Literature DB >> 32420858

The signal detection problem of aposematic prey revisited: integrating prior social and personal experience.

Liisa Hämäläinen1,2,3, Rose Thorogood1,4,5.   

Abstract

Ever since Alfred R. Wallace suggested brightly coloured, toxic insects warn predators about their unprofitability, evolutionary biologists have searched for an explanation of how these aposematic prey evolve and are maintained in natural populations. Understanding how predators learn about this widespread prey defence is fundamental to addressing the problem, yet individuals differ in their foraging decisions and the predominant application of associative learning theory largely ignores predators' foraging context. Here we revisit the suggestion made 15 years ago that signal detection theory provides a useful framework to model predator learning by emphasizing the integration of prior information into predation decisions. Using multiple experiments where we modified the availability of social information using video playback, we show that personal information (sampling aposematic prey) improves how predators (great tits, Parus major) discriminate between novel aposematic and cryptic prey. However, this relationship was not linear and beyond a certain point personal encounters with aposematic prey were no longer informative for prey discrimination. Social information about prey unpalatability reduced attacks on aposematic prey across learning trials, but it did not influence the relationship between personal sampling and discrimination. Our results suggest therefore that acquiring social information does not influence the value of personal information, but more experiments are needed to manipulate pay-offs and disentangle whether information sources affect response thresholds or change discrimination. This article is part of the theme issue 'Signal detection theory in recognition systems: from evolving models to experimental tests'.

Entities:  

Keywords:  aposematism; predator–prey interactions; signal detection theory; social information use

Mesh:

Year:  2020        PMID: 32420858      PMCID: PMC7331014          DOI: 10.1098/rstb.2019.0473

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  40 in total

1.  Predator mixes and the conspicuousness of aposematic signals.

Authors:  John A Endler; Johanna Mappes
Journal:  Am Nat       Date:  2004-04-19       Impact factor: 3.926

Review 2.  Social learning strategies.

Authors:  Kevin N Laland
Journal:  Learn Behav       Date:  2004-02       Impact factor: 1.986

3.  When more is less: the fitness consequences of predators attacking more unpalatable prey when more are presented.

Authors:  Hannah M Rowland; Elizabeth Wiley; Graeme D Ruxton; Johanna Mappes; Michael P Speed
Journal:  Biol Lett       Date:  2010-05-05       Impact factor: 3.703

4.  Diversity in Müllerian mimicry: The optimal predator sampling strategy explains both local and regional polymorphism in prey.

Authors:  Thomas G Aubier; Thomas N Sherratt
Journal:  Evolution       Date:  2015-10-28       Impact factor: 3.694

5.  Investigating Müllerian mimicry: predator learning and variation in prey defences.

Authors:  E Ihalainen; L Lindström; J Mappes
Journal:  J Evol Biol       Date:  2007-03       Impact factor: 2.411

6.  Observation learning in day-old chicks using a one-trial passive avoidance learning paradigm.

Authors: 
Journal:  Anim Behav       Date:  1998-12       Impact factor: 2.844

7.  Context-dependent decision-making: a simple Bayesian model.

Authors:  Kevin Lloyd; David S Leslie
Journal:  J R Soc Interface       Date:  2013-02-20       Impact factor: 4.118

8.  Social transmission of avoidance among predators facilitates the spread of novel prey.

Authors:  Rose Thorogood; Hanna Kokko; Johanna Mappes
Journal:  Nat Ecol Evol       Date:  2017-12-18       Impact factor: 15.460

9.  Individual differences in the use of social information in foraging by captive great tits.

Authors: 
Journal:  Anim Behav       Date:  2000-07       Impact factor: 2.844

Review 10.  The reach of gene-culture coevolution in animals.

Authors:  Hal Whitehead; Kevin N Laland; Luke Rendell; Rose Thorogood; Andrew Whiten
Journal:  Nat Commun       Date:  2019-06-03       Impact factor: 14.919

View more
  1 in total

1.  Signal detection, acceptance thresholds and the evolution of animal recognition systems.

Authors:  A V Suarez; H M Scharf; H K Reeve; M E Hauber
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-05-18       Impact factor: 6.237

  1 in total

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