DOI: 10.5061/dryad.v6wwpzh6g
title: Data from: Genotype predicts quantitative song variety in a chickadee hybrid zone despite limited sampling

description: In the avian sub-order Passeri (the songbirds), song develops according to
 both a flexible neural template and auditory input from conspecifics,
 making innately-constrained characters of song difficult to isolate. In a
 hybridizing population of Black-capped Chickadees (Poecile atricapillus)
 and Carolina Chickadees (Poecile carolinensis), we found that genetic
 ancestry was weakly predictive of a multidimensional measure of song
 variety (a continuously distributed quantitative alternative to
 categorical song repertoire size) but did not successfully predict
 one-dimensional song variety. We used species-diagnostic autosomal markers
 to genotype 55 individuals inside and outside of the Black-capped
 Chickadee/Carolina Chickadee hybrid zone in Missouri and Kansas. Using
 active recording methods, we then obtained high-volume, high-quality song
 recordings of 10 genotyped chickadees from a single hybrid zone population
 on a small, lake-bounded peninsula in west-central Missouri. We extracted
 acoustic data from these recordings to generate measurements of song
 variety across one, two and three dimensions of multivariate acoustic
 space for each individual. We tested how well, and in what direction,
 genetic ancestry predicted song variety for each of these
 dimensionalities, after predicting that song variety would increase with
 Carolina Chickadee ancestry. Linear models predicting song variety in two
 and three dimensions from genetic ancestry ranging from carolinensis-like
 backcrosses to pure carolinensis explained 41% and 43% of the variation
 respectively, with slope values in the predicted direction. A linear model
 predicting song variety in one dimension from genetic ancestry explained
 12% of the variation. Our results are suggestive but not conclusive of
 genetic predispositions for song variety. Our findings provide support for
 the continued use of multidimensional song variety measurements and offer
 future directions for tackling the question of the genotype-song
 relationship in hybrid zones between species with vocal learning.
description: # Data from: Genotype predicts quantitative song variety in a chickadee
 hybrid zone despite limited sampling Dataset DOI:
 [10.5061/dryad.v6wwpzh6g](10.5061/dryad.v6wwpzh6g) ## Description of the
 data and file structure ### Files and variables ## Folders ####
 Sparrowfoot_Park_original_recordings.zip **Description:** This folder
 contains the recordings made at Sparrowfoot Park from which data were
 extracted in their original state. Recordings are split into folders by
 individual bird, and each folder is named with the bird's individual
 ID code used in publication and, in parentheses, an informal name with
 which it was referred to in the field. Metadata is included verbally at
 the end of each recording and embedded within the file names in the
 following format:
 `Poecile.sp_LeftColorBands.RightColorBands_Date_Locality.County.State_RecordistInitials_RecordingSequence`. All files are in `.wav` format. #### Chickadee-MS-directory.zip **Description:** This folder is the working directory for all scripts associated with this manuscript. All code used to run the analyses for this study can be reproduced using the files within. File descriptions are listed below. * **fig1songs**: Folder containing `.wav` files used to generate the spectrograms in Figure 1 * **LateAdditionSongs**: Folder containing recordings added to the dataset after the initial song measurement had been run * **ml-recordings**: Empty folder intended to house the recordings sourced from the Macaulay Library of Natural Sounds ([https://www.macaulaylibrary.org/](https://www.macaulaylibrary.org/)) used in the range-wide song analysis in Supplemental Materials. * To obtain the recordings for this subdirectory, submit a data acquisition request with the Macaulay Library ([Submit a ticket : Help Center](https://support.ebird.org/en/support/tickets/new)) with the file **ml-metadata.csv** attached clarifying that you would like to download the recordings in the `ML Catalog Number` column to reproduce analyses from this study. In a few business days, you should receive an email with a link allowing you to download a compressed `.tar` file containing all recordings and a metadata sheet that should look identical to **ml-metadata.csv.** Extract the files and move them to the **ml-recordings** folder. * **xc_recordings**: Empty folder intended to house the recordings sourced from xeno-canto ([xeno-canto.org](xeno-canto.org)) used in the range-wide song analysis in Supplemental Materials. * To obtain the recordings for this subdirectory, run the code in the first chunk of the **chickadee-ms-rangewide.Rmd** R Markdown script. This should download the necessary recordings into the **xc_recordings** folder. * **xc_ml_recordings**: Empty folder that should contain all publicly sourced recordings (from both Macaulay Library and xeno-canto). Once all of these recordings are acquired, paste them into this subdirectory before  * **Quality_check_spectros**: Empty folder into which spectrograms will be written for the visual quality check step of the hybrid zone song analysis in the main manuscript. * **rangewide_spectros**: Empty folder into which spectrograms will be written for the visual quality check step of the range-wide song analysis in the Supplemental Materials. * **redlist_species_data_BCCH**: Empty folder into which shapefiles from the IUCN Red List website may be downloaded to create the *atricapillus* portion of the range map in Figure 2. * To obtain the contents for this folder, navigate to [https://www.iucnredlist.org/species/22711716/118687681](https://www.iucnredlist.org/species/22711716/118687681) and select 'Download' &gt; 'Range data - Polygons (SHP)'. You will be asked to make an account with IUCN Red List and then to provide a description of intended data use. IUCN Red List should approve your data request shortly and you should get an email indicating as such and directing you to the 'Available downloads' page. From there, you should be able to download the necessary files for this folder. * **redlist_species_data_CACH**: Empty folder into which shapefiles from the IUCN Red List website may be downloaded to create the *carolinensis* portion of the range map in Figure 2. * To obtain the contents for this folder, navigate to [https://www.iucnredlist.org/species/22711708/94306849](https://www.iucnredlist.org/species/22711708/94306849) and select 'Download' &gt; 'Range data - Polygons (SHP)'. You will be asked to make an account with IUCN Red List and then to provide a description of intended data use. IUCN Red List should approve your data request shortly and you should get an email indicating as such and directing you to the 'Available downloads' page. From there, you should be able to download the necessary files for this folder. * **sels_ml**: Folder containing selection tables (`.txt` files) created in and exported from Raven Pro that delineate the portions of a recording that contain song (Macaulay Library recordings) * **sels_xc**: Folder containing selection tables (`.txt` files) created in and exported from Raven Pro that delineate the portions of a recording that contain song (xeno-canto recordings) * **Sparrowfoot_Park_chopped_recordings**: Folder containing `.wav` files segmented from the raw recordings in **Sparrowfoot_Park_original_recordings.zip** that each contain a single rendition of song. File names are identical to that of the raw recording from which each recording was chopped, with the addition of a timestamp indicating the start time of that song within the raw recording (e.g., 1.23 for 1 minute, 23 seconds) * **structure_11march25**: Folder containing STRUCTURE output files * **HZCH_StructureInput_100325.txt**: Text file containing the PCR-RFLP molecular marker data and relevant metadata used in the program STRUCTURE. This file has the following structure: * Row 1: Individual identifying codes for each marker, maintaining the naming system from McQuillan et al. (2017) * Row 2: Map distances (in base pairs) between the marker in the corresponding column in Row 1 and the sequentially following marker. Physically unlinked markers (those mapping to different chromosome assemblies in the *P. atricapillus* reference genome) have a value of -1.  * Rows 3-112, Column 1: Individual identifying codes for each bird in the final dataset. Each ID occupies 2 cells for the 2 alleles at each locus. * Rows 3-112, Column 2: Numeric identifiers for the broad sampling locality of the individual in the corresponding row. * `1`: Manhattan, Riley County, Kansas, USA * `2`: Lawrence, Douglas County, Kansas, USA * `3`: Lake Quivira, Johnson County, Kansas, USA * `4`: Post Oak Township, Johnson County, Missouri, USA * `5`: Butler Lake, Bates County, Missouri, USA * `6`: Clinton City Park, Henry County, Missouri, USA * `7`: Sparrowfoot Park, Henry County, Missouri, USA * `8`: Bird Song Conservation Area, St. Clair County, Missouri, USA * `9`: Valley Water Mill, Greene County, Missouri, USA * `10`: Table Rock Lake, Stone County, Missouri, USA * Rows 3-112, Columns 3-11: Numeric identifiers for alleles scored from the PCR-RFLP protocol outlined in the main manuscript, for the individual in the corresponding row and the allele in the corresponding cell of Row 1: * `1`: *atricapillus*-specific allele * `2`: *carolinensis*-specific allele * `-9`: missing data * **ml-metadata.csv**: Metadata for recordings downloaded from the Macaulay Library of Natural Sounds ([https://www.macaulaylibrary.org/](https://www.macaulaylibrary.org/)) for the range-wide song analysis in Supplemental Materials. This file is provided by email along with the requested recordings. * **xc-metadata.csv**: Metadata for recordings sourced from [xeno-canto.org](xeno-canto.org) for the range-wide song analysis in Supplemental Materials. This file is automatically downloaded  * **structure_data_localities.csv**: STRUCTURE output data for each individual combined with sampling locality data. Column header definitions are as follows * `ind_num`: Individual identifying codes for each bird in the final dataset. * `pop_ID`: Numeric identifiers for the broad sampling locality of the individual in the corresponding row, following the same numbering scheme as **HZCH_StructureInput_100325.txt** * `prob_BC`: Probability of assignment to the *atricapillus*-like population cluster generated by STRUCTURE * `prob_CA`: Probability of assignment to the *carolinensis*-like population cluster generated by STRUCTURE * `species_range`: Identifies the range assignment of the individual in the corresponding row. * `BC`: *atricapillus* * `CA`: *carolinensis* * `HZ`: hybrid zone * **structure_data_localities_latlong.csv**: **structure_data_localities.csv** with the addition of latitude and longitude for each sampling locality. File structure is identical to **structure_data_localities_latlong.csv** except for the addition of `latitude` and `longitude` columns (in decimal degrees). * **PCR-RFLP_data_11april2025.csv**: PCR-RFLP and sampling locality data for each individual. Column header definitions are as follows: * `Ind`: Individual identifying codes for each bird in the final dataset. * `Pop`: Identifies the range assignment of the individual in the corresponding row. * `BC`: *atricapillus* * `CA`: *carolinensis* * `HZ_HENMO`: hybrid zone * Headers 3-20: Individual identifying codes for each marker, maintaining the naming system from McQuillan et al. (2017). Columns for each of the two alleles at each locus are named as such: * Allele 1: `c0p###` * Allele 2: `c0p###_2` #### Chickadee-MS-output.zip **Description:** This folder contains all of the output files of the scripts in this repository. These can be cross-checked with files written out from the R scripts in the main directory. File descriptions are below. * `.png` files with the naming structure **figure#_[figure-description].png** are the figures in the main manuscript. - `.png` files with the naming structure **figureS#_[figure-description].png** are the figures in the supplementary materials file. * `.txt` files with the naming structure **table#_[table-description].txt** are the tables in the main manuscript. - `.txt` files with the naming structure **tableS#_[table-description].txt** are the tables in the main supplementary materials file. - `.txt` files with the naming structure **[one,two,three]D_[lm,qm]_coef.txt** are tables of model coefficients concatenated to make the regression table in Table S7. * The first part of the file name defines the dimensionality of the acoustic space used to generate the 'song variety' response variable in this model (oneD = one-dimensional; twoD = two-dimensional; threeD = three-dimensional). * The second part of the file name defines the type of model (lm = linear model; qm = quadratic model). - `.csv` files with the naming structure **[lm,qm]_[one,two,three]D_summary.csv **are files containing summary statistics used to label figures displaying linear (Figure 7) and quadratic (Figure S5) regression models. * The first part of the file name defines the type of model (lm = linear model; qm = quadratic model). * The second part of the file name defines the dimensionality of the acoustic space used to generate the 'song variety' response variable in this model (oneD = one-dimensional; twoD = two-dimensional; threeD = three-dimensional). * `.csv` files with the naming structure **HZCH_note-level-measurements_#.csv** are the acoustic measurements taken of individual notes of songs recorded from chickadees at Sparrowfoot Park. The number at the end of the file name denotes seqential runs of measurements after quality checking steps that are documented in the measurement script **chickadee-ms-song-measurements.R**. Column header names indicate the following: * `note_num`: Sequential position of the measured note within the whole song * `file_name`: Name of the `.wav` file associated with the measurements for that row * `max_freq`: Maximum dominant frequency (kHz) * `min_freq`: Minimum dominant frequency (kHz) * `mean_freq`: Mean dominant frequency (kHz) * `median_freq`: Median dominant frequency (kHz) * `sd_freq`: Standard deviation of the dominant frequency trace * `abs_max_slope`: Maximum absolute value of the slope of the dominant frequency trace * `duration`: Note duration (s) - `.csv` files with the naming structure **HZCH_song-level-measurements_#.csv** are the song-level acoustic measurements made using the data from the note-level dataset. The number at the end of the file name denotes seqential runs of measurements after quality checking steps and addition of new recordings that are documented in the measurement script **chickadee-ms-song-measurements.R**. Column header names indicate the following: * `file_name`: Name of the `.wav` file associated with the measurements for that row * `ind_ID`: Individual identification code unique to the bird whose songs are being measured (Abbreviated color band combination) * `number_notes`: Number of notes in the song * `duration`: Song duration (s) * `max_note_dur`: Duration of the longest note in the song (s) * `min_note_dur`: Duration of the shortest note in the song (s) * `mean_note_dur`: Mean of all note durations (s) * `stdev_note_dur`: Standard deviation of all note durations * `signal_pause_ratio`: Ratio of signal to silence across the temporal domain of the song * `max_freq`: Highest value of maximum dominant frequencies across notes (kHz) * `min_freq`: Lowest value of minimum dominant frequencies across notes (kHz) * `stdev_note_max_freq`: Standard deviation of note maximum frequencies (kHz) * `abs_max_slope`: Highest of maximum absolute values of the slope of the dominant frequency trace across notes * `stdev_slope`: Standard deviation of maximum absolute values of the slope of the dominant frequency trace across notes - **SPPUA_song_level_measurements_final.csv**: Final dataset of acoustic measurements after removal of a few low-quality recordings that were repeatedly measured incorrectly by our custom measurement functions. File structure follows **HZCH_song-level-measurements_#.csv.** - **Quality_check_spectros**: folder containing spectrograms overlain by amplitude profiles and `timer()` signal delineation periods of Sparrowfoot Park recordings to check the effectiveness of signal detection thresholds - **rangewide_spectros**: folder containing spectrograms overlain by amplitude profiles and `timer()` signal delineation periods of range-wide *atricapillus* and *carolinensis* recordings to check the effectiveness of signal detection thresholds - **pc_scores_all_songs.csv**: PC scores for the PCA run on the Sparrowfoot Park dataset. * Column headers with the naming structure `PC#` indicate which principal component's scores are contained in that column * The column named `ind_ID` contains individual identification codes unique to the birds in the final dataset (Abbreviated color band combination) - **PCR-RFLP_triangle-plot_data.csv**: file with data from **PCR-RFLP_data_11april2025.csv** with the followng differences: * *atricapillus*-like allele is coded as `0` and *carolinensis*-like allele is coded as `1` * `hybrid_index`: Added column containing hybrid index values such that pure *atricapillus* = `0` and pure *carolinensis* = `1` * `interspecies_heterozygosity`: Added column containing interspecies heterozygosity values such that fully homozygous individuals have values of `0` and fully heterozygous individuals have values of `1` - **cleaned_metadata_rangewide.csv**: Combined metadata from **ml-metadata.csv** and **xc-metadata.csv** - **rangewide_song_data.csv**: Song-level acoustic measurements of recordings in the range-wide *atricapillus* and *carolinensis* dataset. Column headers follow the naming system of **HZCH_song-level-measurements_#.csv**, other than the replacement of the `ind_ID` column with the `species` column. - **sels_ml_conc.csv**: Concatenated selection tables from the folder **sels_ml** with added columns that define alterations to be made to the signal filtering and delineation processes determined on a case-by-case basis after checking images in **rangewide_spectros**. Columns 1-8 follow naming conventions of Raven Pro selection tables (Charif et al. 2010). The remaining column headers indicate the following: * `file.type`: `mp3` or `wav` taken from the file extension of each recording * `use.y.n` Indicator of whether the recording is of high enough quality for use in analyses. Coded `Y` for yes and `N` for no. * `threshold`: Designated amplitude threshold argument in the signal delineation function `timer()`. * `bpf.from`: Lower limit for bandpass filter. * `bpf.to`: Upper limit for bandpass filter. - **sels_xc_conc.csv**: Concatenated selection tables from the folder **sels_xc **with added columns that define alterations to be made to the signal filtering and delineation processes determined on a case-by-case basis after checking images in **rangewide_spectros**. File structure is identical to **sels_ml_conc.csv.** - **singers_all_data.csv**: All necessary data to run linear and quadratic models predicting song variety from genotype and to generate Table 2, which summarizes the generation of song variety scores in multiple dimensions of acoustic space. Column headers indicate the following: * `ind_num`: Individual identification code for each bird * `ind_ID`: Abbreviated color band combination for each bird * Columns 3-8 are means and standard errors of repeatedly-generated song variety scores by randomly sampling 100 songs per individual bird. These columns have the following naming system: `[one,two,three]D_[mean,se]` * The first part of the name defines the dimensionality of the acoustic space used to generate the song variety score (oneD = one-dimensional; twoD = two-dimensional; threeD = three-dimensional) * The second part of the name designates mean (`mean`) or standard error (`se`) of repeatedly-generated song variety scores by randomly sampling 100 songs per individual * `num_songs`: Number of individual songs in the final dataset for that individual bird * `pop_ID`: Population assignment; follows the naming system from **HZCH_StructureInput_100325.txt** * `prob_BC`: Probability of assigment to the *atricapillus*-like genetic cluster * `prob_CA`: Probablilty of assignment to the *carolinensis*-like genetic cluster * `species_range`: Range assignment; follows the naming system of **structure_data_localities_latlong.csv** * Columns 14-16 are means of repeatedly-generated song variety scores by randomly sampling 100 songs per individual bird, scaled across the different dimensional spaces. These columns have the following naming system: `[one,two,three]D_mean_scaled` * The first part of the name defines the dimensionality of the acoustic space used to generate the song variety score (oneD = one-dimensional; twoD = two-dimensional; threeD = three-dimensional) - **SPPUA_Hz_Quality-and-exceptions.csv** and **SPPUA_Hz_Quality-and-exceptions_2.csv** define alterations to be made to the signal filtering and delineation processes determined on a case-by-case basis after two rounds of checking images in the folder **Quality_check_spectros**. Column headings define the following: * `file_names`: Name of `.wav` file segmented to the song level * `include `Indicator of whether the recording is of high enough quality for use in analyses. Coded `Y` for yes and `N` for no. * `threshold`: Designated amplitude threshold argument in the signal delineation function `timer()`. * `trim.s`: Time (s) into the recording indicating where to start trim using `cutw()` function (to exclude extraneous noise) * `trim.f`: Time (s) into the recording indicating where to end trim using `cutw()` function (to exclude extraneous noise) ## R Scripts ##### To reproduce analyses done for this manuscript, the following R scripts should be run in the order listed using the folder 'Chickadee-MS-directory.zip' as a working directory. #### File: chickadee-ms-song-quality-control.R **Description:** This script does the following: 1) generates spectrograms of all .wav files to be used in analyses to allow for visual evaluation of signal quality; 2) generates a .csv file so that necessary alterations can be documented during spectrogram checks. #### File: chickadee-ms-song-measurements.R **Description:** This script does the following: 1) extracts acoustic measurements from all .wav files that passed the visual quality check; 2) checks measurements for erroneous values #### File: chickadee-ms-analyses.Rmd **Description:** This script runs all analyses detailed in the main body of the manuacript and generates tables for the Supplementary Materials.  #### File: chickadee-ms-figs-rmd.Rmd **Description:** This script generates all figures in the main body of the manuscript and Fig. S5 in the Supplementary Materials. #### File: chickadee-ms-rangewide.Rmd **Description:** This script runs all analyses and generates Figs. S3 and S4 for the range-wide song analysis in the Supplementary Materials. ## References McQuillan, M. A., A. V. Huynh, S. A. Taylor, and A. M. Rice (2017). Development of 10 novel SNP-RFLP markers for quick genotyping within the black-capped (Poecile atricapillus) and Carolina (P. carolinensis) chickadee hybrid zone. *Conservation Genetics Resources* 9:261–264. Charif, R. A., L. M. Strickman, and A. M. Waack (2010). Raven Pro 1.4 User’s Manual. The Cornell Lab of Ornithology, Ithaca, NY. Available from [https://www.ravensoundsoftware.com/knowledge-base/](https://www.ravensoundsoftware.com/knowledge-base/)