Data from: pavo: an R package for the analysis, visualization and organization of spectral data

1. 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. 2. Despite this
growing interest, a unified cross-platform framework for analyzing 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) analyze data using spectral curve shape properties and visual system
modeling for a broad range of taxa. 3. In this paper, we present a summary
of the functions implemented in pavo and how they integrate in a workflow
to explore and analyze spectral data. We also present an exact solution
for the calculation of colour volume overlap in colourspace, thus
expanding previously published methodologies. 4. 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. 5. 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.