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 toward 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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Blouch：用于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会使比较方法和测试适应性假设复杂化。基于 Ornstein-Uhlenbeck 过程的模型允许通过允许性状向固定的适应性最优值（例如，制度或生态位）进化或跟踪可能受其他性状影响的不断变化的最优值来测试关于适应的假设。这些模型允许估计由于任何来源性状进化而导致的适应和系统发育惯性对适应的抵抗力的影响，这种方法称为“适应惯性”框架。然而，该框架的先前应用以及为处理物种非独立性问题而提出的大多数方法都是基于最大似然法，因此很难在分析中包含基于先前生物学知识的信息，这可能会影响结果推断。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器的贝叶斯框架中拟合了连续性状进化的异速生长和自适应模型，并结合了测量误差。我首先简要讨论了在 Blouch 中实现的模型，然后是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势，允许不同的效应（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表现良好。 为了在实证数据集上证明 Blouch 的工作流程，我检验了这样一个假设，即体型较大的鹿的相对较大的鹿角是更强烈的性选择的结果，伴随着它们倾向于生活在更大的繁殖群体中。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与其他群体具有不同且更陡峭的鹿角大小与体型的缩放模式。这些结果与以前的发现相反，并且可能认为不同类型的性选择或其他选择压力决定了最小繁殖群体的最佳鹿角大小。