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Comparative Phylogenetic Comparisons of Tyrannus OTU Morphometrics

Author: Maggie P. MacPherson

Copyright: This documentation is available under a Creative Commons licence

Modification History

Purpose

Prepare a phylogeny composed of all currently recognized Tyrannus subspecies with which to conduct comparative phylogenetic principal components analyses and phylogenetic ANOVA to assess morphological patterns across migratory, partially migratory, and sedentary lineages.

Preliminary Steps (not shown)

1. Download the Harvey et al. 2021 suboscine UCE phylogeny here

2. Extract the Tyrannus genus. This is the MacPherson_Tyrannus_base.tre file that is used in Step 1, below.

Steps:

1. Follow the 1_Tyrannus_phylogeny.R script to add in additional Tyrannus subspecies not present in the Harvey et al. 2021 UCE phylogeny.

This creates the Tyrannus_phylogeny.tre file used in subsequent comparative phylogenetic analyses.

2. Follow the 2_morphometric_data_processing.R script to process measurements from voucher specimens into the formats needed for comparative phylogenetic analyses.

This code requires the following files as inputs: Tyrannus_voucher_table.csv Tyrannus_phylogeny.tre (used to match OTU names in phylogeny to their names in the voucher table), and Tyrannus_subspecies_MigrationStrategies.csv (a list of OTUs and their assignment as migratory, partially migratory or sedentary).

This code creates the following files as outputs: Tyrannus morphology data.csv (morphometrics for all individuals along with names that match up with the names on the phylogeny), morphology_summary_table.csv (the mean ± standard deviation and sample size of each morphometric for each OTU), Tyrannus_data.csv (the mean morphometric measurement for each OTU with names that match the names in the phylogeny and movement behaviour), and cv_summary_table.csv (the coefficient of variation for each morphometric for each OTU with names that match the names in the phylogeny and movement behaviour).

3. Follow the 3_phylogenetic_PCA.R script to conduct phylogenetic principal components analysis of bill and feather morphometrics, and build a figure showing the phylogeny, ancestral state reconstruction of movement ecology and Bill PPC2, and PPCA plots for bills and 2 PPCA plots for feathers (one with all individuals, and one zoomed in to see the trend excluding most of the individuals from long-tailed OTUs).

This code requires the following file as inputs: Tyrannus_data.csv, Tyrannus_phylogeny.tre, Tyrannus morphology data.csv, cv_summary_table.csv, Tyrannus morphology + PCA avg.csv (made during this part of the pipeline and used for th ancestral state reconstruction for the figure), and Tyrannus_subspecies_MigrationStrategies.csv.

This code creates the following files as outputs: Tyrannus morphology + PCA avg.csv, cv_summary.csv, Tyrannus_phylogenetic_PCA.png.

4. Follow the 4_phyloANOVA.R script to conduct the appropriate phylogenetic ANOVAs for each part of the dataset: morphometrics while accounting for body size (using tarsus length), PPCA scores, and coefficients of variation.

This code requires the following files as inputs: Tyrannus_phylogeny.tre, Tyrannus morphology + PCA avg.csv, and cv_summary.csv.

This code creates the following code as outputs: phylANOVA_output.txt, phylANOVA_output_PCscores.txt, phylANOVA_cv_output.txt, and phylANOVA_tarsus-corrected_residuals.csv (used to build boxplots in Boxplots_Figures.R).

Also included:

1. An .R script to produce our boxplot figures here.

2. An .R script to assess age and sex class influences on mean morphometric values here.

Other things to note before diving right in to using this code:

1. The .R scripts are all set up so that new runs save outputs to the source folder. All files created by the author are found in the Output Files folder.

2. Code to make separate output files, conduct separate analyses and create separate figures for females and males are commented out in the .R script files. Follow the instructions in each .R script to exchange lines of code with the sex-specific lines of code for analyses looking at sexes separately.

Enjoy!

Sincerely,

Maggie

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