title: Quantifying individual variation in behaviour: mixed-effect modelling approaches.
abstract: 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.
authors.affiliation: Evolutionary Ecology of Variation Group, Max Planck Institute for Ornithology, Eberhard-Gwinner-Straße, 82319 Seewiesen (Starnberg), Germany. ndingemanse@orn.mpg.de
authors.forename: Niels J
authors.initials: NJ
authors.lastname: Dingemanse
authors.forename: Ned A
authors.initials: NA
authors.lastname: Dochtermann
mesh_terms: D000818:Animals; D001522:Behavior, Animal; D017753:Ecosystem; D008954:Models, Biological; D015203:Reproducibility of Results; D012107:Research Design