Quantifying individual variation in behaviour: mixed-effect modelling approaches

Growing interest in proximate and ultimate causes and consequences of between- and within-individual variation in labile components of the phenotype such as behaviour or physiology characterizes current research in evolutionary ecology. The study of individual variation requires tools for quantification and decomposition of phenotypic variation into between- and within-individual components. This is essential as variance components differ in their ecological and evolutionary implications. We provide an overview of how mixed-effect models can be used to partition variation in, and correlations among, phenotypic attributes into between- and within-individual variance components. Optimal sampling schemes to accurately estimate (with sufficient power) a wide range of repeatabilities and key (co)variance components, such as between- and within-individual correlations, are detailed. Mixed-effect models enable the usage of unambiguous terminology for patterns of biological variation that currently lack a formal statistical definition (e.g. animal personality or behavioural syndromes), and facilitate cross-fertilisation between disciplines such as behavioural ecology, ecological physiology and quantitative genetics.