How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature
How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature
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DOI：
10.1111/evo.14213
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发表时间：
2021-03
期刊：
影响因子：
3.3
通讯作者：
J. Uyeda;Nicholas Bone;Sean W. McHugh;J. Rolland;Matthew W. Pennell
中科院分区：
文献类型：
--
作者：
J. Uyeda;Nicholas Bone;Sean W. McHugh;J. Rolland;Matthew W. Pennell
系统发育比较方法经常被用来测试性状之间的功能关系。然而，百万年的宏观进化观测数据集无法明确证明性状之间的因果关系-相关性不等于因果关系，并且在这样的时间尺度上进行实验操作是不可能的。虽然这一警告被广泛理解，但很少有人意识到，不同的系统发育方法意味着对性状功能关系的不同因果假设。为了做出有意义的推论，我们的统计方法必须做出生物学上合理的假设。在这里，我们通过检查Avaria-Llautureo等人（2019）最近的一项研究来说明因果推理在比较生物学中的重要性。他们测试了恒温动物的代谢率和体温的进化耦合，发现这些特征在进化过程中是不相关的，平均来说，新生代早期的体温比今天高。我们认为，因果关系的假设嵌入到他们的模型，使他们无法测试相关的功能和进化的假设。我们使用更适合生物学的模型重新分析他们的数据，并找到支持完全相反结论的证据，证实了以前来自生理学和古生物学的证据。我们强调因果思维的重要性，即使实验是不可能的。
Phylogenetic comparative methods are often used to test functional relationships between traits. However, million‐year macroevolutionary observational datasets cannot definitively prove causal links between traits—correlation does not equal causation and experimental manipulation over such timescales is impossible. Although this caveat is widely understood, it is less appreciated that different phylogenetic approaches imply different causal assumptions about the functional relationships of traits. To make meaningful inferences, it is critical that our statistical methods make biologically reasonable assumptions. Here we illustrate the importance of causal reasoning in comparative biology by examining a recent study by Avaria‐Llautureo et al (2019). that tested for the evolutionary coupling of metabolic rate and body temperature across endotherms and found that these traits were unlinked through evolutionary time and that body temperatures were, on average, higher in the early Cenozoic than they are today. We argue that the causal assumptions embedded into their models made it impossible for them to test the relevant functional and evolutionary hypotheses. We reanalyze their data using more biologically appropriate models and find support for the exact opposite conclusions, corroborating previous evidence from physiology and paleontology. We highlight the vital need for causal thinking, even when experiments are impossible.