Literature DB >> 17567563

Mimicry on the edge: why do mimics vary in resemblance to their model in different parts of their geographical range?

George R Harper1, David W Pfennig.   

Abstract

Batesian mimics-benign species that predators avoid because they resemble a dangerous species-often vary geographically in resemblance to their model. Such geographical variation in mimic-model resemblance may reflect geographical variation in model abundance. Natural selection should favour even poor mimics where their model is common, but only good mimics where their model is rare. We tested these predictions in a snake-mimicry complex where the geographical range of the mimic extends beyond that of its model. Mimics on the edge of their model's range (where the model was rare) resembled the model more closely than did mimics in the centre of their model's range (where the model was common). When free-ranging natural predators on the edge of the model's range were given a choice of attacking replicas of good or poor mimics, they avoided only good mimics. By contrast, those in the centre of the model's range attacked good and poor mimics equally frequently. Generally, although poor mimics may persist in areas where their model is common, only the best mimics should occur in areas where their model is rare. Thus, counter-intuitively, the best mimics may occur on the edge of their model's range.

Mesh:

Year:  2007        PMID: 17567563      PMCID: PMC2275182          DOI: 10.1098/rspb.2007.0558

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  8 in total

1.  Frequency-dependent Batesian mimicry.

Authors:  D W Pfennig; W R Harcombe; K S Pfennig
Journal:  Nature       Date:  2001-03-15       Impact factor: 49.962

2.  Batesian mimicry and signal detection theory.

Authors:  A Oaten; C E Pearce; M E Smyth
Journal:  Bull Math Biol       Date:  1975-08       Impact factor: 1.758

3.  Predator learning favours mimicry of a less-toxic model in poison frogs.

Authors:  Catherine R Darst; Molly E Cummings
Journal:  Nature       Date:  2006-03-09       Impact factor: 49.962

Review 4.  Snake venom variability: methods of study, results and interpretation.

Authors:  J P Chippaux; V Williams; J White
Journal:  Toxicon       Date:  1991       Impact factor: 3.033

5.  Coral snake mimicry: does it occur?

Authors:  H W Greene; R W McDiarmid
Journal:  Science       Date:  1981-09-11       Impact factor: 47.728

6.  Coevolutionary chase in two-species systems with applications to mimicry.

Authors:  S Gavrilets; A Hastings
Journal:  J Theor Biol       Date:  1998-04-21       Impact factor: 2.691

7.  Predators favour mimicry in a tropical reef fish.

Authors:  M Julian Caley; Dolph Schluter
Journal:  Proc Biol Sci       Date:  2003-04-07       Impact factor: 5.349

8.  Electrophoretic and immunochemical studies of Micrurus snake venoms.

Authors:  A Alape-Girón; B Lomonte; B Gustafsson; N J Da Silva; M Thelestam
Journal:  Toxicon       Date:  1994-06       Impact factor: 3.033

  8 in total
  20 in total

1.  A comparative analysis of the evolution of imperfect mimicry.

Authors:  Heather D Penney; Christopher Hassall; Jeffrey H Skevington; Kevin R Abbott; Thomas N Sherratt
Journal:  Nature       Date:  2012-03-21       Impact factor: 49.962

Review 2.  Mimics without models: causes and consequences of allopatry in Batesian mimicry complexes.

Authors:  David W Pfennig; Sean P Mullen
Journal:  Proc Biol Sci       Date:  2010-05-19       Impact factor: 5.349

Review 3.  The Interface Theory of Perception.

Authors:  Donald D Hoffman; Manish Singh; Chetan Prakash
Journal:  Psychon Bull Rev       Date:  2015-12

4.  Signal verification can promote reliable signalling.

Authors:  Mark Broom; Graeme D Ruxton; H Martin Schaefer
Journal:  Proc Biol Sci       Date:  2013-09-25       Impact factor: 5.349

5.  Frequency-dependent variation in mimetic fidelity in an intraspecific mimicry system.

Authors:  Arne Iserbyt; Jessica Bots; Stefan Van Dongen; Janice J Ting; Hans Van Gossum; Thomas N Sherratt
Journal:  Proc Biol Sci       Date:  2011-03-02       Impact factor: 5.349

Review 6.  The perfection of mimicry: an information approach.

Authors:  Thomas N Sherratt; Casey A Peet-Paré
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-07-05       Impact factor: 6.237

7.  Rapid evolution of mimicry following local model extinction.

Authors:  Christopher K Akcali; David W Pfennig
Journal:  Biol Lett       Date:  2014-06       Impact factor: 3.703

8.  Sensory bias and signal detection trade-offs maintain intersexual floral mimicry.

Authors:  Avery L Russell; David W Kikuchi; Noah W Giebink; Daniel R Papaj
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-05-18       Impact factor: 6.237

9.  Multiple models generate a geographical mosaic of resemblance in a Batesian mimicry complex.

Authors:  Christopher K Akcali; Hibraim Adán Pérez-Mendoza; David W Kikuchi; David W Pfennig
Journal:  Proc Biol Sci       Date:  2019-09-18       Impact factor: 5.349

10.  High-model abundance may permit the gradual evolution of Batesian mimicry: an experimental test.

Authors:  David W Kikuchi; David W Pfennig
Journal:  Proc Biol Sci       Date:  2009-12-02       Impact factor: 5.349

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