DOI: 10.5061/dryad.8sf7m0ctf
title: Predicting body mass in Ruminantia using postcranial measurements

description: Size plays an important role in mammalian ecology. Accurate prediction of
 body mass is therefore critical for inferring aspects of ecology in
 extinct mammals. The unique digestive physiology of extant ruminant
 artiodactyls, in particular, is suggested to place constraints on their
 body mass depending on the type of food resources available. Therefore,
 reliable body mass estimates could provide insight into habitat
 preferences of extinct ruminants. While most regression equations proposed
 thus far have used craniodental predictors, which for ungulates may
 produce misleading estimates based on indirect relationships between tooth
 dimensions and size, post-cranial bones support the body and may be more
 accurate predictors of body mass. Here, I use phylogenetically informed
 bivariate and multiple regression techniques to establish predictive
 equations for body mass in 101 species of extant ruminant artiodactyls
 based on 56 post-cranial measurements. Within limb elements, stepwise
 multiple regression models were typically preferred, though bivariate
 models often received comparable support based on AIC scores. The globally
 preferred model for predicting mass is a model including both proximal and
 distal width of the humerus, though several models from the radioulna
 received comparable support. In general, widths of long bones were good
 predictors, while lengths and midshaft circumferences were not. Finally, I
 show that where the best elements for prediction are unavailable for
 fossil taxa, selection of the model with lowest perecent prediction error
 for the lowest level clade to which the fossil can be assigned could be a
 productive and novel way forward for predicting mass and subsequently
 aspects of ecology in fossil mammals.
description: This dataset was collected by taking linear measurements on
 postcranial bones in museum collections. The data has been processed using
 R scripts.
description: This document contains descriptions of each of the items involved with
 analyses for "Predicting body mass in Ruminantia using post-cranial
 measurements" * "akaike_weights_all.csv": This table is
 generated from the R.markdown file "predict_body_mass.Rmd" and
 contains AIC (Akaike's information criterion) values for all models
 compared to each other. Three values can be found: fit (the information
 score or AIC score for the model), delta (the difference between each
 model and the optimal model), and w (the Akaike weight of the model). *
 "all_ppe_species.csv": This table is generated from the
 R.markdown file "predict_body_mass.Rmd". It gives the percent
 prediction error (PPE or %PE) for each individual species by each
 regression model generated in this study to predict body mass. PPE is
 calculated using the equation: [(Observed Mass - Predicted Mass)/Predicted
 Mass] * 100. * "body_mass_data.csv": This excel file has the
 average body mass (kg) for each species and species-averaged postcranial
 linear measurements for each species. Family, subfamily, and tribe level
 information are also included. This is the file used for analyses in the
 R.markdown file "predict_body_mass.Rmd". *
 "coef_info_by_bone.csv": This table is generated from the
 R.markdown file "predict_body_mass.Rmd". It lists the model,
 which bony element it belongs to (Group), the slope, intercept and
 residual standard error (RSE) for each regression model. *
 "fossil_data.csv": This excel file has the linear measurement
 data for three fossil specimens: Aletomeryx sp. (F:AM 42883), Cosoryx
 furcatus (AMNH 51031), and Bison antiquus (AMNH 130792). Empty cells are
 intentional and mean that the measurement was not available for that
 specimen. This file is used to generate body mass estimates in the
 "predict_body_mass.Rmd" script. *
 "fossil_merge_groups.csv": This table is generated from the
 R.markdown file "predict_body_mass.Rmd" and contains the
 combined body mass estimates for each fossil based on the regressions
 created from extant data. Cells with "NA" are intentional and
 reflect missing measurement(s) that were not available for that specimen,
 so mass was unable to be estimated using that particular regression. *
 "MCC_tree.tree": This is a maximum clade credibility tree from
 Zurano et al. (2019). This time-scaled molecular phylogeny is derived from
 Bayesian inference of topology branch lengths using mitochondrial genomes
 for 206 living and recently extinct ruminant species and 21 fossil
 calibrations. It is read into "predict_body_mass.Rmd" for all
 phylogenetic analyses. * "model_info_by_bone.csv": This table is
 generated from the R.markdown file "predict_body_mass.Rmd". It
 details for each model which bony element the model is associated with
 (Group), the sample size (N), the AIC score (AIC), delta AIC (delta), and
 the Akaike weight (AICw). It also gives a lambda value (lambda), residual
 standard error (RSE), and log mean (Log.Mean.PPE), minimum (Log.Min.PPE),
 and maximum percent prediction error (Log.Max.PPE) for each regression
 model. * "predict_body_mass.Rmd": This is an R.markdown file
 containing the scripts for all analyses including bivariate regressions,
 stepwise multiple regressions, and calculation of percent prediction error
 for all regressions. First, bivariate regressions are calculated for each
 individual measurement taken across the postcranial skeleton. Then,
 stepwise multiple regressions are calculated using all measurements for
 each individual bone. Finally, stepwise multiple regressions are conducted
 with only measurements pertaining to proximal or distal regions of some
 long bones. This script also has the analyses for predicting body mass for
 the three fossil specimens named in the manuscript. *
 "raw_postcranial_measurements.csv": This .csv file contains all
 of the raw measurement data for each individual used to create a species
 average for this study. Empty cells are intentional and mean that the
 measurement was not available for that particular specimen. Images of each
 postcranial measurement can be found in Figure 2 of the manuscript.
 Descriptions of each measurement are found in Table S3 of the Supporting
 Information.