Differential geographic patterns in song components of male Albert’s lyrebirds
Cite this dataset
Backhouse, Fiona et al. (2022). Differential geographic patterns in song components of male Albert’s lyrebirds [Dataset]. Dryad. https://doi.org/10.5061/dryad.w3r2280pn
Abstract
Geographic variation in bird song has received much attention in evolutionary studies, yet few consider components within songs that may be subject to different constraints and follow different evolutionary trajectories. Here we quantify patterns of geographic variation in the socially-transmitted ‘whistle’ song of Albert’s lyrebirds (Menura alberti), an oscine passerine renowned for its remarkable vocal abilities. Albert’s lyrebirds are confined to narrow stretches of suitable habitat, allowing us to map likely paths of cultural transmission using a species distribution model and least cost paths. We use quantitative methods to break the songs into three components present in all study populations: the introductory elements, the song body, and the final element. We compare geographic separation between populations with variation in these components as well as the full song. All populations were distinguishable by song, and songs varied according to the geographic distance between populations. However, within songs, only the introductory elements and song body could be used to distinguish among populations. The song body and final element changed with distance, but the introductory elements varied independently of geographic separation. These differing geographic patterns of within-song variation are unexpected, given that the whistle song components are always produced in the same sequence and may be perceived as a temporally-discrete unit. Knowledge of such spatial patterns of within-song variation enables further work to determine possible selective pressures and constraints acting on each song component, and provides spatially-explicit targets for preserving cultural diversity. As such, our study highlights the importance for science and conservation management of investigating spatial patterns within seemingly discrete behavioural traits at multiple levels of organisation.
Methods
See paper (open access).
Usage notes
Description of each file:
~~~~~
ALB.elements.csv
Measurements of all elements within all songs used in the analysis. This dataset was used in the PCA on all elements (Fig. 2) and to create all other song datasets.
|
Description of columns in ALB.elements.csv |
|
|
Name of Column |
Description |
|
View |
Specifies measurement was taken from the spectrogram |
|
Begin.Time |
Begin time of the element within the recording |
|
End.Time |
End time of the element within the recording |
|
Low.Freq |
The lowest frequency of the element |
|
High.Freq |
The highest frequency of the element |
|
BW.90 |
Frequency bandwidth within which 90% of the power within the element occurs |
|
Peak.Freq |
Frequency with the highest power in the element |
|
Centre.Freq |
Frequency that divides the element into two frequency intervals of equal energy |
|
Begin.File |
Name of the recording file the element is in |
|
Location |
Study site the recording of the element was taken from |
|
Bird.ID |
Identity of bird recorded |
|
Dur.90 |
Duration within which 90% of the power within the element occurs |
|
Peak.Freq.Contour |
Vector of the peak frequencies of each spectrogram slice in the selection |
|
Freq.5 |
Frequency at which 5% of the energy in the element is below |
|
Freq.95 |
Frequency at which 95% of the energy in the element is below |
|
Type |
Broad categorical description of the element shape/quality |
|
Song |
Song the element is from. Unique within each recording file |
|
Order.pct |
The order at which the element occurs in the song, calculated as a percentage of the number of elements in the song. |
|
Begin.freq |
The first frequency in the peak frequency contour |
|
End.freq |
The last frequency in the peak frequency contour |
|
Slope |
The difference between End.freq and Begin.freq |
|
Type.cat |
The type of element within the song - introductory, body, or final |
|
Type.b |
The type of element within the song, distinguishing the "buzz" final elements of Goomburra from other final elements |
|
PC1 |
The first principal component as calculated in Minitab |
|
PC2 |
The second principal component as calculated in Minitab |
|
PC3 |
The third principal component as calculated in Minitab |
~~~~~
intro.elements.csv
Contains the data required for the analysis on the introductory elements.
|
Description of columns in intro.elements.csv |
|
|
Name of Column |
Description |
|
Begin.File |
Name of the recording file the element is in |
|
Location |
Study site the recording was taken in |
|
Bird.ID |
Identity of the bird recorded |
|
Song |
Song within the recording the element is from |
|
BW.90 |
Frequency bandwidth within which 90% of the power within the element occurs |
|
Peak.Freq |
Frequency with the highest power in the element |
|
Dur.90 |
Duration within which 90% of the power within the element occurs |
|
Begin.freq |
The first frequency in the peak frequency contour |
|
End.freq |
The last frequency in the peak frequency contour |
|
log.dur |
log transformation of 90% duration |
|
PC1 |
The first principal component as calculated in Minitab |
|
PC2 |
The second principal component as calculated in Minitab |
|
PC3 |
The third principal component as calculated in Minitab |
|
PC4 |
The fourth principal component as calculated in Minitab |
|
PC5 |
The fifth principal component as calculated in Minitab |
~~~~~
final.elements.nobuzz.csv
Contains the data required for the analysis on final elements. Note that this does not include the "buzz" elements from Goomburra. A dataset with all final elements including the "buzz" elements derived from "ALB.elements.csv" is included as "final.elements.csv".
|
Description of columns in final.elements.nobuzz.csv |
|
|
Name of Column |
Description |
|
Begin.File |
Name of the recording file the element is in |
|
Location |
Study site the recording was taken in |
|
Bird.ID |
Identity of the bird recorded |
|
Song |
Song within the recording the element is from |
|
BW.90 |
Frequency bandwidth within which 90% of the power within the element occurs |
|
Peak.Freq |
Frequency with the highest power in the element |
|
Dur.90 |
Duration within which 90% of the power within the element occurs |
|
Begin.freq |
The first frequency in the peak frequency contour |
|
End.freq |
The last frequency in the peak frequency contour |
|
log.endfr |
log transformation of 4000 minus End.freq |
|
PC1 |
The first principal component as calculated in Minitab |
|
PC2 |
The second principal component as calculated in Minitab |
|
PC3 |
The third principal component as calculated in Minitab |
|
PC4 |
The fourth principal component as calculated in Minitab |
|
PC5 |
The fifth principal component as calculated in Minitab |
~~~~~
song.body.csv
ALB.songs.csv
Contains the data required for the analysis on the song body and the full song respectively. Column names and descriptions are identical in each dataset.
|
Description of columns in song.body.csv and ALB.songs.csv |
|
|
Column Name |
Description |
|
Location |
Study site the recording was taken in |
|
Bird.ID |
Identity of the bird recorded |
|
Begin.File |
Name of the recording file the element is in |
|
Song |
Song identity within each recording |
|
Length |
Song duration |
|
Freq.range.90 |
90% song bandwidth |
|
Max.freq |
Peak frequency of the higest element in the song |
|
Min.freq |
Peak frequency of the lowest element in the song |
|
CV.pf |
Coefficient of variation of element peak frequency |
|
CV.dur |
Coefficient of variation of 90% element duration |
|
slope |
Song slope as a regression of centre frequency over the position of the element within the song (order.pct) |
|
PC1 |
The first principal component as calculated in Minitab |
|
PC2 |
The second principal component as calculated in Minitab |
|
PC3 |
The thiird principal component as calculated in Minitab |
|
PC4 |
The fourth principal component as calculated in Minitab |
|
PC5 |
The fifth principal component as calculated in Minitab |
~~~~~
distances.csv
Contains the geographic distance measures between each population, required for the mantel tests. Can be converted into distance matrices.
|
Description of columns in distances.csv |
|
|
Column name |
Description |
|
Site.x |
First location in the distance measure. BB = Lamington (Binna Burra), BR = Border Ranges, GB = Goomburra, KL = Killarney, MJ = Mt Jerusalem, TM = Tamborine |
|
Site.y |
The second location in the distance measure |
|
PathCost |
Cost of the least cost path between locations |
|
Length |
Length of the least cost path between locations |
|
SL.dist |
Straight line (geodetic) distance between locations |
|
resist.length |
Cost x length of the least cost path between locations, used in paper as measure of geographic separation |
~~~~~
ALB_Whistle_song_analysis.R
R code used to create the song and song component datasets, and for each analysis. R code is annotated.
~~~~~
SDM_layer.zip
The Species Distribution Model layer, used to calculate least cost paths between locations. The layer file is called "species.asc" and can be opened in ArcMap.
Funding
National Science Foundation, Award: 1730791
BirdLife Northern NSW*
BirdLife Northern NSW