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      Cliff-edge model of obstetric selection in humans

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      Proceedings of the National Academy of Sciences
      Proceedings of the National Academy of Sciences

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          Abstract

          The strikingly high incidence of obstructed labor due to the disproportion of fetal size and the mother’s pelvic dimensions has puzzled evolutionary scientists for decades. Here we propose that these high rates are a direct consequence of the distinct characteristics of human obstetric selection. Neonatal size relative to the birth-relevant maternal dimensions is highly variable and positively associated with reproductive success until it reaches a critical value, beyond which natural delivery becomes impossible. As a consequence, the symmetric phenotype distribution cannot match the highly asymmetric, cliff-edged fitness distribution well: The optimal phenotype distribution that maximizes population mean fitness entails a fraction of individuals falling beyond the “fitness edge” (i.e., those with fetopelvic disproportion). Using a simple mathematical model, we show that weak directional selection for a large neonate, a narrow pelvic canal, or both is sufficient to account for the considerable incidence of fetopelvic disproportion. Based on this model, we predict that the regular use of Caesarean sections throughout the last decades has led to an evolutionary increase of fetopelvic disproportion rates by 10 to 20%.

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          Most cited references47

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          The Measurement of Selection on Correlated Characters

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            The strength of phenotypic selection in natural populations.

            How strong is phenotypic selection on quantitative traits in the wild? We reviewed the literature from 1984 through 1997 for studies that estimated the strength of linear and quadratic selection in terms of standardized selection gradients or differentials on natural variation in quantitative traits for field populations. We tabulated 63 published studies of 62 species that reported over 2,500 estimates of linear or quadratic selection. More than 80% of the estimates were for morphological traits; there is very little data for behavioral or physiological traits. Most published selection studies were unreplicated and had sample sizes below 135 individuals, resulting in low statistical power to detect selection of the magnitude typically reported for natural populations. The absolute values of linear selection gradients |beta| were exponentially distributed with an overall median of 0.16, suggesting that strong directional selection was uncommon. The values of |beta| for selection on morphological and on life-history/phenological traits were significantly different: on average, selection on morphology was stronger than selection on phenology/life history. Similarly, the values of |beta| for selection via aspects of survival, fecundity, and mating success were significantly different: on average, selection on mating success was stronger than on survival. Comparisons of estimated linear selection gradients and differentials suggest that indirect components of phenotypic selection were usually modest relative to direct components. The absolute values of quadratic selection gradients |gamma| were exponentially distributed with an overall median of only 0.10, suggesting that quadratic selection is typically quite weak. The distribution of gamma values was symmetric about 0, providing no evidence that stabilizing selection is stronger or more common than disruptive selection in nature.
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              Sexual Dimorphism, Sexual Selection, and Adaptation in Polygenic Characters

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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                December 20 2016
                December 20 2016
                December 20 2016
                December 05 2016
                : 113
                : 51
                : 14680-14685
                Article
                10.1073/pnas.1612410113
                5187675
                27930310
                e1c488c0-9ccf-46b5-ae3e-ed5e7ab8b054
                © 2016

                Free to read

                http://www.pnas.org/site/misc/userlicense.xhtml

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