DOI: 10.5061/dryad.05qfttfh8
title: Integrating multiple field measurements in a Bayesian parallel regression framework to estimate Tasmanian devil age

description: Understanding age structure in populations is foundational for ecological
 study. Yet ascertaining the age of individuals in the wild can be
 problematic. Methods typically rely on the prior determination of a
 relationship between age and some morphological measurement specific to
 the species or animal group under investigation. We present a novel method
 to incorporate multiple measures of animal size and development to
 estimate age, using Bayesian parallel regression to integrate multiple
 regression relationships into predictions. We apply the method to
 Tasmanian devils, a carnivorous marsupial that is threatened by a
 transmissible cancer. We estimate devil age based on measures of mass,
 head width, canine over-eruption and molar characteristics. This dataset
 includes data required to run and test code. See published article for
 full methodology.
description: # Integrating multiple field measurements in a Bayesian parallel
 regression framework to estimate Tasmanian devil age Dataset DOI:
 [10.5061/dryad.05qfttfh8](https://doi.org/10.5061/dryad.05qfttfh8) ##
 Description of the data and file structure This dataset constituted 2,448
 capture events of 1,119 unique Tasmanian devils.  Six were caught more
 than ten times, while 93 individuals were caught more than five times, and
 653 individuals were captured only once.  On each capture, a range of
 morphometric and dental records were collected, providing a suite of
 measurements that relate to growth and age. Dataset is for use in the R
 Language and Environment for Statistical Computing. Variables are
 described below: dN - number of data records (2,448 captures) dCount -
 number of individuals (1,119 devils) dIndex - links each individual to
 their capture records for multiple captures dCaptDate - capture dates in
 continuous time (days) dMass - devil mass (kgs) dSex - devil gender (coded
 as dSex == 1 for males, dSex == 2 for females) dHead - devil head width
 (mm) dTD - devil canine overeruption (mm) dM2 - 2nd molar wear (Molar wear
 was scored from 0 to 5 in the field, where 0 indicates no damage, 1 the
 tip has been worn, 2 that some dentine is visible, 3 that the cusps are
 identical, 4 that just half or less of the tooth is present, and 5 that
 the tooth is worn flat to the gum. For the purposes of modelling, all
 scores were incremented by one (thus ranging 1-6).  Any missing data were
 grouped using a seventh dummy score.) dE4 - 4th molar eruption (molar
 eruption is scored from 0 to 3, such that 0 indicates the tooth is still
 below the gum, 1 indicates the first cusp is exposed, 2 that two cusps are
 exposed, and three that the tooth has fully erupted. For modelling, all
 scores were incremented by one (thus scores range from 1-4). Any missing
 data were grouped using a fifth dummy score.) ### Files and variables ####
 File:
 20240828_Data_for_Kerlin_et_al_Integrating_multiple_field_measurements_to_predict_Tasmanian_devil_age.Rdata **Description:** R data file containing data for running model as described in the paper ## Code/software Code has been provided in the Supplementary Info for the manuscript. All modelling was conducted using the JAGS program (Plummer 2003) and R 4.0.2 (R Core Team 2020). Plummer, M. (2003) JAGS: a program for analysis of Bayesian graphical models using Gibbs sampling. *Proceedings of the 3rd International Workshop on Distributed Statistical Computing*, pp. 611. Vienna, Austria. R Core Team (2020) R: A language and environment for statistical computing. *R Foundation for Statistical Computing*. Vienna, Austria.