Fernández-Meirama Mónica, Estévez Daniel, Ng Terence P T, Williams Gray A, Carvajal-Rodríguez Antonio, Rolán-Alvarez Emilio
Departamento de Bioquímica, Genética e Inmunología Facultad de Biología Universidad de Vigo Vigo Spain.
School of Biological Sciences The Swire Institute of Marine Science The University of Hong Kong Hong Kong SAR China.
Ecol Evol. 2017 Mar 22;7(9):2883-2893. doi: 10.1002/ece3.2835. eCollection 2017 May.
Mating preference can be a driver of sexual selection and assortative mating and is, therefore, a key element in evolutionary dynamics. Positive mating preference by similarity is the tendency for the choosy individual to select a mate which possesses a similar variant of a trait. Such preference can be modelled using Gaussian-like mathematical functions that describe the strength of preference, but such functions cannot be applied to empirical data collected from the field. As a result, traditionally, mating preference is indirectly estimated by the degree of assortative mating (using Pearson's correlation coefficient, ) in wild captured mating pairs. Unfortunately, and similar coefficients are often biased due to the fact that different variants of a given trait are nonrandomly distributed in the wild, and pooling of mating pairs from such heterogeneous samples may lead to "false-positive" results, termed "the scale-of-choice effect" (SCE). Here we provide two new estimators of mating preference ( and ) derived from Gaussian-like functions which can be applied to empirical data. Computer simulations demonstrated that coefficient showed robust estimations properties of mating preference but it was severely affected by SCE, showed reasonable estimation properties and it was little affected by SCE, while showed the best properties at infinite sample sizes and it was not affected by SCE but failed at biological sample sizes. We recommend using combined with the coefficient to infer mating preference in future empirical studies.
交配偏好可以成为性选择和选型交配的驱动力,因此是进化动力学中的一个关键要素。基于相似性的正向交配偏好是指挑剔的个体倾向于选择具有相似性状变体的配偶。这种偏好可以用描述偏好强度的类高斯数学函数来建模,但这类函数不能应用于从野外收集的实证数据。因此,传统上,交配偏好是通过野生捕获的交配配对中的选型交配程度(使用皮尔逊相关系数)来间接估计的。不幸的是,由于给定性状的不同变体在野外是非随机分布的,并且从这种异质样本中汇总交配配对可能会导致“假阳性”结果,即所谓的“选择规模效应”(SCE),所以该系数及类似系数往往存在偏差。在这里,我们提供了两个从类高斯函数推导出来的交配偏好新估计量(和),它们可以应用于实证数据。计算机模拟表明,系数显示出稳健的交配偏好估计特性,但它受到SCE的严重影响,显示出合理的估计特性且受SCE影响较小,而在无限样本量时显示出最佳特性且不受SCE影响,但在生物样本量时失效。我们建议在未来的实证研究中结合系数来推断交配偏好。