DOI: 10.5061/dryad.w3r2280pn
title: Differential geographic patterns in song components of male Albert’s lyrebirds

description: 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.
description: See paper (open access).
description: 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 
 <b>Name of Column</b> 
 <b>Description</b> 
 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 <b>Name of
 Column</b> 
 <b>Description</b> 
 
 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 
 <b>Name of
 Column</b> 
 <b>Description</b> 
 
 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 
 <b>Column
 Name</b> 
 <b>Description</b> 
 
 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 <b>Column
 name</b> 
 <b>Description</b> 
 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 
 <br clear="all"> ~~~~~
 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.