Correlated evolution between repertoire size and song plasticity predicts that sexual selection on song promotes open-ended learning

Some oscine songbird species modify their songs throughout their lives (‘adult song plasticity’ or ‘open-ended learning’), while others crystallize their songs around sexual maturity. It remains unknown whether the strength of sexual selection on song characteristics, such as repertoire size, affects adult song plasticity, or whether adult song plasticity affects song evolution. Here, we compiled data about song plasticity, song characteristics, and mating system and then examined evolutionary interactions between these traits. Across 67 species, we found that lineages with adult song plasticity show directional evolution toward increased syllable and song repertoires, while several other song characteristics evolved faster, but in a non-directional manner. Song plasticity appears to drive bi-directional transitions between monogamous and polygynous social mating systems. Notably, our analysis of correlated evolution suggests that extreme syllable and song repertoire sizes drive the evolution of adult song plasticity or stability, providing novel evidence that sexual selection may indirectly influence open- versus closed-ended learning.


Sample-size estimation
• You should state whether an appropriate sample size was computed when the study was being designed • You should state the statistical method of sample size computation and any required assumptions • If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
• You should report how often each experiment was performed • You should include a definition of biological versus technical replication • The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates • If you encountered any outliers, you should describe how these were handled • Criteria for exclusion/inclusion of data should be clearly stated • High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: This study includes computational phylogenetic analyses, so no individual subjects were sampled for this study.
Since this is a computational analysis, biological and technical replicates do not apply. We do resampling and jackknife tests, which are described in the Methods and Results section. Our criteria for inclusion/exclusion of data is described in the Methods section, and all data are available in the Supplementary information.

Statistical reporting
• Statistical analysis methods should be described and justified • Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) • For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) • Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
• Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied • Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") • We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table • Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table • Include model definition files including the full list of parameters used • Include code used for data analysis (e.g., R, MatLab) • Avoid stating that data files are "available upon request" Please indicate the figures or tables for which source data files have been provided: All statistics are reported in Results and figure legends, with sample sizes and exact p-values provided. Raw results from our computational analysis are shown in scatter plots next to summary plots (box plots, arrow diagrams, etc.) We state how samples were assigned to our two groups (song plasticity and song stability) and we performed a jackknife resampling of the analyses with each sample reassigned to the other group. This information is found in Methods, Results, and Supplementary information.
We have uploaded all source data and code with our submission.