DOI: 10.5061/dryad.5qfttdzjq
title: Assessing the use of 3D printed traps to evaluate Hemlock Woolly Adelgid (Hemiptera: Adelgidae) infestation levels

description: Hemlock woolly adelgid (HWA), Adelges tsugae (Annaand), is an invasive
 insect that has devastated millions of eastern hemlocks, Tsuga canadensis
 (L.) Carrière, in eastern North America since the 1950s. In Michigan, HWA
 was first detected in 2015 and has spread to several counties in west
 Michigan. Conservation practitioners are managing HWA through a statewide,
 landscape-level pesticide management plan. The traditional method of using
 randomized branch sampling to estimate infestation levels is
 time-consuming but allows managers to monitor how HWA responds to
 treatments. Our main objective was to determine if molecular techniques
 could replace traditional methods for estimating infestation levels. We
 selected six treated sites and three untreated sites in west Michigan.
 During the fall and winter of 2022, we estimated the densities of the
 sistens generation using a randomized branch sampling method, and during
 the summer of 2023, we deployed five traps at each site to capture adelgid
 crawlers and performed qPCR analysis to quantify HWA DNA. To determine if
 qPCR is an appropriate method to assess HWA infestation level, we used
 linear regressions to determine whether relationships existed between (1)
 crawler counts and qPCR values, (2) sistens counts and qPCR values, and
 (3) sistens counts and crawler counts. We found that qPCR analyses and
 adelgid crawler counts have comparable, strong correlations with
 traditional estimation methods, particularly during the peak crawler
 period. Managers can use either qPCR or crawler counts from the peak
 crawler period to understand how HWA infestations respond to treatment or
 to prioritize treatment in high-risk areas.
description: <em>Site selection</em> We
 selected six treated sites with varying levels of HWA infestation and
 three infested, untreated sites. The infested, untreated sites are Meinert
 County Park (MNPK), Duck Creek Natural Area (FRPK), and Pioneer County
 Park (PIPK). Our treated sites included several private properties: BRHA,
 SPLT, HMDV, and BBAP. Two of the treated sites are public parcels owned by
 Golden Township (GDNR) and the Muskegon Conservation District (MKGR)
 (Table 1; Figure 1). Only abbreviations for private properties are given
 for anonymity. At the treated sites, crews from local organizations
 treated all hemlocks with imidacloprid products with a trunk injection or
 basal bark application, depending on the tree size and proximity to
 water. <em>Sistens Generation
 Counts</em> We used a modified version of the
 RBS methodology outlined by Evans and Gregoire (2007) to quantify the HWA
 infestation levels. During fall and winter of 2022 and into early 2023, we
 randomly selected 10 trees at each of the nine sites to sample, for a
 total of 90 hemlocks sampled. Because these sites were assessed for HWA by
 local and state groups, all hemlocks within stands were previously tagged
 with unique identifying numbers. At each tree, we randomly selected nine
 branches maximum within reaching distance. We collected new growth twigs
 from each of the selected branches and stored the twigs at 4℃ in Ziploc
 bags. We used a Nikon SMZ645 dissecting microscope to count the
 individuals from the sistens generation present near the base of 100 new
 growth needles on the front and back of each twig. Counting individuals
 from the sistens generation is an appropriate measure for HWA because it
 is this generation that settles on new growth, which allows us to compare
 infestation levels between sites and years (Evans and Gregoire 2007). To
 obtain the average number of sistentes for each site, we first averaged
 the sistens counts from all sampled branches per tree, and then we
 averaged the number of sistentes counted across the 10 trees per
 site. During the fall and winter of 2023, we again
 sampled the same trees across six of the original sites (GDNR, BBAP, FRPK,
 PIPK, MKGR, and MNPK) and used the protocol described above to collect the
 average number of sistentes for each site. However, the number of total
 trees sampled in 2023 was lower than in 2022 because some trees no longer
 produced new growth due to a decline in hemlock health. In total, 50 trees
 were assessed across the six sites in 2023, ranging from 6-10 trees per
 site.   <em>Trap
 Deployment</em> Our lab developed 3-D printed
 traps that each hold four microscope slides (Figure 2) for HWA monitoring.
 The traps were initially designed based on a fungal spore trap developed
 by Quesada et al. (2018), and we modified them to increase the capture
 probability of HWA crawlers and associated HWA material (ovisacs) in
 infested areas (Sanders et al. 2023) while limiting the by-catch of larger
 arthropods. We dipped one side of each slide in sterilized petroleum jelly
 and placed the slides in the traps with the petroleum jelly face-up. We
 mounted the traps on a 1.5 m wooden pole and attached a tag with trap
 identification and project information. For each of the
 nine sites, we used ArcGIS to map 1-acre grids on the properties and
 randomly selected a point in five different grids to deploy traps within
 each site (ESRI 2023). The traps were placed within the hemlock stand
 closest to the randomly selected point. This resulted in a total of 45
 traps across the nine sites (five traps per site). On April 24th, 2023, we
 deployed the traps and exchanged slides every two weeks until August 1st,
 2023, totaling seven collection periods. This allows us to sample across
 most of the adelgid crawler period. For each two-week collection period,
 we collected one field blank per site to ensure we did not contaminate the
 samples during sample collection. We stored samples at 4℃ in 50 mL tubes
 until slide processing. In spring 2024, we deployed the
 traps in six of the nine original sites (GDNR, BBAP, FRPK, PIPK, MKGR, and
 MNPK). We deployed five traps within each site, and each trap was placed
 in the same location as those deployed in 2023. Traps were deployed on
 April 23, 2024, and slides were exchanged every two weeks until July 3,
 2024, totaling five collection periods. These traps were only assessed for
 crawler counts and not for qPCR. <em>Crawler
 Counts</em> We inspected each slide under a
 Nikon SMZ645 dissecting microscope to count the number of HWA crawlers on
 the slides and noted any evidence of other adelgid material (i.e., ovisac
 material). Since each trap had four slides, we summed these counts to give
 the total number of crawlers per trap. To limit DNA contamination, we
 counted the crawlers in a separate lab than the DNA extraction lab. The
 microscope and lab bench were cleaned between each trap with either 10%
 bleach or DNA Away. <em>DNA
 Extraction</em> Immediately after counting the
 crawlers from the 2023 slides, we removed the petroleum jelly from each of
 the four slides on a trap using a stainless-steel micro spatula and placed
 it in a single Zymo bead bashing tube containing 0.1 mm and 2.0 mm beads
 (Zymo Research, CA, USA), resulting in 315 samples, which represented one
 tube per trap per collection period. In between processing traps, we
 cleaned the micro spatula using flame sterilization and DNA Away.  For the
 remainder of the benchwork, we moved to a different lab to reduce the risk
 of DNA contamination. We used Quick-DNA Tissue/Insect
 Microprep Kits (Zymo Research, CA, USA) and modified the manufacturer’s
 protocols to separate the DNA from the petroleum jelly. We placed the
 tubes in a heat block at 65℃ for 15 minutes to liquefy the petroleum
 jelly. Then, we homogenized the samples in a Qiagen TissueLyser LT
 (Hilden, Germany) at 50 rps for 2 minutes. We repeated the heating/bashing
 cycle until the tubes were homogenized for at least 10 minutes. After the
 final heat cycle, we separated the petroleum jelly from the homogenized
 samples by centrifuging the tubes at 11,000 rpm for 1 minute. This allowed
 for any aqueous material to collect at the bottom of the tube, and the
 petroleum jelly to collect at the top of the tube. We used a sterilized
 toothpick to poke a hole through the upper layer of the petroleum jelly
 and pipetted out the remaining aqueous solution into a Zymo-Spin III F
 filter column inside a collection tube. We followed the manufacturer’s
 protocols for the remainder of the procedure, except that we eluted the
 DNA in a final volume of 20 mL. For each set of samples, we processed a
 petroleum jelly blank and an extraction blank using the same method to
 ensure the petroleum jelly and reagents were not contaminated. We stored
 the samples at -20℃ until qPCR analysis.
 <em>qPCR Protocol</em> We
 created a seven-point standard curve using a gBlock standard for HWA
 designed by Kirtane et al. (2022) (Integrated DNA Technologies, IA, USA).
 The standard curve consisted of a 1:10 serial dilution with concentrations
 ranging from 2x10⁶ gene copies (gc)/µL – 2.0 gc/µL. We
 ran the standard curve, all samples, and no template controls in
 triplicate. The qPCR reactions consisted of 1X TaqMan Environmental Master
 Mix, 0.6 µM final concentration of the forward and reverse primer, 0.3 µM
 final concentration for the probe (Fam labeled with a Zen/Iowa
 Black<sup>TM</sup> FQ double quencher; Integrated DNA
 Technologies, IA, USA), 2.0 mg/mL final concentration of bovine serum
 albumin (BSA), and 2.0 µL of DNA for a total volume of 20 µL. Kirtane et
 al. (2022) developed the primers and probes, which target a region of the
 cytochrome oxidase 1 (COX1) gene. These were previously tested against
 multiple adelgid species and determined to be HWA-specific (Sanders 2021,
 Kirtane et al. 2022). We ran the samples on a Step One Plus Real-Time PCR
 System (Applied Biosystems, MA, USA). The thermal cycle profile included a
 pre-holding stage at 60ºC for 30 seconds, followed by a holding stage of
 50ºC for 2 minutes and then 95ºC for 10 minutes. The cycling stage
 consisted of 95ºC for 15 seconds, followed by 60ºC for 1 minute for 40
 cycles. All standard curves needed an efficiency between 90% – 110% and an
 R<sup>2 </sup>&gt; 0.98 to pass quality control and be
 included in the analyses, which are the standard thresholds used in other
 studies (Rogers-Broadway and Karteris 2015). We processed 315 samples (45
 traps across 7 sampling periods) but removed four samples before analysis
 due to technical errors during laboratory processing.
 <em>LOD and LOQ Determination for
 qPCR</em> We compiled data from 35 of our HWA
 qPCR standard curves to determine the LOD and LOQ of our HWA assay. In
 addition, we included several samples with HWA concentrations of 1.0
 gc/µL, 5.0 gc/µL, 10.0 gc/µL, and 15.0 gc/µL to help determine our LOD. We
 defined the LOD as the lowest number of gc/reaction that produced a
 positive reaction in at least 95% of the samples (Klymus et al. 2019). We
 defined the LOQ as the lowest gc/reaction that could be quantified with a
 coefficient of variation (CV) of less than 35%. We estimated the LOD and
 LOQ in R (version 4.4.0; R Core Team 2024) using code developed by Merkes
 et al. (2019, Klymus et al. 2019). To quantify gc/reaction, we obtained
 the number of gc/µL produced from the standard curve and multiplied this
 by the 2.0 µL of DNA that we added to the reaction. For example, our
 lowest standard curve template was 2.0 gc/µL, so the number of gc/reaction
 would be 4.0 gc. <em>Relationship between 2023
 Adelgid Crawler Counts and qPCR Values Across Sites</em>
 To identify whether there was a correlation between the number of
 adelgid crawlers captured on the trap slides and the qPCR values
 associated with those traps, we first ran a linear regression between the
 number of adelgid crawlers captured per trap and the qPCR value of that
 trap for each of the seven collection periods across all nine infested
 sites. We then ran individual linear regressions for each site to examine
 how this relationship varied across sites. Before the regression analysis,
 all data were transformed using log(value + 1) due to the large variance
 between individual counts and gc/reaction values across samples. We
 performed all analyses using R (version 4.4.0; R Core Team
 2024). <em>Relationship between 2022 Sistens
 Generation Counts and Trap Values During the 2023 Crawler
 Peak</em> Our initial goal was to evaluate the
 general relationship between sistens generation counts and the trap data.
 To do this, we focused on our 2022 sistens counts to see how they compared
 to our 2023 trap data. We used the average sistens counts for each site
 and only used the average adelgid crawler counts and the average qPCR
 values per site generated during the peak crawler period. This is the
 period when we would expect to see the strongest relationship between HWA
 qPCR values and sistens generation counts since this is when the majority
 of the adelgid crawlers (i.e., the generation produced by the sistens
 generation) are mobile and will be moving to new locations to settle. The
 peak crawler period for 2023 was the June 7<sup>th</sup>, 2023
 collection period, which was the deployment period from May
 24<sup>th</sup>, 2023 – June 7<sup>th</sup>,
 2023. We analyzed the relationship between average
 sistens generation counts, average adelgid crawler counts from the traps,
 and their corresponding qPCR values using a correlation analysis. Firstly,
 we performed a Spearman correlation analysis between average sistens
 generation counts and the average adelgid crawler counts per site.
 Secondly, we performed a Pearson correlation analysis between average
 sistens generation counts and the average qPCR values per site. Before the
 correlation analysis, some data were transformed using log(value + 1) due
 to the large variance between individual counts and gc/reaction values
 across samples and assessed for normality. We performed all analyses using
 R (version 4.4.0; R Core Team 2024).
 <em>Assessment of 2024 Peak Crawler Data to Predict 2023
 Sistens Generation Counts</em> Because crawler
 counts had the strongest correlation to sistens generation counts (see
 results below), we evaluated whether we could use average crawler counts
 to predict average sistens counts within a site. To do this, we assessed
 how well data collected the following year (2023 sistens counts and 2024
 crawler counts) fit within a generalized linear model developed from the
 2022 sistens and 2023 crawler count data. Average crawler counts during
 the peak crawler period in 2024 were assessed as described above, except
 the peak crawler period was earlier and ranged from May 8, 2024 – May 29,
 2024, due to a warmer winter. Before our analysis, we removed data from
 one of the traps (FRPK Trap 1). Crawler data from this trap appeared to be
 influenced by one highly infested tree, with crawler counts averaging over
 23,000 crawlers for the peak crawler period. This was significantly higher
 than the other traps in the site and it was considered an
 outlier. We used a Spearman correlation to assess the
 relationship between the 2023 sistens generation counts and 2024 crawler
 counts to compare to the previous year’s data. We then ran a generalized
 linear model (glm) based on the previous year’s data and used the
 glm.predict function to see how well the 2024 crawler counts predicted the
 2023 sistens generation counts. We performed all analyses using R (version
 4.4.0; R Core Team 2024).
description: # Dryad dataset Dataset DOI:
 [10.5061/dryad.5qfttdzjq](10.5061/dryad.5qfttdzjq) ## Description of the
 data and file structure There are four data files associated with the
 manuscript. These files consist of (1) results from qPCR analysis that
 were used to determine the lower limit of detection and limit of
 quantification for our qPCR analysis, (2) HWA crawler counts collected
 from traps that were deployed in nine different infested sites sites
 across seven collection periods, and their corresponding qPCR values, (3)
 HWA infestation data that consists of sistents counts, crawler counts, and
 qPCR values averaged across each of the nine sites, (4) HWA infestation
 data that consists of sistents counts and crawler counts averaged across
 six sites.  ### Files and variables #### File:
 Compiled_LOD_LLoQ_062124_clean_gene-rxn.csv **Description:**  Results from
 qPCR analysis that were used to determine the lower limit of detection and
 limit of quantification for our qPCR analysis ##### Variables * Well: The
 location of the sample in the 96-well plate * Flour: The fluorescent tag
 attached to the probe * Sample: The DNA concentration of each standard.
 NTC indicates non-template controls * Quencher: The type of quencher
 molecule used for the assay * Cq: The cycle threshold determined for each
 sample. Undetermined values indicate that no amplification occurred in the
 sample.  * SQ: The known DNA concentration of each sample in gene copies
 per reaction. NA values indicate that there is no DNA in the sample and
 these samples are non-template controls.  * Target: The species target, in
 this case it will be hemlock woolly adelgid (HWA) #### File:
 peak_crawler_period_and_averaged_sisten_counts_2022-2024.csv
 \**Description: **HWA infestation data that consists of sistents counts
 and crawler counts averaged across six sites for two separate years #####
 Variables * Population: The population that was sampled * Crawler_Avg: The
 average number of crawlers detected per sites during the peak crawler
 period * Sisten_Avg: The average number of sistens that were counted
 across 10 hemlock trees in each site * Year: The year the sistens counts
 were conducted  #### File:
 peak_crawler_period_qPCR_AND_averaged_sisten_counts_gc_per_reaction.csv
 **Description:** HWA infestation data that consists of sistents counts,
 crawler counts, and qPCR values averaged across each of the nine sites
 ##### Variables * Population: The population that was sampled * CT_Avg:
 The cycle threshold averaged across the five trap samples collected during
 the peak crawler period. * Q_Avg: The number of gene copies per reaction
 averaged across the five trap samples collected during the peak crawler
 period. * Crawler_Avg: The average number of crawlers detected per sites
 during the peak crawler period * Sisten_Avg: The average number of sistens
 that were counted across 10 hemlock trees in each site #### File:
 qPCR.counts.allsite.06252024.gc_per_reaction.csv **Description:**  HWA
 crawler counts collected from traps that were deployed in nine different
 infested sites sites across seven collection periods, and their
 corresponding qPCR values ##### Variables * Trap: The unique trap ID for
 all 45 deployed traps.  * Population: The population that was sampled *
 CT_Mean: The cycle threshold for each trap sample based on on qPCR
 analysis * Q_Mean: The number of gene copies per reaction detected for
 each trap sample * Crawler_Count: The total number of crawlers counted on
 each trap ## Code/software All files are in csv format and no special
 software is needed to view the files.  ## Access information Other
 publicly accessible locations of the data: * NA Data was derived from the
 following sources: * NA