pavo: an R package for the analysis, visualization and organization of spectral data
Article first published online: 1 AUG 2013
© 2013 The Authors. Methods in Ecology and Evolution © 2013 British Ecological Society
Methods in Ecology and Evolution
Volume 4, Issue 10, pages 906–913, October 2013
How to Cite
Maia, R., Eliason, C. M., Bitton, P.-P., Doucet, S. M., Shawkey, M. D. (2013), pavo: an R package for the analysis, visualization and organization of spectral data. Methods in Ecology and Evolution, 4: 906–913. doi: 10.1111/2041-210X.12069
- Issue published online: 7 OCT 2013
- Article first published online: 1 AUG 2013
- Accepted manuscript online: 22 MAY 2013 10:43AM EST
- Manuscript Accepted: 13 MAY 2013
- Manuscript Received: 3 JAN 2013
- NSF. Grant Numbers: DEB-1210630, EAR-1251895
- AMNH Chapman research
- Sigma XI GIAR
- HFSP. Grant Number: RGY0083
- AFOSR. Grant Number: FA9550-09-1-0159
- University of Akron
- NSERC Discovery
- NSERC Graduate Scholarship
- animal communication;
- receptor noise;
- sensory ecology;
- visual model
- Recent technical and methodological advances have led to a dramatic increase in the use of spectrometry to quantify reflectance properties of biological materials, as well as models to determine how these colours are perceived by animals, providing important insights into ecological and evolutionary aspects of animal visual communication.
- Despite this growing interest, a unified cross-platform framework for analysing and visualizing spectral data has not been available. We introduce pavo, an R package that facilitates the organization, visualization and analysis of spectral data in a cohesive framework. pavo is highly flexible, allowing users to (a) organize and manipulate data from a variety of sources, (b) visualize data using R's state-of-the-art graphics capabilities and (c) analyse data using spectral curve shape properties and visual system modelling for a broad range of taxa.
- In this paper, we present a summary of the functions implemented in pavo and how they integrate in a workflow to explore and analyse spectral data. We also present an exact solution for the calculation of colour volume overlap in colourspace, thus expanding previously published methodologies.
- As an example of pavo's capabilities, we compare the colour patterns of three African glossy starling species, two of which have diverged very recently. We demonstrate how both colour vision models and direct spectral measurement analysis can be used to describe colour attributes and differences between these species. Different approaches to visual models and several plotting capabilities exemplify the package's versatility and streamlined workflow.
- pavo provides a cohesive environment for handling spectral data and addressing complex sensory ecology questions, while integrating with R's modular core for a broader and comprehensive analytical framework, automated management of spectral data and reproducible workflows for colour analysis.