Problems with using comparative analyses of avian brain size to test hypotheses of cognitive evolution

There are multiple hypotheses for the evolution of cognition. The most prominent hypotheses are the Social Intelligence Hypothesis (SIH) and the Ecological Intelligence Hypothesis (EIH), which are often pitted against one another. These hypotheses tend to be tested using broad-scale comparative studies of brain size, where brain size is used as a proxy of cognitive ability, and various social and/or ecological variables are included as predictors. Here, we test how robust conclusions drawn from such analyses may be. First, we investigate variation in brain and body size measurements across >1000 bird species. We demonstrate that there is substantial variation in brain and body size estimates across datasets, indicating that conclusions drawn from comparative brain size models are likely to differ depending on the source of the data. Following this, we subset our data to the Corvides infraorder and interrogate how modelling decisions impact results. We show that model results change substantially depending on variable inclusion, source and classification. Indeed, we could have drawn multiple contradictory conclusions about the principal drivers of brain size evolution. These results reflect concerns from a growing number of researchers that conclusions drawn from comparative brain size studies may not be robust. We suggest that to interrogate hypotheses of cognitive evolution, a fruitful way forward is to focus on testing cognitive performance within and between closely related taxa, with an emphasis on understanding the relationship between informational uncertainty and cognitive evolution.

Automated summary

This article examines the hypotheses and conclusions drawn from comparative brain size studies in the field of cognitive evolution. The study finds significant variations in brain and body size estimates across different datasets, leading to changing model results depending on variable inclusion, source, and classification. The authors suggest focusing on testing cognitive performance within and between closely related taxa and understanding the relationship between informational uncertainty and cognitive evolution.