Dataset DOI: 10.5061/dryad.z08kprrtz

Description of the data and file structure

Landmark-based geometric morphometric analyses were used to quantify shape variation in three morphological features that may distinguish juvenile flapper skate and common blue skate: full disc shape, anterior disc margin shape, and head and rostrum shape.

All data were derived from dorsal and ventral photographs of juvenile skates captured during the 2021 Marine Institute Irish Groundfish Survey. Photographs were taken onboard with a ruler included for scale, and fin clips were collected for genetic identification. Individuals retained for analysis represent early- and mid-juvenile life stages.

Digital images were organised and randomised prior to landmark digitisation. Landmark-based geometric morphometric data were generated using anatomically homologous landmarks and, where appropriate, semi-landmarks to capture curvature along disc outlines. Semi-landmarks were digitised along defined curves with a fixed number of equidistant points and scaled using image-based reference rulers. Three morphometric datasets were produced: full disc shape (9 homologous landmarks), anterior disc margin shape (5 homologous landmarks and 32 semi-landmarks), and head and rostrum shape (7 homologous landmarks and 16 semi-landmarks).

Landmark definitions
Landmark-based geometric morphometric analyses were conducted on three morphological features: full disc (FD), anterior disc margin (ADM), and head and rostrum (HR). For each feature, anatomically homologous landmarks were defined at repeatable reference points, and semi-landmarks were used where necessary to characterise curvature along outlines.

Full Disc (FD)

The full disc analysis comprises nine homologous landmarks, positioned to capture overall disc shape and symmetry while excluding the tail:

1. Left pectoral fin insertion
2. Left posterior disc apex
3. Left disc corner
4. Left concave midpoint of the anterior disc margin
5. Tip of the snout
6. Right concave midpoint of the anterior disc margin
7. Right disc corner
8. Right posterior disc apex
9. Right pectoral fin insertion

These landmarks define disc width, anterior concavity, posterior disc extent, and snout position.

Anterior Disc Margin (ADM)

The anterior disc margin analysis includes five homologous landmarks and 32 semi-landmarks describing curvature between homologous points:

Homologous landmarks:

1. Left disc corner
2. Left concave midpoint of the anterior disc margin
3. Tip of the snout
4. Right concave midpoint of the anterior disc margin
5. Right disc corner

Semi-landmarks (32 points):

Semi-landmarks were digitised along the anterior disc outline between the left and right disc corners, passing through the snout region. These points were placed at fixed, equidistant intervals along a traced curve to quantify variation in anterior disc curvature.

Head and Rostrum (HR)

The head and rostrum analysis includes seven homologous landmarks and 16 semi-landmarks, capturing cranial and rostral morphology:

Homologous landmarks:

1. Left anterior margin of the spiracle
2. Left orbit centre
3. Left base of the rostrum
4. Tip of the snout
5. Right base of the rostrum
6. Right orbit centre
7. Right anterior margin of the spiracle

Semi-landmarks (16 points):

Semi-landmarks were placed along the lateral margins of the rostrum and head between the left and right rostrum bases, capturing rostral width, taper, and curvature.

Data Availability

Raw landmark coordinates for each feature are provided in TPS format, preserving the original digitisation structure. 

Files and variables

Data files

File: main_script.R

Description:
The script imports TPS digital landmark files for three morphological features (full disc, anterior disc margin, and head and rostrum), performs Generalised Procrustes Analysis (GPA), generates principal component analyses (PCA), and tests species effects on multivariate shape variation using Procrustes ANOVA. The effects of log-transformed centroid size and sex on shape variation are also assessed. Canonical variate analysis (CVA) is performed on retained principal component scores to evaluate species discrimination, with cross-validation metrics calculated to assess classification performance. Deformation vector plots and shape visualisations are generated to illustrate morphological differences between species. The script also analyses ventral coloration data, testing interspecific differences in coloration extent and greyscale intensity and examining relationships between coloration metrics and body length. Outputs include figures and statistical results published in the manuscript.

File: metadata_full.csv

Description:
CSV file listing metadata for all samples used in the study.

Variables:

• length: Total length (cm) of sample
• sex: Biological sex of sample
• species: Species of sample, confirmed with molecular barcoding. The COI sequences are available in GenBank under accession numbers PZ664735 - PZ664819.

File: banding_data.csv

Description:
Image-derived measurements quantifying ventral coloration along the lateral disc margins of juvenile skates.

Variables:

• ID: Unique specimen identifier
• area_body: Area of the measured ventral disc region (pixels)
• area_band: Area of the ventral coloration band (pixels)
• per_band: Ventral coloration area expressed as a percentage of disc area
• mean_grey_body: Mean greyscale value of the ventral disc region
• mean_grey_band: Mean greyscale value of the ventral coloration band
• per_dif_grey: Difference in greyscale values between disc and coloration band

note: dashes (-) in the dataset represent null values where no measurement was taken.

File: FBODY.tps

Description:
Raw landmark coordinate file in TPS format for the full body geometric morphometric analysis, including anatomically homologous landmarks and semi-landmarks digitised from dorsal photographs.

File: ADM.tps

Description:
Raw landmark coordinate file in TPS format for the anterior disc margin geometric morphometric analysis, including anatomically homologous landmarks and semi-landmarks digitised from dorsal photographs.

File: RS.tps

Description:
Raw landmark coordinate file in TPS format for the head and rostrum geometric morphometric analysis, including anatomically homologous landmarks and semi-landmarks digitised from dorsal photographs.

Notes on reuse

All files share a common specimen identifier (ID) to enable linkage across datasets. The repository includes raw landmark coordinates , allowing full reproducibility of the original morphometric analyses and comparative studies of skate morphology and coloration.

Code / software

All data files can be viewed using standard spreadsheet software capable of opening CSV files (e.g. LibreOffice Calc) and text editors for TPS files. Geometric morphometric landmark files in TPS format can be opened and analysed using tpsDig2 and tpsUtil (Rohlf), or imported into MorphoJ.

Geometric morphometric analyses and figure generation were conducted in R (version 3.6.2 or later) using RStudio (v2025.11, Posit). The primary analysis script (Main_script.R) reproduces the statistical analyses and visualisations presented in the study. The script imports TPS landmark files and associated metadata, performs Generalised Procrustes Analysis (GPA), principal component analysis (PCA), and Procrustes ANOVA to test effects of species, log-transformed centroid size, and sex on shape variation. Canonical variate analysis (CVA) is then performed on retained principal component scores to assess species discrimination, including leave-one-out cross-validation, CV1 score visualisation, and calculation of principal component contributions to the canonical axis. The script also generates deformation vector plots illustrating species-level differences in mean shape and shape variation along the first canonical variate axis.

Ventral colouration analyses are performed using extracted image-based measurements of ventral banding characteristics. The script tests species differences in colouration metrics and evaluates relationships between ventral banding extent and body length.

The following R packages were used:

• geomorph – geometric morphometric analyses, including Generalised Procrustes Analysis, PCA, Procrustes ANOVA, and shape visualisation
• MASS – linear discriminant analysis (LDA)/canonical variate analysis (CVA)
• caret – cross-validation performance metrics and classification statistics
• ggplot2 – data visualisation and figure generation
• dplyr – data manipulation and processing
• ggpubr – figure arrangement and export
• sf – spatial data handling (if required)Access information

Other publicly accessible locations of the data:

• Not applicable

Data was derived from the following sources:

• Not applicable