Predicting body mass in Ruminantia using postcranial measurements

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 r..., This dataset was collected by taking linear measurements on postcranial bones in museum collections. The data has been processed using R scripts., , 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 postcrani...