Literature DB >> 28189670

A model for conditional male trimorphisms.

J Mark Rowland1, Clifford R Qualls2, Bruno A Buzatto3.   

Abstract

Conditional dimorphisms are widespread in color, morphology, behavior, and life history. Such traits have been successfully modeled in game theory as conditional strategies, and in quantitative genetics as threshold traits. Conditional trimorphisms have recently been unveiled, and here we combine the rock-paper-scissors (RPS) model of game theory and the environmental threshold (ET) model of quantitative genetics to model trimorphisms that are environmentally induced and result from the expression of two thresholds. We investigated the tactic fitness structure for maintenance of alternative reproductive tactics in scarab dung beetles that constitute the first known examples of conditional male trimorphism. We parameterized a novel ternary fitness landscape that explains how conditional male trimorphism in these beetles can be maintained. We tracked changes in tactic frequencies in a wild population of Phanaeus triangularis and detected fitness intransitivity consistent with RPS dynamics. Quantitative predictions of our model compare favorably with corresponding observed parameters. The ternary landscape further reveals how geographic populations of these beetles can evolve between conditional trimorphism and dimorphism. The ternary model also suggests that polyphenic systems could potentially evolve between conditional and purely genetic mediation.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Alternative reproductive tactics; Conditional strategy; Male polymorphism; Polyphenism; Threshold trait

Mesh:

Year:  2017        PMID: 28189670     DOI: 10.1016/j.jtbi.2017.02.006

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  1 in total

1.  Diverse and complex male polymorphisms in Odontolabis stag beetles (Coleoptera: Lucanidae).

Authors:  Keita Matsumoto; Robert J Knell
Journal:  Sci Rep       Date:  2017-12-01       Impact factor: 4.379

  1 in total

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