DOI: 10.5061/dryad.rv15dv4dx
title: Data from: Blouch: Bayesian linear Ornstein-Uhlenbeck models for comparative hypotheses

description: Relationships among species in the tree of life can complicate comparative
 methods and testing adaptive hypotheses. Models based on the
 Ornstein-Uhlenbeck process permit hypotheses about adaptation to be tested
 by allowing traits to either evolve towards fixed adaptive optima (e.g.,
 regimes or niches) or track continuously changing optima that can be
 influenced by other traits. These models allow estimation of the effects
 of both adaptation and phylogenetic inertia – resistance to adaptation due
 to any source – on trait evolution, an approach known as the
 “adaptation-inertia” framework. However, previous applications of this
 framework, and most approaches suggested to deal with the issue of species
 non-independence, are based on a maximum likelihood approach and thus it
 is difficult to include information based on prior biological knowledge in
 the analysis, which can affect resulting inferences. Here I present
 Blouch, (Bayesian Linear Ornstein-Uhlenbeck Models for Comparative
 Hypotheses), which fits allometric and adaptive models of continuous trait
 evolution in a Bayesian framework based on fixed or continuous predictors
 and incorporates measurement error. I first briefly discuss the models
 implemented in Blouch, and then the new applications for these models
 provided by a Bayesian framework. This includes the advantages of
 assigning biologically meaningful priors when compared to non-Bayesian
 approaches, allowing for varying effects (intercepts and slopes), and
 multilevel modeling. Validations on simulated data show good performance
 in recovering the true evolutionary parameters for all models. To
 demonstrate the workflow of Blouch on an empirical dataset, I test the
 hypothesis that the relatively larger antlers of larger bodied deer are
 the result of more intense sexual selection that comes along with their
 tendency to live in larger breeding groups. While results show that larger
 bodied deer that live in larger breeding groups have relatively larger
 antlers, deer living in the smallest groups appear to have a different and
 steeper scaling pattern of antler size to body size than other groups.
 These results are contrary to previous findings and may argue that a
 different type of sexual selection or other selective pressures govern
 optimum antler size in the smallest breeding groups.
description: Tsuboi et al. (2024) collected an expansive dataset on antler
 size and body size and generated a new Cervidae phylogeny. I supplemented
 this dataset with data on Cervidae breeding group size from Plard et al.
 (2011) and Clutton-Brock et al. (1980).
description: # Supplementary Materials associated with Grabowski (in press) - Blouch:
 Bayesian Linear Ornstein-Uhlenbeck Models for Comparative Hypotheses These
 datasets are used in the empirical example from Grabowski (in press). They
 are taken from Tsuboi et al. (2024), who collected an expansive dataset on
 Cervidae antler size and body size and generated a new Cervidae phylogeny.
 This dataset was supplemented with data on Cervidae breeding group size
 from Plard et al. (2011) and Clutton-Brock et al. (1980). The PDF file is
 the complete supplementary materials from Grabowski (in press).
 **Description of the data and file structure** *
  Blouch_empirical_dataset.xlsx - Data includes a Microsoft Excel file with
 complete empirical example data associated with Grabowski (in press). This
 is broken down into Cervidae species information for natural logged antler
 volume (log_ant_vol) in liters, natural logged posterior skull length
 (log_psl) in centimeters, standard deviation of logged antler volume
 (log_ant_vol_sd) in liters, standard deviation of logged posterior skull
 length (log_psl_sd) in centimeters, estimated variance of logged posterior
 skull length (log_psl_var_est) in units of squared trait units following
 procedure outlined in Grabowski et al. (2016), estimated variance of
 logged antler volume (log_vol_var_est) in units of squared trait units
 following procedure outlined in Grabowski et al. (2016), and breeding
 group size (BGS) data following the same format as Plard et al. (2011) and
 derived from Plard et al. (2011) and Clutton-Brock et al. (1980). NA:
 Missing antler data follows Tsuboi et al. (2024), while missing BGS data
 was not recorded in the original datasets. * cervidae_renamed.tre -
 phylogeny in NEXUS format matching empirical example data. - Supplementary
 Materials.pdf - Supplementary text, figures, and tables corresponding to
 main article text. * Blouch Validation and Model Checking.pdf - Blouch
 validation and model checking results. **Dataset citation:** Grabowski M.
 (in press) Blouch: Bayesian Linear Ornstein-Uhlenbeck Models for
 Comparative Hypotheses.