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The gene expression profile of Monochamus alternatus in response to deltamethrin exposure
Biological Journal of the Linnean SocieQ (1994), 53: 165-173
Measuring individual variation in colour: a comparison of two techniques MARLENE ZUK AND JOSEPH G. DECRUYENAERE
Department of Biology, University of California, Riverside, California, U.S.A. 92521 Received I Nouember 1993, accepted for publication 21 January 1994
Objective and reliable assessment of animal colouration is of great value to workers in the biological sciences. We present the results of a comparison between two colour measurement techniques: Munsell colour standard matching and spectroradiometry. As part of ongoing research on sexual selection in red jungle fowl (Gallusgallus), feather and comb colour of 49 roosters was measured using both techniques. Previous research showed that hens use variation in feather and comb colour in mate choice, and we allowed hens to choose between paired roosters. Colour matching and spectroradiometry scores were generally correlated, but spectroradiometry was more sensitive in detecting variation and also provided a better estimate of the role of secondary sexual characters in male mating success. ADDITIONAL KEY WORDS:-Colouration characters - spectroradiometry.
- colour measurement - Munsell
-
secondary sex
CONTENTS Introduction . . . . . . . . . Material and methods. . . . . . . Colour measurement . . . . . . Estimating chroma and hue from Li-Cor data Mate choice trials . . . . . . Results . . . . . . . . . . . Discussion . . . . . . . . . Acknowledgements . . . . . . . References . . . . . . . . .
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I65 166 166 167 168 169 I72 173 173
INTRODUCTION
Measurement of animal colour patterns and of individual variation in colour is of interest to workers in a wide variety of fields, including behaviour, physiology, genetics, and evolutionary biology. Both inter- and intra-specific comparisons of the degree of development of colourful secondary sex characters, for example, are important in sexual selection studies (Hoglund, 1989; Houde, 1988). Such comparisons often rely on quantifying differences in ‘brightness’ or ‘showiness’ among individuals, using a variety of techniques. Endler (1990) lists subjective ranking by human observers, matching to commercially produced colour standards, and spectroradiometry as methods for evaluating colour in animals.
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M. ZUK AND J. G. DECRUYENAERE
As Endler (1990) points out, however, both subjective ranking of individuals as ‘bright’ or ‘dull’ and the use of colour standards for matching are problematic. Subjective ranking obviously may vary with the observer. Similarly, both environmental variation of background and lighting conditions at the time of comparison and variation among people in perception of colour can affect the results of colour matching between the standard and the sample (Endler, 1990; Neitz & Jacobs, 1986). Human vision is also different from that of other animal groups. Endler (1990) therefore suggests the use of reflectance spectroradiometers, machines which read the reflectance of light from the sample, to more objectively quantify colour. Here we report the results of a comparison of two of these techniques: colour matching using the Munsell system of colour standards, and measurements of reflectance using a Li-Cor 1800 portable spectroradiometer (Li-Cor, 1982). Both techniques were employed to examine feather and comb colours in captive male red jungle fowl (Callus gallus), a species currently the subject of sexual selection studies (Zuk et al., 1990). Females use colour of male ornaments in mate choice (Zuk el aE., 1990), so the accurate measurement of colour is critical for understanding female preference. First, we examine the correlation between measurements of the same trait using the two methods. Second, we compare the ability of each set of measurements to explain variation in male mating success using variation in the colours of male sexual characters. Assuming that females are better than humans at detecting colour variation, a measurement technique that explains more variation in female choice is the more accurate one. Finally, we discuss some limitations of the techniques for field workers using live terrestrial animals. MATERIAL AND METHODS
Colour measurement Jungle fowl in the study were all males in their first breeding season, aged 8-12 months, housed individually on the campus of the University of California at Riverside in outdoor pens. Commercial chicken feed and water were available ad libitum. Feather and comb colours were measured using two techniques, the Munsell Book of Color, Glossy Finish Collection and the Li-Cor LI-1800 Portable Research Spectroradiometer. T h e Munsell method uses a graded series of colour samples, each on a separate ‘chip’. Chips are organized according to hue, value, and chroma. Hue refers to colour in the colloquial sense, i.e. red, orange, green, blue, etc. Hues are arranged in a 100-hue circuit and divided into ten colour categories: red, yellow-red, yellow, green-yellow, green, blue-green, blue, purpleblue, purple, and red-purple. Value refers to the relative darkness in the colour sample, and chroma indicates the degree to which the sample is saturated with the hue in question (Burley & Coopersmith, 1987; Munsell, 1976). The differences between each of the hues, values, and chromas represent visually, equally-spaced gradations based on the human perception of changes in each of these parameters (Munsell, 1976). Munsell measurements took place in the laboratory under standardized conditions of indoor fluorescent lighting next to a large window to provide indirect sunlight and allow more realistic estimates and colour. Colour was
COLOUR MEASUREMENT COMPARISON
167
measured on the comb, head feathers, hackle feathers (feathers around the base of the neck), saddle base and saddle tip feathers (lanceolate feathers growing over the back, with base feathers closer to the neck and tips more posteriorly oriented). Measurements were made over a period of several weeks and were carried out only on sunny days to avoid the risk of inconsistency in the colour matching due to differences in lighting. In Riverside, sunny day are the norm, so few measurements were delayed. All Munsell measurements were made by the same two persons, with discussion until a consensus was reached on the best match. While the birds were in the lab for Munsell measurement, a representative sample of each feather type (usually the same feather used to make the match with Munsell chips) was clipped from the bird and mounted with glue on a 7.5 cm x 12.7 cm white card. Feathers were glued on the card to yield an opaque layer for scanning. Combs were measured using the Li-Cor by holding the bird's comb under the lens, and feathers were measured using the samples on the cards. Combs of most of the birds were scanned on the same day. T o use the Li-Cor, samples must be illuminated under a constant, intense light source. In addition to the ambient light of the room, we used the Foster FO-150 fibreoptic light with a Tripp-Lite line stabilizer/conditioner to regulate voltage going to the light so that any power spikes would not change the reflectance from the sample to the Li-Cor. Measurement consisted of first scanning a blank card of the type used for the feather samples as a reference standard under the LI-1800 with attached 1800-10 Fibre Optic Probe, 1800-06 Telescope/Microscope Receptor, and 1800-01B Portable Terminal. After scanning the reference card, the feather or comb was scanned. The Li-Cor LI-1800 contains a magnifying lens which directs the image being scanned to a fibreoptic cable. The image carried by the cable is read by a computer, which assigns a numerical value for reflectance in intervals of two nanometers. The distribution of these reflectances generates a curve representing reflectance versus wavelength. The area under this curve represents the total reflectance for the range of wavelengths along the x-axis (for our purposes, 380-700 nm). This reflectance is analogous to value in the Munsell system.
Estimating chroma and hue from Li-Cor data Methods for converting Li-Cor values to chroma and hue were adapted from Endler ( 1990) and Hamilton (unpublished manuscript). Comparing the two methods involves mathematical manipulations of the Li-Cor data to convert reflectance into chroma and hue. First the range of wavelengths in question is divided into four equal bandwidths, A, B, C and D. Graphically, A corresponds to positive-X, B to positive-", C to negative-X, and D to negative-Y. The differences in reflectance between segments A and C and segments B and D yield coordinates from which chroma and hue are determined. The coordinates for maximum reflectance of a sample are (A-C), (B-D), where A, B, C and D are the reflectances in their respective bandwidths.
,
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M. ZUK AND J. G . DECRUYENAERE
The origin represents neutrality or the absence of chroma; chroma increases with distance from the origin and can be quantified by finding the linear distance from the origin to the coordinates defined above, with the equation Ch = [(A-C)’+
(B-D)’]-”*,
where Ch is the chroma. Hue changes with direction and can be calculated by finding the coordinates’ angle relative to an arbitrarily assigned position; let us assign this position to the ‘A’ direction. B is therefore go”, C is 180” and D is 270”. The hue for any given coordinate pair can be found by
H = arcsin [IA-Cl/Ch] = arcCos [IB-DI/Ch], H being hue. Note that the colour ‘circle’ devised for this experiment is based on the spectral range of avian visual systems, and is, therefore, not interchangeable with the hue circuit of Munsell, which is based on human vision. The accepted range for human vision is 400-700 nm (Hurvich, 1981); the range of wavelengths used in our calculations was 380-700 nm. This range was selected to include the near ultraviolet spectrum, which is visible to birds (Hurvich, 1981), while working within the limitations of the Li-Cor spectroradiometer and the standard lamp.
M a t e choice trials After colour measurements were taken, the males were used in mate-choice trials. These were done in the same manner as in previous experiments with jungle fowl (Zuk et al., 1990). Pairs of males were randomly selected from four groups totalling 44 individuals, of which 37 were used. The groups consisted of ‘young’ (8-9 months old) and ‘old’ (10-1 1 months old) males, with half of each group given a subcutaneous implant of testosterone. Testosterone-implanted and control males were randomly paired within each age group. Later analysis showed that the implants had not affected development of secondary sex characters (Zuk, unpublished data), and results are reported without regard for the manipulation. A total of 69 trials was run, and each male was used 2-3 times. Females were selected at random and used only once. Males and females were separated for about three months prior to the trials; males were isolated in individual pens, and females were kept multiply in all-female pens. Trials were run outdoors in enclosures measuring about 4.9 m by 4.9 m, and were observed from blinds fitted with one-way glass outside the pens. Each male was tethered at the far end of the enclosure on either side of a wood partition which hid them from each other’s view. The tethers were long enough to allow the males to move about their own individual compartments but did not extend past the wood partition. At the near end of the pen was a smaller pen from which the female was able to observe both males; this smaller pen could be opened from the observation blind by a rope, allowing the observer to let the female out without entering the pen and disturbing the birds. As soon as the males had been tethered, the female was placed in her pen, and the three birds were left undisturbed. After one hour had elapsed the female was released and allowed to interact with the two males. The trial ended with the first copulation or when 30 min had elapsed. If no copulation occurred before
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the end of the 30 min, the choice was scored for the male to whom the female showed a clear solicitation crouch. If the female crouched for neither or both males the trial was discarded. I n most earlier work, relatively few females did not choose ( < 10%). Data were analysed using correlation, regression, and stepwise regression procedures in PC-SAS. The stepwise procedure is an exploratory model-building procedure by which variables are selected and rejected according to how well they fit into a multiple regression analysis (SAS, 1985). Stepwise procedures were run using the MAXR option. This option builds models by adding and removing variables until the model with the highest R2 value is reached and presents the ‘best’ model for any number of variables contained in the data set. RESULTS
Munsell and Li-Cor scores for value of comb, head feathers, hackle feathers, saddle base feathers, and saddle tip feathers were compared using Pearson correlation in SAS-PC (abbreviations for traits in Table 1). The data range for most of the measures was sufficiently narrow that the data are approximately normally distributed. Scores for hue and chroma were not analysed in this procedure because scores for Li-Cor are not independent measures, being derived from total reflectance, whereas the analogous Munsell scores are taken directly. Three of the five pairs of variables-head, hackle and saddle tip-were highly significantly correlated; saddle base and comb were not (Table 2). SBVM (Saddle Base Value as measured by Munsell) was the same for all birds, leaving no variance to compare with SBVL (Saddle Base Value as measured by Li-Cor). Comb colour was measured by the two methods on different days and may actually have changed between measurements (Table 2). T o find which of the two methods could best explain variation in mating success using feather and comb colour, stepwise regressions were run on both data sets. Mating success, calculated as the proportion of trials in which a male was chosen out of the total trials he attended (expressed as ‘wins’), was used as TABLE 1 . Abbreviations for variables measured using Munsell and Li-Cor techniques for assessing colour in male red jungle fowl Trait Comb Hue Comb Value Comb Chroma HAckle Hue HAckle Value HAckle Chroma HEad Hue HEad Value HEad Chroma Saddle Base Hue Saddle Base Value Saddle Base Chroma Saddle Tip Hue Saddle Tip Value Saddle Tip Chroma
Munsell abbreviation
Li-Cor abbreviation
CHM CVM CCM HAHM HAVM HACM HEHM HEVM HECM SBHM SBVM SBCM STHM STVM STCM
CHL CVL CCL HAHL HAVL HACL HEHL HEVL HECL SBHL SBVL SBCL STHL STVL STCL
M. ZUK AND J. G. DECRUYENAERE
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TABLE 2. Pearson correlation coefficients, P-values, and number of observations for feather and comb colours measured in red jungle fowl using Munsell colour matching and Li-Cor spectroradiometry techniques. Values are missing for Saddle Base Value correlations because no variation in these feathers was detected using the Munsell system. Abbreviations in Table 1
CVL HEVL HAVL SBVL STVL
CVM
HEVM
HAVM
0.070 0.646 n = 45 0.033 0.820 n = 49 -0.315 0.027 n = 49 -0.039 0.788 n = 49 -0.245 0.089 n = 49
-0.073 0.634 45 0.424 0.002 49 -0.248 0.085 49 0.21 1 0.146 49 0.284 0.048 49
0.105 0.492 45 0.482 0.001 47 0.587 0.001 49 0.178 0.222 49 0.389 0.006 49
SBVM
STVM 0.321
~
-
0.034
43
44 0.243 0.097 48 0.298 0.040 48 0.254 0.082 48 0.519 0.001 48
-
47 -
47 -
47 -
47
the dependent variable, and hue, value and chroma of the various characters were used as the regressors. Using a probability value of 0.01 as a precondition, the Munsell data produced a model with a maxim of four variables (F = 4.08, P = 0.01, 4 d.f.); the Li-Cor data produced a model of nine variables (F = 3.14, P = 0.01, 9d.f.) (Tables 3 and 4). The best five-variable model from both stepwise regression was selected, and this was used to predict mating success for each male. The predicted value was then plotted against ‘wins’ to evaluate the model. Data used in the analyses are approximately normally distributed. Both models accounted for more than 30% of the variation in mating success, the Munsell model with R2 = 0.34, P < 0.01 and the Li-Cor with R2 = 0.39, P < 0.002. All of the variables used in the Li-Cor model were statistically significant predictors of mating success (P< 0.05), compared with only one of the Munsell variables (Table 5 and 6). TABLE 3. Results of stepwise regression of male mating success on Munsell colour matching scores for feather and comb colours. This model contained the most variables while still yielding an overall P-value of < 0.01. Abbreviations in Table 1 d.f.
Sum of Squares
F
P
4 38 42
1.62 3.76 5.37
4.08
0.01
Variable
Type I1 Sum of Squares
F
P
CCM HAHM HEHM SLHM
0.17 0.09 0.41 0.73
I .89 0.95 4.16 7.38
0.20 0.34 0.05 0.01
Regression Error Total
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TABLE 4. Results of stepwise regression of male mating success on Li-Cor spectroradiometry scores for feather and comb colours. This model contained the most variables while still yielding a n overall P-value of < 0.01. Abbreviations in Table 1 d.f.
Sum of Squares
F
P
9 34
2.35 2.83
3.14
0.01
Type I1 Sum of Squares
F
P
0.69 0.70 0.67 0.16 0.07 I .07 0.54 0.05 0.09
8.25 8.42 8.09 1.95 0.81 12.90 6.50 0.60 1.12
0.01 0.01 0.01 0.17 0.38 0.00 0.02 0.44 0.30
Regression Error V ari abte CCL HAHL HAVL HEHL HECL SDCL SLHL SLVL SLCL
TABLE 5. Best 5-variable model found using stepwise regression of male mating success on Munsell colour matching scores for feather and comb colours. Abbreviations in Table 1 Source
d.f.
F
P
r2
Model Error
5 36
3.74
0.0079
0.34
Variable
T for HO: Parameter = 0 Prob > IT1
HAHM HEHM HECM SBHM STHM
0.08 1.18 1.44 1.51 2.28
0.29 0.25 0.16 0.14 0.03
TABLE 6. Best 5-variable model found using stepwise regression of male mating success on Li-Cor spectroradiometry scores for feather and comb colours. Abbreviations in Table 1 Source
d.f.
F
P
P
Model
5 37
4.83
< 0.01
0.39
Error
Variable
T for H,: Parameter = 0 Prob > IT1
CCL HAHL HAVL SBCL STHL
-2.15 3.42 -3.20 3.61 2.44
0.04 0.00
0.00 0.00 0.02
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M. ZUK AND J. G. DECRUYENAERE DISCUSSION
As Endler ( 1990) suggested, spectroradiometry provided a higher resolution measure of colour than did the Munsell colour matching technique. Although the two assessments of value, or amount of black, in feather colours were generally correlated (Table 2), the Li-Cor scores were able to explain a greater portion of variation in mating success with more individually significant independent variables (R2 of nearly 40% using the Li-Cor scores vs R2 of 34% using Munsell). Both techniques lead to the conclusion that morphology is important in female choice, but more information about the role of invididual characters is obtained with the Li-Cor scores. Several factors probably contributed to the superiority of the Li-Cor technique. First, the spectroradiometer can quantify much finer distinctions between colours, as evidenced by the variation in scores for saddle base feather value obtained using the Li-Cor when the observers gave all of the samples identical ranks (Table 2). Although observers may be able to discern differences in feather colours, they are constrained by the available colour standards. Second, day to day variation in either observer judgement or environmental conditions can be minimized by scanning all the samples under the spectroradiometer in a single session with a standard light source, as well as by the obvious lack of subjectivity in reading the reflectance scores compared with evaluating the accuracy of a match between a feather and a colour standard. A third advantage not directly employed here is that by keeping the feather clippings, any samples can be re-measured using the spectroradiometer with the exception that the resulting scores will be the same as before, assuming equivalent ambient lighting conditions; even if the same samples were subjected to Munsell matching on different occasions, the variation mentioned above could be expected to lead to a lack of repeatability in measurement. Despite these advantages, some difficulties remain both in using the Li-Cor and in interpreting its findings. Measurement of feather samples after they have been clipped from the bird is obviously straigthforward, but this technique is not feasible for fleshy parts such as the comb which must be scored on live animals. The males were sometimes difficult to restrain under the scanner, and it was therefore impossible to safely measure iris colour, although iris colour was important in previous measures of male mating success (Zuk et al., 1990). Colours of combs and eyes may also change during handling, and if measurement time varies depending on how the animal is to restrain, repeatedly may suffer. The extent of this kind of limitation will depend on the species being measured. Another drawback to the use of spectroradiometry is the correspondence between reflectance scores and a human concept such as ‘showiness’ or ‘brightness’. As Endler (1990) discusses, it may be necessary to take into account the difference in colour between patches on the same individual, or the contrast between the animal and its background. In addition, the sensory abilities of the animal may not correspond to those of the spectroradiometer. Use of the variances or coefficients of variation for the spectroradiometry measurements is also recommended (Endler, 1990). For monochromatic species or for those which are not usually seen against a consistent background, even these suggestions may not provide a complete solution to the problem. Nevertheless,
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reflectance spectroradiometry offers the potential for less subjective colour measurement of animals, and as we have shown here, scores can be integrated with data on mating success to yield biologically interesting interpretations of the role of secondary sex characters in sexual selection. ACKNOWLEDGEMENTS
We are grateful to Cassandra Hayes for invaluable help in measuring birds, Paul Hamilton for preliminary work on use of the Li-Cor, John T. Rotenberry for statistical advice, and Torgeir Johnsen, Paul Hamilton and Mark Chappell for comments on the manuscript. Torgeir Johnsen, Troy MacLarty, Eric Focht, and Christopher Janus helped maintain the jungle fowl colony. This research is supported by National Science Foundation grants IBN-9 120902 and DEB-9257749 and Research Experience for Undergraduate supplements to MZ. REFERENCES
Burley N, Coopersmith CB. 1987. Bill color preferences of zebra finches. Ethology 76: 133-151. b d l e r JA. 1990. On the measurement and classification of colour in studies of animal colour patterns. Biological journal of the Linnean Society 41: 315-352. Hoglund J. 1989. Size and plumage dimorphism in lek-breeding birds: a comparative analysis. American Naturalist 134: 72-87. Houde AE. 1988. Genetic differentiation in female choice between two guppy populations. Animal Behauiour 36: 511-516. Hurvich LM. 1981. Color uision. Sunderland (Mass.): Sinauer Associates, Inc. Li-Cor. 1982. Radiation measurements and instrumentation. Publication No. 8208-LM. Lincoln, Nebraska. Munsell (Color Company). 1976. Munsell Book of Color, Glossy Finish Collection (2 volumes). Baltimore: Munsell/Macbeth/Kollmorgan Corp. Neitt J, Jacobs GH.1986. Polymorphism of the long-wavelength cone in normal human colour vision. Nature (London) 323: 623-625. SAS. 1985. S A S I S T A T Guide f o r personal compulers. Version 5 ed. SAS Institute, Cary, N.C. Zuk MyThornhill R, Ligon JD, Johnson K, Austad S, Ligon S, Thornhill N W , Costin C. 1990. The role of male ornaments and courtship behavior in female mate choice of red jungle fowl. The American Naturalist 136: 459-473.
Measuring individual variation in colour: a comparison of two techniques MARLENE ZUK AND JOSEPH G. DECRUYENAERE
Department of Biology, University of California, Riverside, California, U.S.A. 92521 Received I Nouember 1993, accepted for publication 21 January 1994
Objective and reliable assessment of animal colouration is of great value to workers in the biological sciences. We present the results of a comparison between two colour measurement techniques: Munsell colour standard matching and spectroradiometry. As part of ongoing research on sexual selection in red jungle fowl (Gallusgallus), feather and comb colour of 49 roosters was measured using both techniques. Previous research showed that hens use variation in feather and comb colour in mate choice, and we allowed hens to choose between paired roosters. Colour matching and spectroradiometry scores were generally correlated, but spectroradiometry was more sensitive in detecting variation and also provided a better estimate of the role of secondary sexual characters in male mating success. ADDITIONAL KEY WORDS:-Colouration characters - spectroradiometry.
- colour measurement - Munsell
-
secondary sex
CONTENTS Introduction . . . . . . . . . Material and methods. . . . . . . Colour measurement . . . . . . Estimating chroma and hue from Li-Cor data Mate choice trials . . . . . . Results . . . . . . . . . . . Discussion . . . . . . . . . Acknowledgements . . . . . . . References . . . . . . . . .
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I65 166 166 167 168 169 I72 173 173
INTRODUCTION
Measurement of animal colour patterns and of individual variation in colour is of interest to workers in a wide variety of fields, including behaviour, physiology, genetics, and evolutionary biology. Both inter- and intra-specific comparisons of the degree of development of colourful secondary sex characters, for example, are important in sexual selection studies (Hoglund, 1989; Houde, 1988). Such comparisons often rely on quantifying differences in ‘brightness’ or ‘showiness’ among individuals, using a variety of techniques. Endler (1990) lists subjective ranking by human observers, matching to commercially produced colour standards, and spectroradiometry as methods for evaluating colour in animals.
+
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0 1994 The Linnean Society of London
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M. ZUK AND J. G. DECRUYENAERE
As Endler (1990) points out, however, both subjective ranking of individuals as ‘bright’ or ‘dull’ and the use of colour standards for matching are problematic. Subjective ranking obviously may vary with the observer. Similarly, both environmental variation of background and lighting conditions at the time of comparison and variation among people in perception of colour can affect the results of colour matching between the standard and the sample (Endler, 1990; Neitz & Jacobs, 1986). Human vision is also different from that of other animal groups. Endler (1990) therefore suggests the use of reflectance spectroradiometers, machines which read the reflectance of light from the sample, to more objectively quantify colour. Here we report the results of a comparison of two of these techniques: colour matching using the Munsell system of colour standards, and measurements of reflectance using a Li-Cor 1800 portable spectroradiometer (Li-Cor, 1982). Both techniques were employed to examine feather and comb colours in captive male red jungle fowl (Callus gallus), a species currently the subject of sexual selection studies (Zuk et al., 1990). Females use colour of male ornaments in mate choice (Zuk el aE., 1990), so the accurate measurement of colour is critical for understanding female preference. First, we examine the correlation between measurements of the same trait using the two methods. Second, we compare the ability of each set of measurements to explain variation in male mating success using variation in the colours of male sexual characters. Assuming that females are better than humans at detecting colour variation, a measurement technique that explains more variation in female choice is the more accurate one. Finally, we discuss some limitations of the techniques for field workers using live terrestrial animals. MATERIAL AND METHODS
Colour measurement Jungle fowl in the study were all males in their first breeding season, aged 8-12 months, housed individually on the campus of the University of California at Riverside in outdoor pens. Commercial chicken feed and water were available ad libitum. Feather and comb colours were measured using two techniques, the Munsell Book of Color, Glossy Finish Collection and the Li-Cor LI-1800 Portable Research Spectroradiometer. T h e Munsell method uses a graded series of colour samples, each on a separate ‘chip’. Chips are organized according to hue, value, and chroma. Hue refers to colour in the colloquial sense, i.e. red, orange, green, blue, etc. Hues are arranged in a 100-hue circuit and divided into ten colour categories: red, yellow-red, yellow, green-yellow, green, blue-green, blue, purpleblue, purple, and red-purple. Value refers to the relative darkness in the colour sample, and chroma indicates the degree to which the sample is saturated with the hue in question (Burley & Coopersmith, 1987; Munsell, 1976). The differences between each of the hues, values, and chromas represent visually, equally-spaced gradations based on the human perception of changes in each of these parameters (Munsell, 1976). Munsell measurements took place in the laboratory under standardized conditions of indoor fluorescent lighting next to a large window to provide indirect sunlight and allow more realistic estimates and colour. Colour was
COLOUR MEASUREMENT COMPARISON
167
measured on the comb, head feathers, hackle feathers (feathers around the base of the neck), saddle base and saddle tip feathers (lanceolate feathers growing over the back, with base feathers closer to the neck and tips more posteriorly oriented). Measurements were made over a period of several weeks and were carried out only on sunny days to avoid the risk of inconsistency in the colour matching due to differences in lighting. In Riverside, sunny day are the norm, so few measurements were delayed. All Munsell measurements were made by the same two persons, with discussion until a consensus was reached on the best match. While the birds were in the lab for Munsell measurement, a representative sample of each feather type (usually the same feather used to make the match with Munsell chips) was clipped from the bird and mounted with glue on a 7.5 cm x 12.7 cm white card. Feathers were glued on the card to yield an opaque layer for scanning. Combs were measured using the Li-Cor by holding the bird's comb under the lens, and feathers were measured using the samples on the cards. Combs of most of the birds were scanned on the same day. T o use the Li-Cor, samples must be illuminated under a constant, intense light source. In addition to the ambient light of the room, we used the Foster FO-150 fibreoptic light with a Tripp-Lite line stabilizer/conditioner to regulate voltage going to the light so that any power spikes would not change the reflectance from the sample to the Li-Cor. Measurement consisted of first scanning a blank card of the type used for the feather samples as a reference standard under the LI-1800 with attached 1800-10 Fibre Optic Probe, 1800-06 Telescope/Microscope Receptor, and 1800-01B Portable Terminal. After scanning the reference card, the feather or comb was scanned. The Li-Cor LI-1800 contains a magnifying lens which directs the image being scanned to a fibreoptic cable. The image carried by the cable is read by a computer, which assigns a numerical value for reflectance in intervals of two nanometers. The distribution of these reflectances generates a curve representing reflectance versus wavelength. The area under this curve represents the total reflectance for the range of wavelengths along the x-axis (for our purposes, 380-700 nm). This reflectance is analogous to value in the Munsell system.
Estimating chroma and hue from Li-Cor data Methods for converting Li-Cor values to chroma and hue were adapted from Endler ( 1990) and Hamilton (unpublished manuscript). Comparing the two methods involves mathematical manipulations of the Li-Cor data to convert reflectance into chroma and hue. First the range of wavelengths in question is divided into four equal bandwidths, A, B, C and D. Graphically, A corresponds to positive-X, B to positive-", C to negative-X, and D to negative-Y. The differences in reflectance between segments A and C and segments B and D yield coordinates from which chroma and hue are determined. The coordinates for maximum reflectance of a sample are (A-C), (B-D), where A, B, C and D are the reflectances in their respective bandwidths.
,
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M. ZUK AND J. G . DECRUYENAERE
The origin represents neutrality or the absence of chroma; chroma increases with distance from the origin and can be quantified by finding the linear distance from the origin to the coordinates defined above, with the equation Ch = [(A-C)’+
(B-D)’]-”*,
where Ch is the chroma. Hue changes with direction and can be calculated by finding the coordinates’ angle relative to an arbitrarily assigned position; let us assign this position to the ‘A’ direction. B is therefore go”, C is 180” and D is 270”. The hue for any given coordinate pair can be found by
H = arcsin [IA-Cl/Ch] = arcCos [IB-DI/Ch], H being hue. Note that the colour ‘circle’ devised for this experiment is based on the spectral range of avian visual systems, and is, therefore, not interchangeable with the hue circuit of Munsell, which is based on human vision. The accepted range for human vision is 400-700 nm (Hurvich, 1981); the range of wavelengths used in our calculations was 380-700 nm. This range was selected to include the near ultraviolet spectrum, which is visible to birds (Hurvich, 1981), while working within the limitations of the Li-Cor spectroradiometer and the standard lamp.
M a t e choice trials After colour measurements were taken, the males were used in mate-choice trials. These were done in the same manner as in previous experiments with jungle fowl (Zuk et al., 1990). Pairs of males were randomly selected from four groups totalling 44 individuals, of which 37 were used. The groups consisted of ‘young’ (8-9 months old) and ‘old’ (10-1 1 months old) males, with half of each group given a subcutaneous implant of testosterone. Testosterone-implanted and control males were randomly paired within each age group. Later analysis showed that the implants had not affected development of secondary sex characters (Zuk, unpublished data), and results are reported without regard for the manipulation. A total of 69 trials was run, and each male was used 2-3 times. Females were selected at random and used only once. Males and females were separated for about three months prior to the trials; males were isolated in individual pens, and females were kept multiply in all-female pens. Trials were run outdoors in enclosures measuring about 4.9 m by 4.9 m, and were observed from blinds fitted with one-way glass outside the pens. Each male was tethered at the far end of the enclosure on either side of a wood partition which hid them from each other’s view. The tethers were long enough to allow the males to move about their own individual compartments but did not extend past the wood partition. At the near end of the pen was a smaller pen from which the female was able to observe both males; this smaller pen could be opened from the observation blind by a rope, allowing the observer to let the female out without entering the pen and disturbing the birds. As soon as the males had been tethered, the female was placed in her pen, and the three birds were left undisturbed. After one hour had elapsed the female was released and allowed to interact with the two males. The trial ended with the first copulation or when 30 min had elapsed. If no copulation occurred before
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the end of the 30 min, the choice was scored for the male to whom the female showed a clear solicitation crouch. If the female crouched for neither or both males the trial was discarded. I n most earlier work, relatively few females did not choose ( < 10%). Data were analysed using correlation, regression, and stepwise regression procedures in PC-SAS. The stepwise procedure is an exploratory model-building procedure by which variables are selected and rejected according to how well they fit into a multiple regression analysis (SAS, 1985). Stepwise procedures were run using the MAXR option. This option builds models by adding and removing variables until the model with the highest R2 value is reached and presents the ‘best’ model for any number of variables contained in the data set. RESULTS
Munsell and Li-Cor scores for value of comb, head feathers, hackle feathers, saddle base feathers, and saddle tip feathers were compared using Pearson correlation in SAS-PC (abbreviations for traits in Table 1). The data range for most of the measures was sufficiently narrow that the data are approximately normally distributed. Scores for hue and chroma were not analysed in this procedure because scores for Li-Cor are not independent measures, being derived from total reflectance, whereas the analogous Munsell scores are taken directly. Three of the five pairs of variables-head, hackle and saddle tip-were highly significantly correlated; saddle base and comb were not (Table 2). SBVM (Saddle Base Value as measured by Munsell) was the same for all birds, leaving no variance to compare with SBVL (Saddle Base Value as measured by Li-Cor). Comb colour was measured by the two methods on different days and may actually have changed between measurements (Table 2). T o find which of the two methods could best explain variation in mating success using feather and comb colour, stepwise regressions were run on both data sets. Mating success, calculated as the proportion of trials in which a male was chosen out of the total trials he attended (expressed as ‘wins’), was used as TABLE 1 . Abbreviations for variables measured using Munsell and Li-Cor techniques for assessing colour in male red jungle fowl Trait Comb Hue Comb Value Comb Chroma HAckle Hue HAckle Value HAckle Chroma HEad Hue HEad Value HEad Chroma Saddle Base Hue Saddle Base Value Saddle Base Chroma Saddle Tip Hue Saddle Tip Value Saddle Tip Chroma
Munsell abbreviation
Li-Cor abbreviation
CHM CVM CCM HAHM HAVM HACM HEHM HEVM HECM SBHM SBVM SBCM STHM STVM STCM
CHL CVL CCL HAHL HAVL HACL HEHL HEVL HECL SBHL SBVL SBCL STHL STVL STCL
M. ZUK AND J. G. DECRUYENAERE
I70
TABLE 2. Pearson correlation coefficients, P-values, and number of observations for feather and comb colours measured in red jungle fowl using Munsell colour matching and Li-Cor spectroradiometry techniques. Values are missing for Saddle Base Value correlations because no variation in these feathers was detected using the Munsell system. Abbreviations in Table 1
CVL HEVL HAVL SBVL STVL
CVM
HEVM
HAVM
0.070 0.646 n = 45 0.033 0.820 n = 49 -0.315 0.027 n = 49 -0.039 0.788 n = 49 -0.245 0.089 n = 49
-0.073 0.634 45 0.424 0.002 49 -0.248 0.085 49 0.21 1 0.146 49 0.284 0.048 49
0.105 0.492 45 0.482 0.001 47 0.587 0.001 49 0.178 0.222 49 0.389 0.006 49
SBVM
STVM 0.321
~
-
0.034
43
44 0.243 0.097 48 0.298 0.040 48 0.254 0.082 48 0.519 0.001 48
-
47 -
47 -
47 -
47
the dependent variable, and hue, value and chroma of the various characters were used as the regressors. Using a probability value of 0.01 as a precondition, the Munsell data produced a model with a maxim of four variables (F = 4.08, P = 0.01, 4 d.f.); the Li-Cor data produced a model of nine variables (F = 3.14, P = 0.01, 9d.f.) (Tables 3 and 4). The best five-variable model from both stepwise regression was selected, and this was used to predict mating success for each male. The predicted value was then plotted against ‘wins’ to evaluate the model. Data used in the analyses are approximately normally distributed. Both models accounted for more than 30% of the variation in mating success, the Munsell model with R2 = 0.34, P < 0.01 and the Li-Cor with R2 = 0.39, P < 0.002. All of the variables used in the Li-Cor model were statistically significant predictors of mating success (P< 0.05), compared with only one of the Munsell variables (Table 5 and 6). TABLE 3. Results of stepwise regression of male mating success on Munsell colour matching scores for feather and comb colours. This model contained the most variables while still yielding an overall P-value of < 0.01. Abbreviations in Table 1 d.f.
Sum of Squares
F
P
4 38 42
1.62 3.76 5.37
4.08
0.01
Variable
Type I1 Sum of Squares
F
P
CCM HAHM HEHM SLHM
0.17 0.09 0.41 0.73
I .89 0.95 4.16 7.38
0.20 0.34 0.05 0.01
Regression Error Total
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TABLE 4. Results of stepwise regression of male mating success on Li-Cor spectroradiometry scores for feather and comb colours. This model contained the most variables while still yielding a n overall P-value of < 0.01. Abbreviations in Table 1 d.f.
Sum of Squares
F
P
9 34
2.35 2.83
3.14
0.01
Type I1 Sum of Squares
F
P
0.69 0.70 0.67 0.16 0.07 I .07 0.54 0.05 0.09
8.25 8.42 8.09 1.95 0.81 12.90 6.50 0.60 1.12
0.01 0.01 0.01 0.17 0.38 0.00 0.02 0.44 0.30
Regression Error V ari abte CCL HAHL HAVL HEHL HECL SDCL SLHL SLVL SLCL
TABLE 5. Best 5-variable model found using stepwise regression of male mating success on Munsell colour matching scores for feather and comb colours. Abbreviations in Table 1 Source
d.f.
F
P
r2
Model Error
5 36
3.74
0.0079
0.34
Variable
T for HO: Parameter = 0 Prob > IT1
HAHM HEHM HECM SBHM STHM
0.08 1.18 1.44 1.51 2.28
0.29 0.25 0.16 0.14 0.03
TABLE 6. Best 5-variable model found using stepwise regression of male mating success on Li-Cor spectroradiometry scores for feather and comb colours. Abbreviations in Table 1 Source
d.f.
F
P
P
Model
5 37
4.83
< 0.01
0.39
Error
Variable
T for H,: Parameter = 0 Prob > IT1
CCL HAHL HAVL SBCL STHL
-2.15 3.42 -3.20 3.61 2.44
0.04 0.00
0.00 0.00 0.02
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M. ZUK AND J. G. DECRUYENAERE DISCUSSION
As Endler ( 1990) suggested, spectroradiometry provided a higher resolution measure of colour than did the Munsell colour matching technique. Although the two assessments of value, or amount of black, in feather colours were generally correlated (Table 2), the Li-Cor scores were able to explain a greater portion of variation in mating success with more individually significant independent variables (R2 of nearly 40% using the Li-Cor scores vs R2 of 34% using Munsell). Both techniques lead to the conclusion that morphology is important in female choice, but more information about the role of invididual characters is obtained with the Li-Cor scores. Several factors probably contributed to the superiority of the Li-Cor technique. First, the spectroradiometer can quantify much finer distinctions between colours, as evidenced by the variation in scores for saddle base feather value obtained using the Li-Cor when the observers gave all of the samples identical ranks (Table 2). Although observers may be able to discern differences in feather colours, they are constrained by the available colour standards. Second, day to day variation in either observer judgement or environmental conditions can be minimized by scanning all the samples under the spectroradiometer in a single session with a standard light source, as well as by the obvious lack of subjectivity in reading the reflectance scores compared with evaluating the accuracy of a match between a feather and a colour standard. A third advantage not directly employed here is that by keeping the feather clippings, any samples can be re-measured using the spectroradiometer with the exception that the resulting scores will be the same as before, assuming equivalent ambient lighting conditions; even if the same samples were subjected to Munsell matching on different occasions, the variation mentioned above could be expected to lead to a lack of repeatability in measurement. Despite these advantages, some difficulties remain both in using the Li-Cor and in interpreting its findings. Measurement of feather samples after they have been clipped from the bird is obviously straigthforward, but this technique is not feasible for fleshy parts such as the comb which must be scored on live animals. The males were sometimes difficult to restrain under the scanner, and it was therefore impossible to safely measure iris colour, although iris colour was important in previous measures of male mating success (Zuk et al., 1990). Colours of combs and eyes may also change during handling, and if measurement time varies depending on how the animal is to restrain, repeatedly may suffer. The extent of this kind of limitation will depend on the species being measured. Another drawback to the use of spectroradiometry is the correspondence between reflectance scores and a human concept such as ‘showiness’ or ‘brightness’. As Endler (1990) discusses, it may be necessary to take into account the difference in colour between patches on the same individual, or the contrast between the animal and its background. In addition, the sensory abilities of the animal may not correspond to those of the spectroradiometer. Use of the variances or coefficients of variation for the spectroradiometry measurements is also recommended (Endler, 1990). For monochromatic species or for those which are not usually seen against a consistent background, even these suggestions may not provide a complete solution to the problem. Nevertheless,
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reflectance spectroradiometry offers the potential for less subjective colour measurement of animals, and as we have shown here, scores can be integrated with data on mating success to yield biologically interesting interpretations of the role of secondary sex characters in sexual selection. ACKNOWLEDGEMENTS
We are grateful to Cassandra Hayes for invaluable help in measuring birds, Paul Hamilton for preliminary work on use of the Li-Cor, John T. Rotenberry for statistical advice, and Torgeir Johnsen, Paul Hamilton and Mark Chappell for comments on the manuscript. Torgeir Johnsen, Troy MacLarty, Eric Focht, and Christopher Janus helped maintain the jungle fowl colony. This research is supported by National Science Foundation grants IBN-9 120902 and DEB-9257749 and Research Experience for Undergraduate supplements to MZ. REFERENCES
Burley N, Coopersmith CB. 1987. Bill color preferences of zebra finches. Ethology 76: 133-151. b d l e r JA. 1990. On the measurement and classification of colour in studies of animal colour patterns. Biological journal of the Linnean Society 41: 315-352. Hoglund J. 1989. Size and plumage dimorphism in lek-breeding birds: a comparative analysis. American Naturalist 134: 72-87. Houde AE. 1988. Genetic differentiation in female choice between two guppy populations. Animal Behauiour 36: 511-516. Hurvich LM. 1981. Color uision. Sunderland (Mass.): Sinauer Associates, Inc. Li-Cor. 1982. Radiation measurements and instrumentation. Publication No. 8208-LM. Lincoln, Nebraska. Munsell (Color Company). 1976. Munsell Book of Color, Glossy Finish Collection (2 volumes). Baltimore: Munsell/Macbeth/Kollmorgan Corp. Neitt J, Jacobs GH.1986. Polymorphism of the long-wavelength cone in normal human colour vision. Nature (London) 323: 623-625. SAS. 1985. S A S I S T A T Guide f o r personal compulers. Version 5 ed. SAS Institute, Cary, N.C. Zuk MyThornhill R, Ligon JD, Johnson K, Austad S, Ligon S, Thornhill N W , Costin C. 1990. The role of male ornaments and courtship behavior in female mate choice of red jungle fowl. The American Naturalist 136: 459-473.