Literature DB >> 20676890

On the determination of evolutionary outcomes directly from the population dynamics of the resident.

Roger G Bowers1.   

Abstract

In order to determine the possible evolutionary behaviour of an ecological system using adaptive dynamics, it is necessary in an ab initio calculation to find the fitness and its derivatives at a singular point. It has been suggested that the possible evolutionary behaviour can be predicted directly from the resident population dynamics, without the need for calculation, by applying three criteria-one based on the form of the density dependent rates and two on the role played by the evolving parameters. The existing arguments for these criteria are rather limited: they apply to systems in which individuals enter an initial class and can then move through any number of other population classes sequentially. (Extensions are included but only apply for systems of two and three classes.) Additionally, many of the arguments depend on the use of a phenomenologically motivated fitness (shown equivalent to the standard form but in a rather long and indirect manner). The present paper removes all these flaws-the criteria are established directly from the standard definition of fitness and individuals can enter any class and move through the classes non-sequentially without restriction on their number. The criteria thus established underlie a geometric description of the singular behaviour in adaptive dynamics which allows direct inferences to be made from population dynamics to the possible singular behaviour depending on which of the criteria apply and on the nature of the trade-off between evolving parameters. The method has the great advantage of leaving the trade-off explicit but unspecified.

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Year:  2010        PMID: 20676890     DOI: 10.1007/s00285-010-0356-6

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  10 in total

1.  Community dynamics, trade-offs, invasion criteria and the evolution of host resistance to microparasites.

Authors:  R G Bowers; D E Hodgkinson
Journal:  J Theor Biol       Date:  2001-10-07       Impact factor: 2.691

Review 2.  Adaptive walks on changing landscapes: Levins' approach extended.

Authors:  C Rueffler; T J M Van Dooren; J A J Metz
Journal:  Theor Popul Biol       Date:  2004-03       Impact factor: 1.570

3.  Necessary and sufficient conditions for the existence of an optimisation principle in evolution.

Authors:  Mats Gyllenberg; Robert Service
Journal:  J Math Biol       Date:  2010-04-04       Impact factor: 2.259

4.  The geometric theory of adaptive evolution: trade-off and invasion plots.

Authors:  Roger G Bowers; Andrew Hoyle; Andrew White; Michael Boots
Journal:  J Theor Biol       Date:  2004-12-08       Impact factor: 2.691

5.  Evolution of handling time can destroy the coexistence of cycling predators.

Authors:  E Kisdi; S Liu
Journal:  J Evol Biol       Date:  2006-01       Impact factor: 2.411

6.  The influence of trade-off shape on evolutionary behaviour in classical ecological scenarios.

Authors:  Andrew Hoyle; Roger G Bowers; Andrew White; Michael Boots
Journal:  J Theor Biol       Date:  2007-10-12       Impact factor: 2.691

7.  When is evolutionary branching in predator-prey systems possible with an explicit carrying capacity?

Authors:  Andrew Hoyle; Roger G Bowers
Journal:  Math Biosci       Date:  2007-06-10       Impact factor: 2.144

8.  Evolutionary branching and long-term coexistence of cycling predators: critical function analysis.

Authors:  Stefan A H Geritz; Eva Kisdi; Ping Yan
Journal:  Theor Popul Biol       Date:  2007-03-24       Impact factor: 1.570

9.  Can possible evolutionary outcomes be determined directly from the population dynamics?

Authors:  Andrew Hoyle; Roger G Bowers
Journal:  Theor Popul Biol       Date:  2008-09-23       Impact factor: 1.570

10.  How should we define 'fitness' for general ecological scenarios?

Authors:  J A Metz; R M Nisbet; S A Geritz
Journal:  Trends Ecol Evol       Date:  1992-06       Impact factor: 17.712

  10 in total
  2 in total

1.  What life cycle graphs can tell about the evolution of life histories.

Authors:  Claus Rueffler; Johan A J Metz; Tom J M Van Dooren
Journal:  J Math Biol       Date:  2012-02-05       Impact factor: 2.259

2.  A simple mathematical model of gradual Darwinian evolution: emergence of a Gaussian trait distribution in adaptation along a fitness gradient.

Authors:  Vadim N Biktashev
Journal:  J Math Biol       Date:  2013-03-30       Impact factor: 2.259

  2 in total

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