DOI: 10.5061/dryad.905qfttj4
title: Inferring the effect of species interactions on trait evolution

description: Models of trait evolution form an important part of macroevolutionary
 biology. The Brownian motion model and Ornstein-Uhlenbeck models have
 become classic (null) models of character evolution, in which species
 evolve independently. Recently, models incorporating species interactions
 have been developed, particularly involving competition where abiotic
 factors pull species toward an optimal trait value and competitive
 interactions drive the trait values apart. However, these models assume a
 fitness function rather than derive it from population dynamics and they
 do not consider dynamics of the trait variance. Here we develop a general
 coherent trait evolution framework where the fitness function is based on
 a model of population dynamics, and therefore it can, in principle,
 accommodate any type of species interaction. We illustrate our framework
 with a model of abundance-dependent competitive interactions against a
 macroevolutionary background encoded in a phylogenetic tree. We develop an
 inference tool based on Approximate Bayesian Computation and test it on
 simulated data (of traits at the tips). We find that inference performs
 well when the diversity predicted by the parameters equals the number of
 species in the phylogeny. We then fit the model to empirical data of
 baleen whale body lengths, using three different summary statistics, and
 compare it to a model without population dynamics and a model where
 competition depends on the total metabolic rate of the competitors. We
 show that the unweighted model performs best for the least informative
 summary statistic, while the model with competition weighted by the total
 metabolic rate fits the data slightly better than the other two models for
 the two more informative summary statistics. Regardless of the summary
 statistic used, the three models substantially differ in their predictions
 of the abundance distribution. Therefore, data on abundance distributions
 will allow us to better distinguish the models from one another, and infer
 the nature of species interactions. Thus our framework provides a
 conceptual approach to reveal species interactions underlying trait
 evolution and identifies the data needed to do so in practice.
description: The derivation of the model is
 in Supplementary_material_of_Inferring_the_effect_of_species_interactions_on_trait_evolution.pdf in the attachments.
description: Supplementary results Figures S2-S16. Trait
 trees under different parameter combinations of Scenarios 1, 2, 3 under
 the AWC model and the UWC model for the tree values of scaling parameters,
 s=100,1000,10000. For the figures of the rest of the secenarios, they are
 stored in the folder “abundance_test.” Figures S17-S18.
 Trait trees under different parameter combinations of different
 scenarios. Figures S19-S21. Prediction of the abundance
 distribution versus body length across 1000 simulations using the
 estimated parameters for Scenarios 1-3. For the figures of the rest of the
 scenarios, they are stored in the folder “PredictionDis.”
 Figures S22-S24. Predictions of the trait variance distribution
 across 100 simulations using the estimated parameters for Scenarios 1-3.
 For the figures of the rest of the scenarios, they are stored in the
 folder “PredictionDis.” Figures S25-S27. Comparison of
 the parameter estimates for those generating parameters for which the
 ratio \frac{\sqrt{\alpha/\gamma}}{\text{Richness}} is in the range of
 (0.5,1.5). The figures of other scenarios are stored in the folder
 “Estimation.” Figures S28-S58. Comparison of the
 estimates among different scenarios. Figures S59-S60.
 Parameter estimates under PICs and UMTD+PICs for the AWC model on the
 logtransformed body length. Figures S61-S63. Parameter
 estimates under SMTD, PICs and UMTD+PICs for the AWC model on the
 untransformed body length. Figures S64-S66. Results of
 the model comparison analysis on the untransformed body length.
 Figures S67-S69. Results of the model comparison analysis on the
 logtransformed body length. Figure S70. Abundance
 distributions of the AWC and MWC models. Figure S71.
 Trait variance distributions of the AWC and MWC models.
 Figures S72-74. Distribution of the goodness-of-fit of the three
 models using three summary statistics. The red dashed line represents the
 5% best GOF-values. Figure S75. The predicted contrasts
 using the estimated parameters under the three models and the true
 contrasts for PICs. Figure S76. The predicted contrasts
 using the estimated parameters under the three models and the true
 contrasts for UMTD+PICs. Phylogenetic tree data for
 Scenarios 1-22. They are stored in the folder “SimTreeInfo” and indexed
 accordingly. All the data of generated trees used in
 the simulation study (Scenarios 1-22) are stored in the folder
 “SimTreeInfo.” The inference results of the simulation
 study are stored in the folder “SimEstResults.” The
 baleen whale data and results are stored in the folder
 “BaleenWhaleData&Results.”