DOI: 10.25349/d9p60t
title: Tidewater goby and estuarine fish records from seining, qPCR and metabarcoding data for Southern California estuaries in 2023

description: Many studies have shown that environmental DNA (eDNA) sampling can be more
 sensitive than traditional sampling. For instance, past studies found a
 specific qPCR probe of a water sample is better than a seine for detecting
 the endangered tidewater goby, Eucyclogobius newberryi. Furthermore, a
 metabarcoding sample often detects more fish species than a seine detects.
 Less consideration has been given to sampling costs. To help managers
 choose the best sampling method for their budget, I estimated
 detectability and costs per sample to compare the cost-effectiveness of
 seining, qPCR and metabarcoding for detecting endangered tidewater gobies
 as well as the associated estuarine fish community in California. Five
 samples were enough for eDNA methods to confidently detect tidewater
 gobies, whereas seining required twice as many samples. Fixed program
 costs can be high for qPCR and seining, whereas metabarcoding had high
 per-sample costs, which led to changes in relative cost-effectiveness with
 the number of locations sampled. Under some circumstances (multiple
 locations visited or an already validated assay), qPCR was a bit more
 cost-effective than metabarcoding for detecting tidewater gobies. Under
 all assumptions, seining was the least cost-effective method for detecting
 tidewater gobies or other fishes. Metabarcoding was the most
 cost-effective sampling method for multiple species detection. Despite its
 advantages, metabarcoding still suffers from gaps in sequence databases,
 can yield vague results for some species, and can lead novices to serious
 errors. Seining is still the only way to rapidly assess densities, size
 distributions, and fine-scale spatial distributions. The manuscript relies
 on 8 separate data sets and an R file to analyze them.  Each data
 file has an accompanying metadata file and information file. The subset of
 data used is provided in the data archive
 (Schmelzle&Kinziger_occupancy.csv) so that analyses can be
 reproduced but should be cited as Schmelzle, Molly C.; Kinziger, Andrew P.
 (2015). Data from: Using occupancy modeling to compare environmental DNA
 to traditional field methods for regional-scale monitoring of an
 endangered aquatic species [Dataset]. Dryad.
 https://doi.org/10.5061/dryad.6rs23
description: Water samples were taken for eDNA at four sites known to contain
 tidewater gobies in the past: 16 samples Calleguas Creek (34 06'
 42", 119 04' 54", Ventura County), 21 samples at Ormond
 Lagoon (34 8' 23", 119 11' 20", just west of NVBC),
 and 17 samples at Santa Clara River Mouth (34 4' 8", 119
 15' 53", Ventura County). In addition, two samples were taken at
 Mugu Lagoon (34 5' 30", 119 7' 21", Ventura County)
 and 20 samples were taken at Devereux Slough (34 25' 4", 119
 52' 27", Santa Barbara County). I used commercial aquatic eDNA
 kits from Jonah Ventures ® for US $90 each (this cost includes supplies,
 sequencing and bioinformatics). At all sites, nearshore water samples were
 taken for environmental DNA wearing latex gloves to reduce contamination
 with human DNA. Samples were then filtered through a 1-micron disk filter
 by pushing water through the filter with a 60cc luer-lock syringe until
 clogging (mean sample volume: 174 cc +/- 0.141 S.D.). Filter capsules were
 purged of water before filling with preservative (tris-EDTA) before
 refrigerating until they were express shipped back to Jonah Ventures ® for
 sequencing. Seines were taken at each water sampling site for one of the
 estuaries (Calleguas Creek) that was sampled for eDNA (tidewater gobies
 collection permit #PER0046428) and matched sites and effort. Seine hauls
 were 2.4 m wide by 6.4 m distance on average in 0.6 m water depth.
 Temperature was 21.2 C. conductivity was 32 (close to seawater), and DO
 (mg/L) was 8.3). Jonah Ventures’ ® methods for qPCR and metabarcoding are
 summarized as follows. After the samples were received, DNA was extracted
 using the DNeasy Blood & Tissue Kit. Three qPCR replicates were
 run for a tidewater-goby-specific primer (Schmelzle & Kinziger
 2016). Metabarcoding was done for the mitochondrial 12S ribosomal RNA
 (rRNA) gene which was PCR amplified from each genomic DNA sample using the
 MiFishUF and MiFishUR primers with spacer regions. Amplicon size and PCR
 efficiency were visually inspected and then cleaned by incubating. A
 second round of PCR was performed to complete the sequencing library
 construct. Final indexed amplicons from each sample were cleaned and
 normalized using SequalPrep Normalization Plates and then pooled. Sample
 library pools were sent for sequencing on an Illumina NovaSeq 6000 (San
 Diego, CA) at the Texas A&M Agrilife Genomics and Bioinformatics
 Sequencing Core facility using the SP Reagent Kit v1.5 (500 cycles) (cat#
 20028402). Raw sequence data were then demultiplexed using
 <em>pheniqs</em> v2.10, primers were removed with
 <em>Cutadapt</em> v3.4, and read pairs were merged, denoised
 and chimeras were removed with <em>vsearch</em> v2.15.2. Exact
 sequence variants observed more than 7 times were assigned with a custom
 best-hits algorithm and a reference database that combined Genbank and a
 Jonah Ventures voucher sequence record, following a consensus taxonomy
 with all for any taxonomic level with &gt; 90% agreement across top
 hits. Raw sequences were vouchered through NCBI SRA (SRP#
 PRJNA924783).
description: # Tidewater goby and estuarine fish records from seining, qPCR and
 metabarcoding data for Southern California Estuaries in 2023
 This data archive includes R code
 and data for reproducing the analyses and figures in Lafferty,
 **Metabarcoding is (usually) more cost effective than seining or qPCR for
 detecting tidewater gobies and other estuarine fishes.**   To view the
 supplementary tables, open the Fig&TableSuppl.docx file. This file
 also includes the manuscript figures and tables and some explanatory text
 about how to generate them. To reproduce the figures, open the
 Fig&TableCode.Rmd in R studio and be sure the needed csv files
 included in the Dryad repository are in the working directory. The data
 files include more information than used in the analyses and can be used
 for other purposes. The code is not software, nor is it intended as an R
 package, but the code is annotated so others can understand and manipulate
 it. For each CSV file there is an associated metadata file that defines
 entries and columns and an information file that contains an abstract and
 ownership information. One of the data files required to reproduce the
 analyses (Schmelzle&Kinziger_occupancy.csv) was created from
 previously published data and was not produced by the author.  Please cite
 it as Schmelzle, Molly C.; Kinziger, Andrew P. (2015). Data from: Using
 occupancy modeling to compare environmental DNA to traditional field
 methods for regional-scale monitoring of an endangered aquatic species
 [Dataset]. Dryad.   Files
 included in the archive | Name | Type | Description | |
 :--------------------------------------------------------------------- |
 :-------------------------------- |
 :----------------------------------------------------------- | |
 Fig\&TableCode.Rmd | R markdown | Code used to produce analyses and
 figures from imported data | | Fig\&TableSuppl.docx | Document |
 Supplementary tables | |
 DataToResampleMetabarcodesR\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 DataToResampleMetabarcodesR\_Identification\_Metadata.csv | Information |
 location, date and ownership | | DataToResampleMetabarcodesR.csv |
 original data | A matrix of species presence absence data by sample. | |
 DataToResampleSeinesR\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | |
 DataToResampleSeinesR\_Identification\_Metadata.csv | Information |
 location, date and ownership | | DataToResampleSeinesR.csv | original data
 | A matrix of species presence absence data by sample. | |
 Estuaries2022\_MiFishU\_metadata\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 Estuaries2022\_MiFishU\_metadata\_Identification\_Metadata.csv |
 Information | location, date and ownership | |
 Estuaries2022-MiFishU-metadata.csv | original data | attributes of the
 sampling sites | |
 Final\_Matches\_esv\_data\_Entity\_and\_Attribute\_Metadata.csv | Metadata
 | definitions and units | |
 Final\_Matches\_esv\_data\_Identification\_Metadata.csv | Information |
 location, date and ownership | | Final\_Matches-esv.data.csv | original
 data | Consensus taxonomy for metabarcoding data | |
 InvestmentTable\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | | InvestmentTable\_Identification\_Metadata.csv |
 Information | location, date and ownership | | InvestmentTable.csv |
 original data | Estimates for efforts needed per method | |
 JVB1846\_qpcr\_tabulated\_data\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 JVB1846\_qpcr\_tabulated\_data\_Identification\_Metadata.csv | Information
 | location, date and ownership | | JVB1846-qpcr-tabulated-data.csv |
 original data | tidewater goby qPCR reads per sample | |
 New\_Estuary\_Data\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | | New\_Estuary\_Data\_Identification\_Metadata.csv
 | Information | location, date and ownership | | New\_Estuary\_Data.csv |
 original data | metabarcoding data with consensus taxonomy per sample | |
 Schmelzle\&Kinziger\_occupancy.csv | Schmelzle et al. 2015Dryad. 6rs23
 | published tidewater goby occupancy data by qPCR and seining | |
 SchmelzleandsKinziger\_occupancy\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 SchmelzleandsKinziger\_occupancy\_Identification\_Metadata.csv |
 Information | location, date and ownership |    
 DataToResampleMetabarcodesR.csv Abstract These presence/absence data on
 fish species detections from metabarcoding at Calleguas Creek are
 organized as a matrix with samples/sites as rows and species as columns. 
 An entry of 1 means the species was detected at that site/sample.  A 0
 means it was not detected.  The matrix was developed by summarizing
 information in the New_Estuary_Data.csv file.   Purpose The data are
 resampled to plot the cumulative richness detected from a particular
 sampling effort.  Doing this several times makes it possible to plot
 confidence limits around the estimate.         DataToResampleSeinesR.csv
 Abstract These presence/absence data on fish species detections from
 seining at Calleguas Creek are organized as a matrix with samples/sites as
 rows and species as columns.  An entry of 1 means the species was detected
 at that site/sample.  A 0 means it was not detected.  The matrix was
 developed by summarizing information in the
 Estuaries2022-MiFishU-metadata.csv file.   Purpose The data are resampled
 to plot the cumulative richness detected from a particular sampling
 effort.  Doing this several times makes it possible to plot confidence
 limits around the estimate.     Estuaries2022-MiFishU-metadata.csv
 Abstract Field notes including site attributes like the area sampled,
 temperature, species observations, and locations. The data also include
 the label given to eDNA filters, site names, and the qPCR reads per
 replicate for tidewater gobies and the fish detected by seining.   Purpose
 The data are used to create various data suitable for specific analyses,
 like DataToResampleSeinesR.csv.     Final_Matches-esv.data.csv Abstract
 Metabarcode data offer several hypothesized taxa for each ASV in a sample.
 To convert these data into a single taxon, a consensus taxonomy is
 required. Here, one taxon_name is given per ASV, a second column indicates
 if there are alternative likely names.   Purpose The consensus taxonomy
 can be used to evaluate the biodiversity captured in a metabarcode sample.
 This is used here to create the DataToResampleMetabarcodesR.csv file
 which, in turn, is used to generate species accumulation curves for
 metabarcoding.   InvestmentTable.csv Abstract Sampling requires various
 efforts or investments. This table defines those actions based on author
 experience and then estimates how they vary among different sampling
 approaches. Using the common currency of technician hours makes it
 possible to add up various efforts into a single number. Purpose By
 obtaining a single value for effort, it is possible to plot return on
 investment for different methods.   JVB1846-qpcr-tabulated-data.csv
 Abstract qPCR detection of tidewater gobies with a species-specific primer
 returns a number of amplicon reads in each of three qPCR replicates. 
 Purpose Doing qPCR detection in multiple samples and multiple replicates
 makes it possible to calculate detection probabilities and to then plot
 how detection increases with replication.   New_Estuary_Data.csv Abstract
 This file summarizes the consensus taxonomy for each metabarcoding sample
 per site per estuary along with the sum reads.    This file is derived by
 combining the Final_Matches-esv.data.csv and the
 Estuaries2022-MiFishU-metadata.csv. Note that these data include several
 estuaries in addition to Calleguas Creek   Purpose These data are used to
 estimate how well tidewater gobies are detected by metabarcoding (for
 comparison with qPCR). They are also used to estimate the plausible list
 of taxa detected by metabarcoding.   Fig&TableCode.Rmd Abstract An R
 markdown file that has scripts to achieve various aims of the study.  Note
 that this file does not use the raw data directly, rather it uploads
 several CSV file included in in the supplementary data appendix.  These
 must be loaded in the working directory for the Markdown file to work. The
 markdown file can be used to produce the report *Fig&TableSuppl.docx*,
 which includes the figures and additional analyses.  Or it can be used to
 evaluate assumptions in the analyses or develop additional analyses. The
 Markdown file assumes a basic knowledge of the R language and a strong
 familiarity with the paper.   Purpose The main purpose of this file was to
 analyze data and generate figures. The secondary purpose was to collate
 all analyses in a way that users could reproduce the analyses in the
 paper.  A third purpose is to provide scripts that others might find
 useful when working with qPCR, metabarcoding or seining data.  
 Fig&TableSuppl.docx Abstract A report in Word generated from
 Fig&TableCode.Rmd.  The report includes supplementary tables and
 outputs of the main figures (which may not be identically formatted to
 those in the journal publication).   Purpose The main purpose of this file
 was to make the supplementary tables available, but also to guide those
 interested in working with the code in Fig&TableCode.Rmd.  
 Schmelzle&Kinziger_occupancy.csv Abstract This file is derived from
 previously published data compared seine detections of tidewater gobies
 with qPCR detections.  These data should be cite as Schmelzle et al.
 2015Dryad. 6rs23. Purpose These data were used to compare qPCR with
 seining for detecting tidewater gobies. ## Sharing/Access information
 Files included in the archive | Name | Type | Description | |
 ---------------------------------------------------------------------- |
 --------------------------------- |
 ------------------------------------------------------------ | |
 TWgobyMethodsAppendix.Rmd | R markdown | Code used to produce analyses and
 figures from imported data | | TWgobyMethodsAppendix.docx | Document |
 Supplementary tables | |
 DataToResampleMetabarcodesR\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 DataToResampleMetabarcodesR\_Identification\_Metadata.csv | Information |
 location, date and ownership | | DataToResampleMetabarcodesR.csv |
 original data | A matrix of species presence absence data by sample. | |
 DataToResampleSeinesR\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | |
 DataToResampleSeinesR\_Identification\_Metadata.csv | Information |
 location, date and ownership | | DataToResampleSeinesR.csv | original data
 | A matrix of species presence absence data by sample. | |
 Estuaries2022\_MiFishU\_metadata\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 Estuaries2022\_MiFishU\_metadata\_Identification\_Metadata.csv |
 Information | location, date and ownership | |
 Estuaries2022-MiFishU-metadata.csv | original data | attributes of the
 sampling sites | |
 Final\_Matches\_esv\_data\_Entity\_and\_Attribute\_Metadata.csv | Metadata
 | definitions and units | |
 Final\_Matches\_esv\_data\_Identification\_Metadata.csv | Information |
 location, date and ownership | | Final\_Matches-esv.data.csv | original
 data | Consensus taxonomy for metabarcoding data | |
 InvestmentTable\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | | InvestmentTable\_Identification\_Metadata.csv |
 Information | location, date and ownership | | InvestmentTable.csv |
 original data | Estimates for efforts needed per method | |
 JVB1846\_qpcr\_tabulated\_data\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 JVB1846\_qpcr\_tabulated\_data\_Identification\_Metadata.csv | Information
 | location, date and ownership | | JVB1846-qpcr-tabulated-data.csv |
 original data | tidewater goby qPCR reads per sample | |
 New\_Estuary\_Data\_Entity\_and\_Attribute\_Metadata.csv | Metadata |
 definitions and units | | New\_Estuary\_Data\_Identification\_Metadata.csv
 | Information | location, date and ownership | | New\_Estuary\_Data.csv |
 original data | metabarcoding data with consensus taxonomy per sample | |
 Schmelzle\&Kinziger\_occupancy.csv | Schmelzle et al. 2015Dryad. 6rs23
 | published tidewater goby occupancy data by qPCR and seining | |
 SchmelzleandsKinziger\_occupancy\_Entity\_and\_Attribute\_Metadata.csv |
 Metadata | definitions and units | |
 SchmelzleandsKinziger\_occupancy\_Identification\_Metadata.csv |
 Information | location, date and ownership | ## Code/Software Files were
 created from Excel and R scripts used to summarize and organize the raw
 data into tables more easily analyzed by the R markdown file.