DOI: 10.5061/dryad.tqjq2bwb0
title: Data and code from: Integrating genomics, collections, and community science to delimit species clarifies the taxonomy of a variable monitor lizard (<em>Varanus tristis</em>)

description: The accurate characterization of species diversity is a vital prerequisite
 for ecological and evolutionary research, as well as conservation. Thus,
 it is necessary to generate robust hypotheses of species limits based on
 the inference of evolutionary processes. Integrative species delimitation,
 the inference of species limits based on multiple sources of evidence, can
 provide unique insight into species diversity and the processes behind it.
 Here, we show how community observations can be integrated with standard
 molecular and phenotypic datasets under an integrative framework to
 identify the processes generating genetic and phenotypic variation. We
 implement this approach in Varanus tristis, a widespread and variable
 complex of Australian monitor lizards. Using genomic, phenotypic (linear
 and geometric morphometrics, coloration), spatial, and environmental data,
 we show that disparity in this complex is inconsistent with intraspecific
 variation and instead suggests that speciation has occurred. Based on our
 results, we provide an updated taxonomy for this complex and identify the
 processes that may have been responsible for the geographic sorting of
 variation. Our workflow provides a guideline for the integrative analysis
 of several types of data to identify the occurrence and causes of
 speciation. Furthermore, our study highlights the benefits and caveats
 associated with community science and machine learning—two tools used
 here—in taxonomic research.
description: # Data and code from: Integrating genomics, collections, and community
 science to delimit species clarifies the taxonomy of a variable monitor
 lizard (*Varanus tristis*) Dataset DOI:
 [10.5061/dryad.tqjq2bwb0](10.5061/dryad.tqjq2bwb0) ## Description of the
 data and file structure These repository contains the data and code
 necessary to replicate the analyses in our manuscript, which uses an
 integrative species delimitation approach to delimit species in the
 monitor lizard *Varanus* *tristis*. ### Files and variables #### File:
 Custom_scripts.zip **Description:** Contains custom R scripts needed to
 run the analyses: * gl2fasta_snp_cjpv.R transforms a "genlight"
 object to a "fasta" file. * gl2svdquartets_cjpv.R transforms a
 "genlight" object to an input file for SVDquartets. *
 KeepFromCorrs.R will get you independent variables from a set of
 correlated variables based on a correlation coefficient. *
 KeepFromGraphs.R will get you independent variables from a set of
 correlated variables based on graphs. #### File: MMRR_Wang2013_code.zip
 **Description:** Contains the function to implement the multiple matrix
 regression with randomization approach of Wang (2013)
 ([https://doi.org/10.1111/evo.12134](https://doi.org/10.1111/evo.12134))
 #### File: Script.R **Description:** Script used to run all the analyses
 described in the paper. #### File: Data.zip **Description:** Data used by
 Script.R: * a_hat.csv contains the pairwise a-hat metric of genetic
 distances. "NA" included to allow R to correctly read the file.
 Contains lower triangle of matrix only (blank cells used for diagonal and
 upper triangle). * all_data_inds.csv is the metadata for the individuals
 that have all types of data available: * Collection source: Herpetological
 collections where the specimens associated with each tissue sample are
 deposited. * Collection voucher: Unique identifier for each specimen
 within its respective collection. * Tissue source: Biological sample
 collections where the tissue samples were sourced from. * Tissue voucher:
 Unique identifier for each tissue sample within its respective collection.
 * Lon: Longitude in decimal degrees. * Lat: Latitude in decimal degrees. *
 MorphologyID: Indicates how the individuals are labeled in the
 morphological data files. * MolecularID: Indicates how the individuals are
 labeled in the molecular data files. * bil2d_dorsal_supersom.csv contains
 the geometric morphometric data for the dorsal head shape for the
 individuals included in the SuperSOM analyses. First column (missing
 header; containing source collection and voucher) read by R as row names.
 V1–V66 represent landmark/semi-landmark coordinates. X-value and Y-value
 for each of the 33 landmarks/semi-landmarks given consecutively. *
 citizen_science_data.csv contains metadata for the community science
 photographs used in the coloration analyses: * decimalLatitude: Latitude
 in decimal degrees. * decimalLongitude: Longitude in decimal degrees. *
 url: URL associated with each image. * head: Head color. * col_df.rdata
 contains the environmental data used in the SuperSOM analyses. Once read
 into R, it returns a data frame with the following columns: * Collection
 source: Herpetological collections where the specimens associated with
 each tissue sample are deposited. * Collection voucher: Unique identifier
 for each specimen within its respective collection. * Tissue source:
 Biological sample collections where the tissue samples were sourced from.
 * Tissue voucher: Unique identifier for each tissue sample within its
 respective collection. * Lon: Longitude in decimal degrees. * Lat:
 Latitude in decimal degrees. * MorphologyID: Indicates how the individuals
 are labeled in the morphological data files. * MolecularID: Indicates how
 the individuals are labeled in the molecular data files. * elev: Elevation
 (in m). * solar: Annual mean solar radiation (in kJ/m^2^/day). * bio_1:
 Annual mean temperature (in °C). * bio_4: Temperature seasonality
 (standard deviation in °C * 100) * bio_5: Maximum temperature of warmest
 month (in °C). * bio_6: Minimum temperature of coldest month (in °C). *
 bio_12: Annual precipitation (in mm). * bio_15: Precipitation seasonality
 (coefficient of variation in mm). * bio_13: Precipitation of wettest month
 (in mm). * bio_14: Precipitation of driest month (in mm). *
 color_pred_df.rdata contains the color data and predictors used in the
 SuperSOM analyses. Once read into R, it returns a data frame with the
 following columns: * individual: Unique identifier for each individual. *
 head: Head color. * decimalLatitude: Latitude in decimal degrees * −1.
 Log-transformed and scaled. * dist_to_closest: Great-circle distance to
 closest individual in dataset (in km). Log-transformed and scaled. * elev:
 Elevation (in m). Log-transformed and scaled. * solar: Annual mean solar
 radiation (in kJ/m^2^/day). Log-transformed and scaled. * bio_1: Annual
 mean temperature (in °C). Log-transformed and scaled. * bio_12: Annual
 precipitation (in mm). Log-transformed and scaled. *
 examined_specimens_color.csv contains the color data for examined
 specimens: * download_path: Path to image of each specimen. * recordID:
 Collection and voucher of each specimen. * scientificName: Taxon to which
 each specimen belongs. * decimalLatitude: Latitude in decimal degrees. *
 decimalLongitude: Longitude in decimal degrees. * kml_coords.txt defines
 the polygon used in the EEMS analyses. Given as the coordinates of
 successive points: longitude in decimal degrees, latitude in decimal
 degrees, 0 (0 stands for vertical dimension, which is absent from the
 polygon). * proc2d_lateral_supersom.csv contains the geometric
 morphometric data for the lateral head shape for the individuals included
 in the SuperSOM analyses. First column (missing header; containing source
 collection and voucher) read by R as row names. 1.X,1.Y–10.X,10.Y
 represent landmark coordinates. X-value and Y-value for each of the 10
 landmarks given consecutively. * raw_morphometric_data.csv contains the
 raw linear morphometric data. Missing measurements (e.g., due to
 incomplete toes) given as "NA": * Species: Species. * Clade:
 Subspecific taxon to which each specimen was assigned (*V. t. tristis* or
 *V. t. orientalis*). * Museum: Herpetological collections where the
 specimens are deposited. * Museum.No.: Unique identifier for each specimen
 within its respective collection. * Latitude: Latitude in decimal degrees.
 * Longitude: Longitude in decimal degrees. * Sex: Female (F), male (M), or
 uncertain (NA). * Mature.: Yes (Y), no (N), could be based on body size
 (Y?), uncertain (?). * Tail.complete: Is the tail complete? Yes or no. *
 SVL: Snout-vent length (in mm). * Tail.length..dorsally.: Tail length
 measured along the drosal midline (in mm). *
 Body.length..gular.fold.vent..dorsally.: Body length (between vent and
 gular fold) measured along the dorsal midline (in mm). *
 Head.Length.Mid..snout.ant.ear.: Head length (between anterior end of
 snout and level of anterior edge of ear opening) measured along the dorsal
 midline (in mm). * Head.width..ant.ears. :Head width measured between
 anterior edge of ear openings (in mm).. * Head.depth..mid.eyes.: Head
 depth measured at level of middle of eyes (in mm). * Neck.length: Neck
 length (measured between gular fold and anterior edge of ear opening) (in
 mm). * Hip.width..between.legs..dorsally.: Hip width measured dorsally
 between hindlimbs (in mm). * X1.3.tail.width: Width of tail measured at
 the level of the posterior edge of the anteriormost third of its length
 (in mm). * X1.3.tail.depth: Depth of tail measured at the level of the
 posterior edge of the anteriormost third of its length (in mm). *
 Upper.arm.length: Length of humerus (in mm). * Lower.arm.length: Length of
 ulna (in mm). * Hand.length..wrist.base.of.finger.IV.: Hand length
 (between wrist and base of finger IV) (in mm). *
 X4th.finger.length..NOT.inc..webbing.: Length of finger IV, excluding any
 interdigital webbing (in mm). * Hand.width..perpendicular.base.finger.V.:
 Hand width, measured perpendicular to base of finger V (in mm). *
 Upper.leg.length: Femur length (in mm). * Lower.leg.length: Tibia length
 (in mm). * Foot.length..wrist.base.of.toe.IV.: Foot length (between ankle
 and base of toe IV) (in mm). * X4th.toe.length..NOT.inc..webbing.: Length
 of toe IV, excluding any interdigital webbing (in mm). *
 Foot.width..perpendicular.base.toe.V.: Foot width, measured perpendicular
 to base of finger V (in mm). * ref_table_dorsal.csv contains the metadata
 for the individuals for which geometric morphometric data for dorsal head
 shape is available. First column (missing header) read by R as row names:
 * Photo: Path to photograph from which the data was obtained in local
 computer. * Voucher: Collection and voucher of each specimen. * Species:
 Taxon to which each specimen was assigned (*V. t. tristis* or *V. t.
 orientalis*). * Sex: Female (F) or male (M). * Mature: Indicates whether
 the individual was sexually mature at the time of collection. *
 ref_table_lateral.csv contains the metadata for the individuals for which
 geometric morphometric data for lateral head shape is available. First
 column (missing header) read by R as row names: * Photo: Path to
 photograph from which the data was obtained in local computer. * Voucher:
 Collection and voucher of each specimen. * Species: Taxon to which each
 specimen was assigned (*V. t. tristis* or *V. t. orientalis*). * Sex:
 Female (F) or male (M). * Mature: Indicates whether the individual was
 sexually mature at the time of collection. - Report_DVara19-4371_SNP_1.csv
 is the file containing the DArTseq data (two row format; for each locus,
 Reference row first, SNP row second) as delivered by DArT containing
 outgroups. Each allele scored in a binary fashion ("1" =
 presence, "0" = absence; "-" = null allele).
 Heterozygotes are therefore scored as 1/1 (presence for both alleles/both
 rows). First 18 columns contain the metadata for each locus; asterisks
 used to fill space but with no other meaning. Following columns contain
 the data for each sample; the seven header rows indicate the order number
 to which the sample belongs to, DArT plate barcode, client plate barcode,
 well row position, well column position, sample comments, and genotype
 name, respectively. The first 18 columns contain the following
 information: * AlleleID: Unique identifier for the sequence in which the
 SNP marker occur. * AlleleSequence: The sequence of the Reference allele
 is in the Reference row, the sequence of the SNP allele in the SNP row. *
 AvgCountRef: The sum of the tag read counts for all samples, divided by
 the number of samples with non-zero tag read counts, for the Reference
 allele row. * AvgCountSnp: The sum of the tag read counts for all samples,
 divided by the number of samples with non-zero tag read counts, for the
 SNP allele row. * AvgPIC: The average of the polymorphism information
 content (PIC) of the Reference and SNP allele rows. * CallRate: The
 proportion of samples for which the genotype call is either "1"
 or "0", rather than "-". * CloneID: Unique identifier
 for the sequence in which the SNP marker occurs. * FreqHets: The
 proportion of samples which score as heterozygous. * FreqHomRef: The
 proportion of samples which score as homozygous for the Reference allele.
 * FreqHomSnp: The proportion of samples which score as homozygous for the
 SNP allele. * OneRatioRef: The proportion of samples for which the
 genotype score is "1", in the Reference allele row. *
 OneRatioSnp: The proportion of samples for which the genotype score is
 "1", in the SNP allele row. * PICRef: The polymorphism
 information content (PIC) for the Reference allele row. * PICSnp: The
 polymorphism information content (PIC) for the SNP allele row. * RepAvg:
 The proportion of technical replicate assay pairs for which the marker
 score is consistent. * SNP: This column is blank in the Reference row, and
 contains the base position and base variant details in the SNP row. *
 SnpPosition: The position (zero indexed) in the sequence tag at which the
 defined SNP variant base occurs. * TrimmedSequence: Same as the full
 sequence, but with removed adapters in short marker tags. -
 Report_DVara19-4371_SNP_2.csv is the file containing the DArTseq data (two
 row format; for each locus, Reference row first, SNP row second) as
 delivered by DArT without outgroups. Each allele scored in a binary
 fashion ("1" = presence, "0" = absence; "-"
 = null allele). Heterozygotes are therefore scored as 1/1 (presence for
 both alleles/both rows). First 26 columns contain the metadata for each
 locus; asterisks used to fill space but with no other meaning. Following
 columns contain the data for each sample; the seven header rows indicate
 the order number to which the sample belongs to, DArT plate barcode,
 client plate barcode, well row position, well column position, sample
 comments, and genotype name, respectively. The first 26 columns contain
 the following information: * AlleleID: Unique identifier for the sequence
 in which the SNP marker occur. * AlleleSequence: The sequence of the
 Reference allele is in the Reference row, the sequence of the SNP allele
 in the SNP row. * AvgCountRef: The sum of the tag read counts for all
 samples, divided by the number of samples with non-zero tag read counts,
 for the Reference allele row. * AvgCountSnp: The sum of the tag read
 counts for all samples, divided by the number of samples with non-zero tag
 read counts, for the SNP allele row. * AvgPIC: The average of the
 polymorphism information content (PIC) of the Reference and SNP allele
 rows. * CallRate: The proportion of samples for which the genotype call is
 either "1" or "0", rather than "-". *
 CloneID: Unique identifier for the sequence in which the SNP marker
 occurs. * FreqHets: The proportion of samples which score as heterozygous.
 * FreqHomRef: The proportion of samples which score as homozygous for the
 Reference allele. * FreqHomSnp: The proportion of samples which score as
 homozygous for the SNP allele. * OneRatioRef: The proportion of samples
 for which the genotype score is "1", in the Reference allele
 row. * OneRatioSnp: The proportion of samples for which the genotype score
 is "1", in the SNP allele row. * PICRef: The polymorphism
 information content (PIC) for the Reference allele row. * PICSnp: The
 polymorphism information content (PIC) for the SNP allele row. * RepAvg:
 The proportion of technical replicate assay pairs for which the marker
 score is consistent. * SNP: This column is blank in the Reference row, and
 contains the base position and base variant details in the SNP row. *
 SnpPosition: The position (zero indexed) in the sequence tag at which the
 defined SNP variant base occurs. * TrimmedSequence: Same as the full
 sequence, but with removed adapters in short marker tags. * AlnCnt_[...]:
 Total count of aligning markers / tags with selection criteria described
 below. * AlnEvalue_[...]: E value of the best alignment to an existing
 model genome. * ChromPos_[...]: Position(s) on contig(s) with the best
 alignment of marker / tag to an existing model genome. * Chrom_[...]:
 Contig(s) with the best alignment of marker / tag to an existing model
 genome. - sampling_dart.csv is the metadata for the individuals that were
 sequenced with DArTseq: * Voucher: Collection and voucher of each
 specimen. * Lat: Latitude in decimal degrees. * Lon: Longitude in decimal
 degrees. - tps_dorsal.txt contains the raw geometric morphometric data for
 dorsal head shape in tps format (for each specimen, the following is
 given: LM = number of landmarks/semi-landmarks, landmark coordinates, and
 ID = collection and voucher). - tps_lateral.txt contains the raw geometric
 morphometric data for lateral head shape in tps format (for each specimen,
 the following is given: LM = number of landmarks/semi-landmarks, landmark
 coordinates, and ID = collection and voucher). ## Code/software Analyses
 were run in R 4.2.2. The packages that are needed are: * dartR 2.7.2 * LEA
 3.10.2 * maps 3.4.1 * conStruct 1.0.5 * randomForest 4.7.1.1 * factoextra
 1.0.7 * cluster 2.1.4 * mclust 6.1 * MASS 7.3.58.1 * adegenet 2.1.10 *
 kohonen 3.0.12 * viridis 0.6.2 * missForest 1.5 * geomorph 4.0.5 *
 GroupStruct 0.1.0 * tidyr 1.3.0 * chopper 0 * gdata 2.18.0.1 * sp 1.6.0 *
 stringr 1.5.0 * genepop 1.2.2 * ape 5.7.1 * gdm 1.5.0.9.1 * mapproj 1.2.11
 * raster 3.6.14 * ggthemes 4.2.4 * dplyr 1.1.1 * brms 2.22.0 * pgirmess
 2.0.3