Non-random mating has a significant impact on the evolution of organisms. Here, I developed a modelling framework for discrete traits (with any number of phenotypes) to explore different models connecting the non-random mating causes (mate competition and/or mate choice) and their consequences (sexual selection and/or assortative mating). I derived the formulaefor the maximum likelihood estimates of each model and used information criteria to perform multi-model inference. Simulation results showed a good performance of both model selection and parameter estimation. The methodology was applied to ecotypes data of the marine gastropod Littorina saxatilis from Galicia (Spain), to show that the mating pattern is better described by models with two parameters that involve both mate choice and competition, generating positive assortative mating plus female sexual selection. As far as I know, this is the first standardized methodology for model selection and multi-model inference of mating parameters for discrete traits. The advantages of this framework include the ability of setting up models from which the parameters connect causes, as mate competition and mate choice, with their outcome in the form of data patterns of sexual selection and assortative mating. For some models, the parameters may have a double effect i.e. they produce sexual selection and assortative mating, while for others there are separated parameters for one kind of pattern or another. From an empirical point of view, it is much easier to study patterns than processes and, for this reason, the causal mechanisms of sexual selection are not so well known as the patterns they produce. The goal of the present work is to propose a new tool that helps to distinguish among different alternative processes behind the observed mating pattern. The full methodology was implemented in a software called InfoMating (available at http://acraaj.webs6.uvigo.es/InfoMating/Infomating.htm).

中文翻译：

---

基于信息理论方法的非随机交配的多模型推理。

非随机交配对生物的进化有重要影响。在这里，我为离散性状（具有任意数量的表型）开发了一个建模框架，以探索连接非随机交配原因（交配竞争和/或交配选择）及其后果（性选择和/或分类交配）的不同模型。我导出了每个模型的最大似然估计的公式，并使用信息标准来执行多模型推理。仿真结果表明模型选择和参数估计均具有良好的性能。该方法应用于来自加利西亚（西班牙）的海洋腹足纲腹足纲蜥蜴的生态型数据，表明用具有两个参数的模型更好地描述了交配模式，这两个参数涉及配偶选择和竞争，产生积极的配偶交配以及女性的性选择。据我所知，这是用于离散性状的模型选择和交配参数的多模型推断的第一个标准化方法。该框架的优点包括能够建立模型，参数可以通过这些模型将原因（例如配偶竞争和配偶选择）联系在一起，并以性选择和分类交配的数据模式的形式将其结果联系起来。对于某些模型，这些参数可能会产生双重影响，即它们会产生性别选择和配对交配，而对于其他模型，则存在针对一种或另一种模式的单独参数。从经验的角度来看，研究模式比过程要容易得多，因此，性选择的因果机制并不像它们产生的模式那样众所周知。本工作的目的是提出一种新工具，该工具有助于在观察到的交配模式后区分不同的替代过程。完整的方法在名为InfoMating的软件中实现（可从http://acraaj.webs6.uvigo.es/InfoMating/Infomating.htm获得）。