Relationships among species in the tree of life can complicate comparative methods and testing adaptive hypotheses. Models based on the Ornstein-Uhlenbeck process permit hypotheses about adaptation to be tested by allowing traits to either evolve towards fixed adaptive optima (e.g., regimes or niches) or track continuously changing optima that can be influenced by other traits. These models allow estimation of the effects of both adaptation and phylogenetic inertia - resistance to adaptation due to any source - on trait evolution, an approach known as the "adaptation-inertia" framework. However, previous applications of this framework, and most approaches suggested to deal with the issue of species non-independence, are based on a maximum likelihood approach and thus it is difficult to include information based on prior biological knowledge in the analysis, which can affect resulting inferences. Here I present Blouch, (Bayesian Linear Ornstein-Uhlenbeck Models for Comparative Hypotheses), which fits allometric and adaptive models of continuous trait evolution in a Bayesian framework based on fixed or continuous predictors and incorporates measurement error. I first briefly discuss the models implemented in Blouch, and then the new applications for these models provided by a Bayesian framework. This includes the advantages of assigning biologically meaningful priors when compared to non-Bayesian approaches, allowing for varying effects (intercepts and slopes), and multilevel modeling. Validations on simulated data show good performance in recovering the true evolutionary parameters for all models. To demonstrate the workflow of Blouch on an empirical dataset, I test the hypothesis that the relatively larger antlers of larger bodied deer are the result of more intense sexual selection that comes along with their tendency to live in larger breeding groups. While results show that larger bodied deer that live in larger breeding groups have relatively larger antlers, deer living in the smallest groups appear to have a different and steeper scaling pattern of antler size to body size than other groups. These results are contrary to previous findings and may argue that a different type of sexual selection or other selective pressures govern optimum antler size in the smallest breeding groups.

中文翻译：

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布卢奇：比较假设的贝叶斯线性 Ornstein-Uhlenbeck 模型。


生命之树中物种之间的关系可能会使比较方法和测试适应性假设变得复杂。基于奥恩斯坦-乌伦贝克过程的模型允许通过允许特征向固定的适应性最佳值（例如，制度或生态位）进化或跟踪可能受其他特征影响的不断变化的最佳值来测试关于适应的假设。这些模型可以估计适应和系统发育惰性（由于任何来源而产生的对适应的抵抗）对性状进化的影响，这种方法被称为“适应惯性”框架。然而，该框架以前的应用以及大多数建议处理物种非独立性问题的方法都是基于最大似然方法，因此很难在分析中包含基于先前生物学知识的信息，这可能会影响由此得出的推论。在这里，我介绍了 Blouch（用于比较假设的贝叶斯线性 Ornstein-Uhlenbeck 模型），它在基于固定或连续预测变量的贝叶斯框架中拟合连续性状进化的异速生长和自适应模型，并包含测量误差。我首先简要讨论在 Blouch 中实现的模型，然后讨论贝叶斯框架为这些模型提供的新应用程序。与非贝叶斯方法相比，这包括分配具有生物学意义的先验的优点，允许不同的效果（截距和斜率）和多级建模。对模拟数据的验证表明，在恢复所有模型的真实进化参数方面具有良好的性能。 为了在经验数据集上展示布卢奇的工作流程，我测试了这样一个假设：体型较大的鹿相对较大的鹿角是更强烈的性选择的结果，而这种选择伴随着它们生活在更大的繁殖群体中的倾向。虽然结果表明，生活在较大繁殖群体中的体型较大的鹿具有相对较大的鹿角，但生活在最小群体中的鹿似乎具有与其他群体不同且更陡峭的鹿角尺寸与身体尺寸的比例模式。这些结果与之前的发现相反，并且可能认为不同类型的性选择或其他选择压力控制着最小繁殖群体中的最佳鹿角大小。