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. 2012 Mar 7;279(1730):902-9.
doi: 10.1098/rspb.2011.1362. Epub 2011 Aug 17.

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

Affiliations

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

Robert D Magrath et al. Proc Biol Sci. .

Abstract

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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Figures

Figure 1.
Figure 1.
Spectrograms of playbacks of (a) superb-fairy wren aerial alarm call, (b) crimson rosella piping call, (c) noisy miner aerial alarm call, (d) noisy miner mobbing alarm call and (e) noisy miner begging call on arrival of an adult with food. Spectrograms were prepared in Raven 1.4 using a Blackman window function, 1.11 ms hop size, 43.1 Hz grid spacing and 3 dB filter bandwidth of 150 Hz [42].
Figure 2.
Figure 2.
Locations of playbacks to superb fairy-wrens (FW) at sites where noisy miners (NM) were present or absent. The heavy dashed line separates areas used as replicates in experiment 1. The solid lines are minimum convex polygons around locations of playbacks within a site. The fine dashed line groups smaller sites where miners were present, but where miners did not occur between those sites.
Figure 3.
Figure 3.
The probability of superb fairy-wrens fleeing to cover in response to playbacks of noisy miner and superb fairy-wren aerial alarm calls, and crimson rosella contact calls in experiment 1 (a) area 1 and (b) area 2; n = 15 for each bar. Black bars, miner alarm; white bars, wren alarm; grey bars, rosella control.
Figure 4.
Figure 4.
The response of superb fairy-wrens to playback of noisy miner calls in (a) sites where miners were present, experiment 2 (n = 16), and (b) sites where miners were absent, experiment 3 (n = 15). Black bars, flee; white bars, scan.

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