Data from: Detecting environment-dependent diversification from phylogenies: a simulation study and some empirical illustrations

Understanding the relative influence of various abiotic and biotic variables on diversification dynamics is a major goal of macroevolutionary studies. Recently, phylogenetic approaches have been developed that make it possible to estimate the role of various environmental variables on diversification using time-calibrated species trees, paleoenvironmental data, and maximum-likelihood techniques. These approaches have been effectively employed to estimate how speciation and extinction rates vary with key abiotic variables, such as temperature and sea level, and we can anticipate that they will be increasingly used in the future. Here we compile a series of biotic and abiotic paleodatasets that can be used as explanatory variables in these models and use simulations to assess the statistical properties of the approach when applied to these paleodatasets. We demonstrate that environment-dependent models perform well in recovering environment-dependent speciation and extinction parameters, as well as in correctly identifying the simulated environmental model when speciation is environment-dependent. We explore how the strength of the environment-dependency, tree size, missing taxa, and characteristics of the paleoenvironmental curves influence the performance of the models. Finally, using these models, we infer environment-dependent diversification in two empirical phylogenies: temperature-dependence in Cetacea and δ 13C-dependence in Ruminantia. We illustrate how to evaluate the relative importance of abiotic and biotic variables in these two clades and interpret these results in light of macroevolutionary hypotheses. Given the important role paleoenvironments are presumed to have played in species evolution, our statistical assessment of how environment-dependent models behave is crucial for their utility in macroevolutionary analysis.

阐明各类非生物(abiotic)与生物(biotic)变量对物种多样化动态的相对影响，是宏演化研究的一项核心目标。近年来，研究者开发出了一系列系统发育学方法，可通过时间校准物种树(time-calibrated species trees)、古环境数据(paleoenvironmental data)与最大似然法(maximum-likelihood)，估算各类环境变量对物种多样化的调控作用。此类方法已被有效应用于探究物种形成与灭绝速率随温度、海平面等关键非生物变量的变化规律，且预计未来其应用将愈发广泛。本研究整合了一系列可作为此类模型解释变量的生物与非生物古数据集(paleodatasets)，并通过模拟实验评估了该方法应用于此类古数据集时的统计特性(statistical properties)。我们证实，环境依赖模型(environment-dependent models)能够准确恢复受环境调控的物种形成与灭绝参数，且当物种形成受环境调控时，可正确识别模拟所设定的环境模型类型。我们还探究了环境依赖强度、物种树规模、缺失类群以及古环境曲线特征等因素对模型性能的影响。最后，我们利用此类模型对两个实证系统发育树开展了环境依赖多样化分析：鲸下目(Cetacea)的温度依赖性演化，以及反刍亚目(Ruminantia)的δ13C依赖性演化。我们阐释了如何评估这两个演化支(clades)中非生物与生物变量的相对重要性，并结合宏演化假说对研究结果进行了解读。鉴于古环境被认为在物种演化中发挥了关键作用，我们对环境依赖模型性能的统计评估，对于其在宏演化分析中的应用具有至关重要的意义。