Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-6630
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Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes are fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories.
Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of an asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and fiveloci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction.
For entirely vegetative or sexual reproduction, predictions of the gametic SEIB model were close to the ones of spatially explicit nongametic phenotypic models, but for mixed modes of reproduction they approximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of traits governed by few quantitative trait
loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually miss the optimum and that selection may lead to loci with smaller effects in derived compared with ancestral lines.
|Item Type:||Journal Article, refereed, original work|
|Communities & Collections:||07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies|
|DDC:||570 Life sciences; biology|
590 Animals (Zoology)
|Uncontrolled Keywords:||clonal plants, ecological and evolutionary modelling, genetic variation, life-history evolution, optimal life histories, simulation model|
|Deposited On:||14 Jan 2009 17:14|
|Last Modified:||27 Nov 2013 17:22|
|Publisher:||Oxford University Press|
|Citations:||Web of Science®. Times Cited: 2|
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