DOI: 10.5061/dryad.c59zw3r9r
title: Data from: Home is where the hollow is: Revealing vertebrate tree hollow user biodiversity with eDNA metabarcoding

description: Tree hollows are essential for many vertebrate species, providing both
 nesting sites and shelter. Globally, old hollow-bearing trees are in
 decline resulting in many dependent species being under threat. It is
 therefore imperative that vital hollow-bearing trees are preserved, but it
 is logistically difficult to rapidly determine which hollows are being
 used and by which taxa. Here, we investigate the efficacy of eDNA
 metabarcoding as a survey tool for vertebrate hollow users. We compared
 the identity and richness of hollow-inhabiting vertebrate taxa using eDNA
 metabarcoding of both sediment from the tree hollows, and material
 collected using roller swabs. Samples (n = 138) were collected from
 hollow-bearing tuart trees (Eucalyptus gomphocephala; N = 28), within both
 an urban remnant and a relatively undisturbed forested area of South-West
 Western Australia. We detected a wide range of vertebrate taxa, including
 cryptic species such as the brush-tailed phascogale (Phascogale
 tapoatafa), while also providing ecologically informative data, such as
 hollow use by invasive Rainbow Lorikeet (Trichoglossus moluccanus) within
 the study areas. Our results showed variation in the species detected
 between methods, with the roller swab method detecting a greater number of
 species and a higher mean species richness per sample than hollow sediment
 did. The species detected from both methods did not perfectly overlap,
 highlighting the value of using multiple methods or substrates to detect a
 greater number of taxa. Our results suggest eDNA metabarcoding from tree
 hollow samples offers a sensitive and resource-efficient method of
 monitoring vertebrate hollow users, if enough hollows are sampled. This
 provides not only a broad biodiversity assessment tool but also an
 effective method for detecting taxa that may be elusive using other
 methods.
description: Study sites and Sample collection Samples
 were collected between September 2020 and January 2021 from a total of 28
 tuart trees, including 14 trees from two sites in the Tuart Forest
 National Park, Ludlow (hollows = 37, total samples = 58, roller = 37,
 sediment = 21), and 14 trees from two urban remnants within the City of
 Perth, Kings Park and Bold Park (hollows = 56, total samples = 80, roller
 = 56, sediment = 24; Figure 1). At each site, seven
 hollow-bearing trees were chosen due to their accessibility and likelihood
 of containing at least one potential hollow based on visual surveys,
 resulting in a total of 93 hollows sampled. Within the urban remnants of
 Kings Park (September/November 2020) and Bold Park (December 2020), an
 elevated work platform was used to access tree hollows. Single rope access
 techniques were used to access trees in the Tuart Forest National Park
 (January 2021). For all hollows (n = 93), a roller swab sample, adapted
 from Valentin et al. (2020), was taken using a 40 mm polyester roller
 dampened with distilled water and stored in a zip lock bag. Prior to
 sampling, each hollow was inspected and if an animal was present, only the
 opening and immediate inside walls were swabbed. For all other hollows,
 the opening, inside walls, and across the hollow floor were all sampled.
 Where hollow sediment was present and accessible (n = 45), a 50 ml sterile
 container was used to collect surface sediment randomly from multiple
 locations across each hollow floor, creating one bulk sediment sample per
 hollow. Care was taken not to sample sediment disturbed by the roller
 sampling. Samples were then stored on ice, frozen within 48hrs of
 sampling, and stored at -18 °C prior to extraction. Visual vertebrate
 activity was also recorded (e.g., animal present, feathers, fur, eggs).
 Finally, the location, height to hollow opening, hollow opening diameter,
 depth of hollow, and tree width at breast height were recorded.
 To prevent contamination of samples, sterile gloves were worn
 during sampling and single-use disposable, pre-sterilized collection
 containers were used. Single-use polyester rollers were decontaminated
 prior to use by submerging in a 10 % bleach solution (made using White
 King Premium Bleach, ~ 5 % sodium hypochlorite) for a minimum of 10
 minutes before being thoroughly rinsed with purified distilled water and
 UV-sterilized for a further 10 minutes. All multi-use field sampling
 equipment such as roller frames were decontaminated onsite prior to use by
 submerging in 100 % bleach (White King Premium Bleach, ~ 5 % sodium
 hypochlorite) for a minimum of 10 minutes before being thoroughly rinsed
 with distilled water. Multi-use equipment was also swabbed prior to use
 before being preserved and processed in the same way as field samples as a
 negative control allowing for the detection of possible contamination of
 samples. Sample processing and DNA
 extraction Sample processing and extraction were
 undertaken in dedicated laboratories at the Trace & Environmental
 DNA (TrEnD) Laboratory, Curtin University, Perth, Western Australia. Each
 individual roller swab was placed in a plastic container decontaminated
 with 10 % bleach solution as outlined above, covered with purified
 distilled water (~ 500 mL) for 10 minutes and manually agitated twice for
 30 seconds at 5-minute intervals. Water samples were then individually
 filtered across Pall 0.45μm GN-6 Metricel® mixed cellulose ester membranes
 using a peristaltic Pall Sentino® Microbiology pump (Pall Corporation,
 Port Washington, USA) and frozen at -18°C prior to extraction. DNA was
 extracted from half of the filter membrane using a DNeasy Blood and Tissue
 Kit (Qiagen, Hilden, Germany), with the following modifications to the
 standard protocol: 60 μl of Proteinase K, 540 μl of ATL lysis buffer and a
 17-hour digestion at 56°C. Sediment samples were manually shaken for 30
 seconds to homogenise and DNA was extracted from 0.25 g of sample using a
 DNeasy PowerLyzer PowerSoil Kit (Qiagen, Hilden, Germany) following the
 manufacturer’s instructions. Blank extraction controls (n = 6) containing
 reagents only were processed concurrently with samples to detect any
 cross-contamination and eDNA extracts were then stored at -18°C.
 Assessment of DNA extracts <em>In
 silico</em> studies were conducted using DNA sequences from the 12S
 and 16S rRNA marker regions (Othman et al., 2021) to identify the assay
 able to amplify the widest range of vertebrate taxa in the study region.
 The primer set 12S-V5 F2/R2 (Riaz et al., 2011), previously used to
 successfully amplify vertebrate taxa within the study region (Ryan,
 Bateman, van der Heyde, Fernandes, & Nevill, 2020; Van Der Heyde
 et al., 2021; Van Der Heyde et al., 2020), was broad enough to amplify
 avian, mammalian and reptilian DNA, and short enough to pick up degraded
 DNA. As such, we amplified DNA with the general vertebrate primer 12S-V5
 (Riaz et al., 2011), designed to amplify a 98bp fragment which includes
 the V5 variable region of the 12S rRNA gene with the primers F2
 (5’-TAGAACAGGCTCCTCTAG-3’) and R2 (5’-TTAGATACCCCACTATGC-3’).
 Quantitative PCR (qPCR) was used to assess the quality and
 quantity of DNA in the extracts, as well as potential inhibition to
 determine the optimal dilution level of DNA input (Murray, Coghlan,
 & Bunce, 2015). All qPCR reactions were prepared in dedicated
 clean rooms at the TrEnD Laboratories and performed on a StepOnePlusTM
 Real-Time PCR system (Applied Biosystems, Massachusetts, USA). Reaction
 volumes totalled 25μl containing 1× PCR Gold buffer (Applied Biosystems),
 2.5 mM MgCl2 (Applied Biosystems), 0.4 mg/ml BSA (Fisher Biotec,
 Australia), 0.25 mM of each dNTPs (Astral Scientific Australia), 0.4 μM
 forward and reverse primer, 1 U AmpliTaq Gold (Applied Biosystems), 0.6 µL
 SYBR Green (Life Technologies, USA) and 2 μL of template eDNA (3 PCR
 reactions per extract at Neat, 1:10, and 1:100 dilutions). The cycling
 conditions were initial denaturation for 5 minutes at 95 °C, followed by
 50 cycles of 30 seconds at 95 °C, then 30 seconds at the annealing
 temperature of 60 °C, and 45 seconds at 72 °C, ending with 10 minutes of
 elongation at 72 °C. For each qPCR run, a non-template control (reagents
 only) and positive control (<em>Gallus</em>
 <em>gallus</em>, 100ng) were used to detect contamination and
 to ensure primers attached to DNA strands. DNA
 amplification Samples containing a sufficient quantity
 of amplifiable DNA (n = 76; Table S1) were assigned a unique 6-8 bp
 multiplex identifier tag (MID tag), 12S-V5 specific primers and Illumina
 sequencing adaptors. The unique combinations of MID tag (fusion) primers
 were then used in qPCR which was prepared in a physically separate
 ultra-clean laboratory with 4 μL of template eDNA for reaction volumes
 totalling 27μl, which contained the same reagents, controls and cycling
 conditions described above. A single-step fusion protocol was used with no
 reuse of index combinations. MID-tag amplicons were generated in duplicate
 to reduce the effects of PCR stochasticity (Murray et al., 2015) and
 combined before being pooled with other MID-tag amplicons (i.e. minipool)
 according to qPCR ΔRn values. Minipool concentrations (ng/µl) were
 quantified using a QiAxcel Advanced System (Qiagen, Hilden, Germany)
 before being combined in approximate equimolar ratios based on this
 quantification to create a DNA sequencing library which also contained one
 unrelated project. Amplicons in this library were size selected to 150 –
 300 bp using a PippinPrep 2 % ethidium bromide cassette (Sage Science,
 Beverly, USA), purified using a QIAquick PCR Purification Kit (Qiagen,
 Hilden, Germany), and re-quantified using a Qubit Fluorometer (Invitrogen,
 Carlsbad, USA). Sequencing was then undertaken on an Illumina MiSeq
 platform (Illumina, San Diego, USA) using a single lane flow cell as per
 Illumina protocols for single-end sequencing (MiSeq® v2 Reagent Kit 300
 Cycles PE), with a final library molarity of 6pM containing 7 %
 PhiX. Sequence analysis (filtering and taxonomic
 assignment) Conservative filtering steps were employed
 whilst also attempting to retain as much of the “true” eDNA diversity as
 possible. All sequence filtering, ZOTU formation and taxonomic assignment
 were conducted utilizing the eDNAFlow bioinformatics pipeline
 (Mousavi‐Derazmahalleh et al., 2021) via Zeus, an SGI cluster, based at
 the Pawsey Supercomputing Centre in Kensington, Western Australia.
 Sequence reads were quality checked using FASTQC (Andrews, 2010), and
 quality filtered (Phred quality score &lt;20), including trimming
 sequences with Ns as implemented in eDNAFlow source code by --trimns
 & --trimqualities employing AdapterRemoval v2 (Schubert,
 Lindgreen, & Orlando, 2016). Demultiplexing with obitools
 (ngsfilter; Boyer et al., 2016) and sequences under 60 bp removed
 (obigrep). Dereplication and the creation of zero-radius operational
 taxonomic units (ZOTUs; min sequence abundance = 4) and ZOTU tables were
 then undertaken using the USEARCH unoise3 algorithm (Edgar, 2016). The
 ZOTUs were queried using BLASTN (Altschul, Gish, Miller, Myers, &
 Lipman, 1990) against NCBI’s GenBank nucleotide database using the
 following parameters: % identity ≥ 95, evalue ≤ 1e−3, % query cover 97,
 max target sequences = 10. Erroneous ZOTUs derived by high-throughput
 sequencing were identified and removed using the post-clustering curation
 method LULU with the minimum threshold of sequence similarity at 95 %
 (Frøslev et al., 2017). Finally, curated ZOTUs were taxonomically assigned
 by the lowest common ancestor (LCA) approach using eDNAFlow custom python
 script (Mousavi‐Derazmahalleh et al., 2021), with taxonomic assignment
 collapsed to the LCA if the percent identity of two hits with 97 % query
 cover and 95 % identity, differed by less than 1 % (Table S2).
 Further sample filtering was performed in R v.4.0.2 (R Core Team,
 2018) using the “phyloseq” package (McMurdie & Holmes, 2013). To
 mitigate against cross-contamination and false positives, analysis of
 contamination present in negative controls, and rarefaction curve (Figure
 S1), resulted in taxa with sequence counts fewer than 3 and samples with
 low sequencing depth (&lt;50 reads), being removed. Following this,
 sequences present in negative/extraction controls, taxa not known to
 inhabit or interact with hollows or be the prey of those that may, common
 PCR contaminants (e.g., human, and ungulate sequences) and taxonomic
 assignments higher than family level were removed from the
 dataset. Taxonomic assignments were then corrected
 based on existing species distribution data for each site. Species
 Red-Collared Lorikeet (<em>Trichoglossus rubritorquis</em>),
 short-eared possum (<em>Trichosurus</em>
 <em>caninus</em>) and New Zealand Fantail
 (<em>Rhipidura</em> <em>fuliginosa</em>), which
 are not known to occur within SWWA, were reassigned to local taxa Rainbow
 Lorikeet (<em>Trichoglossus</em>
 <em>moluccanus</em>), brushtail possum
 (<em>Trichosurus</em> <em>vulpecula</em>) and Grey
 Fantail (<em>Rhipidura</em> <em>albiscapa</em>),
 respectively. The genus <em>Tadorna</em> and family
 Pseudocheiridae were reassigned to Australian Shelduck
 (<em>Tadorna</em> <em>tadornoides</em>) and
 western ringtail possum (<em>Pseudocheirus</em>
 <em>occidentalis</em>), respectively, due to these taxa
 containing only a single species in SWWA. The family Strigidae was
 reassigned to genus <em>Ninox</em> again due to known species
 distributions; however, this could not be assigned to a lower level as two
 <em>Ninox</em> species are known to occur within the SWWA. The
 Malayan field rat (<em>Rattus</em>
 <em>tiomanicus</em>) and Himalayan field rat
 (<em>Rattus</em> <em>nitidus</em>) were downgraded
 to genus level, due to species distributions outside of the study area. 
 ZOTUs with multiple possible assignments were left at the closest
 taxonomic level and labelled “sp”. Of these Pstittacidae sp. was
 reassigned to Psittaculidae sp. in line with species distribution
 data.
description: # Data from: Home is where the hollow is: Revealing vertebrate tree hollow
 user biodiversity with eDNA metabarcoding
 [https://doi.org/10.5061/dryad.c59zw3r9r](https://doi.org/10.5061/dryad.c59zw3r9r) ## Description of the data and file structure There are five files included:   **FTP350\_Hollows.fastq.gz** \- Compressed sequencing file containing raw sequences from the illumina MiSeq run **FTP348\_P\_Hollows.fastq.gz** \- Compressed sequencing file containing raw sequences from the illumina MiSeq run **Sample\_barcode.xlsl** \- The information required to demultiplex raw sequences **sample data.csv**\- Sample metadata for the project **filtered\_ZOTU\_table.csv** \- final ZOTU table produced after using eDNAFlow bioinformatics pipeline for sequence analysis\. The taxonomy is included in this file and the details on the bioinformatics steps performed to produce this file are further described in the methods section of the publications and the dryad digital repository\.   Details for **Sample\_barcode.xlsl** MiSeq\_Run                   ID of the MiSeq run MiSeq\_Run\_Date         Date of the sequencing run Sample.ID                     Sample ID Description                   The type of sample taken from hollow (Roller swab/sediment) Site                               The sample site (BP = Bold Park, KP = Kings Park, TNP\_North = Tuart National Park North, TNP\_South = Tuart National Park South) Extraction                    The extraction kit used F\_Tag\_ID                     ID of the Forward multiplex identifier (MID) tag R\_Tag\_ID                     ID of the reverse multiplex identifier (MID) tag F\_Primer, R\_Primer     IDs of the forward and reverse primers F\_Tag\_seq                   sequence of the Forward multiplex identifier (MID) tag R\_Tag\_seq                   sequence of the Reverse multiplex identifier (MID) tag F\_Primer\_Seq              Forward Primer sequence R\_Primer\_Seq             Reverse Primer sequence Primer                          Name for the assay   Details for **sample data.csv** Sample                         Sample ID Site                               The sample site (BP = Bold Park, KP = Kings Park, TNP\_North = Tuart National Park North, TNP\_South = Tuart National Park South) Status                           Site classification, Urban reminant (Urban) and National Park Location                       The location of the sample sites tree\_num                Tree number sampled hollow\_num           Hollow number sampled (per tree) sample\_type                 The type of sample taken from hollow (Roller swab/sediment) Height                          Height to base of hollow sampled Diameter                       Diameter of hollow sampled   Depth                           Depth to base of hollow sampled from hollow entrance