Analyzing Stress as a Multivariate Phenotype

The stress phenotype is multivariate. Recent advances have broadened our understanding beyond characterizing the stress response in a single dimension. Simultaneously, the toolbox available to ecophysiologists has expanded greatly in recent years, allowing the measurement of multiple biomarkers from an individual at a single point in time. Yet these advances-in our conceptual understanding and available methodologies-have not yet been combined in a unifying multivariate statistical framework. Here, we offer a brief review of the multivariate stress phenotype and describe a general statistical approach for analysis using nonparametric multivariate analysis of variance with residual randomization in permutation procedures (RRPP) implemented using the "RRPP" package in R. We also provide an example illustrating the novel insights that can be gained from a holistic multivariate approach to stress and provide a tutorial for how we analyzed these data, including annotated R code and a guide to interpretation of outputs (Online Appendix 1). We hope that this statistical methodology will provide a quantitative framework facilitating the unification of our theoretical understanding and empirical observations into a quantitative, multivariate theory of stress.