DOI: 10.5061/dryad.mkkwh717w
title: Data from: Are modern cryptic species detectable in the fossil record? A case study on agamid lizards

description: Comparisons of extant and extinct biodiversity are often dependent on
 objective morphology-based identifications of fossils and assume a
 well-established and comparable taxonomy for both fossil and modern taxa.
 However, since many modern (cryptic) species are delimitated mainly via
 external morphology and/or molecular data, it is often unclear to what
 degree fossilized (osteological) remains allow classification to a similar
 level. When intraspecific morphological variation in extant taxa is poorly
 known, the definition of extinct species as well as the referral of
 fossils to extant species can be heavily biased, particularly if fossils
 are represented by incomplete isolated skeletal elements. This problem is
 especially pronounced in squamates (lizards and snakes) owing to a lack of
 osteological comparative knowledge for many lower taxonomic groups,
 concomitant with a recent increase of molecular studies revealing great
 cryptic diversity. Here, we apply a quantitative approach using 3D
 geometric morphometrics on 238 individuals of 14 genera of extant
 Australian and Papua New Guinean agamid lizards to test the value of two
 isolated skull bones (frontals and maxillae) for inferring taxonomic and
 ecological affinities. We further test for the consistence of intra- and
 interspecific morphological variability of these elements as a proxy for
 extinct taxonomic richness. We show that both bones are diagnostic at the
 generic level, and both can infer microhabitat and are of palaeoecological
 utility. However, species-level diversity is likely underestimated by both
 elements, with ~40% of species pairs showing no significant differences in
 shape. Mean intraspecific morphological variability is largely consistent
 across species and bones and thus a useful proxy for extinct species
 diversity. Reducing sample size and landmark completeness to approximate
 fossil specimens led to decreased classification accuracy and increased
 variance of morphological disparity, raising further doubts on the
 transferability of modern species borders to the fossil record of agamids.
 Our results highlight the need to establish appropriate levels of
 morphology-based taxonomic or ecological groupings prior to comparing
 extant and extinct biodiversity.
description: # Electronic supplement "Are Modern Cryptic Species Detectable in the
 Fossil Record? A Case Study on Agamid Lizards"
 [https://doi.org/10.5061/dryad.mkkwh717w](https://doi.org/10.5061/dryad.mkkwh717w) ## Description of the data and file structure This supplementary dataset contains data crucial for understanding the results and discussion of our study. It includes specimen metadata and surface models of the included agamid specimens, as well as results of all analyses. In addition we provide custom R code to repeat certain analyses. ### Files and variables #### File: File\_S1\_-\_Metadata\_for\_the\_included\_specimens.xlsx **Description:** Metadata for the included specimens. The table further contains explanations of institutional abbreviations, abbreviations and the cited papers. ##### **Table Columns** * spec_ID: this column contains a specimen specific ID including an abbreviation of the taxonomic name (the first three letters of genus and species name) as well as institutional collection numbers * species: abbreviation of the taxonomic name (the first three letters of genus and species name). This column determines to which species a specimen was assigned. Note that this can differ from the assignment in the spec_ID column, because the taxonomy of specimens was updated according to genetic studies cited in the paper * genus: abbreviation of the genus name. This column determines to which genus a specimen was assigned * microhabitat: abbreviation of the microhabitat. This column determines to which microhabitat a specimen was assigned * juv: this column determines if a specimen was considered juvenile (yes) or not (no) * 3_spec_per_species: this column determines if a specimen was included in the species level analyses, i.e. if three or more specimens of a given species were present in the dataset (yes) * 3_spec_per_genus: this column determines if a specimen was included in the genus level analyses, i.e. if three or more specimens of a given genus were present in the dataset (yes) * frontal_landmarked: this column indicates if the frontal was landmarked for a given specimen, "x" means yes and empty cells mean "no" * max_landmarked: this column indicates if the maxilla was landmarked for a given specimen, "x" means yes and empty cells mean "no" * landmarked: this column indicates if the right maxilla (RM) or left maxilla (LM) was landmarked * resolution (um): scan resolution in micro meters, scan parameters of specimens taken from other studies can be found in the original publications. In these cases cells are left empty. * source voltage (kV): source voltage in kV, scan parameters of specimens taken from other studies can be found in the original publications. In these cases cells are left empty. * source current (uA): source current in micro ampere, scan parameters of specimens taken from other studies can be found in the original publications. In these cases cells are left empty. * citation: this column indicates if a specimen scan was created in the course of the present study. Otherwise the citation is given * position_in_LM_file: this number indicates the position of the specimens in the landmark file #### File: File\_S2\_–*Folder\_containing\_surface\_models*(.ply)\_of\_the\_crania\_of\_the\_included\_specimens\_\_landmark\_pairs\_\_and\_sliding\_landmark\_data.rar **Description:**  This folder contains * surface models of the included specimens in polygon file format (.ply) * a text file (.txt) containing numbers for matched pairs of landmarks across the line of symmetry, which can directly be used in R for the function *bilat.symmetry* in the R package geomorph * two excel files (.csv) indicating sliding landmarks for maxillae (sliders max complete.csv) and frontals (sliders front complete.csv), which can directly be used in R for the function *gpagen* to define sliding landmarks in the R package geomorph. These matrices can be generated with the R function *define.sliders* in geomorph (see [https://rdrr.io/cran/geomorph/man/define.sliders.html](https://rdrr.io/cran/geomorph/man/define.sliders.html) for further details) * an excel file (agamid_database_final.csv) which represents the same table as File S1 (metadata for all included specimens), but which can be loaded directly into R, to be used with the custom code provided along this dataset #### File: File\_S3a\_–\_3D\_landmark\_coordinates\_of\_maxillae.tps **Description:** 3D landmark coordinates (X coordinates: first column, Y coordinates: second column, Z coordinates: third column; unit: mm) of maxillae in thin-plate-spline format (.tps). The order of the specimens in this landmark file is given in *File_S1_-_Metadata_for_the_included_specimens.xlsx* in the column 'position_in_LM_file'. Descriptions and images of the positions of the landmarks can be found in the file *List_of_online_supplements_and_supplementary_figures.docx* (Figures S1 & S2, Tables S1 & S2). **Landmark aquisition methods:** Using a threshold for bone, the heads of all specimens were segmented in Volume Graphics Studio 3.2 (Volume Graphics GmbH, Heidelberg, Germany). Image stacks of the skulls were converted to NifTi format, down sampled if necessary and 3D surface models were created using Stratovan Checkpoint (Stratovan Corporation, Davis, CA) and a threshold for bone. Sets of 3D landmarks were used to characterize frontal and maxillary shape with landmark-based geometric morphometrics. We placed 32 anatomical (single) landmarks as well as 33 semi-landmarks on the maxillae (238 specimens) and 20 anatomical plus 76 semi-landmarks on the frontals (225 specimens) in Stratovan Checkpoint. #### File: File\_S3b\_–*3D\_landmark\_coordinates\_of\_maxillae*(missing\_data\_estimated\_\_curves\_equidistant).tps **Description:** 3D landmark coordinates (X coordinates: first column, Y coordinates: second column, Z coordinates: third column; unit: mm) of maxillae in thin-plate-spline format (.tps), with missing data estimated using the regression based method of the R package LOST, and with semi-landmarks of curves made equidistant with the function *equidistantCurve* in the R package Morpho. The order of the specimens in this landmark file is given in *File_S1_-_Metadata_for_the_included_specimens.xlsx* in the column 'position_in_LM_file'. Descriptions and images of the positions of the landmarks can be found in the file *List_of_online_supplements_and_supplementary_figures.docx* (Figures S1 & S2, Tables S1 & S2). **Landmark aquisition methods:** Using a threshold for bone, the heads of all specimens were segmented in Volume Graphics Studio 3.2 (Volume Graphics GmbH, Heidelberg, Germany). Image stacks of the skulls were converted to NifTi format, down sampled if necessary and 3D surface models were created using Stratovan Checkpoint (Stratovan Corporation, Davis, CA) and a threshold for bone. Sets of 3D landmarks were used to characterize frontal and maxillary shape with landmark-based geometric morphometrics. We placed 32 anatomical (single) landmarks as well as 33 semi-landmarks on the maxillae (238 specimens) and 20 anatomical plus 76 semi-landmarks on the frontals (225 specimens) in Stratovan Checkpoint. #### File: File\_S4a\_–\_3D\_landmark\_coordinates\_of\_frontals.tps **Description:** 3D landmark coordinates (X coordinates: first column, Y coordinates: second column, Z coordinates: third column; unit: mm) of frontals in thin-plate-spline format (.tps). The order of the specimens in this landmark file is given in *File_S1_-_Metadata_for_the_included_specimens.xlsx* in the column 'position_in_LM_file'. Descriptions and images of the positions of the landmarks can be found in the file *List_of_online_supplements_and_supplementary_figures.docx* (Figures S1 & S2, Tables S1 & S2). **Landmark aquisition methods:** Using a threshold for bone, the heads of all specimens were segmented in Volume Graphics Studio 3.2 (Volume Graphics GmbH, Heidelberg, Germany). Image stacks of the skulls were converted to NifTi format, down sampled if necessary and 3D surface models were created using Stratovan Checkpoint (Stratovan Corporation, Davis, CA) and a threshold for bone. Sets of 3D landmarks were used to characterize frontal and maxillary shape with landmark-based geometric morphometrics. We placed 32 anatomical (single) landmarks as well as 33 semi-landmarks on the maxillae (238 specimens) and 20 anatomical plus 76 semi-landmarks on the frontals (225 specimens) in Stratovan Checkpoint. #### File: File\_S4b\_–*3D\_landmark\_coordinates\_of\_frontals*(missing\_data\_estimated\_\_curves\_equidistant).tps **Description:** 3D landmark coordinates (X coordinates: first column, Y coordinates: second column, Z coordinates: third column; unit: mm) of frontals in thin-plate-spline format (.tps), with missing data estimated using the regression based method of the R package LOST, and with semi-landmarks of curves made equidistant with the function *equidistantCurve* in the R package Morpho. The order of the specimens in this landmark file is given in *File_S1_-_Metadata_for_the_included_specimens.xlsx* in the column 'position_in_LM_file'. Descriptions and images of the positions of the landmarks can be found in the file *List_of_online_supplements_and_supplementary_figures.docx* (Figures S1 & S2, Tables S1 & S2). **Landmark aquisition methods:** Using a threshold for bone, the heads of all specimens were segmented in Volume Graphics Studio 3.2 (Volume Graphics GmbH, Heidelberg, Germany). Image stacks of the skulls were converted to NifTi format, down sampled if necessary and 3D surface models were created using Stratovan Checkpoint (Stratovan Corporation, Davis, CA) and a threshold for bone. Sets of 3D landmarks were used to characterize frontal and maxillary shape with landmark-based geometric morphometrics. We placed 32 anatomical (single) landmarks as well as 33 semi-landmarks on the maxillae (238 specimens) and 20 anatomical plus 76 semi-landmarks on the frontals (225 specimens) in Stratovan Checkpoint. #### #### **File S5 – R code for evaluating landmark estimation (.R)** * custom R code to repeat the analysis evalutating different methods of landmark estimation. R is required to run this code #### **File S6 – R code for estimating effects of sample size (.R)** * custom R code to repeat the analysis for estimating effects of sample size on classification accuracy and morphological disparity. R is required to run this code #### **File S7 – R code for estimating effects of missing landmarks (.R)** * custom R code to repeat the analysis for estimating effects of missing landmarks on classification accuracy and morphological disparity. R is required to run this code #### File: File\_S8\_–\_Results\_of\_landmark\_estimation\_performance\_analyses.csv **Description:** ##### **Table Columns** * Procrustes_distance: column containing values of Procrustes distance to the original configuration * estimation_method: column indicating which estimation method was used * percentage_incomplete_specimens: column indicating the percentage of incomplete specimens * percentage_missing_landmarks: column indicating the percentage of missing landmarks * bone: column indicating the bone, max (maxilla), front (frontal) #### File: File\_S9\_–*Pairwise\_Procrustes\_distances\_of\_different\_groupings\_and\_CVA\_results*(maxillae).xlsx **Description:** * The sheet pairwise_distances_max contains multiple tables, of which each contains Pairwise Procrustes distances (d), 95% upper confidence levels (UCL 95%), z-scores (Z) and p-values (Pr &gt; d) of the pairwise Procrustes distances of different groupings. These results were created using the *procD.lm* and *pairwise* functions of the R packages geomorph and RRPP * The sheet CVAs_max contains classification accuracies based on canonical variates analysis of different groupings with and without juveniles #### File: File\_S10\_-*Pairwise\_Procrustes\_distances\_of\_different\_groupings\_and\_CVA\_results*(frontals).xlsx **Description:** * The sheet pairwise_distances_front contains multiple tables, of which each contains Pairwise Procrustes distances (d), 95% upper confidence levels (UCL 95%), z-scores (Z) and p-values (Pr &gt; d) of the pairwise Procrustes distances of different groupings. These results were created using the *procD.lm* and *pairwise* functions of the R packages geomorph and RRPP * The sheet CVAs_front contains classification accuracies based on canonical variates analysis of different groupings with and without juveniles #### File: File\_S11\_-*Pairwise\_Procrustes\_variances\_of\_different\_groupings*(maxillae).xlsx **Description:** * The sheet disparity_max contains multiple tables with Procrustes distances, as well as p-values (indicating significant differences between the respective categories) of genera and species #### File: File\_S12\_-*Pairwise\_Procrustes\_variances\_of\_different\_groupings*(frontals).xlsx **Description:** * The sheet disparity_front contains multiple tables with Procrustes distances, as well as p-values (indicating significant differences between the respective categories) of genera and species #### File: File\_S13\_–\_Results\_of\_sample\_size\_analyses.csv **Description:**  Note that this file is semicolon delimited with a comma as the decimal. ##### **Table Columns** * classification_accuracy_%: values of classification accuracy in percent * disparity_min: values of minimum morphological disparity of genera * disparity_max: values of maximum morphological disparity of genera * disparity_mean: values of mean morphological disparity of genera * distance_min: values of minimum Procrustes distance between genera * distance_max: values of maximum Procrustes distance between genera * distance_mean: values of mean Procrustes distance between genera * sample_size: sample size (3,5,10,15,20,25 specimens) * bone: indicating if results are based on maxillae (max) or frontals (front) * group: the grouping factor, here the three best sampled genera were used, Ctenophorus (cteno), Diporiphora (dipo), Tympanocryptis (tymp) #### File: File\_S14\_–\_Results\_of\_missing\_landmarks\_analyses.csv **Description:**  Note that this file is semicolon delimited with a comma as the decimal. ##### **Table Columns** * classification_accuracy_%: values of classification accuracy in percent * disparity_min: values of minimum morphological disparity of genera * disparity_max: values of maximum morphological disparity of genera * disparity_mean: values of mean morphological disparity of genera * distance_min: values of minimum Procrustes distance between genera * distance_max: values of maximum Procrustes distance between genera * distance_mean: values of mean Procrustes distance between genera * missing_data_%: the percentage of removed landmarks (10,20,50,75) * bone: indicating if results are based on maxillae (max) or frontals (front) * group: the grouping factor, microhabitat (micro), genus and species #### File: File\_S15\_–\_Results\_of\_estimation\_vs.\_deletion\_analyses.xlsx **Description:** ##### **Table Columns** * percentage_missing_data: the percentage of removed landmarks (10,20,50,75) * bone: indicating if results are based on maxillae (max) or frontals (front) * estimated_or_deleted: indicating if landmarks were estimated (est) or deleted (del) * correctly_classified_individuals: number of correctly classified individuals (out of 1000 runs) * percentage_correctly_classified: percentage of correctly classified individuals ## Code/software We used R Studio 2023.09.0 to run the respective analyses. All R packages and their respective versions are cited in the main text of the manuscript. ## Access information Other publicly accessible locations of the data: * n/a Data was derived from the following sources: Some of the surface models used were previously published with the following studies * Gray, J. A., E. Sherratt, M. N. Hutchinson, and M. E. H. Jones. 2019. Evolution of cranial shape in a continental-scale evolutionary radiation of Australian lizards. Evolution 73:2216–2229. - Melville, J., K. Chaplin, C. A. Hipsley, S. D. Sarre, J. Sumner, and M. Hutchinson. 2019. Integrating phylogeography and high-resolution X-ray CT reveals five new cryptic species and multiple hybrid zones among Australian earless dragons. Royal Society Open Science 6:191166.