Acoustic communication in noise: regulation of call characteristics in a New World monkey
Freie Universität Berlin, Institut für Biologie, Verhaltensbiologie, Haderslebener Str. 9, 12163 Berlin, Germany
* Author for correspondence (e-mail: brumm{at}zedat.fu-berlin.de)
Accepted 27 October 2003
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Summary |
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Key words: acoustic communication, environmental noise, signal masking, vocal plasticity, Lombard effect, common marmoset, Callithrix jacchus
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Introduction |
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In some habitats acoustic communication is severely impaired by the
constant masking of high intensity background noise caused e.g. by
fast-flowing streams or waterfalls. An evolutionary response of frogs and
birds living in such noisy habitats is to evade masking by producing high
pitched vocalizations in narrow frequency-bands
(Dubois and Martens, 1984). In
addition, many animals evolved short-term adaptations to mitigate interference
from more temporary background noise. On this short-term level, two different
vocal mechanisms of noise-dependent vocal plasticity have been documented to
date. Japanese quail Coturnix coturnix japonica
(Potash, 1972
) and king
penguins Aptenodytes patagonicus
(Lengagne et al., 1999
)
increase the number of syllables per call series with increasing background
noise or wind. This relationship is in line with predictions from information
theory indicating that the probability of receiving a message in noise can be
improved by increasing the redundancy of the signal
(Shannon and Weaver, 1949
). It
is not known, however, whether mammals counteract interference from background
noise by increasing the redundancy of their signals.
Secondly, a signaller may increase the amplitude of its vocalizations in
response to an increase in the background noise level. This mechanism of
amplitude regulation is termed the `Lombard effect'
(Lombard, 1911) and has been
shown for birds (Potash, 1972
;
Manabe et al., 1998
;
Cynx et al., 1998
;
Brumm and Todt, 2002
), macaques
(one pig-tailed macaque Macaca nemestrina and one long-tailed macaque
Macaca fascicularis; Sinnott et
al., 1975
) and humans (reviewed in
Lane and Tranel, 1971
). It is
not clear to date whether the Lombard effect in the studied primate species
reflects a special adaptation of Old World monkeys or whether it is a more
widespread form of primate vocal plasticity.
In addition to the increase in amplitude and of redundancy, there might be
a third vocal mechanism to counteract masking effects of environmental noise.
Perceptional studies in a variety of species have shown that the detectability
of brief acoustic signals improved considerably with increasing signal
duration (e.g. Johnson, 1968;
Dooling, 1979
;
Brown and Maloney, 1986
;
Klump and Maier, 1990
). This
phenomenon is based on the temporal summation of signal energy in the
peripheral auditory system of receivers and plays an important role,
especially in the detection of acoustic signals in noise, such as in the
natural environment. Dooling and Searcy
(1985
) studied the temporal
integration of acoustic signals masked by a background of broadband white
noise in budgerigars (Melopsittacus undulatus). They found a decrease
in the birds' threshold for the detection of brief pure tones (of duration
<200 ms) along with increasing signal duration. To date, temporal summation
has been used to explain the evolution of signals of duration 200 ms or more
in some species (Klump, 1996
).
In the context of short-term adaptations, however, one might also reasonably
assume that the duration of briefer signals may be individually increased to
reduce the masking effects of temporally increased environmental noise. To our
knowledge, this hypothesis has not yet been tested.
We investigated the three issues outlined above in a small, arboreal New
World monkey, the common marmoset Callithrix jacchus. This species is
a good model to study the mechanisms of vocal plasticity, not only because
common marmosets readily vocalize a lot but also because their vocal
repertoire has been described (Winter and
Rothe, 1979) and we know much about their production and usage of
vocalizations (e.g. Epple,
1968
; Schrader and Todt,
1993
; Geiss and Schrader,
1996
; Hook-Costigan and
Rogers, 1998
; Norcross et al.,
1999
).
A call type uttered very often by common marmosets is the twitter call
(Fig. 1). It may play a role in
group cohesion and consists of very brief syllables (<120 ms; A. Sagüi
de Tufos-Brancos, personal communication), which are uttered in homotype call
series with varying syllable numbers
(Winter and Rothe, 1979).
Because of these characteristics and the frequent occurrence of twitter calls,
this call type should be particular well suited for the investigation of
communication in noise. We studied possible noise-induced changes in marmoset
twitter calls by experimentally manipulating the background noise and
measuring the sound level of vocalizations, the number of syllables per call
series, and the duration of syllables.
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Materials and methods |
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Procedure
At the beginning of each test session a randomly selected level of white
noise (40, 50, 60 or 65 dB SPL) or no noise was played back. After 30
minanother noise level was randomly chosen. Whenever a marmoset entered the
test cage, its identity was recorded as well as its position in the cage when
it was vocalizing. This procedure allowed us to analyse only recordings from
monkeys sitting on the platform. We conducted one test session on each of
three consecutive days. The sound level of the noise playbacks was set
according to previous measurements of the playback level done with an EZGA 2
(Rohde & Schwarz, München, Germany) precision sound level meter
(using the time constant `Fast' and a linear frequency weighting, measuring
frequency range 1025 000 Hz) at the position of the platform in the
test cage. For these measurements the volume of the amplifier was changed and
the given sound level was controlled with the sound level meter at the
position normally occupied by the monkey's head. The ambient noise level (when
no white noise was broadcast) was ca. 30 dB SPL (measured as described
above).
Data analysis
We examined the twitter calls of all monkeys that uttered at least one such
call series in three different noise conditions. This was the case for three
males and the female. The calls of these marmosets were analysed using
Avisoft-SASLab Pro software (R. Specht, Berlin, Germany). We digitized the
recordings with 16-bit resolution and a sampling rate of 44.1 kHz. For sound
level measurements of the recorded calls, Avisoft was calibrated: 2 s of white
noise at 65 dB was analysed for each test session and the digitized sound
level of the recorded noise was set to the value directly measured with the
sound level meter at the position of the microphone. Then the maximum
root-mean-squared sound pressure value of each call syllable was measured
(with an averaging time of 1 ms). To determine the sound level of each
syllable, we finally subtracted the sound level of the added noise (or the
ambient noise level when no white noise was added) from the measurements
according to the logarithmic computation procedures given in Weißing
(1984). The duration of the
syllables was measured in sonagrams calculated with a Fast Fourier
Transformation-length of 64 points (resulting in a temporal resolution smaller
than 2 ms). For the sound level measurements we used only recordings not
disturbed by noise produced by the other marmosets, especially their
vocalizations. For this reason the sample sizes of the sound level
measurements may be smaller than those of the other analyses.
For each individual, we examined the relationship between the measured
characteristics of the call series (median sound level, median duration of
syllables, and the number of syllables per series) and the background noise
level using two-tailed Spearman rank correlations. We used the
Dunnidák method
(Sokal and Rohlf, 2001
) to
calculate a-level-corrected P-values (hereafter
Pc).
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Results |
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In contrast to these noise-dependent changes in call level and call syllable duration, none of the subjects showed any tendency to increase the number of call syllables in response to increased background noise (Fig. 4).
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Discussion |
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A crucial effect of background sounds on the evolution of frequency traits
of animal vocalizations has been suggested for birds and primates
(Wiley and Richards, 1982;
Ryan and Brenowitz, 1985
;
Waser and Brown, 1986
). Blue
monkeys Cercopithecus mitis and pygmy marmosets Cebuella
pygmaea produce calls with dominant frequencies coinciding with typical
low-amplitude regions in the environmental noise spectra of their habitats,
which may be the result of an evolutionary shaping of call phonetics to
minimise masking by background noise (Brown
and Waser, 1984
; de la Torre
and Snowdon, 2002
). Furthermore, de la Torre and Snowdon
(2002
) could show that with
varying communication distance, pygmy marmosets use two different call types
that transmit particularly well over the respective distance. In addition to
this context-specific use of different call types and the evolutionary shaping
of signal structure, however, our results demonstrate a primate's capability
for individual regulation of the parameters of a given call to mitigate signal
masking from background noise. This finding shows that primates can control
the production of their vocalizations (at least with respect to signal
duration and amplitude).
However, unlike quails and penguins
(Potash, 1972;
Lengagne et al., 1999
), the
examined marmosets did not vary the number of syllables per call series in
relation to the background noise level. Although there was some variability in
the number of syllables, the monkeys did not use an increased serial
redundancy of the vocal signals to counteract the communicative constraints of
environmental noise.
Our study is the first to report a noise-dependent prolongation of acoustic
signals in an animal communication system. This regulation of signal duration
is possibly adapted to the perception mechanisms of the addressees, for the
detectability of brief acoustic signals increases with signal prolongation,
based on temporal summation of signal energy
(Watson and Gengel, 1969).
Closely related to the perceptional accomplishment of signal detection is the
localization of stimuli. Similar to the improved detection in noise, a
prolongation of brief sounds can considerably improve their localization
(Hofman and van Opstal, 1998
;
Macpherson and Middlebrooks,
2000
). Since marmosets live in forests where visibility is
limited, maintaining a sufficient locatability of calls may be crucial for the
animals when signalling their position to group mates.
In addition to the noise-dependent prolongation of syllables, the examined marmosets also exhibited the Lombard effect. All monkeys increased the amplitude of their twitter calls in response to increased levels of white noise. Like the prolongation of syllables, this response to background noise helps to counteract the environmental constraints on the communication channel. Hence, our findings show that a New World monkey is able to actively maintain the distance in which another conspecific can perceive its calls. Thus the active space seems to be a dynamic feature rather than a rigid property of a given signal system. As environmental conditions may quickly change, some animals regulate the characteristics of their vocal signals accordingly.
Alternatively, animals could always produce their vocalizations with high
amplitudes and durations irrespective of the background noise level. But
obviously there is a tradeoff between maximising signal transmission and
factors that favour inconspicuous vocalizations. Keeping signal amplitude and
duration at a low level may reduce the probability of signal detection and
localization by unwanted receivers, e.g. predators. Corroborative evidence to
support this comes from studies on vocal amplitude in songbirds
(Dabelsteen et al., 1998;
Brumm and Todt, 2002
;
Brumm, in press
). Finally the
reported short-term adaptations in signal production may reflect ways of
limiting the energetic costs of vocalizing.
Studies on the Lombard effect are not only of interest for elucidating communication in noise but also for investigating the relationship between hearing and vocal production. In this context, our results provide evidence for a neuronal feedback loop between auditory perception and vocal production in common marmosets. Obviously, monkeys monitor their own vocalizations and assess the intensity of background noise. Thus the adjustment of vocal amplitude may serve to maintain a specific signal-to-noise ratio that is favourable for signal production.
In conclusion, the overall picture shows that the common problem of communication in noise has shaped the common solution of amplitude regulation in all vertebrate taxa tested so far. In addition, some bird species also adjust the redundancy of their signals to mitigate interference from environmental noise. Further studies in different species will show whether the revealed regulation of brief signal durations in common marmosets represents a general mechanism of vocal production in animal communication systems or whether it is a special adaptation of only few taxa.
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Acknowledgments |
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