DOI: 10.5061/dryad.fqz612jzn
title: Data from: Foraging predicts the evolution of warning coloration and mimicry in snakes

description: Warning coloration and Batesian mimicry are classic examples of Darwinian
 evolution, but empirical evolutionary patterns are often paradoxical. We
 test whether a new factor, trade-offs with foraging, influences the
 evolution of striking coloration by integrating genetic and ecological
 data for aposematic and mimetic snakes (Elapidae and Dipsadidae). Our
 phylogenetic comparison of a total of 432 species demonstrated that
 dramatic changes in coloration were well-predicted by the foraging
 strategy. Multiple tests consistently indicated that warning coloration
 and conspicuous mimicry were more likely to evolve in species where
 foraging costs of conspicuous appearance were relaxed by the poor vision
 of their prey or concealed habitat. Reversion to crypsis was also
 well-predicted by ecology for elapids, but not for dipsadids. In contrast
 to a theoretical prediction and general trends, snakes’ conspicuous
 coloration was correlated with secretive ecology, suggesting that a
 selection regime underlies evolutionary patterns. We also found evidence
 that mimicry of inconspicuous models (pitvipers) may have evolved in
 association with foraging demand for crypsis. These findings demonstrate
 that foraging is an important factor necessary to understand the
 evolution, persistence, and diversity of warning coloration and mimicry of
 snakes, highlighting the significance of additional selective factors in
 solving the warning coloration paradox.
description: # Data from: Foraging predicts the evolution of warning coloration and
 mimicry in snakes Recommended citation for this dataset:  Kojima, Y., Ito,
 R. K., Fukuyama, I., Ohkubo, Y., and Durso, A. M. (2024). Data from:
 Foraging predicts the evolution of warning coloration and mimicry in
 snakes. Dryad Digital
 Repository. [https://doi.org/10.5061/dryad.fqz612jzn](https://doi.org/10.5061/dryad.fqz612jzn) ## DATA OVERVIEW List of data stored in "DataFiles"  1\) Clustering 2\) Tree reconstruction 3\) Time calibration 4\) ASR 5\) Pagel's test 6\) CCT 7\) Regression 8\) Zaher et al's tree 9\) Polytomic trees 10\) Dataset List of scripts stored in "Scripts"  1\) Clustering 2\) Regression ## DESCRIPTION OF DATA ### 1) Clustering: Input and results of cluster analysis on diets * Elapidae.csv, Dipsadidae.csv: Dietary data. Each raw represents a species (see results for species name). The values are percentages. See Dataset S4 for references. * Results.xlsx: Results of the analysis ### 2) Tree reconstruction: Input/output of ML phylogenetic inference using RaxML-NG * Elapidae.fasta, Dipsadidae.fasta: DNA sequence data (see Table S1 for accession numbers) * Elapidae.fasta.part.bic, Dipsadidae.fasta.part.bic: Nucleotide substitution models selected using Modeltest-NG * Elapidae.raxml.support, Dipsadidae.raxml.support: ML phylogenetic trees ### 3) Time calibration: Input/output of divergence time estimation using MCMCtree * baseml: the directory that contains the input and output files for calculating the gradient and Hessian matrix for MCMCtree * baseml.ctl: The control file which specifies the parameter settings for baseml * Elapidae.phy, Dipsadidae.phy: Sequence data for baseml * Elapidae.tre, Dipsadidae.tre: Tree files for baseml * mcmctree: the directory that contains the input and output files for divergence time estimation * Elapidae.tre, Dipsadidae.tre: Trees with calibration data * mcmctree.ctl: the control file which contains the parameter settings for mcmctree * in.BV: Output of baseml used for mcmctree * out_usedata2.txt: Results of divergence time estimation ### 4) ASR: Input/output of ancestral state reconstruction (ASR). The directory names ‘Activity’, ‘Mode’, and ‘Type’ correspond to diel activity, foraging mode, and foraging type, respectively. * data.txt: phenotypic data. The first and second columns are abbreviated species names (the first 2 letters of genus and species names) and the trait values, respectively. See also the text, Dataset S2, S3 for coding and references * commands.txt: The command file that specifies parameters and setting * Elapidae.tre.nex, Dipsadidae.tre.nex: time-calibrated trees obtained using RaxML-NG and MCMCtree ### 5) Pagel’s test: Input/output of tests on the correlation of two binary variables using BayesTraits. The correlation between coloration and ecological traits was tested. Directories and tested ecological traits correspond as follows: 'Mode', foraging mode; 'Activity', diel activity; 'Terrestrial', terrestrial habitat; 'Fossorial' fossorial habitat; 'Aquatic', aquatic habitat; 'L_FCC', foraging type A+B; 'LM_FCC', foraging type A–C; 'General' general/anuran diet (Elapidae), general/lizard diet (Dipsadidae); 'Fish' fish diet; 'Anuran', anuran diet; 'Lizard', lizard diet; 'Snake', snake diet (Elapidae), snake/wormlizard diet (Dipsadidae); 'Wormlizard', wormlizard/caecilian diet (Elapidae), wormlizard diet (Dipsadidae); 'Mammal', mammal/bird diet; 'Invertebrate', invertebrate diet; 'Caudata' caudatan diet; 'Egg', egg diet * data.txt: Phenotypic data. See also the text, Dataset S2, S3 for coding and references * commands.txt: The command file which specifies parameters and settings * Elapidae.tre.nex, Dipsadidae.tre.nex: time-calibrated trees obtained using RaxML-NG and MCMCtree ### 6) CCT: Input and results of concentrated changes test (CCT) on the correlation of two binary variables using MacClade. The correlation between coloration and ecological traits was tested * Nexus files: tree files with phenotypic data constructed using MacClade. See the description for ‘Pagel’s test’ above for file names * Results: output of CCT analysis ### 7) Regression: The input of regression analysis to test the correlation between coloration and foraging type using generalized linear mixed models (GLMMs) * Elapidae.tre.nex, Dipsadidae.tre.nex: time-calibrated trees obtained using RaxML-NG and MCMCtree * coloration.csv: Data on coloration. The columns ‘Sp’ and ‘coloration’ contain abbreviated species names and phenotypic values, respectively. See also the text and Dataset S2 for coding and references * type.csv: Data on foraging type. The columns ‘Sp’ and ‘type’ contain abbreviated species names and phenotypic values, respectively. See also the text and Dataset S3 for coding and references * logit_M1.stan, logit_M2.stan, logit_M3.stan: Descriptions of GLMMs ### 8) Zaher et al's tree: Input/output of analyses using the phylogenetic tree of Zaher et al (2019). See above for details of the analyses * Clustering * ASR * Pagel’s test * CCT * Regression ### 9) Polytomic tree Input/output of analyses using polytomic trees * Consensus Tree * Elapidae.raxml.bootstraps, Dipsadidae.raxml.bootstraps: 2,000 trees obtained from a bootstrap sampling of RaxML-NG * ElapidaeMR.nex, DipsadidaeMR.nex: 50% consensus tree generated from the 2,000 trees * Regression: See above for details of the analyses ### 10) Dataset Supplementary datasets * Dataset S1.xlsx: DNA sequence dataset (accession numbers). * Dataset S2.xlsx: List of bold-colored species and putative pitviper-mimics * Dataset S3.xlsx: Ecological dataset * Dataset S4.xlsx: Dietary dataset * Dataset S5.xlsx: Supplementary references ## DESCRIPTION OF SCRIPTS 1\) Clustering: * clustering.Elapidae.R, clustering.Dipsadidae.R: R scripts for the cluster analysis 2\) Regression: * Elapidae.main.R, Dipsadidae.main.R: R scripts for the regression analysis