DOI: 10.5061/dryad.70rxwdc6q
title: Data for: Novel quantification of eggshell surfaces in Dromaius novaehollandiae with implications for the fossil eggshells of Oviraptorosauria (Dinosauria)

description: The external surface of non-avian dinosaur eggs is not usually smooth like
 those of their avian descendants. Unique ornamentation patterns sculpt the
 exterior of the eggs, a trait that is difficult to interpret because of
 its scarcity in modern taxa. One avian species that does homoplastically,
 present similar external eggshell ornamentation to that of non-avian
 dinosaurs is Dromaius novaehollandiae Latham, 1790, the emu. Here we use
 D. novaehollandiae eggs in conjunction with a clutch of oviraptorosaurian
 dinosaur eggs (NCSM 33576, Macroelongatoolithus carlylei) to test new
 methods of quantifying external eggshell ornamentation. Currently, the
 only scientific language for describing and comparing ornamentation styles
 in fossil ootaxa is restricted to qualitative categorization, which
 introduces issues of subjectivity and overly broad and overlapping
 typification. In this study, we derived and tested a new statistical
 quantitative approach to quantifying ornamentation that includes two
 existing functions of the molaR package in R previously applied to shape
 quantifications of fossil teeth, and ‘Orientation’, a novel function
 presented as a proxy for ‘direction’, needed to capture directionality.
 Results demonstrate that 1) the quantitative approach provides statistical
 backing to gross qualitative observations;  2) statistically
 significant differences exist between the ornamentation in D.
 novaehollandiae and M. carlylei, particularly in terms of relief; and 3)
 intranest variation of M. carlylei can be demonstrated from harmonic mean
 p-value differences between different pairs of eggs. This method offers a
 strong platform to consolidate quantitative measures with existing
 qualitative categories, improve the diagnoses of ootaxa, and answer broad
 ecological and evolutionary questions regarding dinosaur reproduction.
 Moreover, wider application of the technique is encouraged for a
 multi-proxy quantitative analysis of any paleontological or biological
 surfaces.
description: To compare eggs, we measured morphometrics (egg length and width)
 using digital calipers. We weighed <em>D. novaehollandiae</em>
 eggs using digital scales, and calculated egg volume using the equation
 from Hoyt [45]. We digitized the eight fossil and six extant eggs using
 the application Metascan on an Apple iPhone 12 Pro, following the methods
 of Avrahami and Herzog [46]. We coupled the iPhone camera with a 15x macro
 lens and a 10 cm diameter ring light. Meshes built this way achieved
 comparable resolutions to μCT scans (mean pixel size of c. 11 microns),
 and provided a methodology that could compare <em>D.
 novaehollandiae</em> eggs with <em>M. carlylei</em> that
 could not be CT scanned at high resolution in its current nest
 configuration. These high-fidelity scans also compare favorably to other
 portable surface scanners for the relatively low relief and high detail of
 eggshell surface texture versus other paleontological surfaces. Completed
 scans were exported as .gltf files from the application, preserving all
 raw data including texture and coloration. These files were imported to
 Blender (version 3.4). Here, we subsampled the eggshell surfaces so that
 we had uniformly-sized (10mm diameter) sections that could be analyzed in
 molaR, to avoid the effects of taphonomic cracks or non-representative
 breaks on the surface of the eggs that could alter their original surface
 topography. We extracted surface sections across the eggs by adding 10 mm
 diameter cylindrical meshes through the surface and using the Boolean
 modifier to intersect cylinders with the egg surface (Fig 2A). The
 sections were exported as .stl files using the batch export feature and
 were subsequently imported into MeshLab2022.02 where they were aligned on
 the X-Y axis (i.e., with a vertical Z axis; Fig 2B) and decimated to 5000
 triangular faces using the Quadric Edge Collapse Decimation tool. To
 import these into R for molaR analysis, we exported aligned surfaces as
 .ply files. We binned the samples from each egg into one of five zones
 along the long axis of the egg, consistent with those described in [47]
 and matching eggs as they were laid in nidus. It is worth noting that this
 means Zone 1 in <em>M. carlylei</em> is the blunt end of the
 egg, and Zone 5 is the acute end, but in <em>D.
 novaehollandiae</em> Zone 1 is the acute end and Zone 5 the blunt
 end. To quantitatively analyze the topography of each
 surface, we made use of the R package molaR (version 5.3) [48]. MolaR is
 an analysis tool with a suite of functions developed initially for the 3D
 analysis of dentition, and our study represents the first use of the
 analysis beyond this scope. Each .ply mesh was analyzed using two of the
 functions existing in molaR: Dirichlet Normal Energy (DNE) [49] and Slope
 [50]. These two metrics provide proxies for surface ‘complexity’ and
 ‘relief’ respectively. We also modified the Orientation Patch Count
 function [51] to write a new function called ‘Orientation’, which analyzes
 the relative surface area of faces occupying each of the eight 45
 directional bins (Fig 2C) to calculate both the direction and strength of
 orientation (pole-to-pole along the egg long axis or around the egg short
 axis; full details below). We used pairwise, nonparametric, two-sample
 Kolmogrov-Smirnov tests to test the statistical significance of
 differences between distributions, and Welch’s two-sample T-test for mean
 differences, between the <em>D. novaehollandiae</em> eggs and
 <em>M. carlylei</em> and nests. For each metric, we used both
 full datasets and datasets averaged per egg zone to reduce the likelihood
 of sampling size bias. Mean values for DNE, Slope, and Orientation are
 reported for each zone to represent trends across the egg, as an average
 of sub-sampling within these zones that was intended only to give uniform,
 unaltered meshes. We calculated the inter-relationship of metrics using
 Pearson’s correlation coefficient. We calculated harmonic mean p-values
 [52,53] to meta-analyze the p-values found for the three metrics. We
 selected a harmonic mean over a meta-analysis like Fisher’s method [53] to
 account for the non-independence of DNE, Slope, and Orientation
 values. ‘Orientation’ is a new function in the molaR
 package [48] that draws on the existing Orientation Patch Count function
 (‘OPC’). The existing OPC function calculates the number of patches (where
 a patch is three or more triangles on a 3D mesh) that fall into each
 45-degree bin about the X-Y plane (Figure 2D). This measure alone does not
 distinguish patch count size because a patch can incorporate three
 adjoining faces but also orders of magnitude more faces, and these are
 calculated by OPC as a single patch of equal value. To account for
 directionality, we use the surface area value from the ‘Patch Details’
 output of this function, which calculates the total surface area occupied
 by faces in each bin. The function then calculates the ratio of surface
 area in the bins oriented along the long axis (bins 1, 4, 5, and 8) to
 those oriented around the short axis (bins 2, 3, 6, 7). An additional
 calculation is added to this ratio to produce a scale from -100 to +100
 that indicates both the direction (positive along the long axis; negative
 around the short axis) and strength (higher numbers correlate to stronger
 directionality) of the orientation. This function will be available in the
 next update of the molaR package. We include functions both for individual
 meshes (‘Orientation)’ and a batch export to a .csv file with the DNE and
 Slope values, for the Statistical Complexity, Orientation, and Relief of
 Eggshell (SCORE).
description: # Data for: Novel quantification of eggshell surfaces in *Dromaius
 novaehollandiae* with implications for the fossil eggshells of
 Oviraptorosauria (Dinosauria)
 [https://doi.org/10.5061/dryad.70rxwdc6q](https://doi.org/10.5061/dryad.70rxwdc6q) ## Description of the data and file structure ### Files and variables #### File: EmuOvi\_PMatrix.csv **Description:** This is the taxon or NCMNS ID number followed by each egg used (egg 1 = e1 etc.) ##### Variables * Harmonic Mean: combined mate-analysis value for DNE, Slope, and Orientation. * NCSM33576_E1: first egg of the Deep Eddy *M. carlylei* nest. * NCSM33576_E2: second egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E3: third egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E4: fourth egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E5: fifth egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E6: sixth egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E7: seventh egg of the Deep Eddy *M. carlylei* nest. * NCSM 33576_E8: eighth egg of the Deep Eddy *M. carlylei* nest. * Emu_1: first emu egg * Emu_2: second emu egg * Emu_3: third emu egg * Emu_4: fourth emu egg * Emu_5: fifth emu egg * Emu_6: sixth emu egg #### File: Emu\_Ovi\_Zones.csv **Description:** csv file with quantitative metric values for all eggs in the study organized by egg zone ##### Variables * Taxon: either emu eggs or *Macroelongatoolithus carlylei* (fossil) * Zone: refers to the egg zone in correspondence with those laid out in the methods. * Metric: one of DNE, Slope, or Orientation as calculated by molaR functions * Values: unitless measure of the value. #### File: Emu\_Ovi\_Eggs.csv **Description:** csv file with quantitative metric values for all eggs in the study ##### Variables * Taxon: either emu eggs or *Macroelongatoolithus carlylei* (fossil) * Egg: which egg the value refers to (egg numbers explained above in EmuOvi_PMatrix.csv --&gt; Variables) * Metric: one of DNE, Slope, or Orientation as calculated by molaR functions * Values: unitless measure of the value. ## Code/software * Initial three-dimensional scans of half to whole eggs are created in Metascan. This process and application require at least an iPhone 12, which is optimized with the addition of a 10 cm diameter ring light and 15 x magnification macro lens attachment. * These three-dimensional objects are exported to cloud storage as .gltf files and downloaded into Blender 3.4. * In Blender, subsections of the egg surface are extracted at a uniform size (1cm diameter) using the boolean modifier. This was repeated wherever possible on all eggs, avoiding taphonomic surface effects and overlap. Files were extracted and labelled according to the egg zone (after Simon, 2014). * Isolated subsections were exported as .stl files. * These .stl files were imported to MeshLab 2022.02. * Each subsection file was standardized to 5000 triangular faces using the quadric edge collapse decimation tool. * Each subsection file was aligned along its X-Y axis, so that the Z-axis was oriented vertically, with the eggshell surface facing up. * Each subsection file was exported as a .ply file. These were exported to a specified folder that became the working directory for R studio. * In R studio, required packages include molaR and Pracma. The working directory was set to where the .ply files were exported. * The orientation/SCORE function as provided is coded, and the batch processing of .ply files is run. Orientation will run an individual file and calculate its orientation. SCORE will batch process all .ply files in the working directory and output a .csv file with orientation, DNE, and Slope values. * Outputted values were tested in R Studio for normality using a Shapiro-Wilk test. Outliers were removed using the Inter Quartile Range. 95% confidence intervals were calculated with 1000 iterations of bootstrapping. * Differences in the distribution patterns of DNE, Slope, and Orientation were calculated by running pairwise kolmogorov-smirnov tests of the values for each egg against each other. * Values for a harmonic mean meta-analysis of eggs against each other in terms of DNE, Orientation, and Slope were run with the 'harmmean' function in Pracma.