis of variance (permANOVA) using function
 ‘adonis’ in the package <em>vegan</em> (Oksanen <em>et
 al.</em>, 2020). Multivariate homogeneity of dispersions within
 independent variable groups were checked with the PERMDISP2 procedure
 using function ‘betadisper’ in <em>vegan</em>. We visualized
 distance between samples with non-metric multidimensional scaling using
 function ‘metaMDS’ and confirmed ordination stress was sufficiently low in
 k=2 dimensions using function ‘dimcheckMDS’. All figures were created
 using package <em>ggplot2 </em>(Wickham, 2016).
description: # Nontarget impacts of neonicotinoids on nectar-inhabiting microbes
 \[[https://doi.org/10.5061/dryad.gf1vhhmw2](https://doi.org/10.5061/dryad.gf1vhhmw2)]([https://doi.org/10.5061/dryad.gf1vhhmw2](https://doi.org/10.5061/dryad.gf1vhhmw2)) This README file was generated on 2024-03-06 by Jacob M. Cecala. \# GENERAL INFORMATION 1\. Title of Dataset: Nontarget impacts of neonicotinoids on nectar-inhabiting microbes 2\. Author Information A. Principal Investigator Contact Information Name: Jacob M. Cecala Institution: University of California, Davis Address: Davis, CA, USA Email: [jmcecala@gmail.com](mailto:jmcecala@gmail.com) B. Associate or Co-investigator Contact Information Name: Rachel L. Vannette Institution: University of California, Davis Address: Davis, CA, USA Email: [rlvannette@ucdavis.edu](mailto:rlvannette@ucdavis.edu) 3\. Years of data collection: 2021-2022 4\. Geographic location of data collection: University of California, Davis, CA, USA 5\. Information about funding sources that supported the collection of the data: USDA NIFA Postdoctoral Fellowship # 2021-67034-35157 to J.M.C.; NSF DEB # 1846266 to R.L.V ## # SHARING/ACCESS INFORMATION 1\. Licenses/restrictions placed on the data: CC0 1.0 Universal (CC0 1.0) Public Domain 2\. Links to publications that cite or use the data: Cecala, J.M. and Vannette, R.L. (2024). Nontarget impacts of neonicotinoids on nectar-inhabiting microbes. Environmental Microbiology. 3\. Links to other publicly accessible locations of the data: None 4\. Links/relationships to ancillary data sets: None 5\. Was data derived from another source? No A. If yes, list source(s): NA 6\. Recommended citation for this dataset: Cecala, J.M. and Vannette, R.L. (2024). Data from: Nontarget impacts of neonicotinoids on nectar-inhabiting microbes. Dryad Digital Repository. [https://doi.org/10.5061/dryad.gf1vhhmw2](https://doi.org/10.5061/dryad.gf1vhhmw2) ## DATA & FILE OVERVIEW 1\. File # List: 1\) Book1_2021_11_23_Met_SYN.xlsx 2\) Book1_2021_12_13_Aci_SYN.xlsx 3\) Book1_2021_12_13_Aci_TS.xlsx 4\) Book1_2021_12_17_Neo_SYN.xlsx 5\) Book1_2021_12_17_Neo_TS.xlsx 6\) Book1_2021_12_20_Ros_SYN.xlsx 7\) Book1_2021_12_20_Ros_TS.xlsx 8\) Book1_2021_12_27_Pan_SYN.xlsx 9\) Book1_2021_12_27_Pan_TS.xlsx 10\) Book1_2022_01_03_Met_SYN.xlsx 11\) Book1_2022_01_03_Met_TS.xlsx 12\) Book1_2022_01_07_Aur_SYN.xlsx 13\) Book1_2022_01_07_Aur_TS.xlsx 14\) Book1_2022_01_14_Api_SYN.xlsx 15\) Book1_2022_01_14_Api_TS.xlsx 16\) Book1_2022_01_17_VALIDATION_SYN.xlsx 17\) Book1_2022_01_17_VALIDATION_TS.xlsx 18\) GH_canola_expt_2022.xlsx 19\) Jake_9240-69_PesticidePeakAreas.xlsx 2\. Relationship between files, if important: None 3\. Additional related data collected that was not included in the current data package: None 4\. Are there multiple versions of the dataset? No A. If yes, name of file(s) that was updated: NA i. Why was the file updated? NA ii. When was the file updated? NA ## GENERAL DESCRIPTION OF DATA AND FILE STRUCTURE Broadly, the data contained here belong to two main groups. The first group (Files #1-17; see File List above) correspond to the in vitro spectrophotometer plate reader experiments. The data contained therein are optical density (OD600) readings for 96-well plates in which the microbes were growing in the presence of different concentrations of neonicotinoids. Also contained in these files are treatment keys for the layout of these 96-well plates, which denote which wells corresponded to which experimental treatments for each trial run. The second group (Files #18 and #19) contain data related to the greenhouse canola experiment in which a community of four microbes were inoculated into flowers. These data encompass the nectar samples, which treatments and plants they belonged to, flower traits like nectar volume and floral mass, microbial growth (CFUs) from agar media on which the nectar samples were plated, and LC-MS results for neonicotinoid residue analyses in nectar samples. ### ABBREVIATIONS USED \* Aci = *Acinetobacter* \* Met = *Metschnikowia* \* Neo = *Neokomagataea* \* Ros = *Rosenbergiella* \* Pan = *Pantoea* \* Aur = *Aureobasidium* \* Api = *Apilactobacillus* \* SYN and TS: these terms refer to the individual plate reader which was used to collect the data in that file. \* GH = greenhouse (canola experiment) \* expt = experiment \######################################################################### \# DATA-SPECIFIC INFORMATION FOR FILE #1: Book1_2021_11_23_Met_SYN.xlsx Sheets and variables: Sheet 1: Plate 1 - Sheet1 ``` * Software Version: self-explanatory \* Experiment File Path: self-explanatory \* Protocol File Path: self-explanatory \* Plate Number: self-explanatory \* Date: date experiment was conducted \* Time: time of day protocol was initiated \* Reader Type: the reader the experiment was run on (SYN or TS) \* Reader Serial Number: self-explanatory \* Reading Type: self-explanatory ``` Procedure Details ``` \* Plate Type: self-explanatory \* Eject plate on completion: self-explanatory \* Set Temperature: the temperature at which the experiment was set to run at (°C) ``` Start Kinetic ``` \* Shake: the duration (MM:SS) and intensity (cpm) at which plates were shaken \* Read: details of how the plate was read, including the frequency (nm) ``` End Kinetic Layout: schematic of the columns of the 96 well plate with row and column designations ``` Note the following abbreviations/conventions: SPL_\_ = sample #_\_ well; highlighted in a darker blue color BLK = blank (media only) well; highlighted in a lighter blue color ``` 600 (cells of column headers shaded blue for visual clarity only) Time: time (HH:MM:SS) since the protocol was initiated T° 600: temperature (°C) at that timepoint Columns (A1-H12): absorbance values (OD) for a given well at a given timepoint Blank 600: same as above, but showing blank-corrected absorbance values (OD) \* Note: Sheet 1 in this particular file represents a trial data collection run and was not included in the manuscript. Sheet 2: treatments \* sample: well identifier \* inoculation: whether a well was inoculated with microbes or served as a sterile control \* neonic.type: which of the 6 neonicotinoid compounds the well contained \* neonic.conc: the concentration in ppb of the neonicotinoid in the well Sheet 3: validation_trts \* sample: well identifier \* inoculation: as above \* microbe: the species of microbe inoculated into the well \* broth.conc: the concentration of the broth relative to its undiluted (100%) state \################################################################# \# DATA-SPECIFIC INFORMATION FOR FILES #2-17 Data conventions these files follow those outlined for Sheet 1 in File #1: Book1_2021_11_23_Met_SYN.xlsx Each file refers to a separate experimental run for each microbe and reader. FILE NAME MICROBE READER 2\) Book1_2021_12_13_Aci_SYN.xlsx Acinetobacter SYN 3\) Book1_2021_12_13_Aci_TS.xlsx Acinetobacter TS 4\) Book1_2021_12_17_Neo_SYN.xlsx Neokomagataea SYN 5\) Book1_2021_12_17_Neo_TS.xlsx Neokomagataea TS 6\) Book1_2021_12_20_Ros_SYN.xlsx Rosenbergiella SYN 7\) Book1_2021_12_20_Ros_TS.xlsx Rosenbergiella TS 8\) Book1_2021_12_27_Pan_SYN.xlsx Pantoea SYN 9\) Book1_2021_12_27_Pan_TS.xlsx Pantoea TS 10\) Book1_2022_01_03_Met_SYN.xlsx Metschnikowia SYN 11\) Book1_2022_01_03_Met_TS.xlsx Metschnikowia TS 12\) Book1_2022_01_07_Aur_SYN.xlsx Aureobasidium SYN 13\) Book1_2022_01_07_Aur_TS.xlsx Aureobasidium TS 14\) Book1_2022_01_14_Api_SYN.xlsx Apilactobacillus SYN 15\) Book1_2022_01_14_Api_TS.xlsx Apilactobacillus TS 16\) Book1_2022_01_17_VALIDATION_SYN.xlsx validation run SYN 17\) Book1_2022_01_17_VALIDATION_TS.xlsx valudation run TS \# DATA-SPECIFIC INFORMATION FOR FILES #18: GH_canola_expt_2022.xlsx Sheet 1: trt_data *block: experimental block (I-V) to which pot belonged *pot.number: identifier number for pot (1-60) *irrigation.rate: whether the pot received a low or high rate of irrigation *neonic.type: whether the pot was treated with imidacloprid (IMI), dinotefuran (DIN), or no neonicotinoid (control) *neonic.dose: how much neonicotinoid was applied to the pot: none, low, high *date.planted: date that seeds in that pot were planted Sheet 2: nectar_data *date.inoculated: date that flower was inoculated. *inoc.date.hi.temp: high temperature of the day flower was inoculated (°F) *date.harvested: date that flower was removed from the plant (day after inoculation) *pot.number: identifier number for pot (1-60) *action: whether nectar sample was plated or frozen *plated: was nectar sample plated? (y=yes) *full.sample.id: unique identifier for nectar sample *thrips: if thrips were present in the flower at time of harvesting *pollen: if pollen was present in nectar at time of harvesting *mm.nectar: length of nectar column in microcapillary tube upon extraction (mm) *microcap.vol: volume of microcapillary tube used to extract nectar (µL) *nectar.vol: calculated volume of nectar extracted from flower (µL) *flower.mass.mg: mass of flower after nectar extraction (mg) *non.inoc.control: whether or not flower served as a non-inoculated control (yes or blank=no) *notes: miscellaneous notes about flower Sheet 3: plate_data *date.plated: date that nectar was plated onto agar media *pot.number: identifier number for pot (1-60) *full.sample.id: unique identifier for nectar sample *media.type: type of agar media nectar sample was plated on: yeast media (YM), tryptic soy (TS), or de Man, Rogosa and Sharpe (MRS) *B01 through F10: colony forming unit (CFU) counts for different morphotypes on agar *total.cfus: sum of all CFUs on that media type *total.mtypes: total number of distinct morphotypes on that media type Sheet 4: nectar_samples *order.box: order of sample in freezer storage box (1-31) *SAMPLE.ID: sample identifier (1-27) *date: date that nectar sample was collected *pot.number: identifier number for pot (1-60) *block: see Sheet 1 *irrigation.rate: see Sheet 1 *neonic.type: see Sheet 1 *neonic.dose: see Sheet 1 *time.picked: time of day that flower was removed from plant *n.flowers: number of individuals flowers pooled to make sample *deg.bx: dissolved solids concentration of nectar sample (°Bx) *approx.vol.uL: approximate volume of nectar sample (µL) *thrips.present: if thrips were present in nectar sample (N=no, Y=yes) *notes: miscellaneous notes about nectar sample \# DATA-SPECIFIC INFORMATION FOR FILES #19: Jake_9240-69_PesticidePeakAreas.xlsx Sheet 1 *Sample ID: unique sample identifier (1-27) *Imidacloprid: concentration of imidacloprid in diluted nectar sample (as peak area) *Dinetofuran: concentration of dinotefuran in diluted nectar sample (as peak area) "Calculated concentrations"" are in units of ppb. Sheet 2: conversions *Sample ID: unique sample identifier (1-27) *Imidacloprid: concentration of imidacloprid in diluted nectar sample (as peak area) *Dinetofuran: concentration of dinotefuran in diluted nectar sample (as peak area) *ppb: concentration of active ingredient (ppb) in diluted nectar sample *neonic.type: whether plant was treated with imidacloprid (IMI) or dinotefuran (DIN) *neonic.dose: whether sample was water or came from a plant treated with different levels of pesticide (none, low, or high) *dilution.factor: how many times nectar sample was diluted in water before LC-MS analyses *undiluted.conc: calculated active ingredient concentration in undiluted nectar sample (ppb) ## Sharing/Access information The data contained here are original and not derived from any other source. They are only accessible here. ## Code/Software The two R scripts were created in R version 4.1.1 using RStudio version 2021.09.0. Operating system was Mac OS version 10.15.5. R Packages used in running the scripts (also listed in the scripts themselves) include the following: growthcurver, readxl, dplyr, ggplot2, car, lme4, AICcmodavg, MuMIn, emmeans, magrittr, multcomp, scales, plyr, visreg, tidyr, ggpubr, summarytools, fitdistrplus, vegan, arm, glmmTMB, ggfortify, goeveg, corrplot, Hmisc. The R script "neonic_microbe_plates_2021_EXPT.R" analyzes data in the Excel files starting with "Book1" (17 total files). The remaining 2 Excel files are analyzed using the R script "GH canola expt 2022.R".