A micro-geography of fear: learning to eavesdrop on alarm calls of neighbouring heterospecifics

Many vertebrates eavesdrop on alarm calls of other species, which is a remarkable ability, given geographical variation in community composition and call diversity within and among species. We used micro-geographical variation in community composition to test whether individuals recognize heterospecific alarm calls by: (i) responding to acoustic features shared among alarm calls; (ii) having innate responses to particular heterospecific calls; or (iii) learning specific alarm calls. We found that superb fairy-wrens ( Malurus cyaneus ) fled to cover to playback of noisy miner ( Manorina melanocephala ) aerial predator alarm calls only in locations where miners were present, suggesting that learning rather than acoustic structure determines response. Sites with and without miners were well within the dispersal distance of fairy-wrens, and philopatric males and dispersing females showed the same pattern, so that local genetic adaptation is extremely unlikely. Furthermore, where miners were present, fairy-wrens responded appropriately to different miner calls, implying eavesdropping on their signalling system rather than fleeing from miners themselves. Learned eavesdropping on alarm calls enables individuals to harvest ecologically relevant information from heterospecifics on an astonishingly fine spatial scale. Such phenotypic plasticity is valuable in a changing world, where individuals can be exposed to new species.

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Alarming features: birds use specific acoustic properties to identify heterospecific alarm calls

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2012.2539 ◽

2013 ◽

Vol 280 (1754) ◽

pp. 20122539 ◽

Cited By ~ 34

Author(s):

Pamela M. Fallow ◽

Benjamin J. Pitcher ◽

Robert D. Magrath

Keyword(s):

Frequency Modulation ◽

Alarm Call ◽

Acoustic Properties ◽

Alarm Calls ◽

Acoustic Similarity ◽

Acoustic Features ◽

Alarm Signal ◽

Antipredator Response ◽

Malurus Cyaneus

Vertebrates that eavesdrop on heterospecific alarm calls must distinguish alarms from sounds that can safely be ignored, but the mechanisms for identifying heterospecific alarm calls are poorly understood. While vertebrates learn to identify heterospecific alarms through experience, some can also respond to unfamiliar alarm calls that are acoustically similar to conspecific alarm calls. We used synthetic calls to test the role of specific acoustic properties in alarm call identification by superb fairy-wrens, Malurus cyaneus . Individuals fled more often in response to synthetic calls with peak frequencies closer to those of conspecific calls, even if other acoustic features were dissimilar to that of fairy-wren calls. Further, they then spent more time in cover following calls that had both peak frequencies and frequency modulation rates closer to natural fairy-wren means. Thus, fairy-wrens use similarity in specific acoustic properties to identify alarms and adjust a two-stage antipredator response. Our study reveals how birds respond to heterospecific alarm calls without experience, and, together with previous work using playback of natural calls, shows that both acoustic similarity and learning are important for interspecific eavesdropping. More generally, this study reconciles contrasting views on the importance of alarm signal structure and learning in recognition of heterospecific alarms.

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Cooperative bird discriminates between individuals based purely on their aerial alarm calls

Behavioral Ecology ◽

10.1093/beheco/arz182 ◽

2019 ◽

Vol 31 (2) ◽

pp. 440-447

Author(s):

Lucy F Farrow ◽

Ahmad Barati ◽

Paul G McDonald

Keyword(s):

Social Contexts ◽

Conclusive Evidence ◽

Alarm Calls ◽

Alarm Signals ◽

Additional Information ◽

Alarm Calling ◽

Noisy Miner ◽

Individual Discrimination ◽

Social Calls ◽

Manorina Melanocephala

Abstract From an evolutionary perspective, the ability to recognize individuals provides great selective advantages, such as avoiding inbreeding depression during breeding. Whilst the capacity to recognize individuals for these types of benefits is well established in social contexts, why this recognition might arise in a potentially deadly alarm-calling context following predator encounters is less obvious. For example, in most avian systems, alarm signals directed toward aerial predators represent higher predation risk and vulnerability than when individuals vocalize toward a terrestrial-based predator. Although selection should favor simple, more effective alarm calls to these dangerous aerial predators, the potential of these signals to nonetheless encode additional information such as caller identity has not received a great deal of attention. We tested for individual discrimination capacity in the aerial alarm vocalizations of the noisy miner (Manorina melanocephala), a highly social honeyeater that has been previously shown to be able to discriminate between the terrestrial alarm signals of individuals. Utilizing habituation–discrimination paradigm testing, we found conclusive evidence of individual discrimination in the aerial alarm calls of noisy miners, which was surprisingly of similar efficiency to their ability to discriminate between less urgent terrestrial alarm signals. Although the mechanism(s) driving this behavior is currently unclear, it most likely occurs as a result of selection favoring individualism among other social calls in the repertoire of this cooperative species. This raises the intriguing possibility that individualistic signatures in vocalizations of social animals might be more widespread than currently appreciated, opening new areas of bioacoustics research.

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Perception of terrestrial and aerial alarm calls by honeyeaters and falcons

Australian Journal of Zoology ◽

10.1071/zo99020 ◽

2000 ◽

Vol 48 (2) ◽

pp. 127 ◽

Cited By ~ 23

Author(s):

Sharon R. Wood ◽

Ken J. Sanderson ◽

Christopher S. Evans

Keyword(s):

Computer System ◽

Prey Species ◽

Narrow Band ◽

Broad Band ◽

Alarm Calls ◽

Avian Predators ◽

Noisy Miner ◽

Distress Calls ◽

Manorina Melanocephala ◽

Reduce Risk

This study tested the responses to aerial and terrestrial alarm and distress calls in an avian predator, the brown falcon, Falco berigora, and two potential avian prey species, the New Holland honeyeater, Philidonyris novaehollandiae, and noisy miner, Manorina melanocephala. Calls were delivered from a computer system at intensities 5–20 dB above background, to birds held in large cages. All birds located the broad-band alarm and distress calls easily, but they had difficulty locating the narrow-band aerial alarm calls, although they were able to detect most of these. Aerial alarm calls thus reduce risk to the caller. The performance of raptors and songbirds was similar. This result suggests that there are no reliable differences in the auditory characteristics of avian predators and prey, as have been described in species from the Northern Hemisphere.

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Influence of the Noisy Miner Manorina melanocephala on avian diversity and abundance in remnant Grey Box woodland

Pacific Conservation Biology ◽

10.1071/pc980055 ◽

1998 ◽

Vol 4 (1) ◽

pp. 55 ◽

Cited By ~ 99

Author(s):

Merilyn J. Grey ◽

Michael F. Clarke ◽

Richard H. Loyn

Keyword(s):

Bird Species ◽

The Other ◽

Avian Diversity ◽

Short Term ◽

Experimental Removal ◽

Noisy Miner ◽

Insect Infestations ◽

Eucalypt Woodlands ◽

Manorina Melanocephala ◽

The One

The abundance of an aggressive Australian honeyeater, the Noisy Miner Manorina melanocephala, was reduced at four small (<8 ha) Grey Box Eucalyptus microcarpa woodland remnants by experimental removal. The diversity and abundance of small insectivorous and nectarivorous birds increased at three of the four sites (relative to matching control sites) over the twelve months following the removal of the Noisy Miners. The one exception occurred at a pair of sites where eucalypts began flowering at one site and finished at the other during the Noisy Miner removal period. These results, taken together with those from three earlier experiments where the abundance of Noisy Miners was reduced in Mugga Ironbark E. Sideroxylon woodland remnants, demonstrate that Noisy Miners affect avian diversity and abundance by aggressive exclusion of other species. In five out of seven experiments, Noisy Miners did not reinvade the small woodland remnants during the ensuing twelve months. When Noisy Miner abundance was reduced, increased populations of small insectivorous and nectarivorous birds used small degraded woodland remnants. Colonizing populations of small birds have the potential to reduce insect infestations and may assist in the recovery of dieback-affected woodland remnants. Research is continuing to test this hypothesis. Reducing the abundance of Noisy Miners in remnant eucalypt woodlands may also be a useful, short-term measure, which could assist in the recovery of threatened or endangered bird species.

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Recognition of other species' aerial alarm calls: speaking the same language or learning another?

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2008.1368 ◽

2008 ◽

Vol 276 (1657) ◽

pp. 769-774 ◽

Cited By ~ 69

Author(s):

Robert D Magrath ◽

Benjamin J Pitcher ◽

Janet L Gardner

Keyword(s):

Sympatric Species ◽

Specific Structure ◽

Geographical Range ◽

Alarm Calls ◽

Acoustic Similarity ◽

Complex Task ◽

Signal Design ◽

Interspecific Recognition ◽

Malurus Cyaneus

Alarm calls given by other species potentially provide a network of information about danger, but little is known about the role of acoustic similarity compared with learning in recognition of heterospecific calls. In particular, the aerial ‘hawk’ alarm calls of passerines provide a textbook example of signal design because many species have converged on a design that thwarts eavesdropping by hawks, and call similarity might therefore allow recognition. We measured the response of fairy-wrens ( Malurus cyaneus ) to playback of acoustically similar scrubwren ( Sericornis frontalis ) aerial alarm calls. First, if call similarity prompts escape independent of learning, then fairy-wrens should flee to playback of scrubwren calls outside their geographical range. However, fairy-wrens fled only in sympatry. Second, if call similarity is necessary for learning heterospecific calls, then fairy-wrens should not respond to sympatric species with different calls. We found, on the contrary, that fairy-wrens fled to the very different aerial alarm calls of a honeyeater ( Phylidonyris novaehollandiae ). Furthermore, response to the honeyeater depended on the specific structure of the call, not acoustic similarity. Overall, call similarity was neither sufficient nor necessary for interspecific recognition, implying learning is essential in the complex task of sifting the acoustic world for cues about danger.

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Songs Recognition Using Audio Information Fusion

International Journal of Electronics and Telecommunications ◽

10.1515/eletel-2015-0005 ◽

2015 ◽

Vol 61 (1) ◽

pp. 37-41

Author(s):

Paweł Biernacki

Keyword(s):

Information Fusion ◽

Audio Signal ◽

Relevant Information ◽

Correct Identification ◽

Acoustic Features ◽

Signal Features ◽

Information Fusion Technique ◽

Music Audio ◽

Audio Information ◽

Fusion Approach

Abstract The article presents information fusion approach for song classification with use of acoustic signal. Many acoustic features can contribute to correct identification of a song. Taking into consideration only one set of features may result in omission of relevant information. It is possible to improve the accuracy of identification process by means of the information fusion technique, in which various aspects of acoustic fingerprint are taken into consideration. Two sets of signal features were distinguished: one were based on frequency analysis (harmonic elements) and the other were based on multidimensional correlation ratios. An identification of a commercial was made with use of SVM and k-NN classifiers. The music audio signal database was used for assessing the effectiveness of the proposed solution. Results show an improved effectiveness of identification in relation to applying only one set of song features

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