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Honest begging: expanding from Signal of Need

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  • Douglas W. Mock
  • Matthew B. Dugas
  • Stephanie A. Strickler

Abstract

Overt soliciting for parental resources, primarily food, is often explained as having evolved to express the fitness gain a signaling offspring would derive from a favorable parental response. This Signal of Need model makes 4 unheralded assumptions: 1) that parents' life-history objective is egalitarian; 2) that contemporaneous siblings participate nepotistically; 3) that dependent young can assess their own reproductive value from internal sources; and 4) that the morphological and behavioral signals we call "begging" are essential for transferring such cryptic information reliably. We review 2 parsimonious alternative types of honest begging. First, if the life-history assumption is relaxed, solicitation signals may be positively correlated with reproductive value, obviating the nepotism assumption. According to this Signal of Quality logic, solicitation signals can be seen as typical handicap-type advertisements of personal merit. Second, by relaxing the assumptions concerning cryptic fitness information entirely, solicitation signals might be purely proximate Signals of Hunger, with parents basing their overriding life-history decisions on nonsignal information streams (ecological costs of foraging plus offspring cues already in the public domain). These 3 hypotheses are easily testable, along with existing models that do not require parents to have complete control over resources. Copyright 2011, Oxford University Press.

Suggested Citation

  • Douglas W. Mock & Matthew B. Dugas & Stephanie A. Strickler, 2011. "Honest begging: expanding from Signal of Need," Behavioral Ecology, International Society for Behavioral Ecology, vol. 22(5), pages 909-917.
  • Handle: RePEc:oup:beheco:v:22:y:2011:i:5:p:909-917
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    File URL: http://hdl.handle.net/10.1093/beheco/arr091
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    1. Bates, Douglas & M├Ąchler, Martin & Bolker, Ben & Walker, Steve, 2015. "Fitting Linear Mixed-Effects Models Using lme4," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i01).
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