Limits...
Rival assessment among northern elephant seals: evidence of associative learning during male-male contests.

Casey C, Charrier I, Mathevon N, Reichmuth C - R Soc Open Sci (2015)

Bottom Line: We evaluated the acoustic displays of breeding male northern elephant seals (Mirounga angustirostris), and found that social knowledge gained through prior experience with signallers was sufficient to maintain structured dominance relationships.Using sound analysis and playback experiments with both natural and modified signals, we determined that males do not rely on encoded information about size or dominance status, but rather learn to recognize individual acoustic signatures produced by their rivals.Our findings demonstrate that social knowledge of rivals alone can regulate dominance relationships among competing males within large, spatially dynamic social groups, and illustrate the importance of combining descriptive and experimental methods when deciphering the biological relevance of animal signals.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, and , University of California Santa Cruz , Santa Cruz, CA 95060, USA.

ABSTRACT
Specialized signals emitted by competing males often convey honest information about fighting ability. It is generally believed that receivers use these signals to directly assess their opponents. Here, we demonstrate an alternative communication strategy used by males in a breeding system where the costs of conflict are extreme. We evaluated the acoustic displays of breeding male northern elephant seals (Mirounga angustirostris), and found that social knowledge gained through prior experience with signallers was sufficient to maintain structured dominance relationships. Using sound analysis and playback experiments with both natural and modified signals, we determined that males do not rely on encoded information about size or dominance status, but rather learn to recognize individual acoustic signatures produced by their rivals. Further, we show that behavioural responses to competitors' calls are modulated by relative position in the hierarchy: the highest ranking (alpha) males defend their harems from all opponents, whereas mid-ranking (beta) males respond differentially to familiar challengers based on the outcome of previous competitive interactions. Our findings demonstrate that social knowledge of rivals alone can regulate dominance relationships among competing males within large, spatially dynamic social groups, and illustrate the importance of combining descriptive and experimental methods when deciphering the biological relevance of animal signals.

No MeSH data available.


Related in: MedlinePlus

Individual signatures of the acoustic displays of male northern elephant seals. (a) As shown by the central graph and accompanying spectrograms on the sides, calls can be reliably assigned to individuals using two acoustic parameters (mean±s.e.): the centroid of the frequency spectrum and the number of pulses per call (the two main factors that separate individuals on the first discriminant function of the cross-validated DFA). The confusion matrix provided is obtained from the cross-validated DFA. It shows by colouring cell (i,j) the conditional probability of guessing that the test call came from individual j when in fact it was emitted by i. The yellow diagonal of the matrix underscores the high probability of correct classification (average=61.3% versus chance=6.3%, see text for details), highlighting the strength of the individual signatures. (b) Both spectrograms illustrate the consistency of an individual's calls in two different social contexts (calling alone and calling to a rival). The distribution of the Euclidian distances (density curves) underscores the similarity of calls within and between contexts (in the two-dimensional space defined by the calls' frequency centroid and the pulse rate; n=8 individuals, 2–6 calls individual−1, see Material and methods). (c) Both pairs of spectrograms illustrate the consistency of an individual's calls over successive years. The distribution of Euclidian distances (density curves) shows the remarkable proximity of calls within and between years (n=10 individuals, 5–6 calls individual−1 year−1). The calls represented by spectrograms in the figure are available as electronic supplementary material, audio S1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4555858&req=5

RSOS150228F5: Individual signatures of the acoustic displays of male northern elephant seals. (a) As shown by the central graph and accompanying spectrograms on the sides, calls can be reliably assigned to individuals using two acoustic parameters (mean±s.e.): the centroid of the frequency spectrum and the number of pulses per call (the two main factors that separate individuals on the first discriminant function of the cross-validated DFA). The confusion matrix provided is obtained from the cross-validated DFA. It shows by colouring cell (i,j) the conditional probability of guessing that the test call came from individual j when in fact it was emitted by i. The yellow diagonal of the matrix underscores the high probability of correct classification (average=61.3% versus chance=6.3%, see text for details), highlighting the strength of the individual signatures. (b) Both spectrograms illustrate the consistency of an individual's calls in two different social contexts (calling alone and calling to a rival). The distribution of the Euclidian distances (density curves) underscores the similarity of calls within and between contexts (in the two-dimensional space defined by the calls' frequency centroid and the pulse rate; n=8 individuals, 2–6 calls individual−1, see Material and methods). (c) Both pairs of spectrograms illustrate the consistency of an individual's calls over successive years. The distribution of Euclidian distances (density curves) shows the remarkable proximity of calls within and between years (n=10 individuals, 5–6 calls individual−1 year−1). The calls represented by spectrograms in the figure are available as electronic supplementary material, audio S1.

Mentions: Our qualitative observation that experienced observers could identify males solely by their calls was supported by a quantitative cross-validated and pDFA. The results of the cross-validation step showed that individual identification on the basis of six spectral and three temporal acoustic parameters was highly reliable (average rate of correct classification=61.3%, range: 35.9–99.5%; chance=6.3%; n=16 adult males with 15.8±3.5 calls/individual, range: 9–20; p<0.001; see classification matrix in figure 5a; electronic supplementary material, audio S1). The two main acoustic factors separating individuals on the first discriminant function were one temporal and one frequency parameter: call pulse rate and the centroid of the call frequency spectrum (table 4). The combination of these two cues was sufficient to characterize the unique acoustic space of each individual (figure 5a), even without further consideration of notable differences in fine-scale pulse structure.Figure 5.


Rival assessment among northern elephant seals: evidence of associative learning during male-male contests.

Casey C, Charrier I, Mathevon N, Reichmuth C - R Soc Open Sci (2015)

Individual signatures of the acoustic displays of male northern elephant seals. (a) As shown by the central graph and accompanying spectrograms on the sides, calls can be reliably assigned to individuals using two acoustic parameters (mean±s.e.): the centroid of the frequency spectrum and the number of pulses per call (the two main factors that separate individuals on the first discriminant function of the cross-validated DFA). The confusion matrix provided is obtained from the cross-validated DFA. It shows by colouring cell (i,j) the conditional probability of guessing that the test call came from individual j when in fact it was emitted by i. The yellow diagonal of the matrix underscores the high probability of correct classification (average=61.3% versus chance=6.3%, see text for details), highlighting the strength of the individual signatures. (b) Both spectrograms illustrate the consistency of an individual's calls in two different social contexts (calling alone and calling to a rival). The distribution of the Euclidian distances (density curves) underscores the similarity of calls within and between contexts (in the two-dimensional space defined by the calls' frequency centroid and the pulse rate; n=8 individuals, 2–6 calls individual−1, see Material and methods). (c) Both pairs of spectrograms illustrate the consistency of an individual's calls over successive years. The distribution of Euclidian distances (density curves) shows the remarkable proximity of calls within and between years (n=10 individuals, 5–6 calls individual−1 year−1). The calls represented by spectrograms in the figure are available as electronic supplementary material, audio S1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4555858&req=5

RSOS150228F5: Individual signatures of the acoustic displays of male northern elephant seals. (a) As shown by the central graph and accompanying spectrograms on the sides, calls can be reliably assigned to individuals using two acoustic parameters (mean±s.e.): the centroid of the frequency spectrum and the number of pulses per call (the two main factors that separate individuals on the first discriminant function of the cross-validated DFA). The confusion matrix provided is obtained from the cross-validated DFA. It shows by colouring cell (i,j) the conditional probability of guessing that the test call came from individual j when in fact it was emitted by i. The yellow diagonal of the matrix underscores the high probability of correct classification (average=61.3% versus chance=6.3%, see text for details), highlighting the strength of the individual signatures. (b) Both spectrograms illustrate the consistency of an individual's calls in two different social contexts (calling alone and calling to a rival). The distribution of the Euclidian distances (density curves) underscores the similarity of calls within and between contexts (in the two-dimensional space defined by the calls' frequency centroid and the pulse rate; n=8 individuals, 2–6 calls individual−1, see Material and methods). (c) Both pairs of spectrograms illustrate the consistency of an individual's calls over successive years. The distribution of Euclidian distances (density curves) shows the remarkable proximity of calls within and between years (n=10 individuals, 5–6 calls individual−1 year−1). The calls represented by spectrograms in the figure are available as electronic supplementary material, audio S1.
Mentions: Our qualitative observation that experienced observers could identify males solely by their calls was supported by a quantitative cross-validated and pDFA. The results of the cross-validation step showed that individual identification on the basis of six spectral and three temporal acoustic parameters was highly reliable (average rate of correct classification=61.3%, range: 35.9–99.5%; chance=6.3%; n=16 adult males with 15.8±3.5 calls/individual, range: 9–20; p<0.001; see classification matrix in figure 5a; electronic supplementary material, audio S1). The two main acoustic factors separating individuals on the first discriminant function were one temporal and one frequency parameter: call pulse rate and the centroid of the call frequency spectrum (table 4). The combination of these two cues was sufficient to characterize the unique acoustic space of each individual (figure 5a), even without further consideration of notable differences in fine-scale pulse structure.Figure 5.

Bottom Line: We evaluated the acoustic displays of breeding male northern elephant seals (Mirounga angustirostris), and found that social knowledge gained through prior experience with signallers was sufficient to maintain structured dominance relationships.Using sound analysis and playback experiments with both natural and modified signals, we determined that males do not rely on encoded information about size or dominance status, but rather learn to recognize individual acoustic signatures produced by their rivals.Our findings demonstrate that social knowledge of rivals alone can regulate dominance relationships among competing males within large, spatially dynamic social groups, and illustrate the importance of combining descriptive and experimental methods when deciphering the biological relevance of animal signals.

View Article: PubMed Central - PubMed

Affiliation: Department of Ecology and Evolutionary Biology, and , University of California Santa Cruz , Santa Cruz, CA 95060, USA.

ABSTRACT
Specialized signals emitted by competing males often convey honest information about fighting ability. It is generally believed that receivers use these signals to directly assess their opponents. Here, we demonstrate an alternative communication strategy used by males in a breeding system where the costs of conflict are extreme. We evaluated the acoustic displays of breeding male northern elephant seals (Mirounga angustirostris), and found that social knowledge gained through prior experience with signallers was sufficient to maintain structured dominance relationships. Using sound analysis and playback experiments with both natural and modified signals, we determined that males do not rely on encoded information about size or dominance status, but rather learn to recognize individual acoustic signatures produced by their rivals. Further, we show that behavioural responses to competitors' calls are modulated by relative position in the hierarchy: the highest ranking (alpha) males defend their harems from all opponents, whereas mid-ranking (beta) males respond differentially to familiar challengers based on the outcome of previous competitive interactions. Our findings demonstrate that social knowledge of rivals alone can regulate dominance relationships among competing males within large, spatially dynamic social groups, and illustrate the importance of combining descriptive and experimental methods when deciphering the biological relevance of animal signals.

No MeSH data available.


Related in: MedlinePlus