PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses

Abstract One of the main limitations of phylogenetic comparative analyses is that associations between traits can only be interpreted as correlations. Here, we present a novel Bayesian structural equation model (PhyBaSE) which allows us to disentangle direct from indirect relationships among variabl...

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Main Authors: Achaz vonHardenberg, Alejandro Gonzalez‐Voyer
Format: Article
Language:English
Published: Wiley 2025-06-01
Series:Methods in Ecology and Evolution
Subjects:
Online Access:https://doi.org/10.1111/2041-210X.70044
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author Achaz vonHardenberg
Alejandro Gonzalez‐Voyer
author_facet Achaz vonHardenberg
Alejandro Gonzalez‐Voyer
author_sort Achaz vonHardenberg
collection DOAJ
description Abstract One of the main limitations of phylogenetic comparative analyses is that associations between traits can only be interpreted as correlations. Here, we present a novel Bayesian structural equation model (PhyBaSE) which allows us to disentangle direct from indirect relationships among variables to propose potential causal hypotheses while accounting for phylogenetic non‐independence. Compared with the existing maximum‐likelihood based approach, PhyBaSE models are more flexible, allowing the inclusion of trait and phylogenetic uncertainty, as well as non‐continuous variables. To facilitate the application of the method, we provide worked examples, data and code. We exemplify the method both with simulated as well as empirical data. Our analyses with simulated data indicate that PhyBaSE models have higher power than classic Phylogenetic Path Analysis to discriminate between competing models. As an example of PhyBaSE using empirical data, we revisit different hypotheses proposed to explain the relationship between relative brain size and group size in Bovids. Our results challenge the previously supported social brain hypothesis and provide support for an allometric effect of body size on social group size and an effect of brain size on life span, as predicted by the cognitive buffer hypothesis. The flexibility of PhyBaSE models will allow researchers to explore more complex hypotheses on the evolution of behavioural, ecological and life history traits at a macroevolutionary level and how these are linked to anthropogenic drivers of biodiversity loss and extinction, taking full advantage of the increasing number of publicly available species‐specific datasets.
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spelling doaj-art-41644b99420a4e80b6a49e4e1d2dee542025-08-20T03:28:06ZengWileyMethods in Ecology and Evolution2041-210X2025-06-011661136114810.1111/2041-210X.70044PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analysesAchaz vonHardenberg0Alejandro Gonzalez‐Voyer1Department of Earth and Environmental Sciences University of Pavia Pavia ItalyInstituto de Ecología, Universidad Nacional Autónoma de México Ciudad de México MexicoAbstract One of the main limitations of phylogenetic comparative analyses is that associations between traits can only be interpreted as correlations. Here, we present a novel Bayesian structural equation model (PhyBaSE) which allows us to disentangle direct from indirect relationships among variables to propose potential causal hypotheses while accounting for phylogenetic non‐independence. Compared with the existing maximum‐likelihood based approach, PhyBaSE models are more flexible, allowing the inclusion of trait and phylogenetic uncertainty, as well as non‐continuous variables. To facilitate the application of the method, we provide worked examples, data and code. We exemplify the method both with simulated as well as empirical data. Our analyses with simulated data indicate that PhyBaSE models have higher power than classic Phylogenetic Path Analysis to discriminate between competing models. As an example of PhyBaSE using empirical data, we revisit different hypotheses proposed to explain the relationship between relative brain size and group size in Bovids. Our results challenge the previously supported social brain hypothesis and provide support for an allometric effect of body size on social group size and an effect of brain size on life span, as predicted by the cognitive buffer hypothesis. The flexibility of PhyBaSE models will allow researchers to explore more complex hypotheses on the evolution of behavioural, ecological and life history traits at a macroevolutionary level and how these are linked to anthropogenic drivers of biodiversity loss and extinction, taking full advantage of the increasing number of publicly available species‐specific datasets.https://doi.org/10.1111/2041-210X.70044Bayesian statisticscausal inferencepath analysisphylogenetic comparative methodsstructural equation models
spellingShingle Achaz vonHardenberg
Alejandro Gonzalez‐Voyer
PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
Methods in Ecology and Evolution
Bayesian statistics
causal inference
path analysis
phylogenetic comparative methods
structural equation models
title PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
title_full PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
title_fullStr PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
title_full_unstemmed PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
title_short PhyBaSE: A Bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
title_sort phybase a bayesian structural equation model approach to causal inference in phylogenetic comparative analyses
topic Bayesian statistics
causal inference
path analysis
phylogenetic comparative methods
structural equation models
url https://doi.org/10.1111/2041-210X.70044
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