...
首页> 外文期刊>The Journal of Heredity >Analogues of the fundamental and secondary theorems of selection, assuming a log-normal distribution of expected fitness
【24h】

Analogues of the fundamental and secondary theorems of selection, assuming a log-normal distribution of expected fitness

机译:假设预期健身的对数正常分布的基本和次要定理的类似物

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

It is increasingly common for studies of evolution in natural populations to infer the quantitative genetic basis of fitness (e.g., the additive genetic variance for relative fitness), and of relationships between traits and fitness (e.g., the additive genetic covariance of traits with relative fitness). There is a certain amount of tension between the theory that justifies estimating these quantities, and methodological considerations relevant to their empirical estimation. In particular, the additive genetic variances and covariances involving relative fitness are justified by the fundamental and secondary theorems of selection, which pertain to relative fitness on the scale that it is expressed. However, naturally-occurring fitness distributions lend themselves to analysis with generalized linear mixed models (GLMMs), which conduct analysis on a different scale, typically on the scale of the logarithm of expected values, from which fitness is expressed. This note presents relations between evolutionary change in traits, and the rate of adaptation in fitness, and log quantitative genetic parameters of fitness, potentially reducing the discord between theoretical and methodological considerations to the operationalization of the secondary and fundamental theorems of selection.
机译:对天然群体的进化来推断适应性的定量遗传基础(例如,相对适应性的添加剂遗传方差)以及特质与适应性之间的关系(例如,具有相对健身的性状的添加剂遗传协方差的关系越来越常见)。在理论之间存在一定程度的张力,证明了与其实证估计相关的这些数量和方法论考虑因素。特别地,涉及相对适应性的添加剂遗传差异和共协方差是由选择的基本和次要定理的合理性,这与表达规模的相对适应性有关。然而,天然存在的健身分布赋予了与广义线性混合模型(GLMM)分析的分析,该模型对不同规模进行分析,通常在预期值的对数的规模上,从而表达了健身。本说明呈现出进化变化的性状变化与适应性的适应速度,以及健身的日志定量遗传参数,潜在地减少了理论和方法论之间的不和谐,对选择的二次和基本定理的运作。

著录项

相似文献

  • 外文文献
  • 中文文献
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号