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FISHER'S GEOMETRICAL MODEL OF FITNESS LANDSCAPE AND VARIANCE IN FITNESS WITHIN A CHANGING ENVIRONMENT
Author(s) -
Zhang XuSheng
Publication year - 2012
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/j.1558-5646.2012.01610.x
Subject(s) - biology , fitness landscape , selection (genetic algorithm) , variance (accounting) , genetic fitness , fitness function , stabilizing selection , evolutionary biology , fisher information , constant (computer programming) , statistics , genetics , mathematics , genetic variation , computer science , biological evolution , mathematical optimization , gene , genetic algorithm , artificial intelligence , population , demography , accounting , sociology , business , programming language
The fitness of an individual can be simply defined as the number of its offspring in the next generation. However, it is not well understood how selection on the phenotype determines fitness. In accordance with Fisher's fundamental theorem, fitness should have no or very little genetic variance, whereas empirical data suggest that is not the case. To bridge these knowledge gaps, we follow Fisher's geometrical model and assume that fitness is determined by multivariate stabilizing selection toward an optimum that may vary among generations. We assume random mating, free recombination, additive genes, and uncorrelated stabilizing selection and mutational effects on traits. In a constant environment, we find that genetic variance in fitness under mutation‐selection balance is a U‐shaped function of the number of traits (i.e., of the so‐called “organismal complexity”). Because the variance can be high if the organism is of either low or high complexity, this suggests that complexity has little direct costs. Under a temporally varying optimum, genetic variance increases relative to a constant optimum and increasingly so when the mutation rate is small. Therefore, mutation and changing environment together can maintain high genetic variance. These results therefore lend support to Fisher's geometric model of a fitness landscape.