Biology subjects

Toyama, K. S.

Publications and source records attributed to Toyama, K. S..

3 recordsLinked to original sources

bioRxiv2023

JNplots: an R package to visualize outputs from the Johnson-Neyman technique for categorical and continuous moderators, including options for phylogenetic regressions.

The analysis of two-way interactions in linear models is common in the fields of ecology and evolution, being often present in allometric, macroevolutionary, and experimental studies, among others. However, the interpretation of significant interactions can be incomplete when limited to the examination of model coefficients and significance tests. The Johnson-Neyman technique represents a step forward in the interpretation of significant two-way interactions, allowing the user to examine how changes in the moderator variable, it being categorical or continuous, affect the significance of the relationship between the dependent variable and the predictor. Despite its implementation in several software since its initial development, the available options to perform the method lack certain functionality aspects, including the visualization of regions of non-significance when the moderator is categorical, the implementation of phylogenetic corrections, and more intuitive graphical outputs. Here I present the R package JNplots, which aims to fill gaps left by previous software regarding the calculation and visualization of regions of non-significance when fitting two-way interaction models. JNplots includes two basic functions which allow the user to investigate different types of interaction models, including cases where the moderator variable is categorical or continuous. The user can also specify whether the model to explore should be phylogenetically informed and choose a particular phylogenetic correlation structure to be used. Finally, the functions of JNplots produce plots that are largely customizable and allow a more intuitive interpretation of the interaction term. Here I provide a walkthrough on the use of JNplots using three different examples based on empirical data, each representing a different common scenario in which the package can be useful. Additionally, I present the different customization options for the graphical outputs of JNplots.

evolutionary biology↗

bioRxiv2022

Bergmann's rule in Microlophus lizards: testing for latitudinal and climatic gradients of body size.

Broadscale environmental gradients exert selection pressures that can result in macroevolutionary patterns of phenotypic diversity. Bergmanns rule, one of the most studied ecogeographical patterns, states that among related species or populations, larger body sizes should occur at higher latitudes or colder climates given the efficacy of larger sizes to conserve heat. However, there is still much debate regarding the mechanisms that underlie the rule and whether they should be different between endotherms and ectotherms. Here we test for Bergmanns rule in Microlophus lizards, a genus distributed in western South America and the Galapagos Islands, and test for associations between body size and climatic variables. Our results indicate that mainland Microlophus species follow Bergmanns rule, meaning that larger species are found towards the southernmost latitudes encompassed by the genus distribution. This relationship was similar for males and females, suggesting that patterns of sexual size dimorphism are not driven by differing latitudinal gradients of body size between the sexes. We identified negative associations between body size and temperature, precipitation, and isothermality, meaning that larger species are found in colder, drier, and more thermally variable environments. We discuss the possible mechanisms behind this pattern, the implications of insularity and ecology for the evolution of body size in this genus, and emphasize the need for additional natural history information to allow for the elucidation of the mechanisms behind the patterns presented in this work.

evolutionary biology↗

bioRxiv2021

A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree

Numerous questions in phylogenetic comparative biology revolve around the correlated evolution of two or more phenotypic traits on a phylogeny. In many cases, it may be sufficient to assume a constant value for the evolutionary correlation between characters across all the clades and branches of the tree. Under other circumstances, however, it is desirable or necessary to account for the possibility that the evolutionary correlation differs through time or in different sections of the phylogeny. Here, we present a method designed to fit a hierarchical series of models for heterogeneity in the evolutionary rates and correlation of two quantitative traits on a phylogenetic tree. We apply the method to two datasets: one for different attributes of the buccal morphology in sunfishes (Centrarchidae); and a second for overall body length and relative body depth in rock- and non-rock-dwelling South American iguanian lizards. We also examine the performance of the method for parameter estimation and model selection using a small set of numerical simulations.

evolutionary biology↗