DOI: 10.5061/dryad.r2280gbrj
title: Data from: Fecundity in fossil Bryozoa: Accounting for colony fragmentation and the spatial division of reproductive labor

description: Our ability to measure evolution by natural selection in the fossil record
 is limited by the near impossibility of estimating the fecundity and thus
 relative fitness of most fossil organisms. Neocheilostome bryozoans are an
 important exception, because they have calcified larval brood chambers
 known as ovicells that provide an approximate estimate of the colony’s
 sexual fecundity. This clade has a rich fossil record dating back ~100
 million years, providing potential opportunities to observe changes in
 relative fitness and natural selection through many past intervals of
 environmental change. However, neocheilostome fossil specimens are often
 highly fragmented, and fragments are not necessarily randomized subsets of
 a colony. To make use of the majority of the neocheilostome fossil record,
 we need to test the effect colony organization has on our methods of
 inferring colony fecundity from fragmented specimens. In this study, we
 measure colony fecundity in a population of Recent neocheilostome bryozoan
 specimens of the species Parasmittina eccentrica Winston &
 Jackson, 2021, and quantify the nonrandom spatial arrangement of
 ovicells due to colony organization. We then simulate fragmenting these
 specimens and test the statistical robustness of standard methods one
 might use to reconstruct fecundity from fossil specimens. We find that
 ovicells are clustered and concentrated at mid-distances from the
 ancestrula (the oldest part of the colony). As a result, estimates of a
 colony’s fecundity from a single fragment have higher variance than would
 be expected if ovicells were randomly distributed. When estimating average
 population fecundity, observed variance among fossil fragments is a better
 estimator of sample variance than methods that assume spatial independence
 (such as a binomial distribution), especially for fragment sizes of 8 mm
 or less. While there is much to be learned about neocheilostome ovicell
 arrangement across taxa and environments, we can robustly estimate
 fecundity from small fossil fragments even in extinct neocheilostome
 species.
description: # Data from: Fecundity in fossil Bryozoa: Accounting for colony
 fragmentation and the spatial division of reproductive labor Dataset DOI:
 [10.5061/dryad.r2280gbrj](https://doi.org/10.5061/dryad.r2280gbrj) ##
 Description of the data and file structure In this study, we map the
 location of ovicells (larval brood chambers) across 27 bryozoan colonies
 in the species *Parasmittina eccentrica*. The dataset includes the 27
 colony maps and the code for quantifying the arrangement of ovicells
 across a colony. The original specimens are from the Smithsonian National
 Museum of Natural History (USNM PAL Collection # 787). The specimen
 images are available upon request from the corresponding author. ### Files
 and variables #### File: alldata_submission.RData
 **Description:** This.RData file will load everything necessary to run the
 R script (except packages) into your R Environment, so you can recreate
 all results and figures. There is no need to use the raw colony map files
 (ColonyMapFiles.zip) if you use this.RData file. **Variables** **1)**
 **Colony_distboot**: Simulated versions of the colonies with randomized
 ovicell locations X: row number Colony: Colony ID Density_distclass:
 average density of ovicells a given distance from the ancestrula distance:
 A range of distances from the ancestrula in mm (e.g. "6-8" means
 6 to 8 mm from the ancestrula) **2)** **data**: Observed data from the
 real colonies X: row number File: Colony mapping file the data come from
 Colony: Colony ID Pointtype: "A" for ancestrula, "NOV"
 for zooid without ovicell, and "OVI" for zooid with ovicell x: x
 coordinate in mm (measured from the lower left corner of the image) y: y
 coordinate in mm (measured from the lower left corner of the image)
 Parent: Parent of the Colony (if Parent is the same as Colony, then the
 Colony is said Parent) x_a: x coordinate in mm measured from the
 ancestrula  y_a: y coordinate in mm measured from the ancestrula  r:
 radius, i.e. the straight-line distance from the ancestrula to the point
 theta: angle in radians from the ancestrula to the point Zooids: total
 zooids in the colony NonOv: number of zooids without ovicells in the
 colony  Ovicells: number of zooids with ovicells in the colony Density:
 number of ovicells divided by number of zooids in the colony distance: A
 range of distances from the ancestrula in mm (e.g. "6-8" means 6
 to 8 mm from the ancestrula) Zooids_distclass: number of zooids in the
 given distance bracket from the ancestrula NonOv_distclass: number of
 zooids without ovicells in the given distance bracket from the ancestrula
 Ovicells_distclass: number of zooids with ovicells in the given distance
 bracket from the ancestrula Density_distclass: number of ovicells divided
 by number of zooids in the colony in the given distance bracket **3)
 Ov_data:** for every zooid with an ovicell, what proportion within a
 certain radius also have ovicells? X: placeholder text, each row is data
 for one ovicell in the colony V1: Colony ID V2 - V19: density of ovicells
 within a radius of this ovicell, each column is a new radius in mm, from
 0-2, 2-4, 4-6, 6-8, 8-10, 10-12, 12-14, 14-16, 16-18, 18-20, 20-22, 22-24,
 24-26, 26-28, 28-30, 30-32, 32-34, 34-36 **4) Ov_databoot**: randomized
 simulations of Ov_data, where the ** is a placeholder for a given colony
 e.g. there is Ov_databoot_Pa55 and there is Ov_databoot_Pa55M11). In each,
 the variables are: X: row number Colony: Colony ID distance_Ovi: distance
 from the ovicell in mm Density: the simulated average density of ovicells
 in that distance bracket **5) SEMsim_data:** simulated fragments of a real
 colony Colony: Colony ID SubColonyArea: The area in squared mm of the
 colony fragment SampleSize: The number of Zooids in the colony fragment,
 always 1 or greater Sim_Density: the density of ovicells on the simulated
 fragment colony_xmin: the lower x limit of the colony image in mm from the
 ancestrula  colony_xmax: the upper x limit of the colony image in mm from
 the ancestrula  colony_ymin: the lower y limit of the colony image in mm
 from the ancestrula  colony ymax: the upper y limit of the colony image in
 mm from the ancestrula  frag_x: the x coordinate of the center of the
 fragment frag_y: the y coordinate of the center of the fragment frag_r:
 the radial distance from the ancestrula to the center of the fragment
 sim_number: the iterative number of the simulation (All other data files
 starting with SEMsim_data\_  have been merged into SEMsim_data) **6)
 sim_boot:** Randomized version of SEMsim_data. All the variables are the
 same. (All other data files starting with sim_boot\_  have been merged
 into sim_boot) #### File: RCode_submission.Rmd **Description:** This R
 Markdown file includes all the code necessary to recreate the entire
 manuscript, including loading packages, importing the raw data,
 quantifying ovicell arrangement, and running the simulations. You may run
 this by loading the files in ColonyMapFiles.zip, or you can load in
 alldata_submission.RData. #### File: SpeciesID_ZooidMeasurements.xlsx
 **Description:** The specimens used in this study are from a museum
 collection, and we updated their species identification from *Parasmittina
 areolata* to *Parasmittina eccentrica*. This file includes some zooid
 measurements to support this taxonomic claim, which is just a minor note
 in the paper. ##### Variables * Colony: The official specimen ID in USNM
 PAL #787 (the Smithsonian National Museum of Natural History collection) *
 Measurement: The quantity measured in micrometers * Value: The part of the
 zooid we were measuring (orifice length, zooid width, etc.) #### File:
 ColonyMapFiles.zip **Description:** This file contains 121 .mrk.json
 files, which are colony maps containing the coordinates of ovicellate and
 non-ovicellate zooids on the 27 bryozoan colonies. These are imported by
 the R Markdown file. The colony maps were created in 3D Slicer. ####
 **Zenodo Supplement: SuppFig1.tiff** **Description:** Supplementary Figure
 1 for the affiliated manuscript. Caption: Light microscope images to
 support reclassification of study specimens from *Parasmittina areolata*
 Canu & Bassler, 1927 to P. eccentrica Winston & Jackson, 2021
 (Winston & Jackson, 2021; Farias et al., 2024). Mean Zooid Length =
 532 μm, Mean Zooid Width = 395 μm, Mean Primary Orifice Length = 114 μm,
 Mean Primary Orifice Width = 119 μm. A) Peripheral zooids have 2–3 oral
 spines (colony Pa67M157). B) Most zooids have two large elongate
 avicularia (colony Pa62M115). C) A minority of zooids have large spatulate
 avicularia (colony Pa69M113). D) Many zooids also have small avicularia
 triangular to elliptical in shape, which unlike the other two avicularia
 types do not seem to share a common location or orientation on zooids
 (colony Pa69M117). Avicularia types also appear clustered, which is worthy
 of further research. #### **Zenodo Supplement: SuppFig2.tiff**
 **Description:** Supplementary Figure 2 for the affiliated manuscript.
 Caption: The estimates and 95% confidence intervals of average population
 fecundity for a random sample of colony fragments for each of the 3
 methods (methods described in Table 1). The “true” ovicell density of each
 colony is indicated with a vertical black line. There are 500 iterations
 per method per colony, 13,500 total iterations per method. For brevity,
 this figure only depicts the estimates for the 2–4 mm size class. ####
 **Zenodo Supplement: SuppFig3.tiff** **Description:** Supplementary Figure
 3 for the affiliated manuscript. Caption: There is a significant but weak
 positive correlation between ovicell density and the number of zooids in a
 colony (R^2^ = 0.22, p = 0.009). Each point represents one of the 27
 colonies. The line is a linear regression, but the 95% confidence interval
 is too small to see (SE = 3e-5). #### Code/software The. Rmd and .RData
 files can be used to entirely recreate this study. We used RStudio Version
 2024.12.0+467 and R Version 4.4.2. The following R packages are necessary
 (which are all cited in the main article): *Morpho, geomorph, tidyverse,
 ggpubr, ggforce, ggtext, ggplot2, doParallel, foreach, and* scales.