Literature DB >> 9268441

Why do animals repeat displays?

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Abstract

Both agonistic and sexual animal displays often involve more than one performance of some specific display action. Since repetition is energetically costly there must be good reasons why a signaller should carry out such repetitive actions, rather than simply displaying once. We briefly review three different 'reasons' which arise from three different receiver assessment rules: when assessment is based on the average magnitude of all display actions so far, the reason for the repetition is to improve the accuracy of the estimate (model A); when the assessment is based solely on the action of greatest magnitude so far, the repetition is to replace the signal with one of greater magnitude (model B); when the assessment is based on the cumulative sum of all display actions so far, the repetition is to augment that sum (model C). We discuss how to characterize each case from an understanding of its expected optimal behaviour as predicted by formal models. For model A the mean magnitude of display actions should stay constant and the contest duration should depend on relative qualities. In models B and C the encounter duration depends only on the weaker participant. In model B each display action is greater than the previous, but only a small number of steps are expected. In model C the magnitude of display actions can either escalate, stay constant, or even decrease. The displays of cichlid fish, the roaring contests of red deer, Cervus elaphusthe calling of Blanchard's cricket frogs, Acris crepitans blanchardiand the pheromonal exchanges of yeast gametes are used as illustrative examples.

Entities:  

Year:  1997        PMID: 9268441     DOI: 10.1006/anbe.1996.0391

Source DB:  PubMed          Journal:  Anim Behav        ISSN: 0003-3472            Impact factor:   2.844


  23 in total

1.  Cumulative or sequential assessment during hermit crab shell fights: effects of oxygen on decision rules.

Authors:  M Briffa; R W Elwood
Journal:  Proc Biol Sci       Date:  2000-12-07       Impact factor: 5.349

2.  Use of energy reserves in fighting hermit crabs.

Authors:  Mark Briffa; Robert W Elwood
Journal:  Proc Biol Sci       Date:  2004-02-22       Impact factor: 5.349

3.  Weak rappers rock more: hermit crabs assess their own agonistic behaviour.

Authors:  Elizabeth Edmonds; Mark Briffa
Journal:  Biol Lett       Date:  2016-01       Impact factor: 3.703

4.  A poisonous surprise under the coat of the African crested rat.

Authors:  Jonathan Kingdon; Bernard Agwanda; Margaret Kinnaird; Timothy O'Brien; Christopher Holland; Thomas Gheysens; Maxime Boulet-Audet; Fritz Vollrath
Journal:  Proc Biol Sci       Date:  2011-08-03       Impact factor: 5.349

5.  Animal personality as a cause and consequence of contest behaviour.

Authors:  Mark Briffa; Lynne U Sneddon; Alastair J Wilson
Journal:  Biol Lett       Date:  2015-03-25       Impact factor: 3.703

6.  Animal vocal sequences: not the Markov chains we thought they were.

Authors:  Arik Kershenbaum; Ann E Bowles; Todd M Freeberg; Dezhe Z Jin; Adriano R Lameira; Kirsten Bohn
Journal:  Proc Biol Sci       Date:  2014-10-07       Impact factor: 5.349

Review 7.  The role of skill in animal contests: a neglected component of fighting ability.

Authors:  Mark Briffa; Sarah M Lane
Journal:  Proc Biol Sci       Date:  2017-09-27       Impact factor: 5.349

8.  How does environment influence fighting? The effects of tidal flow on resource value and fighting costs in sea anemones.

Authors:  Alexandre V Palaoro; Mariana Velasque; Sandro Santos; Mark Briffa
Journal:  Biol Lett       Date:  2017-05       Impact factor: 3.703

9.  Testing game theory models: fighting ability and decision rules in chameleon contests.

Authors:  Devi Stuart-Fox
Journal:  Proc Biol Sci       Date:  2006-06-22       Impact factor: 5.349

10.  Emotion in animal contests.

Authors:  Andrew Crump; Emily J Bethell; Ryan Earley; Victoria E Lee; Michael Mendl; Lucy Oldham; Simon P Turner; Gareth Arnott
Journal:  Proc Biol Sci       Date:  2020-11-18       Impact factor: 5.349

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