View source: R/summary.rspec.R
summary.rspec | R Documentation |
Calculates all 23 colourimetric variables reviewed in Montgomerie (2006).
## S3 method for class 'rspec'
summary(object, subset = FALSE, lim = NULL, wlmin = NULL, wlmax = NULL, ...)
object |
(required) a data frame, possibly an object of class |
subset |
Either |
lim |
The range of wavelengths used in calculations. The default is to use
the entire range in the |
wlmin, wlmax |
Deprecated. Use the |
... |
class consistency (ignored) |
A data frame containing either 23 or 5 (subset = TRUE
) variables described
in Montgomerie (2006) with spectra name as row names.
The colorimetric variables calculated by this function are
described in Montgomerie (2006) with corrections included in the README CLR
file from the May 2008 distribution of the CLR software. Authors should reference
both this package,Montgomerie (2006), and the original reference(s).
Description and notes on the measures:
B1 (Total brightness): Sum of the relative reflectance over the entire spectral range (area under the curve). Frequently used but should be discouraged because values are difficult to compare across studies (B2 is preferred). REF 1-3, 7, 9-11, 13
B2 (Mean brightness): Mean relative reflectance over the entire spectral range. This is preferred to B1 since values are easier to compare across studies. REF 4, 12
B3 (Intensity): Maximum relative reflectance (Reflectance at wavelength of maximum reflectance). Note that may be sensitive to noise near the peak. REF 1, 5, 6
S1 (Chroma): Relative contribution of a spectral range to the total brightness (B1) S1 is arbitrarily divided in 6 measures of chroma based on the wavelength ranges normally associated with specific hues. The values are calculated using the following ranges: S1U (UV, if applicable): lambda min-400nm; S1V (Violet) lambda min-415nm; S1B (Blue) 400nm-510nm; S1G (Green) 510nm-605nm; S1Y (Yellow) 550nm-625nm; S1R (Red) 605nm-lambda max. REF 2, 7, 8, 11-13
S2 (Spectral saturation): Rmax/Rmin This measure is sensitive to spectral noise. Proper interpretation of this value may be difficult for spectra with multiple peaks in the range of interest. REF 1
S3 (Chroma): Reflectance over the Rmax +- 50nm range divided by B1. Values for peaks within 50nm of either the minimum or maximum range of the data will not be comparable since the area under the curve for the area of interest will not always be based on the same wavelength range. Therefore, S3 should be interpreted with caution for peaks in the UV or Red range. REF 11
S4 (Spectral purity): |bmaxneg| , calculated by approximating the derivative of the spectral curve. As such, it is very sensitive to noise and should only be considered when data is adequately smoothed. NAs are returned for curves which do not, at any range of wavelength, decrease in intensity. Therefore, reflectance curves for brown and red surfaces, for example, should not generate a values. REF 1
S5 (Chroma): Similar in design to segment classification measures (see Montgomerie 2006 for details). REF 10
S6 (Contrast): Rmax - Rmin. Because it uses both Rmin and Rmax, this measure may be sensitive to spectral noise. REF 5, 6
S7 (Spectral saturation): Difference between the relative reflectance before and after the wavelength at which reflectance is halfway between its minimum (Rmin) and its maximum (Rmax). Somewhat sensitive to noise and can be misleading when more than one maxima and/or minima are present. REF 3, 9
S8 (Chroma): (Rmax - Rmin)/B2. Because it uses both Rmin and Rmax, this measure may be sensitive to spectral noise. REF 3, 13
S9 (Carotenoid chroma): (R700 - R450)/R700. Should only be used when the colour of the surface is clearly due to carotenoid pigmentation and R450 is lower than R700. Could be sensitive to noise. REF 8
S10 (Peaky chroma): (Rmax - Rmin)/B2 x |bmaxneg|. Should be used with properly smoothed curves. REF 7
H1 (Peak wavelength, hue): Wavelength of maximum reflectance. May be sensitive to noise and may be variable if there is more than one maxima. REF 1, 2, 4, 6, 7, 10-13
H2 (Hue): Wavelength at bmaxneg. Should be calculated using smoothed data. REF 2, 13
H3 (Hue): Wavelength at Rmid. Sensitive to noisy spectra and may be variable if there are more than one maxima and minima. REF 3, 9, 13
H4 (Hue): Similar in design to segment classification measures see Montgomerie (2006) for details. REF 10
H5 (Hue): Wavelength at bmax. Sensitive to noise and may be variable if there is more than one maxima and minima. REF 5
If minimum wavelength is over 400, UV chroma is not computed.
Variables which compute bmax and bmaxneg should be used with caution, for they rely on smoothed curves to remove noise, which would otherwise result in spurious results. Make sure chosen smoothing parameters are adequate.
Smoothing affects only B3, S2, S4, S6, S10, H2, and H5 calculation. All other variables can be reliably extracted using non-smoothed data.
Thomas E. White thomas.white026@gmail.com
Pierre-Paul Bitton bittonp@windsor.ca
Rafael Maia rm72@zips.uakron.edu
Montgomerie R. 2006. Analyzing colors. In Hill, G.E, and McGraw, K.J., eds. Bird Coloration. Volume 1 Mechanisms and measurements. Harvard University Press, Cambridge, Massachusetts.
References describing variables:
1- Andersson, S. 1999. Morphology of uv reflectance in a whistling-thrush: Implications for the study of structural colour signalling in birds. Journal of Avian Biology 30:193-204.
2- Andersson, S., J. Ornborg, and M. Andersson. 1998. Ultraviolet sexual dimorphism and assortative mating in blue tits. Proceedings of the Royal Society B 265:445-450.
3- Andersson, S., S. Pryke, J. Ornborg, M. Lawes, and M. Andersson. 2002. Multiple receivers, multiple ornaments, and a trade-off between agonistic and epigamic signaling in a widowbird. American Naturalist 160:683-691.
4- Delhey, K., A. Johnsen, A. Peters, S. Andersson, and B. Kempenaers. 2003. Paternity analysis reveals opposing selection pressures on crown coloration in the blue tit (Parus caeruleus). Proceedings of the Royal Society B 270:2057-2063.
5- Keyser, A. and G. Hill. 1999. Condition-dependent variation in the blue-ultraviolet coloration of a structurally based plumage ornament. Proceedings of the Royal Society B 266:771-777.
6- Keyser, A.J. and G. Hill. 2000. Structurally based plumage coloration is an honest signal of quality in male blue grosbeaks. Behavioural Ecology 11:202-209.
7- Ornborg, J., S. Andersson, S. Griffith, and B. Sheldon. 2002. Seasonal changes in a ultraviolet structural colour signal in blue tits, Parus caeruleus. Biological Journal of the Linnean Society 76:237-245.
8- Peters, A., A. Denk, K. Delhey, and B. Kempenaers. 2004. Carotenoid-based bill colour as an indicator of immunocompetence and sperm performance in male mallards. Journal of Evolutionary Biology 17:1111-1120.
9- Pryke, S., M. Lawes, and S. Andersson. 2001. Agonistic carotenoid signalling in male red-collared widowbirds: Aggression related to the colour signal of both the territory owner and model intruder. Animal Behaviour 62:695-704.
10- Saks, L., K. Mcgraw, and P. Horak. 2003. How feather colour reflects its carotenoid content. Functional Ecology 17:555-561.
11- Shawkey, M., A. Estes, L. Siefferman, and G. Hill. 2003. Nanostructure predicts intraspecific variation in ultraviolet-blue plumage colour. Proceedings of the Royal Society B 270:1455-1460.
12- Siefferman, L. and G. Hill. 2005. UV-blue structural coloration and competition for nestboxes in male eastern bluebirds. Animal Behaviour 69:67-72.
13- Smiseth, P., J. Ornborg, S. Andersson, and T. Amundsen. 2001. Is male plumage reflectance correlated with paternal care in bluethroats? Behavioural Ecology 12:164-170.
# Load data
data(sicalis)
# Calculate and display all spectral summary variables
summary(sicalis)
# Calculate only subset of B2, S8 and H1 as per Andersson (1999)
summary(sicalis, subset = TRUE)
# Calculate user-specified subset of B1 and H4
summary(sicalis, subset = c("B1", "H4"))
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