How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature. (1st May 2021)

• Record Type: Journal Article
• Authors: Uyeda, Josef C.; Bone, Nicholas; McHugh, Sean; Rolland, Jonathan; Pennell, Matthew W.
• Is Part Of: Evolution. Volume 75:Number 5(2021)
• Page Start: 1097
• Page End: 1105
• Publication Date: 2021-05-01
• Subjects: Macroevolution -- models/simulations -- phylogenetics -- physiology; Evolution -- Periodicals; Heredity -- Periodicals; Évolution (Biologie) -- Périodiques; Hérédité -- Périodiques; 338.47004094
• DOI: 10.1111/evo.14213
• Languages: English
• ISSNs: 0014-3820

Abstract

Abstract: 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.