ArticlePDF Available

Fooling the experts: Accurate vocal mimicry in the song of the superb lyrebird, Menura novaehollandiae


Abstract and Figures

The degree of resemblance between mimics and models provides valuable insight into the evolutionary dynamics of mimicry signalling systems, but for many systems mimetic resemblance has not been quantified. Superb lyrebirds have a reputation for accurately imitating an astonishing variety of sounds that they incorporate into their sexual displays. We assessed the accuracy with which males imitate the complex song of the grey shrike-thrush, Colluricincla harmonica. We measured vocal accuracy by (1) using playback experiments as a bioassay, to determine whether and how shrike-thrushes distinguish between their own song and imitations of shrike-thrush songs by lyrebirds and (2) comparing acoustic properties of mimicked and model songs. Shrike-thrushes reacted just as strongly towards mimetic song as to their own when songs were presented alone. When mimetic song was accompanied by lyrebird song sequences (emulating the lyrebird's natural singing style), shrike-thrushes still usually approached the speaker but less often than when mimetic song was presented alone or when model songs were broadcast. Acoustic analyses showed that imitations were remarkably similar to model songs. However, while lyrebirds maintained the structure and complexity of model songs, they sang fewer repetitions of individual element types. This 'abridging' of model songs is consistent with a trade-off between demonstrating both mimetic accuracy and versatility. Overall, these results indicate strong selection on male lyrebirds to imitate accurately the complex vocalizations of other species, and show that species can integrate contextual information with the signal structure to distinguish between their own signals and imitations. Crown Copyright (c) 2012. Published on behalf of The Association for the Study of Animal Behaviour by Elsevier Ltd. All rights reserved.
Content may be subject to copyright.
Fooling the experts: accurate vocal mimicry in the song of the superb lyrebird,
Menura novaehollandiae
Anastasia H. Dalziell
, Robert D. Magrath
Division of Evolution, Ecology and Genetics, Australian National University, Canberra, Australia
article info
Article history:
Received 12 August 2011
Initial acceptance 19 September 2011
Final acceptance 20 February 2012
Available online 13 April 2012
MS. number: 11-00636R
Menura novaehollandiae
rejection threshold
sexual signal
signal design
song learning
vocal accuracy
vocal mimicry
The degree of resemblance between mimics and models provides valuable insight into the evolutionary
dynamics of mimicry signalling systems, but for many systems mimetic resemblance has not been
quantied. Superb lyrebirds have a reputation for accurately imitating an astonishing variety of sounds
that they incorporate into their sexual displays. We assessed the accuracy with which males imitate the
complex song of the grey shrike-thrush, Colluricincla harmonica. We measured vocal accuracy by (1)
using playback experiments as a bioassay, to determine whether and how shrike-thrushes distinguish
between their own song and imitations of shrike-thrush songs by lyrebirds and (2) comparing acoustic
properties of mimicked and model songs. Shrike-thrushes reacted just as strongly towards mimetic song
as to their own when songs were presented alone. When mimetic song was accompanied by lyrebird
song sequences (emulating the lyrebirds natural singing style), shrike-thrushes still usually approached
the speaker but less often than when mimetic song was presented alone or when model songs were
broadcast. Acoustic analyses showed that imitations were remarkably similar to model songs. However,
while lyrebirds maintained the structure and complexity of model songs, they sang fewer repetitions of
individual element types. This abridgingof model songs is consistent with a trade-off between
demonstrating both mimetic accuracy and versatility. Overall, these results indicate strong selection on
male lyrebirds to imitate accurately the complex vocalizations of other species, and show that species
can integrate contextual information with the signal structure to distinguish between their own signals
and imitations.
Crown Copyright Ó2012. Published on behalf of The Association for the Study of Animal Behaviour by
Elsevier Ltd. All rights reserved.
Mimicry is a classic example of adaptive signal design in which
individuals benet from imitating the signals of other species
(Bates 1862;Müller 1878;Vane-Wright 1980) or conspecics
(Dominey 1980;Gross 1996;Norman et al. 1999;Whiting et al.
2009). Despite considerable advances over the last 150 years,
many aspects of mimetic signalling systems are only beginning to
be understood (Ruxton & Speed 2005;Chittka & Osorio 2007;
Vereecken & McNeil 2010). One area attracting recent attention is
the accuracy of mimetic signals (McGuire et al. 2006;Chittka &
Osorio 2007;Pekár et al. 2011), as it has become clear that the
degree of resemblance between mimics and models can provide
valuable insight into the selective forces driving mimicry signalling
systems (e.g. Holen & Johnstone 2004;Coleman et al. 2007;
Stoddard & Stevens 2010).
Traditional theory assumes that selection will always favour
mimics that most closely resemble the species or conspecic they
imitate, the model, but several studies have challenged the
simplicity of this view (Johnstone 2002;Sherratt 2002;Holen &
Johnstone 2004;Chittka & Osorio 2007;Harper & Pfennig 2007;
Cheney & Marshall 2009;Pekár et al. 2011). How closely the mimic
resembles the model is a function of the costs and benets of
mimicry among all three protagonists in the mimicry complex: the
mimic, the model and the receiver of the signal. The benets of
mimicry include gaining protection from predators, increased
access to food and reproductive advantages (Starrett 1993;Cheney
2010). The costs of mimicry include increased detection by preda-
tors, conicting signal requirements and costs imposed by the
model (Edmunds 2000;Sherratt 2002;Holen & Johnstone 2004;
Estrada & Jiggins 2008;Stoddard & Stevens 2010). Physiological and
phylogenetic constraints on the mimic will also limit resemblance.
Furthermore, mimetic accuracy can depend on the receivers ability
to discriminate between models and mimics, and inaccurate
mimics may evolve as a result of weak selection on the receiver for
ne discrimination, or physiological constraints on the receiver
(Chittka & Osorio 2007;Cheney & Marshall 2009;Kikuchi & Pfennig
2010). Mimetic accuracy is the outcome of these benets, costs and
constraints. Thus, highly accurate mimicry implies both an
*Correspondence: A. H. Dalziell, Building 116, Division of Evolution, Ecology and
Genetics, Research School of Biology, Australian National University, Canberra 0200,
E-mail address: (A. H. Dalziell).
Contents lists available at SciVerse ScienceDirect
Animal Behaviour
journal homepage:
0003-3472/$38.00 Crown Copyright Ó2012. Published on behalf of The Association for the Study of Animal Behaviour by Elsevier Ltd. All rights reserved.
Animal Behaviour 83 (2012) 1401e1410
advantage for accuracy in the mimic as well as strong selection on
the receiver to discriminate between models and mimics. The
nature of the differences between model and mimic are equally
informative about the selection pressures shaping the mimetic
Several species of bird from disparate families habitually mimic
the sounds produced by other species with remarkable accuracy
(Chisholm 1932), but the evolutionary drivers of vocal mimicry are
usually unclear (Baylis 1982;Kroodsma 2004;Garamszegi et al.
2007;Kelley et al. 2008). In some bird species mimicry functions
deceptively (Langmore et al. 2003,2008;Flower 2011) or may
provide increased protection from predators (Goodale & Kotagama
2006a,b). Alternatively, mimicry may not be deceptive and instead
function to attract mates or repel rivals (Dobkin 1979). This rarely
tested hypothesis is plausible in versatile mimics: oscine passerines
in which males incorporate imitations of multiple sounds into
elaborate, song-like displays (e.g. the northern mockingbird, Mimus
polyglottos, marsh warbler, Acrocephalus palustris, and European
starling, Sturnus vulgaris:Catchpole & Slater 2008). Here, the
conspecic receiver driving the evolution of mimicry gains infor-
mation about the quality of the singer by evaluating the singers
mimetic song. However, the structures of mimetic songs have
seldom been examined.
Assessment of mimetic accuracy could help resolve the debate
over which vocal features of versatile mimics are targeted by natural
selection. Selection may favour large repertoires rather than mimicry
per se, since repertoire size affects mate choice and territory defence
in nonmimetic birds (reviewed in Catchpole & Slater 2008). Mimicry
would thus evolve as a shortcut to gaining a large repertoire (Howard
1974) or as a by-product of repertoire acquisition itself (Hindmarsh
1986;Kelley et al. 2008). However, highly accurate mimicry
provides evidence that mimicry itself is under selection, for two
reasons. First, if repertoire size alone is important, accurate resem-
blance between model and mimetic vocalizations is unlikely to be
maintained because accumulated copying errors and differential
selection pressures between models and mimics should eventually
lead to divergent acoustic structures. Second, it is doubtful that
accurate mimicry is selectively neutral given strong evidence that
precise vocal production is challenging (reviewed in Podos et al.
2009) and that individual species appear to have physiological
adaptations optimized for species-specic vocalizations (Zollinger &
Suthers 2004). Versatile mimics, then, are probably under selection
for both mimetic accuracy and versatility, a conclusion supported by
the only study to investigate the relationship between mating
success and both mimetic accuracy and versatility (Coleman et al.
2007). Investigating mimetic accuracy is thus fundamental to
elucidating the evolution of mimicry.
Superb lyrebirds are large (880e1100 g) oscine passerines with
versatile vocal mimicry and appear to be subject to strong sexual
selection (Higgins et al. 2001). Males have extravagant tails while
females are cryptic, only females care for the young (Lill 1979), and
during the winter breeding season males are geographically clus-
tered in a lek-like pattern (Robinson & Curtis 1996). Males incor-
porate mimicry into a amboyant vocal display with approximately
70% of vocalizations consisting of imitations of about 20 different
species of local birds (Higgins et al. 2001;Zann & Dunstan 2008).
Vocal displays are performed both as a prelude to mating and
during territorial interactions with other males, occurring most
often during the breeding season (Higgins et al. 2001). These
observations strongly suggest that mimetic songs sung by males are
a sexually selected trait and the receiver is either a rival male or
a potential mate.
Adult superb lyrebirds enjoy a reputation for highly accurate
mimicry (e.g. Attenborough 2002;Zoos South Australia 2009), but
there has been only one study of mimetic accuracy in this species
(Zann & Dunstan 2008). Acoustic analysis revealed that adult males
reproduce individual elements from two species of bird with
remarkable accuracy. Furthermore, adult males are more accurate
mimics than juveniles of indeterminate sex, suggesting that
mimetic accuracy improves with age. We built on this introductory
investigation into mimetic accuracy in lyrebirds by analysing
a complex model sound with multiple elements and by using two
methods to measure accuracy: acoustic analysis and a bioassay.
Acoustic analysis is a powerful tool to investigate the accuracy
of vocal parameters but an additional approach is to employ
a bioassay to use a birds assessment of mimetic accuracy (Lemaire
1975;Brenowitz 1982). The sensory systems of the model should be
attuned to its own song making it a sensitive assessor of mimetic
accuracy. Moreover, the model may be under selection to distin-
guish between conspecics and mimics to avoid costly, unneces-
sary responses to mimetic signals. Studies of nonmimetic oscine
passerines have shown that birds respond differently to subtle
differences in species-specic songs (Stoddard 1996;Illes et al.
2006;Blumenrath et al. 2007;Botero et al. 2007;Nicholls 2008;
de Kort et al. 2009). Thus bioassays have the dual advantage of
being able to reveal differences between model and mimetic songs
that may not be detectable using acoustic analysis, and of providing
insight into signal discrimination by model species.
Our aim was to investigate the selective forces acting on
mimetic song in lyrebirds by quantifying mimetic resemblance
from the perspective of the model using a bioassay, and by directly
measuring acoustic features of model and mimetic songs. In addi-
tion, we examined how a model species distinguished between
model and mimetic songs. The grey shrike-thrush, Colluricincla
harmonica, produces a complex, multielement song and is regularly
imitated by lyrebirds (Zann & Dunstan 2008). Shrike-thrushes are
ideal subjects for a bioassay because there is no evidence from our
study or published accounts that shrike-thrushes interact directly
with lyrebirds, making it unlikely that they select for mimicry in
lyrebirds. We conducted two playback experiments. First, we tested
whether shrike-thrushes could discriminate between model and
mimetic songs. Given the likely costs of unnecessary responses, and
the sophisticated auditory systems of oscine passerines, we
assumed that shrike-thrushes would respond similarly to model
and mimic only if mimicry is highly accurate. Second, since lyre-
birds typically imitate several species in succession, we tested
whether the model was more alert to acoustic differences if songs
were presented with lyrebird mimicry of other species.
Study Site and Species
We studied populations of superb lyrebirds and grey shrike-
thrushes in Sherbrooke Forest (37
), part of the Dande-
nong Ranges National Park in Victoria, Australia. The population of
lyrebirds has been monitored for 50 years by the Sherbrooke Lyre-
bird Study Group (e.g. Kenyon 1972; N. Carter, unpublished data) and
many lyrebirds are individually colour-banded as nestlings. Further
individuals are distinguishable by plumage. Lyrebird songs were
recorded in JuneeJuly 2007 for the playback experiments, and these
were supplemented with recordings made in 2008 for the sound
analysis. Grey shrike-thrushes are socially monogamous, territorial
passerines (Higgins & Peter 2002) and both sexes sing discrete, 3 s
songs fromwhat is probably a large repertoire of song types (Higgins
& Peter 2002). The sexes can be distinguished by slight differences in
plumage (Higgins & Peter 2002) but not by song. Shrike-thrushes are
most vocal and territorially active from August to September, just
before their breeding season. Thus they sing most when lyrebirds are
relatively quiet.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e14101402
Song types of grey shrike-thrushes can be classed into two
different groups: (1) song types beginning with repeated, low-
frequency, piping elements (Fig. 1) and (2) high-frequency song
types without introductions (Higgins & Peter 2002). Low-frequency
song types were more common in both species (unpublished data),
so only these were considered in this study. Song types were easily
identied by visual inspection of spectrograms (Fig. 1). All record-
ings of shrike-thrushes were made in AugusteOctober 2007.
General Playback Design
We carried out two experiments involving the playback of
imitations of shrike-thrushes (mimetic songs) to territorial shrike-
thrush pairs in Sherbrooke forest from September to October 2007.
Both experiments employed a matched design so that the 15
shrike-thrush pairs in each of two experiments received all treat-
ments. Territorial boundaries were determined by observing
singing shrike-thrushes before experiments. During some play-
backs both sexes responded while in others only one bird respon-
ded. Since we could not always identify each sex at all times during
playbacks we measured the pairs response to the playback (e.g. the
latency of the rst bird to approach the speaker and the combined
song output). We use the term pairthroughout to refer to each
replicate. For each pair, the speaker was set up 1e2 m above the
ground, at least 30 m inside a territorial boundary and within 30 m
of the birdscurrent location, although birds would sometimes
move further away before an experimented started. Per pair, all
playbacks were presented from the same location and adjacent
locations were no closer than 600 m to reduce the chance that the
same pair was sampled more than once. A 15 m radius was agged
around the speaker to facilitate measurements of approach
distance (after Vehrencamp et al. 2007). Playbacks were not started
until at least 10 min after any aggressive interactions.
Songs used in playback experiments had high signal to noise
ratios, and were recorded using a Sennheiser ME66 shotgun
microphone and a Marantz PMD670 digital recorder sampling
wave les at 44.1 kHz and 16 bits. Recordings were ltered below
400 Hz in Syrinx (J. Burt, Playback
tracks were normalized to 90% using Audacity 1.2.6 (http:// We played back songs at 71 dB at 9 m,
which we found to be the mean natural amplitude of shrike-
thrushes at that distance. We used a Peerless4-inch, midrange
speaker, attached via an amplier to a Roland Edirol R-09 HR solid-
state digital player.
Each pair of shrike-thrushes was played recordings from one
individual lyrebird and one shrike-thrush, both of which were
recorded at least 3 km away from the experimental subjects. Pairs
received playbacks of a unique set of individuals. Treatments con-
sisted of a silent, 5 min, preplayback period, a 5 min playback
period and 5 min of silent, postplayback observation. The playback
period contained two sets of identical, 2 min stimuli separated by
1 min of silence. Dictated observations and vocal responses of
shrike-thrushes were recorded using the Marantz recorder and
shotgun microphone described above.
We assessed the response of shrike-thrushes to each playback
treatment by (1) counting the songs sung, (2) determining whether
shrike-thrushes type-matched broadcast songs, and (3) scoring
whether they approached within 15 m of the speaker. To determine
vocal responses we used spectrograms of the sound recordings of
the experiment and scored separately for pre-, during and post-
playback periods. Differential responses to the two experiments
resulted in additional measurements of approach behaviours
specic to each experiment (below).
Experiment 1: Mimic versus Model
We tested whether shrike-thrushes could distinguish between
model and mimicked songs. Each shrike-thrush pair received
a shrike-thrush song sung by a shrike-thrush, a lyrebird imitation of
a shrike-thrush song and a lyrebird imitation of a an eastern
whipbird, Psophodes olivaceus, duet. This last treatment controlled
for any shrike-thrush response to lyrebird mimicry of other species
or to the sounds of ecologically neutral sympatric species. Treat-
ments were played on the same day with at least 10 min between
each playback and began when the pair was within 15e50 m of the
speaker. Each 2 min stimulus contained 13 repetitions of one song,
emulating natural shrike-thrush singing (unpublished data). The
sequence of treatments was balanced between pairs to control for
1 1.5 2
1 1.5 2
Time (s)
Frequency (kHz)
1.5 2
1 1.5 2
1 1.5 2
1 1.5 2
Figure 1. (aec) Three different grey shrike-thrush song types sung by grey shrike-thrushes and (def) the same song types imitated by superb lyrebirds. Songs are subdivided into
phrases containing repeats of one element type (c).
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410 1403
potential order effects. We also measured (4) the shrike-thrushs
latency to approach within 15 m of the speaker, (5) the latency to
retreat from a 15 m radius circle, (6) the closest approach to the
speaker and (7) the time spent within the circle.
Experiment 2: Song Context
We tested whether the presence of lyrebird song caused shrike-
thrushes to respond differently to playbacks of either their own
speciessong or imitations of their song. Each shrike-thrush pair
was played four playback treatments that differed in both the
species singing the song (shrike-thrush or lyrebird) and the
acoustic context of the song (with additional lyrebird song or
alone). Each playback consisted of a clip of one song repeated
approximately every 20 s, reecting the song rate of shrike-
thrushes and the rate shrike-thrush songs were sung by lyrebirds.
Playbacks presented aloneconsisted of songs separated by periods
of silence (Fig. 2a). Playbacks with a lyrebird contextconsisted of
songs separated by an approximately 18 s period of lyrebird song
(Fig. 2b): a natural sequence of mimicked sounds of different
species of bird interspersed with vocalizations unique to lyrebirds.
These periods were edited to exclude vocalizations of shrike-
thrushes and extremely loud sounds. The sequence was then
amplied so that the amplitude of the shrike-thrush song was
similar to the majority of sounds in the sequence of mimicry.
The four playbacks were presented using a split-plot design and
were played over 2 days. Day A consisted of the two shrike-thrush
treatments: a model song presented (1) alone and (2) in a lyrebird
context. Similarly, day B consisted of the two imitationtreat-
ments. The order of the tracks within days and the order of the
2 days themselves were balanced among pairs. This design limited
the number of days required to complete a set of treatments (and
thus avoiding long gaps between treatments caused by unsuitable
weather) while minimizing potential order effects. Within a day,
tracks were separated by at least 15 min and playbacks of groups
A and B were separated by 1e3 days. Pairs had to be between 25
and 40 m from the speaker before the playback started. In addition
to the three measurements outlined above (see General playback
design) we also measured whether pairs moved at least 5 m
towards the speaker because, unlike the previous experiment,
some shrike-thrushes ew towards the speaker but did not come
within 15 m of it (N¼9 of 60 playbacks).
Quantifying Differences in Vocal Parameters
We quantied acoustic differences between model and mimetic
songs by spectrographic analyses of 38 songs with the highest
signal to noise ratio and with one song from each individual. This
sample included 19 different song types with an example of each
song type from both the mimic and the model. We used this design
because in our sample of recordings shrike-thrushes very rarely
shared song types and there was a large repertoire of shrike-thrush
song types in both model and mimic (72 types sung by shrike-
thrushes of which 25 were imitated by lyrebirds). In two cases,
there were two songs with signal to noise ratios that were indis-
tinguishable and here we used a random number generator to
choose between examples of a particular type.
We used three different approaches to quantify differences
between model and mimetic songs. First, we compared model and
mimetic songs in seven characteristics of the entire song: the
number of different elements, the length of the song, the sound
duration (sum of the duration of all elements), the average element
duration, the number of different element types, the rate of
elements and the peak frequency (the frequency with maximum
power). Second, we compared model and mimetic songs in ve
characteristics of element structure including the duration,
maximum frequency, frequency difference, peak frequency and the
RMS amplitude (the root-mean-square amplitude across the
duration of the element). Third, we tested for differences between
the two species in how consistently they produced repeated song
elements. Here we chose a subset of 16 song types in which both
lyrebirds and shrike-thrushes produced at least one repeat of the
rst element in the song (e.g. Fig. 1a and d). We then compared the
last two elements in the rst phrase (Fig. 1) using the spectro-
graphic cross-correlation analysis (SPCC) to obtain a peak correla-
tion score for each song. We tested whether correlation scores
2 4 6 8 10 12 14 16 18 20 22
Time (s)
lyrebird song
Frequency (kHz)
14 16 18 20 22
Figure 2. Sections from playback stimuli used in experiment 2 on song context. Playback songs were presented in (a) the grey shrike-thrushs singing style (alone) and (b) the
superb lyrebirds singing style (lyrebird song context). For the lyrebird song context, each shrike-thrush song (at 1 and 21 s) is interspersed with mimicry and lyrebird-specic
vocalizations. Depicted at the beginning and the end of each sequence is (a) a song sung by a shrike-thrush and (b) an imitation of a shrike-thrush by a lyrebird.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410140 4
differed between species and within song types. SPCC was not used
in the other two analyses because of its unsuitability for analyses
involving sequences of elements and sensitivity to small trans-
positions in frequency (Charif et al. 1995).
All vocal parameters were quantied in Raven Pro 1.3 (Cornell
Laboratory of Ornithology, Ithaca, NY, U.S.A.). Analyses were con-
ducted on a spectrogram display type Blackman(lter bandwidth:
70.7 Hz; size: 1024 samples; grid resolution: 11.3 ms, 43.1 Hz).
Amplitudes of whole songs were maximized in Syrinx before
analyses. SPCC analysis was performed in Raven using a biased
normalization procedure, a band-pass lter of 400e10 000 Hz and
a linear power spectrograph of the Blackmantype (lter band-
width: 120 Hz; frame length: 603 samples; grid resolution:
3.42 ms, 43.1 Hz).
Statistical Analyses
Generalized linear models (GLM) using a logit link function and
assuming a binomial distribution of error were constructed for
approach behaviours in both experiments, while a Poisson distri-
bution with a logarithmic link function was used to model the
number of birds that approached the speaker and the number of
songs shrike-thrushes sang during the playbacks. Dispersion
parameters for Poisson distribution models were estimated in
GenStat (Payne 2010a). Final models were chosen by rst tting
a saturated model. We then discarded nonsignicant interaction
terms, followed by other nonsignicant terms unless there was an
a priori reason to retain control variables such as those accounting
for the structure in the data. Since Genstat employs a sequential
sums of squares approach, we built the saturated model by rst
entering control variables into the model before the variables of
interest. Control variables included the distance of the closest
shrike-thrush to the speaker before the playback started and the
presentation order of the treatments, and are reported only when
signicant. Models of the number of songs sung also controlled for
the number of songs sung during the 5 min before the playback. For
all GLMs, residual plots were used to check that the assumptions of
linear models were met (Grafen & Hails 2002) and variates were
transformed as appropriate.
We employed GLMs instead of GLM mixed models because the
latter failed to converge. Instead, we controlled for repeated
sampling of pairs by incorporating the blocking term pairinto
GLMs as the rst term. The split-plot design of the song context
experiment (experiment 2) resulted in nesting of the context of the
playback (lyrebird or alone) in species (shrike-thrush or lyrebird),
which was in turn nested in pair. We controlled for this further level
of structure by tting an interaction term between pairand
speciesbefore tting the context of the playback (lyrebird or
alone), and the interaction between context and species.I
experiments, we used nonparametric tests if data failed to conform
to diagnostic tests for a normal distribution of residuals.
Differences between the acoustic structures of model and
mimetic songs were analysed using univariate models of individual
parameters. Continuous measures of whole songs were rst
modelled using a mixed models approach with species tted as
axed effect and song typemodelled as a random term. In several
models, the error of this random term was large, and the variance
was small, relative to the xed effect. Therefore, we conducted
a likelihood ratio test of the difference in deviance between a model
containing song type and one without (Payne 2010b). If the test
statistic approached zero, song type was dropped from the model
to permit more accurate estimates. The measurement song
complexitycontained just three levels and was thus analysed using
a Wilcoxon signed-ranks test with the data paired according to
song type. For analyses of element structure, the random
components consisted of the phrase within the song nested in song
type to account for the structure in the data (elements, nested
within phrases, nested within song types, Fig. 1).
Performing multiple statistical tests can increase the probability
of falsely rejecting the null hypothesis (Grafen & Hails 2002) but we
were also concerned with type II errors. To balance these two
inversely related errors, we emphasize stronger effects in the
discussion (P<0.01) and report least signicant differences (LSD)
and 95% condence intervals (CI) of effect sizes where possible. In
line with recent theory (Colegrave & Ruxton 2003), our conclusions
regarding the similarity between model and mimetic song rely
most heavily on measurements with smaller condence intervals of
the effect size (or LSD).
All statistical tests were carried out using GenStat 11.1 (VSN
International, Hemel Hempstead, U.K.) except for Wilcoxon signed-
ranks tests and associated CI, which were calculated using Stats-
Direct 2.7.8 (StatsDirect Ltd, Altrincham, U.K.).
Ethical Note
This research was conducted under permits from the Animal
Experimentation Ethics Committee of the Australian National
University and the Victorian Department of Sustainability and
Experiment 1: Mimic versus Model
There was no difference between the behaviour of grey shrike-
thrushes towards mimetic and model songs in any measure of
speaker approach. Shrike-thrushes were equally likely to approach
within 15 m of a speaker broadcasting model songs as mimetic
songs (12/15 pairs in each case), but only 1/15 came within 15 m of
the lyrebird imitation of whipbirds (Fig. 3; GLM:
P<0.001). Similarly, the number of birds approaching within 15 m
of the speaker was identical after playback of model and mimetic
songs, but lower following playback of an imitation whipbird duet
0.6 LSD
ST Imitation ST
back stimulus
P(approach within 15 m)
Imitation WB
Figure 3. Experiment 1, mimic versus model: the proportion of grey shrike-thrush
pairs that approached within 15 m of a speaker broadcasting a song sung by an
actual shrike-thrush (ST), an imitation of an ST song by a superb lyrebird (imitation ST)
or a lyrebird imitating an eastern whipbird duet (imitation WB). Columns show
predicted means generated from the model and the bar indicates the average least
signicant difference (LSD) of the means at the 5% level; N¼15 pairs. Statistics are
reported in the text.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410 1405
¼13.1, P<0.001; imitation shrike-thrush: mean ¼1.13;
shrike-thrush: mean ¼1.13; imitation whipbird: mean ¼0.13;
average LSD ¼0.53). We did not detect anysubtle differences in the
approach responses of shrike-thrushes to playbacks of imitations or
shrike-thrush songs after excluding the control playback (Table 1),
suggesting that shrike-thrushes did not distinguish between model
and mimetic songs; however, given the broad condence intervals
for some measurements, there was still room for smaller, unde-
tected differences in responses.
Shrike-thrushes sang a similar number of songs during playback
of mimetic songs as model songs and responded with fewer songs
to playback of an imitation whipbird duet (Fig. 4,Table 2). This
result was independent of an increase in the number of songs when
more birds were singing, and the tendency of some pairs to sing
consistently more than others (Table 2). Shrike-thrushes also
responded with more songs after playback of mimetic and model
songs than after a whipbird duet during the 5 min after the play-
back had ended (Table 2).
The only measure of shrike-thrush response that differed
between model and mimetic songs was that shrike-thrushes were
more likely to type-match model songs (two-tailed binomial test:
model ¼mimic; model: 7/15; mimic: 1/15; P¼0.013), although
the number of type matches after playback of model sounds varied
greatly (1e36).
Experiment 2: Song Context
Shrike-thrush pairs were less likely to approach a speaker
broadcasting a mimetic song when it was embedded within
a lyrebirds natural song sequence than when it was presented
alone, but they nearly always approached model songs regardless
of context (Fig. 5,Table 3). The number of birds approaching the
speaker was not affected by the type of playback or any other of the
modelled variables (P>0.1).
Shrike-thrushes sang more songs during playback of model
songs than mimetic songs (model mean ¼22.0 songs; mimic
mean ¼14.1; LSD ¼6.72; Table 4) but there was no effect of the
context of the song (context: P¼0.2; interaction: P¼0.6). Shrike-
thrushes continued to sing more songs during the 5 min after
a playback of model songs than mimetic songs (model mean ¼20.6
songs; mimic mean ¼14.0; LSD ¼6.90; Table 4) after we controlled
for a greater song rate among pairs associated with closer proximity
to the speaker before the beginning of the playback (Table 4). Again,
there was no effect of the context of the song (context: P¼0.6;
interaction: P¼0.1). Unsurprisingly, the total number of songs sung
increased with the number of birds singing in both playback
periods (Table 4). There was no evidence that shrike-thrushes were
more likely to type-match some playback treatments more than
others (species singing the song: models ¼6/15; mimetic ¼2/15;
two-tailed binomial test: H
model ¼mimic: P¼0.10; song
context: alone ¼5/15; song sequence ¼4/15; two-tailed binomial
test: H
alone ¼song sequence: P¼0.69).
Acoustic Analyses
Of 13 measures of acoustic properties, only three differed
between model and mimetic songs. We detected no differences
between model and mimetic element structures (Tabl e 5) suggesting
that lyrebirds accurately reproduced the structure of elements
within shrike-thrush songs. In addition, spectrographic cross-
correlation analysis showed that lyrebirds produced the elements
in the rst phrase of imitations just as consistently as shrike-
thrushes (lyrebird median ¼0.93; shrike-thrush median ¼0.95;
pairwise median difference ¼0.015; 95.6% CI ¼e0.050e0.11; Wil-
coxon signed-ranks test: T¼88, N¼16, P¼0.3). The only differ-
ences between mimetic and model songs were foundin measures of
length (Table 5 ); for example, mimetic songs had fewer elements
than model songs. However, the distribution of the number of
elements in the songs of both species still overlapped (Fig. 6).
Mimetic songs did not differ from model songs in the number of
different types of elements (Wilcoxon signed-ranks test: T¼4,
Table 1
Experiment 1, mimic versus model: paired comparisons of speaker approach
behaviours by grey shrike-thrushes during playback of model and mimetic songs
Dependent variable Test T/t P Mean/median (95% CI)
of difference (shrike-
Closest approach (m) T50.5 0.77 0.15 (5.4 e11.6)
Latency to approach (s) T54 0.95 1.44 (149 e56.3)
Time within 15 m (s) t0.57 0.58 80.7 (224 e385)
Latency to approach
within 15 m (s)
t0.25 0.81 16.8 (128 e162)
Latency to retreat
further than 15 m (s)
t0.39 0.70 50.1 (225 e326)
Wilcoxon signed-ranks tests (T) were used instead of paired ttests (t) where data
were not normally distributed. N¼15.
Median differences are shown for Wilcoxon signed-ranks tests and approximate
95% CI. Means and exact 95% CI are shown for ttests.
ST Imitation ST
back stimulus
Songs sung
Imitation WB
Figure 4. Experiment 1, mimic versus model: the predicted means of the number of
songs sung by grey shrike-thrushes during the 5 min playback period in response to
playback of a song sung by an actual shrike-thrush (ST), an imitation of a ST song by
a superb lyrebird (imitation ST) or a lyrebird imitating an eastern whipbird duet
(imitation WB). The bar indicates the average least signicant difference (LSD) of the
means at the 5% level; N¼15 pairs. Statistics are shown in Table 2.
Table 2
Experiment 1, mimic versus model: signicant effects on the number of songs grey
shrike-thrushes sang in response to playback of their own song, an imitation of their
song by a superb lyrebird and an imitation of an eastern whipbird duet by a superb
lyrebird (playback type)
Dependent variable Effects df Approximate FP
Songs during
5 min playback
Whole model 17, 27 5.43 <0.001
Pair 14, 27 4.64 <0.001
Playback type*2, 27 8.93 0.001
No. of birds singing 1, 27 9.47 0.005
Songs 5 min
after playback
Whole model 16, 28 5.20 <0.001
Pair 14, 28 5.04 <0.001
Playback type 2, 28 6.29 0.006
Model predictions are shown in Fig. 4.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410140 6
N¼19, P¼0.75) showing that lyrebirds maintained the same song
structure as models but sang fewer repetitions of each element type
(Fig. 1).
Our playback experiments and sound analyses show that superb
lyrebirds are accurate mimics of grey shrike-thrush songs. Indeed,
their mimetic songs were accurate enough to prompt grey shrike-
thrushes to approach the playback speaker in most circum-
stances. However, there were subtle differences between the
mimetic and model songs that models responded to, particularly
once alerted to the presence of a lyrebird.
Accuracy, Signal Context and Model Response
Shrike-thrush pairs responded strongly towards both mimetic
and model songs when both songs were presented in isolation
(experiment 1: mimic versus model). We detected no differences
between the behaviour of shrike-thrushes towards mimetic lyre-
bird songs and those sung by real shrike-thrushes in any measure of
speaker approach behaviour or in singing effort. Most strikingly,
measures of approach within 15 m of broadcasts of mimic and
conspecic song were identical, and birds sang an almost identical
number of songs. The response to mimetic song was not a response
to lyrebird mimicry in general, because shrike-thrushes rarely
approached during control playbacks of lyrebird mimicry of
another species, and in that situation their song rate was half that to
lyrebird mimicry of shrike-thrushes.
Experiments using a similar bioassay to test the accuracy of
mimicry of northern mockingbirds found differences in response
according to model sex and species. Male red-winged blackbirds,
Agelaius phoeniceus (Brenowitz 1982), but not females (Searcy &
Brenowitz 1988), reacted equally strongly to model and mimetic
songs. However, these two studies measured different responses by
each sex and played back songs from onlyone mockingbird, making
it difcult to draw general conclusions. A third, well-replicated
study found that Florida scrub-jays, Aphelocoma coerulescens,
responded less strongly to mockingbird imitations of their terri-
torial weepcalls than towards conspecic weep calls (Owen-
Ashley et al. 2002). These studies suggest that either mimetic
accuracy varies with the model or that discriminatory ability differs
between models.
Our second experiment showed that shrike-thrushes were more
likely to approach a speaker broadcasting mimetic songs when they
were presented alone, than together with lyrebird song containing
Song context
P(flight towards speaker)
Imitation STShrike-thrush
Song context
P(approach within 15 m)
Imitation ST
back stimulus
Figure 5. Experiment 2, song context: the proportion of grey shrike-thrush pairs that
(a) ew at least 5 m towards the speaker or (b) approached within 15 m of a speaker,
broadcasting a song sung by an actual shrike-thrush (shrike-thrush) or an imitation of
a shrike-thrush song by a superb lyrebird (imitation ST). Each song was either
embedded in a stream of mimicry sung by a lyrebird (lyrebird song context) or
presented in isolation (alone). Columns show model predictions and the average
least-signicant difference (LSD) of the means at the 5% level are shown; N¼15 pairs.
Statistics are shown in Table 3.
Table 3
Experiment 2, song context: nal generalized linear models of grey shrike-thrush
approach behaviours in response to playback of shrike-thrush song sung by either
a superb lyrebird or a shrike-thrush (species), embedded in either a period of
silence or a sequence of lyrebird song (context)
Dependent variable Effects df Approximate
Flight 5m
towards the
Whole model 31 1.78 0.005
Pair 14 1.68 0.051
Species 1 7.83 0.005
Pair*Species 14 0.85 0.615
Context 1 2.66 0.103
Context*Speciesy1 9.11 0.003
Approach within
15 m of the
Whole model 31 2.54 <0.001
Pair 14 2.12 0.008
Species 1 7.99 0.005
Pair*Species 14 1.75 0.039
Context 1 w0.00 <1
Context*Speciesy1 7.76 0.005
The dependent variable was dichotomous and the experiment had a split-plot
Model predictions are shown in Fig. 5.
Table 4
Experiment 2, song context: nal generalized linear models of the number of songs
grey shrike-thrushes sang in response to playback of shrike-thrush song sung by
either a superb lyrebird or a shrike-thrush (species), embedded in either a period of
silence or a sequence of lyrebird song (context)
Dependent variable Effects df Approximate FP
during 5 min
Whole model 16, 43 2.75 0.004
Pair 14, 43 1.97 0.045
Species*1, 43 5.59 0.023
Number of birds
1, 43 11.19 0.002
Songs 5 min
after playback
Whole model 17, 42 2.54 0.007
Pair 14, 42 1.64 0.106
Initial distance
from speaker
1, 42 7.47 0.011
Species*1, 42 6.01 0.021
Number of birds
1, 42 7.33 0.010
Model predictions are reported in the text.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410 1407
imitations of other species. Discrimination was not simply based on
the presence of lyrebird song: shrike-thrushes more often
approached model than mimetic songs when both were presented
with lyrebird song. However, even when mimetic songs were
presented with lyrebird song, shrike-thrushes still approached 50%
of the time, suggesting that discriminating between mimic and
model continued to be difcult.
Two further results from our experiments suggest that while
shrike-thrushes responded strongly towards their songs sung by
both conspecics and lyrebirds, their reaction was more intense
towards their own song. First, in the context experiment (experi-
ment 2) shrike-thrushes sang fewer songs in response to playbacks
of imitations than to model songs. This effect was not present in the
rst experiment, possibly because many pairs had started incu-
bating by the time the second experiment was conducted, forcing
birds to respond strongly only to the greatest threats. Second,
shrike-thrushes were more likely to song type-match a playback of
a song sung by a conspecic than an imitation, although this effect
was only present in experiment 1. Song type matching can be
a more aggressive signal than singing a nonmatching song type
(Molles & Vehrencamp 2001;Beecher & Campbell 2005), again
suggesting that shrike-thrushes responded marginally more
strongly towards playback of models. Importantly, these effects
were subtle and the presence of lyrebird song was the only factor
inuencing whether or not a shrike-thrush approached a playback
of an imitation.
That shrike-thrushes are more discriminating when mimicry
was presented with a sequence of lyrebird song shows that shrike-
thrushes have a exible acceptance threshold and that they inte-
grate cues to distinguish model from mimetic songs. Traditional
theory argues that it is impossible to reduce the risk of responding
to a false signal, such as an imitation, without simultaneously
increasing the risk of failing to respond to a real signal, and vice
versa (Wiley 1994). However, animals can mitigate the costs of
mistakenly responding to a mimic by varying their threshold
criteria for signal identication (acceptance) depending on other
cues (exible acceptance thresholds:Reeve 1989). For example,
several host species of brood parasites are more likely to reject
unusual eggs if they have recently been exposed to a cuckoo (Davies
& Brooke 1988;Moksnes & Røskaft 1989;Davies et al. 1996;Bártol
et al. 2002), or had additional evidence that cuckoos were present
(Hauber et al. 2006;Stokke et al. 2008;Langmore et al. 2009). In
our study, shrike-thrushes appeared to use the context of the signal
to decide whether or not to approach playback of a mimetic song.
Contrary to the predictions of signal detection theory, raising their
acceptance threshold did not simultaneously reduce the chance
they would fail to respond to their own song, although further
experiments are required to explore this hypothesis. To our
knowledge, only one other study has formally tested the use of
context by model species in a vocal mimicry system (Owen-Ashley
et al. 2002). However, this study found that models responded
weakly to mimetic calls regardless of context. In contrast, our study
adds to the growing literature showing that signal acceptance
thresholds are plastic and context dependent.
Acoustic Differences Between Model and Mimetic Songs
Our comparison between the acoustic parameters of mimicked
and model songs revealed few differences. Lyrebirds accurately
reproduced the temporal patterning of elements that characterize
shrike-thrush songs. This is an unusual characteristic in birds that
Number of elements in son
Lyrebird imitation
Number of songs
Figure 6. The number of songs with different numbers of elements sung by both grey
shrike-thrushes and superb lyrebirds. The sample contained one song sung by a lyre-
bird and one by a shrike-thrush for 19 different song types. Statistics are shown in
Table 5.
Table 5
Differences between the acoustic structures of model and mimetic songs
Effects Estimate SED LSD df F P
Number of elements*1.2105 0.3613 0.7326 1, 36.0 11.23 0.002
Song length*0.3374 0.1072 0.2173 1, 36.0 9.91 0.003
Sound duration 0.14184 0.04958 0.1042 1, 18.0 8.19 0.010
Average element length 0.004723 0.005139 0.01080 1, 18.0 0.84 0.37
Peak frequencyy0.005280 0.008055 0.01692 1, 18.0 0.43 0.52
Element rate*0.05544 0.1660 0.3367 1, 36.0 0.11 0.74
Frequency range 119 76.4 150.7 1, 176.6 2.43 0.121
Peak frequencyy,z1.975 58.49 0.05412 1, 179.0 w0 0.973
Maximum frequency 55.7 99.06 195.5 1,177.3 0.32 0.575
RMS amplitudex501.6 444.9 877.8 1,181.9 1.27 0.261
Duration 0.00267 0.006125 0.01209 1, 178.5 0.19 0.663
Parameters were modelled in univariate linear mixed models or linear models with species as a xed effect. Song-level analyses contained Song typemodelled as a random
term unless the variance of this component approximated zero, in which case Song type was dropped from the model (Payne et al. 2010). For element-level analyses, the
phrase within the song, nested in song type, was modelled as a random term. Estimates of the differences between the means (lyrebirdeshrike-thrush), the standard error of
difference between the means (SED) and the approximate least signicant differences (LSD) at the 5% level are shown.
These models were run without the variable song typeas a random effect.
This variable was log transformed to normalize the residuals.
Frequency with maximum power.
Root-mean square of the amplitude across the duration of the element.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e14101408
imitate many different sounds (versatile avian mimics), which
more commonly imitate fragments of song or short vocalizations
(Hindmarsh 1984;Ferguson et al. 2002). In addition, lyrebird
reproductions of individual elements within the model song were
indistinguishable from model elements. However, lyrebirds may
not be able to imitate all model elements as accurately as shrike-
thrush songs, as lyrebirds are less accurate mimics of the whip
element in the eastern whipbird song, perhaps because of the large
and rapid frequency change (Zann & Dunstan 2008).
In our study, mimetic and model songs differed only in the
number of elements (Table 5), causing mimetic songs to be on
average the shorter of the two. Lyrebirds abridged model songs by
reducing the number of repetitions of particular element types
while conserving the order and number of different element types
and thus the structural complexity of the model song (Fig. 1).
This suggests that differences between mimic and model were
unlikely to be caused by limitations of the lyrebirds auditory
system. Instead, our results support previous speculation that
lyrebirds are not passive imitators of common sounds (Higgins et al.
2001;Zann & Dunstan 2008). Rather, lyrebirds appear either to
imitate selectively shorter examples of model songs or to abridge
the songs they hear. In our study, shrike-thrushes might have used
the differences in element number to distinguish between model
and mimetic songs, but conrmation requires further experiments.
Imitations of shrike-thrush songs are not the only imitations
that lyrebirds appear to shorten. Zann & Dunstan (2008) showed
that lyrebird imitations of male whipbird song had a shorter
introductory toneelement than model songs, and lyrebirds appear
to truncate imitations of the vocalizations of other species such as
the laughcalls of laughing kookaburras, Dacelo novaeguineae
(Smith 1988, A. H. Dalziell, personal observation). Such shortening
of mimicked sounds may be a feature common to versatile avian
mimics. For example, imitations by northern mockingbirds of the
weepcalls produced by Florida scrub-jays were shorter in element
duration than the model species itself (Owen-Ashley et al. 2002).
Why are Lyrebird Imitations Shorter Than Model Songs?
Lyrebirds might sing shorter versions of model songs as a result
of selection pressures imposed by a conspecic receiver. Short
imitations may arise if male lyrebirds need to balance two
requirements: to sing highly accurate imitations, but also to
demonstrate their versatility to a conspecic receiver who may
listen for only a short time. This is a modication of the Jack of all
tradeshypothesis, which predicts that mimetic accuracy is traded
off against mimetic versatility (Edmunds 2000;Zollinger & Suthers
2004). However, rather than being the result of limitations of the
vocal apparatus of the mimic (Zollinger & Suthers 2004), differ-
ences in the length of model and mimetic sounds may reect
conicting signal requirements. Alternatively, male lyrebirds may
sing shorter songs to facilitate discrimination by conspecics
between lyrebirds and model species, although it seems plausible
that visual cues or other acoustic cues, such as song context, should
be sufcient for discrimination. Further research is required to
determine why lyrebirds abridge model songs and whether it is
a widespread strategy among versatile mimics.
Mimetic Accuracy in Nondeceptive Mimicry Systems
Our bioassays combined with acoustic analysis revealed
remarkably accurate mimicry of a complex auditory signal by
a nondeceptive mimic. Given the motor challenges of producing
song in birds (Gil & Gahr 2002;Catchpole & Slater 20 08;Podos et al.
2009), our results are consistent with selection for accurate
mimicry in male lyrebirds and suggest that there is selection for
discrimination in receivers. Future studies will need to conduct
playback experiments to other lyrebirds to conrm whether
conspecics are the receivers selecting for accurate mimicry. In
nondeceptive mimicry systems the conspecic receiver conceivably
has a more complex cognitive task than a heterospecic receiver.
This is because the conspecic receiver not only has to discriminate
between model and mimetic vocalizations, but it also has to
discriminate between mimics on the basis of their mimetic ability.
Overall, our results highlight the complexity of adaptations evolved
by mimics and the value of examining the similarities and differ-
ences between model and mimetic signals.
We are grateful to Alexandra Dorland, Alex Maisey, Simon
Despoja, Sarah Stuart-Smith and Pamela Fallow for eld assistance.
We thank Jan Incoll, Norm Carter and the Sherbrooke Lyrebird
Study Group for advice and permission to study lyrebirds in Sher-
brooke Forest. Parks Victoria granted us permission to work in the
Dandenong Ranges National Park and provided invaluable logistical
assistance. Robert Phillips and Bill Incoll helped with the equip-
ment. We also thank Emlyn Williams for assistance with the
statistics, the late Richard Zann for advice, Michelle Hall, Andrew
Cockburn and Naomi Langmore for equipment loans and
comments that improved the experimental design and the manu-
script. Anja Skroblin, Branislav Igic, Elsie Krebs, David Greene, Justin
Welbergen, Pamela Fallow and three anonymous referees also
provided helpful comments on the manuscript. This study was
supported by two Birds Australia Stuart Leslie Awards to A.H.D., an
Australian Geographic Society Research Award to A.H.D., an
Australian Postgraduate Award to A.H.D., an Australian National
University College of Science Scholarship to A.H.D. and an ARC
Discovery Grant to R.D.M.
Attenborough, D. 2002. Signals and songs. Episode 2. In: The Life of Birds. Bristol:
BBC Natural History Unit [DVD].
Bártol, I., Karcza, Z., Moskát, C., Røskaft, E. & Kisbenedek, T. 2002. Responses of
great reed warblers, Acrocephalus arundinaceus, to experimental brood para-
sitism: the effects of a cuckoo, Cuculus canorus, dummy and egg mimicry.
Journal of Avian Biology,33, 420e425.
Bates, H. W. 1862. Contributions to an insect fauna of the Amazon Valley. Lepi-
doptera: Heliconidae. Transactions of the Linnean Society of London,23,
Baylis, J. R. 1982. Avian vocal mimicry: its function and evolution. In: Acoustic
Communication in Birds (Ed. by D. E. Kroodsma, E. H. Miller & H. Ouellet), pp.
51e83. New York: Academic Press.
Beecher, M. D. & Campbell, S. E. 2005. The role of unshared songs in singing
interactions between neighbouring song sparrows. Animal Behaviour,70,
Blumenrath, S. H., Dabelsteen, T. & Pedersen, S. B. 2007. Vocal neighbour-mate
discrimination in female great tits despite high song similarity. Animal Behav-
iour,73, 789e796.
Botero, C. A., Riveros, J. M. & Vehrencamp, S. L. 2007. Relative threat and recog-
nition ability in the responses of tropical mockingbirds to song playback. Animal
Brenowitz, E. A. 1982. Aggressive response of red-winged blackbirds to mocking-
bird song imitation. Auk,99, 584e586.
Catchpole, C. K. & Slater, P. J. B. 20 08. Bird Song: Biological Themes and Variations.
2nd edn. Cambridge: Cambridge University Press.
Charif, R. A., Mitchell, S. & Clark, C. W. 1995. Canary 1.2 Users Manual. Ithaca, New
York: Cornell Laboratory of Ornithology.
Cheney, K. L. 2010. Multiple selective pressures apply to a coral reef sh mimic:
a case of Batesian-aggressive mimicry. Proceedings of the Royal Society B,277,
Cheney, K. L. & Marshall, N. J. 2009. Mimicry in coral reef sh: how accurate is this
deception in terms of color and luminance? Behavioral Ecology,20, 459e468.
Chisholm, A. G. 1932. Vocal mimicry among Australian birds. Ibis,2, 605e624.
Chittka, L. & Osorio, D. 2007. Cognitive dimensions of predator responses to
imperfect mimicry. PLoS Biology,5, e339.
Colegrave, N. & Ruxton, G. D. 2003. Condence intervals are a more useful
complement to nonsignicant tests than are power calculations. Behavioral
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e1410 1409
Coleman, S. W., Patricelli, G. L., Coyle, B., Siani, J. & Borgia, G. 2007. Female
preferences drive the evolution of mimetic accuracy in male sexual displays.
Biology Letters,3, 463e466.
Davies, N. B. & Brooke, M. d. L. 1988. Cuckoos versus reed warblers: adaptations
and counteradaptations. Animal Behaviour,36, 262e284.
Davies, N. B., Brooke, M. D. L. & Kacelnik, A. 1996. Recognition errors and prob-
ability of parasitism determine whether reed warblers should accept or reject
mimetic cuckoo eggs. Proceedings of the Royal Society B,263, 925e931.
Dobkin, D. S. 1979. Functional and evolutionary relationships of vocal copying
phenomena in birds. Zeitschrift für Tierpsychologie,50,348e363.
Dominey, W. J. 1980. Female mimicry in male bluegill sunsh: a genetic poly-
morphism? Nature,284, 546e548.
Edmunds, M. 2000. Why are there good and poor mimics? Biological Journal of the
Linnean Society,70, 459e466.
Estrada, C. & Jiggins, C. D. 2008. Interspecic sexual attraction because of conver-
gence in warning colouration: is there a conict between natural and sexual
selectio n in mimet ic species? Journal of Evolutionary Biology,21,749e760.
Ferguson, J. W. H., van Zyl, A. & Delport, K. 2002. Vocal mimicry in African Cos-
sypha robin chats. Journal für Ornithologie,143 ,319e330.
Flower, T. 2011. Fork-tailed drongos use deceptive mimicked alarm calls to steal
food. Proceedings of the Royal Society B,278, 1548e1555.
Garamszegi, L. Z., Eens, M., Pavlova, D. Z., Aviles, J. & Møller, A. P. 2007.
A comparative study of the function of heterospecic vocal mimicry in Euro-
pean passerines. Behavioral Ecology,18,1001e1009.
Gil, D. & Gahr, M. 2002. The honesty of bird song: multiple constraints for multiple
traits. Trends in Ecology & Evolution,17,133e141.
Goodale, E. & Kotagama, S. W. 2006a. Context-dependent vocal mimicry in
a passerine bird. Proceedings of the Royal Society B,273, 875e880.
Goodale, E. & Kotagama, S. W. 2006b. Vocal mimicry by a passerine bird attracts
other species involved in mixed-species ocks. Animal Behaviour,72,471e477.
Grafen, A. & Hails, R. 2002. Modern Statistics for the Life Sciences. Oxford: Oxford
University Press.
Gross, M. R. 1996. Alternative reproductive strategies and tactics: diversity within
sexes. Trends in Ecology & Evolution,11,92e98.
Harper, G. R. & Pfennig, D. W. 2007. Mimicry on the edge: why do mimics vary in
resemblance to their model in different parts of their geographical range?
Proceedings of the Royal Society B,274, 1955e19 61.
Hauber, M. E., Moskát, C. & Bán, M. 2006. Experimental shift in hostsacceptance
threshold of inaccurate-mimic brood parasite eggs. Biology Letters,2,177e180.
Higgins, P. J. & Peter, J. M. 2002. Pardalotes to Shrike-thrushes. Handbook of
Australian, New Zealand & Antarctic Birds. Melbourne: Oxford University Press.
Higgins, P. J., Peter, J. M. & Steele, W. K. 2001. Tyrant-ycatchers to Chats. Handbook
of Australian, New Zealand & Antarctic Birds. Melbourne: Oxford University
Hindmarsh, A. M. 1984. Vocal mimicry in starlings. Behaviour,90, 302e324.
Hindmarsh, A. M. 1986. The functional-signicance of vocal mimicry in song.
Behaviour,99,87e10 0.
Holen, Ø. H. & Johnstone, R. A. 2004. The evolution of mimicry under constraints.
American Naturalist,164, 598e613.
Howard, R. D. 19 74. I nuence of sexual selection and interspecic competition on
mockingbird song Mimus polyglottos.Evolution,28, 428e438.
Illes, A. E., Hall, M. L. & Vehrencamp, S. L. 2006. Vocal performance inuences
male receiver response in the banded wren. Proceedings of the Royal Society B,
273, 1907e1912.
Johnstone, R. A. 2002. The evolution of inaccurate mimics. Nature,418, 524e526.
Kelley, L. A., Coe, R. L., Madden, J. R. & Healy, S. D. 2008. Vocal mimicry in
songbirds. Animal Behaviour,76,521e528.
Kenyon, R. F. 1972. Polygyny among superb lyrebirds in Sherbrooke forest park,
Kallista, Victoria. Emu,72,70e76.
Kikuchi, D. W. & Pfennig, D. W. 2010. Predator cognition permits imperfect coral
snake mimicry. American Naturalist,176, 830e834.
de Kort, S. R., Eldermire, E. R. B., Cramer, E. R. A. & Vehrencamp, S. L. 2009. The
deterrent effect of bird song in territory defense.Behavioral Ecology,20, 200e206.
Kroodsma, D. E. 2004. The diversity and plasticity of birdsong. In: Natures Music:
the Science of Birdsong (Ed. by P. Marler & H. Slabbekoorn), pp. 108e131.
Amsterdam: Elsevier Academic Press.
Langmore, N. E., Hunt, S. & Kilner, R. M. 2003. Escalation of a coevolutionary arms
race through host rejection of brood parasitic young. Nature,422,157e160.
Langmore, N. E., Maurer, G., Adcock, G. J. & Kilner, R. M. 2008. Socially acquired
host-specic mimicry and the evolution of host races in Horselds bronze-
cuckoo Chalcites basalis.Evolution,62, 1689e1699.
Langmore, N. E., Cockburn, A., Russell, A. F. & Kilner, R. M. 2009. Flexible cuckoo
chick-rejection rules in the superb fairy-wren. Behavioral Ecology,20,978e984.
Lemaire, F. 1975. Le chant de la rousserolle verderolle (Acrocephalus palustris):
délité des imitations et relations avec les espèces imitées et avec les con-
génères. Gerfaut,65,3e28.
Lill, A. 1979. Assessment of male parental investment and pair bonding in the
polygamous superb lyrebird. Auk,96, 489e498.
McGuire, L., Van Gossum, H., Beirinckx, K. &Sherratt, T. N. 2006. An empirical test
of signal detection theory as it applies to Batesian mimicry. Behavioural
Processes,73, 299e307.
Moksnes, A. & Røskaft, E. 1989. Adaptations of meadow pipits to parasitism by the
common cuckoo. Behavioral Ecology and Sociobiology,24,25e30.
Molles, L. E. & Vehrencamp, S. L. 2001. Songbird cheaters pay a retaliation cost:
evidence for auditory conventional signals. Proceedings of the Royal Society B,
Müller, F. 1878. On the advantages of mimicry in butteries. Zoologischer Anzeiger,1,
Nicholls, J. A. 2008. Site specicity in advertisement calls and responses to play-
backs of local and foreign call variants in satin bowerbirds, Ptilonorhynchus
violaceus.Behavioral Ecology and Sociobiology,62,831e841.
Norman, M. D., Finn, J. & Tregenza, T. 1999. Female impersonation as an alter-
native reproductive strategy in giant cuttlesh. Proceedings of the Royal Society
Owen-Ashley, N. T., Schoech, S. J. & Mumme, R. L. 2002. Context-specic response
of Florida scrub-jay pairs to northern mockingbird vocal mimicry. The Condor,
104, 858e865.
Payne, R. 2010a. A Guide to Regression, Nonlinear and Generalized Linear Models in
GenStat. Hemel Hempstead: VSN International.
Payne, R. W. E. 2010b. Guide to GenStat. Part 2: Statistics. Hemel Hempstead: VSN
Payne, R., Welham, S. & Harding, S. 2010. A Guide to REML in GenStat. Hemel
Hempstead: VSN International.
Pekár, S., Jarab, M., Fromhage, L. & Herberstein, M. E. 2011. Is the evolution of
inaccurate mimicry a result of selection by a suite of predators? A case study
using Myrmecomorphic spiders. American Naturalist,178 ,124e134.
Podos, J., Lahti, D. C. & Moseley, D. L. 2009. Vocal performance and sensorimotor
learning in songbirds. Advances in the Study of Behavior,40,159e195.
Reeve, H. K. 1989. The evolution of conspecic acceptance thresholds. American
Robinson, F. N. & Curtis, H. S.1996. The vocal displays of the lyrebirds (Menuridae).
Emu,96, 258e275.
Ruxton, G. D. & Speed, M. P. 2005. Evolution: a taste for mimicry. Nature,433,
Searcy, W. A. & Brenowitz, E. A. 1988. Sexual differences in species recognition of
avian song. Nature,332,152e154.
Sherratt, T. N. 2002. The evolution of imperfect mimicry. Behavioral Ecology,13,
Smith, L. H. 1988. The Life of the Lyrebird. Melbourne: Heinemann.
Starrett, A. 1993. Adaptive resemblance: unifying concept for mimicry and crypsis.
Biological Journal of the Linnean Society,48, 299e317.
Stoddard, M. C. & Stevens, M. 2010. Pattern mimicry of host eggs by the common
cuckoo, as seen through a birdseye.Proceedings of the Royal Society B,277,
Stoddard, P. K. 1996. Vocal recognition in territorial passerines. In: Ecology and
Evolution of Acoustic Communication in Birds (Ed. by D. E. Kroodsma &
E. H. Miller), pp. 356e374. Ithaca, New York: Cornell University Press.
Stokke, B. G., Hafstad, I., Rudolfsen, G., Moksnes, A., Moller, A. P., Roskaft, E. &
Soler, M. 2008. Predictors of resistance to brood parasitism within and among
reed warbler populations. Behavioral Ecology,19,612e620.
Vane-Wright, R. I. 1980. On the denition of mimicry. Biological Journal of the
Linnean Society,13,1e6.
Vehrencamp, S. L., Hall, M. L., Bohman, E. R., Depeine, C. D. & Dalziell, A. H. 2007.
Song matching, overlapping, and switching in the banded wren: the senders
perspective. Behavioral Ecology,18, 849e859.
Vereecken, N. J. & McNeil, J. N. 2010. Cheaters and liars: chemical mimicry at its
nest. Canadian Journal of Zoology,88,725e752.
Whiting, M. J., Webb, J. K. & Keogh, J. S. 2009. Flat lizard female mimics use sexual
deception in visual but not chemical signals. Proceedings of the Royal Society B,
276, 1585e1591.
Wiley, R. H. 1994. Errors, exaggeration, and deception in animal communication. In:
Behavioral Mechanisms in Evolutionary Ecology (Ed. by L. Real), pp. 157e189.
Chicago: University of Chicago Press.
Zann, R. & Dunstan, E. 2008. Mimetic song in superb lyrebirds: species mimicked
and mimetic accuracy in different populations and age classes. Animal Behav-
iour,76, 1043e1054.
Zollinger, S. A. & Suthers, R. A. 2004. Motor mechanisms of a vocal mimic:
implications for birdsong production. Proceedings of the Royal Society B,271,
Zoos South Australia 2009. Superb Lyrebird Imitating Construction Work. Adelaide Zoo
online video.¼WeQjkQpeJwY. Accessed: 11
August 2011.
A. H. Dalziell, R. D. Magrath / Animal Behaviour 83 (2012) 1401e14101410
... A major conceptual problem with the by-product hypothesis for the production of vocal mimicry during advertisement song is that it does not adequately explain the maintenance of mimetic accuracy (Dalziell & Magrath, 2012;Dalziell et al., 2015;Kelley et al., 2008;Zann & Dunstan, 2008). If females are simply selecting mates that produce the most versatile song, then in theory there is no selection for mimetic accuracy, and mimetic resemblance should erode over time. ...
... Superb lyrebirds are versatile and accurate vocal mimics (Dalziell & Magrath, 2012;Zann & Dunstan, 2008) but despite considerable interest, it has not been clear why male lyrebirds mimic. Superb lyrebirds have a lek-like mating system and are endemic to southeastern Australia (Higgins et al., 2001). ...
... In the wild, males perform a loud flamboyant song consisting of song types exclusive to lyrebirds and extreme levels of imitations of foreign sounds, most commonly the songs and calls of other species of bird (Higgins et al., 2001;Zann & Dunstan, 2008). Imitated sounds are acoustically diverse and astonishingly accurate (Dalziell & Magrath, 2012;Higgins et al., 2001;Zann & Dunstan, 2008), and make up 70e80% of vocal output (Robinson, 1974;Robinson & Curtis, 1996). While both sexes mimic, only males mimic during intersexual interactions, and females mimic primarily in the contexts of femaleefemale interactions and nest defence (Dalziell & Welbergen, 2016a). ...
Mimicry has long been a focus of research, but little is known about how and why many species of bird incorporate imitations of heterospecific sounds into their vocal displays. Crucial to understanding mimetic song is determining what sounds are mimicked and in what contexts such mimicry is produced. The superb lyrebird, Menura novaehollandiae, is a large oscine passerine with a lek-like mating system. Both sexes are accurate and versatile vocal mimics of the vocalizations of other species, but little is known about how males deploy their repertoire of mimicked sounds across contexts. Using extended focal watches, we recorded adult males displaying during the breeding season. We found that males mimicked heterospecific songs and nonalarm calls during ‘recital’ displays usually performed while they were perched and visually inconspicuous. In contrast, during visually conspicuous ‘dance’ displays, commonly performed on display mounds, males only mimicked heterospecific alarm calls. While much rarer than recital displays, dance displays were associated with the final stages of mate choice preceding copulation. These results provide the first evidence of any species varying its repertoire of mimicked sounds with different sexual contexts. Previous work suggests that mimicry in dance displays functions deceptively to manipulate the antipredator responses of females during the final stages of courtship. However, the structure and context of recital mimicry closely resembles the sexual advertisement song performed by nonmimicking songbirds. Given the importance of mimicry in the acoustic ecology of lyrebirds, our results suggest that with recital song males advertise the quality of their mimicry as it likely benefits both male and female offspring. Our finding that male superb lyrebirds mimic functionally distinct heterospecific vocalizations during different modes of courtship suggests that the evolution and maintenance of avian vocal displays are more complex than previously thought.
... Second, Albert's lyrebirds enhance acoustic contrast by juxtaposing acoustically dissimilar units more than expected by chance. The recital mimicry of lyrebirds is suspected to function to attract mates [41,63,64], and the combination of singing with immediate variety and increasing acoustic contrast between successive units strongly implies that mimetic sequences have been selected to maximize perceived repertoire variation or complexity. All acoustic measurements showed high contrast between consecutive units, with the exception of duration, which was similar between consecutive units. ...
... Conversely, Albert's lyrebirds appear to favour diversity by singing with immediate variety, although accuracy is still likely important. Further, superb lyrebirds appear to abridge mimetic units by removing repetitions of certain elements within imitated multi-element sounds, while maintaining the original element order and number of element types [64], suggesting that both extant lyrebird species use several strategies to enhance the perception of mimetic repertoire complexity, while maintaining the complexity of individual mimetic units. Using contrast to increase the efficacy of signals has been shown in visual signals [25] but rarely in acoustic signals [10,28,31]. ...
Full-text available
Most studies of acoustic communication focus on short units of vocalization such as songs, yet these units are often hierarchically organized into higher-order sequences and, outside human language, little is known about the drivers of sequence structure. Here, we investigate the organization, transmission and function of vocal sequences sung by male Albert's lyrebirds ( Menura alberti ), a species renowned for vocal imitations of other species. We quantified the organization of mimetic units into sequences, and examined the extent to which these sequences are repeated within and between individuals and shared among populations. We found that individual males organized their mimetic units into stereotyped sequences. Sequence structures were shared within and to a lesser extent among populations, implying that sequences were socially transmitted. Across the entire species range, mimetic units were sung with immediate variety and a high acoustic contrast between consecutive units, suggesting that sequence structure is a means to enhance receiver perceptions of repertoire complexity. Our results provide evidence that higher-order sequences of vocalizations can be socially transmitted, and that the order of vocal units can be functionally significant. We conclude that, to fully understand vocal behaviours, we must study both the individual vocal units and their higher-order temporal organization.
... Trait comparisons in previous studies have included analyses of colour (e.g. Pek ar & Jarab, 2011), movement or trajectories (Shamble, Hoy, Cohen, & Beatus, 2017), sound (Dalziell & Magrath, 2012), chemical signals (Haynes, Gemeno, Yeargan, Millar, & Johnson, 2002), multivariate biometric measurements (Penney et al., 2012), quantification of pattern and/or colour (Kikuchi & Pfennig, 2010) and grouping into accuracy classes based on the accumulation of mimetic morphological traits (Pek ar, 2014). While general methods have been developed for the quantitative measurement of colour, pattern and movement (see Maia, Gruson, Endler, & White, 2019;McLean & Skowron Volponi, 2018;Van Belleghem et al., 2018), different methods for measuring multivariate or morphological traits are repeatedly developed by researchers and are published in different research papers, making it difficult to compare and select the optimum method to address a specific research question. ...
... As an alternative to actual receivers, the responses of surrogate receivers may be used. Surrogate receivers have included humans (Bae, Kim, Sherratt, Caro, & Kang, 2019), other animals such as pigeons (Dittrich, Gilbert, Green, McGregor, & Grewcock, 1993), computer algorithms (Bain et al., 2007) or even the model from the mimicry complex in question (Dalziell & Magrath, 2012). Despite advances in consideration of animal ethics and the methodological advantages of surrogate receiver trials, difficulty of implementation is likely limiting their more widespread use. ...
Full-text available
The existence of substantial variation in the accuracy of resemblance of mimics to their models remains a fundamental evolutionary question, and the ability to quantify mimetic accuracy is key to addressing this question. Mimicry researchers have used a wide variety of methods to measure accuracy, which can be broadly grouped into (1) receiver responses, such as predator trials, and (2) trait measurements. While receiver responses are fundamental to mimicry research, logistical and ethical concerns mean that only a minority of studies include tests with relevant predator receivers. Trait measurement methods are therefore vital, both to supplement receiver response methods and as standalone methods for quantifying accuracy. Here, we collect and describe five methods for measuring the accuracy of visual mimicry. Three of the methods quantify the similarity of mimetic phenotypic traits: linear morphometrics, geometric morphometrics and biometric trait table. Two methods measure the responses of proxy receivers: machine learning and human assessment. These methods are applicable to any type of visual mimetic traits. We evaluate and compare the effectiveness and cost of these methods by assessing the accuracy of a variety of visual ant mimics to their ant models. The methods vary in the types and number of traits being measured, whether traits are measured directly (trait measurement methods) or indirectly (receiver responses) and in the effort and skills required for implementation. Despite the methods measuring different visual characteristics, the accuracy scores from all five methods were positively correlated when applied to ant mimics, suggesting some generality in how mimics rank in their accuracy. We provide practical advice on the use of these five methods and provide open-source implementations of the scripts used in our analysis. The scripts may be freely reused or used as the basis for new implementations. Our aim is to aid researchers to select and implement methods that are appropriate and suitable for future mimicry research.
... The cases of the Lira bird (Menuranovaehollandiae), who includes in its own repertory environmental and animal sounds collected from the surrounding territory, thus offering an acoustic mapping of it (A.H. Dalziell and R.D. Magrath 2012), and that of the Australian magpie which exchanges information on food sources and migratory routes whit conspecifics through songs (L.J. Rogers and G. Kaplan 1998, p. 86) are well known. Well-documented is also the use of vocalizations with information and referential functions in birds such as the northern royal gull (Larusargentatus), or the Indicator indicator, that uses the song to locate food resources. ...
... The cases of the Lira bird (Menuranovaehollandiae), who includes in its own repertory environmental and animal sounds collected from the surrounding territory, thus offering an acoustic mapping of it (A.H. Dalziell and R.D. Magrath 2012), and that of the Australian magpie which exchanges information on food sources and migratory routes whit conspecifics through songs (L.J. Rogers and G. Kaplan 1998, p. 86) are well known. Well-documented is also the use of vocalizations with information and referential functions in birds such as the northern royal gull (Larusargentatus), or the Indicator indicator, that uses the song to locate food resources. ...
Full-text available
Predictability is a relational, historically and culturally shaped concept. A phenomenon can be defined as predictable in relation to the available knowl- edge, instruments and methods, as well as the epistemic horizons in which its explanation is located (E. Fox Keller 2002). From this point of view, the last hundred years in the field of comparative study of animal behaviours and minds have led to radical changes in our epistemic horizon by extending our understanding of what we have to consider predictable or unpredictable in animal behaviours. Indeed, this historical phase has seen the discovery of entire classes of phenomena related to the expression of animal thought, languages, societies and cultures, which in the preceding decades would have been considered impossible within relevant scientific areas as anthropology, comparative psychology, theoretical and moral philosophy, linguistic and cul- tural studies. For instance, new sound analysis technologies developed over the last decades have allowed a decoding of bird songs that, pushing the limits of our sensory and cognitive channels, allowed us to appreciate its syntactic complexity and the richness of its intraspecific differentiations (cultural tra- ditions), radically modifying our views. In the last ten years, the analysis of the cerebral structures of birds has also demonstrated the presence of areas for processing and decoding acoustic communication similar to those found in our central nervous system. The brain of parrots, corvides and sparrows has been shown to have a higher neuronal density than that of mammals, including primates. Higher is also the percentage of neurons that are part of the brain areas destined to the so-called “superior functions” as the bark in mammals and the Pallium in birds. A research directed by Clifton W. Rags- dale, of the University of Chicago, has recently confirmed a close affinity between the mammal neocortex and the birds’ DVR, or ventricular backbone (J. Dugas-Ford, J.J. Rowell, C.W. Ragsdale 2012). In the last fifty years, the use of microphones suitable for recording in the deep sea, and the com- puterized analysis of sounds, made us begin to understand the complexity of whale songs, or the amazing analogies of the dolphins’ whistling with human names. In the same span of time, progress in the techniques of brain analysis has shown that the cetacean’s paralimbic system makes possible a very rapid integration of perceptions and a richness of information which is considered superior to the human one, and that cetacean such as humpback whales and dolphins have brains with even more cortical convolutions than humans (R. D. Fields 2008). These developments open up new perspectives, making it necessary to overcome, both in scientific training and in research, classical dichotomies such as nature/culture, Natural Sciences/Humanities. They integrate the horizon of the foreseeable, including the expectation of a gradual extension of the class of organisms that we should recognize as “cultural animals”, as well as of the phenomena to which this chapter is devoted: the cases of Cul- tural Convergent Evolution between different species.
... Many bird species have learned to incorporate the songs of other species into their own songs in a process defined as mimicry. Whilst the Superb Lyrebird Menura novaehollandiae is the classic example of a mimic (Dalziell & Magrath 2012), many other Australian birds are excellent mimics, including Olive-backed Oriole Oriolus sagittatus (Diamond 1982), Brown Thornbill Acanthiza pusilla and Spotted Bowerbird Chlamydera maculata (Kelley & Healy 2010). Birds mimic other species because it provides them with a fitness benefit in some way, for example through mate acquisition, foraging efficiency, competitor deception, or nest defence Dalziell et al. 2015). ...
Full-text available
The Regent Honeyeater Anthochaera phrygia is widely understood to mimic other species. To the best of our knowledge, amongst the Meliphagidae mimicry is unique to the Regent Honeyeater. An obvious question, therefore, is why does the Regent Honeyeater appear to be the only honeyeater to mimic other bird species? After spending 5 years monitoring the Regent Honeyeater throughout its range, here I propose that the incorporation of other species’ songs into the repertoires of Regent Honeyeater should not be defined as “mimicry”. Instead, I suggest that interspecific singing is maladaptive, confers no fitness advantage and is a consequence of the Regent Honeyeater occurring at population densities far below those in which it evolved. Low population density appears to be compromising the ability of some individuals to learn the species-specific song, probably due to a lack of other Regent Honeyeater demonstrators to learn songs from during a critical song-learning period in early life.
... The mimic -male superb lyrebird Male superb lyrebirds routinely incorporate vocal imitations of heterospecifics into their vocal displays, 48,49 but while these mimetic vocalizations are implicated in mate attraction, the selective mechanisms are unclear. 20,50 During the winter when females lay their single clutch of one egg, individual males defend territories in which they construct several circular 'display mounds' (1 -2 m in diameter) on the forest floor, and these male territories tend to be clustered. Males play no role in the raising of young 51 and once all females are incubating, males moult their elaborate tail feathers and cease displaying. ...
Darwin argued that females’ “taste for the beautiful” drives the evolution of male extravagance,but sexual selection theory also predicts that extravagant ornaments can arise from sexual conflict and deception. The sensory trap hypothesis posits that elaborate sexual signals can evolve via antagonistic coevolution whereby one sex uses deceptive mimicry to manipulate the opposite sex into mating. Here, the success of deceptive mimicry depends on whether it matches the receiver’s percept of the model, and so has little in common with concepts of aesthetic judgement and ‘beauty.’ We report that during their song and dance displays, male superb lyrebirds (Menura novaehollandiae) create an elaborate acoustic illusion of a mixed-species mobbing flock. Acoustic analysis showed that males mimicked the mobbing alarm calls of multiple species calling together, enhancing the illusion by also vocally imitating the wingbeats of small birds. A playback experiment confirmed that this illusion was sufficient to fool avian receivers. Furthermore, males produced this mimicry only (1) when females attempted to exit male display arenas, and (2) during the lyrebirds’ unusually long copulation, suggesting that the mimicry aims to prevent females from prematurely terminating these crucial sexual interactions. Such deceptive behavior by males should select for perceptual acuity in females, prompting an inter-sexual co-evolutionary arms race between male mimetic accuracy and discrimination by females. In this way the elaboration of the complex avian vocalizations we call ‘song’ could be driven by sexual conflict, rather than a female’s preference for male extravagance.
... The restriction of suitable habitat within the Albert's lyrebird's range also allows us to easily map out likely paths of genetic or cultural transmission. Furthermore, Albert's lyrebirds are one of only two extant species of the Menuridae, an oscine passerine family known for their diverse vocal repertoires including highly accurate vocal mimicry in both species (Dalziell & Magrath, 2012;Dalziell & Welbergen, 2016;Putland et al., 2006;Robinson & Curtis, 1996;Zann & Dunstan, 2008). The species' extraordinary mimetic ability means that morphological and cognitive constraints are likely to have little impact on vocal abilities and are therefore unlikely to drive variation among individuals or populations. ...
Full-text available
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 in Australia, allowing us to map likely paths of cultural transmission using a species distribution model and least cost paths. We use quantitative methods to divide 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 of investigating spatial patterns within seemingly discrete behavioral traits at multiple levels of organization.
Despite Darwin’s declaration that the role of the female songbird is primarily to listen, we now know female song is widespread among many songbird species, including northern mockingbirds (Mimus polyglottos). Much less is known about whether female songbirds imitate the sounds of other species. By examining the audio from nest cameras, we determined that female mockingbirds use vocal mimicry when they sing on the nest, but that compared to males they mimic less frequently and with less variety. Our study opens new avenues of research into the causation, development, function, and evolution of female vocal mimicry.
The introductory part of the chapter will display its whole purpose and topic. First of all, this section of the book aims to clarify the situation of both humanities and behavioural sciences after the discovery of animal thought and cultures. In other words, after the fundamental theoretical assumptions of these two scientific traditions were empirically refuted: the idea of man as the only thinking and cultural animal and other animals as mechanically explainable entities. From this the need for a critical and self-critical re-foundation of both humanities and behavioural sciences arises. A process which is in fact already underway but is still not reflecting enough on the level of theoretical elaboration and on the practical level of a reform of scientific training and research. This need for a new organization of university and post-university education, transversal to the bipartition between human and life sciences, and of meta-disciplinary forms of organization of the basic and applied research, on which the chapter aims to focus, is in various respects close to the goal of a radical self-reform of humanities proposed in Martinelli’s Manifesto of Numanities (Martinelli 2016). In this specific case, the pivot or pillar of this “revolution” of humanities is identifiable in the attempt to reorganize the humanistic field as Interspecific Cultural Studies. That is, as a meta-disciplinary area able to assume a post-anthropocentric approach towards its topics and collaborate, each sector starting from its own specificity, on an enterprise that we are attempting in our age for the first time: to insert the study of past and present human cultures into the broader context of a comparative study of all animal cultures, existing and existed. This enterprise would imply, as its indissoluble condition, the commitment to protect the survival of these animal cultures and of the natural environments in which they have evolved. The following section presents, in extreme synthesis, the state of the art of cultural ethology. The third section introduces, in an equally concise way, the emerging etho-centric approach to the explanation of evolutionary processes in contrast to the geno-centric one, recognizing not genes, but explorative and cognitive behaviours, experiences and cultural traditions as the main driving forces of animal evolution. The fourth section illustrates the basic characteristics of the meta-disciplinary area indicated in the chapter as Interspecific Cultural Studies (ICS) and their close affinities with the program of Numanities. The fifth section focuses, within the ICS framework, on a particular project and object of research: the study of the cases of Interspecific Cultural Convergences (ICC). These are cases in which a technique, an invention, a discovery, an expressive form or use have been independently developed not only by different populations of the same species, but also by societies and traditions of different animal species. The last part illustrates one of the best-known ICC cases: singing. A widespread expressive form in all human cultures and in primates genetically and phylogenetically quite distant from us such as Hylobatidae, Tarsius, Indri and Callicebus yet not among our sister species (chimpanzee, bonobo, gorilla). An expressive form developed by animal species as diverse and from a genetic, phylogenetic, morphological and ecological point of view as different as birds, mice and whales. The diffusion of singing in so different clades and environments obviously cannot be explained as a case of homology (similar characteristic inherited by common ancestor), because the ancestors common to birds and mammals did not sing, just as as those common to insects and birds did not have wings. It is instead the result of mutually independent, but in some aspects similar, evolutionary processes and social or ecological selective pressures. It can be adequately understood only by identifying and comparing the biological and social functions that this kind of expression plays, and the forms it has assumed, in all these animal communities, just as is commonly done by comparing human singing traditions and performances. In the ICS perspective, this approach can be extended to the study of all aspects of animal cultures and of all cases of ICC found.