Detecting mosaic patterns in phenotypic disparity
Evolutionary biologists have long sought to understand the full complexity in pattern and process that shapes organismal diversity. Although phylogenetic comparative methods are often used to reconstruct complex evolutionary dynamics, they are typically limited to a single phenotypic trait. Extensions that accommodate multiple traits lack the ability to partition multidimensional datasets into a set of mosaic suites of evolutionarily linked characters. I introduce a comparative framework that identifies heterogeneity in evolutionary patterns across large datasets of continuous traits. Using a model of continuous trait evolution based on the differential accumulation of disparity across lineages in a phylogeny, the approach algorithmically partitions traits into a set of character suites that best explains the data, where each suite displays a distinct pattern in phylogenetic morphological disparity. When applied to empirical data, the approach revealed a mosaic pattern predicted by developmental biology. The evolutionary distinctiveness of individual suites can be investigated in more detail, either by fitting conventional comparative models or by directly studying the phylogenetic patterns in disparity recovered during the analysis. This framework can supplement existing comparative approaches by inferring the complex, integrated patterns that shape evolution across the body plan from disparate developmental, morphometric, and environmental sources of phenotypic data.