Andre Hermansson

Degree project for Bachelor of Science in

Biology

Zoology 15 hec Spring 2013

Department of Biological and Environmental Sciences University of Gothenburg

Examiner: Johan Höjesjö

Department of Biological and Environmental Sciences

University of Gothenburg

Supervisor: Staffan Andersson

Department of Biological and Environmental Sciences

University of Gothenburg

Growth stress and costs of tail ornamentation in Buff-shouldered widowbird

(Euplectes psammocromius)

Sexual dimorphism and costs of tail

ornamentation in Buffshouldered widowbird

2

Abstract

Costs of male tail ornamentation were investigated in the little studied buff-

shouldered widowbird (Euplectes psammocromius), a species found only in the

grass covered highlands of SW Tanzania and the Nyika Plateau of NE Zambia

and N Malawi. Growth bars (indicating daily growth) and fault bars (indicating

growth stress) were counted in tail feathers collected from males in nuptial

plumage from two breeding seasons, in order to get a measure of feather growth

and fault rate, fault rate being a measure of stress. Growth rate and fault rate were

correlated to each other, tail length and a standardized measure of body condition.

Elongated tail feathers appear to be costly to produce, since a positive relationship

was found between tail length and fault rate. Furthermore, increased growth rate

seems to contribute even more to the cost of producing tail feathers than increased

tail length, particularly increased growth rate in the early phase of feather growth.

The fault bar score (a measure of the absolute amount of fault bars) was greater in

the late (last formed) half of the feather. Final tail length was weakly but

significantly positively related to body condition, suggesting that tail length may

serve as a male quality advertisement in the context of female mate choice.

Sammanfattning

Kostnaden av stjärtfjäderornament undersöktes hos den föga studerade buff-

shouldered widowbird (Euplectes psammocromius), en art som endast återfinns i

de gräsbeklädda höglandsområdena i SV Tanzania och Nyika Platån i NÖ Zambia

och N Malawi. Så kallade ’growth bars’ (som indikerar dygnstillväxt) och ’fault

bars’ (som indikerar tillväxtstress) räknades i stjärtfjädrar insamlade från hanar i

praktdräkt under två häckningssäsonger för att därigenom få ett mått på

tillväxthastighet och ’fault rate’, det senare som ett mått på stress. Fjädermåtten

korrelerades sinsemellan, samt med stjärtlängd och ett standardiserat

konditionsmått. Stjärtfjäderornamentet verkar vara kostsamt att producera då ett

positivt samband hittades mellan fjäderlängd och faultfrekvens. Vidare verkar

ökad tillväxthastighet bidra ännu mer till kostnaden för fjäderproduktionen än

ökad stjärtlängd, framförallt ökad tillväxthastighet tidigt i fjäderbildningen. ’Fault

bar score’ (mått på den absoluta mängden av ’fault bars’) var högre i den inre (sist

bildade) halvan av fjädern. Kondition var svagt men signifikant positivt korrelerat

med stjärtlängd vilket antyder att stjärtlängd kan fungera som en indikator av

hanlig kvalitet i samband med honligt partnerval.

3

Introduction

Study species

The widowbirds and bishops

together form the genus

Euplectes, a group of 17 small

seed-eating Afrotropical

weaverbirds (Staffan

Andersson 1994). The buff-

shouldered widowbird,

Euplectes psammocromius, is

a very little studied (Staffan

Andersson, personal

communication, Mars, 2013)

species of widowbird, that is

only found on the Nyika

Plateau of NE Zambia and N

Malawi and the grass covered

highlands of SW Tanzania,

northeast to Njombe and

Iringa (Fig. 3), where it’s

locally common (Fry 2004).

Like all widowbirds (Staffan Andersson 1994) it has a strongly

sexually dimorphic breeding plumage, breeding males having

black body plumage, black elongated tail feathers and bright

yellow buff shoulder patches, while non-breeding males and

females have a duller, brownish plumage (Fry 2004). (See

Figure 2 for an illustration of the different plumages).

Little is known about its’ breeding habits, but it probably is

polygynous and territorial, with breeding males displaying

their elongated (ca 30 cm) tails making them look like several

tails, in a slow display flight (Fry 2004).

All sexually selected characters are expected to continue

evolving until the mating advantages are balanced by an

opposing cost (Fisher 1930). Unfortunately, these balancing

costs and constraints have been much less studied than female

mate choice based on secondary sexual characteristics

(Andersson 1994). Knowledge of these costs is crucial in

understanding why, for instance, the tail feathers of male

widowbirds are not even longer than observed, given the

assumption that females prefer longer tails. Such a female bias

for longer tails has been found in several other widowbird

species; the long-tailed widowbird, E. progne (Andersson 1982), Jacksons widowbird, E. jacksoni

(Andersson 1992), red-collared widowbird, E. ardens (Sarah R. Pryke 2001) and red-shouldered

widowbird, E. axillaris (Sarah R. Pryke 2002).

Figure 2. Breeding male, non-breeding male

and female, E. psammocromius (Fry 2004)

Figure 1. The distribution of E. psammocromius (BirdLife 2013)

4

Study objectives

This study aims to discover if there are physiological costs of growing elongated tail feathers in breeding

(nuptial) males, and if the final tail length is dependent on male condition, which would suggest that it

could be a male quality advertisement in the context of female mate choice. My hypothesis is that there

likely are significant costs to growing long tail feathers and that it probably is condition dependent, as is

the case in the closely related species, Jackson’s widowbird, E. jacksoni (Andersson 1994). To test this,

various feather measurements on collected tail feathers were performed, and these measures where then

combined with several biometric (body part) measurements of the birds.

Methods

Sampling sites

Feather samples and biometrical data were collected during the course of two breeding seasons,

December-February 2010/2011 and December-February 2011/2012. The study area is located in the

highlands of south-western Tanzania; samples were taken from two study sites, Mtitu (08°12’S 35° 48’E)

and Mtanga (08°08’S 35°50’E). Both sites are located in the grass covered hills and valleys of Kilolo

district in the Iringa region.

Measurements

The birds were captured at territories

or roosting sites using mist nets or

bow nets and were subsequently

ringed with metal rings. The

biometrical measures used were;

tarsus length, tail length and body

mass. Tarsus length (between the

extreme bending points at toes and

heel) was measured with callipers to

the nearest 0.1 mm. Due to the tarsus

measurements in the 2009/2010 and

2010/2011 studies being made in a

different manner, the values obtained

were slightly shorter than in the

latest 2011/2012 study. Therefore, a

slight correction had to be made

when using the data to compensate

for this methodological difference

(see the ‘Statistics and methods of

data analysis’ part at the end of the Methods section). Tail length was measured to the nearest 0.15 cm

using a ruler, and the number of blood quills was counted. The birds' body mass was weighed to the

nearest 0.1 g, using a Pesola spring balance.

For the feather samples the R4 tail feather (retrix), i.e. the 4th from the middle feather, was selected

from each individual bird. Out of the collected tail feathers, the most intact and readily measurable were

selected for analysis; 62 from the latest 2011/2012 season and 25 from the 2010/2011 season. All

Figure 1. Iringa region, Tanzania (GoogleMapMaker 2013)

5

measured feathers were from males with nuptial plumage (black body feathering and elongated black

retrices) except for one eclipse (dull, sparrowy feathering similar to females) male. The attributes

measured in the feathers were; feather length, growth bars and fault bars. Growth bars are alternating light

and dark bands roughly perpendicular to the feather axis (rachis) that denote 24 h cycles, with one dark

band appearing during the day and one light band during the night (Grubb 1989), thus they can be used as

a measure of how long the feather has been growing. Fault bars are translucent bands roughly

perpendicular to the rachis caused by malformation of the barbules, due to malnutrition or other forms of

stress (Riddle 1908, James R. King 1984).

Both the growth bar and fault bar measurements began at a standardized distance (4 cm) from the base

of the feather since, the bars closest to the base were often very difficult to see (due to damaged barbs)

and the feather barbs only start at a certain distance up from the base. The feathers' whole length from tip

to base was measured using a tape measure and the whole length was subsequently divided into two

halves. Growth bars were counted on a light table, first for the whole feather, and then for the early half

of the feather, i.e. the half closest to the tip. Thereafter, the feather was divided into 8 equally long parts

(octiles), which were marked on the rachis. Fault bars were divided into three classes based on their

length (see Appendix 1 for precise definitions) and for each feather octile the number of fault bars of each

class was counted. Both a non-weighted score (i.e. simply the sum of the number of fault bars over all the

octiles) and a weighted score was calculated. The weighted score was calculated by multiplying the

number of fault bars of each class with a class specific weighted factor; 1 for class 1, 2 for class 2 and 3

for class 3, and then summing it all together. Fault bar scores were also calculated for each of the two

halves of the feather by summing the fault bar score of octiles 1-4 for the early half and octiles 5-7 for the

late half (octile 8 is excluded since the measurements started 4 cm from the base of the feather). An

average feather growth rate (mm/day), both for the whole feather and for the two halves separately, was

calculated by dividing the feather length by the number of growth bars (the whole feather length divided

by the total number of growth bars, and half the feather length divided by the number of growth bars of

each half, respectively). A body condition index was calculated as the standardized residuals from a linear

regression of ln(body mass) by 3 x ln(tarsus length)(Sarah R Pryke 2003).

Statistics and methods of data analysis

As previously stated the tarsus lengths differed slightly between the earlier season and the latest one, due

to methodological differences. To account for this, an average length was calculated for the earlier season

and another average for the latest season, subsequently the difference in average between the seasons was

added to all the tarsus lengths from the older season. This enabled data from the different seasons to be

pooled together and be treated as a single data set.

Two different ways of obtaining a standardized fault bar rate were used; one way was by dividing the

fault bar score by the feather length, the other by dividing the fault bar score by the number of growth

bars. This was done to get rid of the dependence of the fault bar score on feather length and feather

growth rate respectively (see Results for the correlations between feather length and fault bar score, and

feather growth rate and fault bar score). A standardized weighted fault bar score for the 1st and 7

th octiles

was obtained by dividing the weighted fault bar score of each octile by the average feather growth rate of

the early and late feather halves respectively. The 1st and 7th octiles were chosen because they are the

furthest apart, thus they should be representative of the early and late growth respectively. Growth rates

had to be used in this case instead of growth bar count, because the growth bars had not been counted for

each octile. This standardization was necessary when comparing the 1st and 7

th octiles (Fig. 9, Results),

because a significantly higher growth rate was found in the late feather half compared to the early (Fig. 8,

Results).

Parametric (Pearson’s r) and non-parametric (Spearman’s ρ, when data did not fulfil normality criteria)

correlation analysis were used to see if any relationships between the ptilometric data (feather

6

Figure 2. The realtionship between the weighted and non-weighted bar scores. Linear

regression: R2=0.92, n=85, p < 0.0001

measurements) and the biometrics could be found. To plot significant correlations, bivariate scatter plots

with linear regression lines were used. In the comparisons done between feather halves and between

octiles, Wilcoxon signed-rank test was used.

Results Notes on the selection of data

Because most of the trends using only the data from the 25 individuals from the earlier season are non-

significant when tested, and the trends are virtually the same but significant when using the data from the

62 individuals from the latest season, the decision was made to pool the data from the two seasons and do

the analysis on the combined data set. Feathers with blood quills are excluded because they were still

growing (Andersson 1994), hence their final length would be impossible to know. Two outliers with

extremely short tails, one of them being the eclipse male mentioned before, are excluded from the

analysis, because they were not deemed representative of the nuptial male population of interest to this

study and will only obscure the relationships of interest if included. For the fault bars, only the weighted

values are used in the analysis. This is because the weighted values do not only show a count of fault

bars; they actually say something about the relative size of the different fault bar types. Furthermore,

when the resulting trends using the weighted values were compared to the ones using the non-weighted,

they were always in the same direction but somewhat stronger. This is to be expected if the weighted and

non-weighted scores are tightly correlated which they are (Fig. 4). The two different standardized fault

bar rates yielded very similar trends when used; therefore, only one of them, the one obtained by dividing

the fault bar count by the number of growth bars, is used in the statistical analysis.

7

Variation in and distribution of data

Before showing the main results it would be useful to consider the variation in and distribution of some

of the measures most important to this study. The variation among males in tail length, average feather

growth rate and weighted fault bar rate is quite large as is shown in Figure 5. For more detailed numbers

(mean, SD, SE, n) of the aforementioned and other measures see Table 1. Both tail length and average

feather growth rate were normally distributed (Shapiro-Wilk test, n=75, p=0.42, and n=85, p=0.56

respectively), the weighted fault bar rate however was not (Shapiro-Wilk test, n=85, p < 0.001).

Table 1. Variation in some of the ptilometric and biomtetric measures used.

Trait Measure or unit Mean SD SE n

Ptilometrics:

Feather length mm 263 28 3 87

Total number of growth bars Growth bar count for whole

feather

69 9 1 87

Average feather growth rate

(whole feather)

mm/day 3.85 0.33 0.04 87

Average fault bar rate

(weighted)

Fault bar weighted score/total

number of growth bars

0.5 0.3 0.0 87

Biometrics:

Tail length mm 276 29 3 78

Tarsus length (corrected for

method difference)

mm 31.9 1.6 0.2 81

Body mass g 39.9 3.6 0.4 79

Body condition Residual mass index -0.0023 0.0469 0.0056 69

Figure 3. Histograms with error bars and accompanying boxplots with outliers shown as dots, showing from left to right;

the distribution of tail length (mm), average feather growth rate (mm/day) and weighted fault bar rate (fault bar weighted

score/total number of growth bars).

8

Correlations with fault bar scores There is a positive relationship between feather length and fault bar score (absolute amount of fault bars),

and feather growth rate and fault bar score (Fig. 6 and 7).

Comparison of growth rate between the two feather halves

There is a significant difference between the two halves (Fig. 8); the late half having a significantly

higher growth rate.

Figure 6. The relationship between weighted fault bar score

(fault bar count multiplied with weight factors) and feather

length (mm). Linear regression: R2=0.16, n=85, p=0.0002

Figure 7. Weighted fault bar score (fault bar count multiplied

with weight factors) plotted against average growth rate

(mm/day). Linear regression: R2=0.15, n=85, p=0.0003

Figure 8. Boxplots comparing the average feather growth rate (mm/day) of the

two feather halves. Wilcoxon signed-rank test, n=85, p < 0.0001

9

Comparison of standardized fault bar score between the 1st and 7th octiles

The standardized (see Methods) weighted fault bar score is significantly higher in the 7th than in the 1st

octile (Fig. 9).

Relationships among ptilometrics, and between ptilometrics and biometrics

A significant, though weak, positive

correlation between male tail length

and body condition was found (Fig.

10). No significant correlation can be

found between body condition and

weighted fault bar rate (Spearman's

ρ=-0.0775, n=72, p=0.52). However, a

significant positive correlation exists

between the average feather growth

rate of the whole feather and weighted

fault bar rate of the whole feather (Fig.

11). When the average feather growth

rate of the early half is used,

significant positive correlations

emerge for the following; average

feather growth rate of the early half

against the weighted fault bar rate of

the whole feather (Spearman's ρ=0.41,

n=85, p < 0.0001), average feather

growth rate of the early half against

the weighted fault bar rate of the early

Figure 9. Boxplots comparing the standardized weighted fault bar scores

of the 1st and 7

th octiles. Wilcoxon signed-rank test, n=85, p < 0.0001

Figure 10. The relationship between body condition (residual mass index,

see Methods) and tail length (mm). Linear regression: R2=0.09, n=68,

p=0.0108

10

Figure 11. Weighted fault bar rate of the whole feather plotted against average

feather growth rate (mm/day) of the whole feather. Linear regression: R2=0.23,

n=85, p < 0.0001

half (Spearman's ρ=0.28, n=85,

p=0.0102), and the average

feather growth rate of the early

half against the weighted fault

bar rate of the late half

(Spearman's ρ=0.34, n=85,

p=0.0016).

When the average feather

growth rate of the late half is

correlated against the same

measures (i.e. weighted fault bar

rate of the whole feather,

weighted fault bar rate of the

early half, weighted fault bar rate

of the late half); there is a

significant positive result for the

correlations with the fault bar

rate of the whole feather

(Spearman's ρ=0.32, n=85,

p=0.0026) and the fault bar rate

of the late half (Spearman's ρ=0.40, n=85, p=0.0001), and a non-significant positive correlation with the

fault bar rate of the early half (Spearman's ρ=0.19, n=85, p=0.0875). In addition to growth rate, tail length

also positively correlates with fault bar rate (Fig. 12).

Figure 12. The weighted fault bar rate (weighted fault bar score/number of growth bars)

plotted against tail length (mm). Linear regression: R2=0.10, n=75, p=0.0054

11

Discussion Is tail ornamentation stressful to produce?

Since there is a positive relationship between feather growth rate and fault bar rate (Fig. 11, Fig. 12), it

appears to be stressful to grow feathers more quickly. Furthermore, the growth rate in the early phase of

feather growth appears to influence the fault bar rate the more, since the correlation coefficient is stronger

for the correlation of the fault bar rate (of the whole feather) with the early half than with the late half

(Spearman's ρ=0.41 and Spearman's ρ=0.32 respectively). In addition, the growth rate of the early half is

also positively correlated with the fault bar rate of the late half, indicating that the growth rate of the early

half positively influences the fault bar rate of the late half. This supports the view that the early growth is

most important in determining the overall fault rate.

The average growth rate of the octiles was substantially higher in the 7th

octile (Fig. 8). This higher

growth rate in the late growth phase could perhaps be explained by the fact that the tail feather used, the

R4 feather, is one of the longest tail feathers. These longer tail feathers keep growing when the shorter

ones have stopped, meaning that more resources are liberated to invest in the late part of their growth

since they are not competing for resources with the shorter feathers (Staffan Andersson, personal

communication, May 28, 2013).

In addition to average growth rate, increased tail length seems to add additional stress since the tail

length is positively correlated with fault bar rate. But, although the regression line was significant, it only

explained 10 % (Fig. 13) of the observed variance, less than half than what is explained by the regression

using average growth rate (Fig. 12). It seems therefore, that average growth rate is the more important

factor in determining the fault bar rate, i.e. increasing the feather growth rate is proportionally more

stressful than increasing the feather length by the same proportion.

It is also interesting to note that the fault bar score (i.e. absolute amount of faults) was significantly

higher in the 7th

than in the 1st octile, even when standardized for the higher growth rate in the 7

th (Fig. 9).

That the fault bar score is substantially greater in the late half of the feather could be due to a decline in

body condition towards the end of tail growth caused by the physiological costs of tail growth, as was

found to be the case in the Jackson’s widowbird (Andersson 1994).

Is male tail length an indicator of body condition?

Figure 10 shows a positive correlation between body condition and final tail length, as was found in a

study of the closely related species Jackson’s widowbird, E. jacksoni (Andersson 1994). This might

indicate that in order for males to grow a long tail they need to be in good condition. However, the low

(0.09) R2 indicates that this relationship may not be that reliable, i.e. some males with low body condition

values still manage to grow long tails and some males with high body condition values only manage to

grow short tails. Because the body condition values are dependent on mass measurements taken at only

one point in time, maybe the males who had low body condition and long tails at the time of

measurement, had low body condition precisely because they had invested a large portion of their prior

condition into growing large tails. This seems unlikely though, since body condition does not seem to

correlate with the fault bar rate (i.e. stress), which should be the case if the long tailed males had invested

a large portion of their prior condition on growing long tails (i.e. they should show signs of stress at the

time of measurement due to having lost so much of their prior condition). Thus, it seems likely that,

although the relationship is far from perfect, tail length is at least to some extent representative of male

body condition. If this is true, then this suggests that tail length may serve as a male quality advertisement

in female mate choice.

12

Future prospects

Regarding the fault bar measurements, it would be recommended for future studies using fault bars as an

indicator of physiological stress to use a classification of fault bars that not only takes fault bar length (as

this study does) but also fault bar intensity or width, into account, and see whether this affects the

resulting correlations and comparisons. Furthermore, it would be interesting to see more studies on the

effect of growth rate on the physiological costs of feather growth. This has been done for at least one

other widowbird species, namely the Jackson’s widowbird, E. jacksoni (Andersson 1994), with the same

result as in this study; i.e. fault rate increased with growth rate.

To be able to tell if male tail length really functions as a male quality advertisement in female choice in

the Buff-shouldered widowbird, further studies are required. For example the tail feather length could be

experimentally manipulated to see whether longer or shorter tail length affects female mate choice, as has

been done for the Long-tailed widowbird, E. progne (Andersson 1982) and Jackson’s widowbird

(Andersson 1992).

Because the body condition measure used in this study is, as previously stated, dependent on mass

measurements taken at only one point in time they might not be very representative of the males’ real

body condition. Thus, it would be desirable to see future studies that use a body condition measure that is

based on measurements taken at several points in time, and see if they get similar results.

Conclusions

Tail ornamentation seems to be costly to produce, since a positive relationship was found between tail

length and fault rate. Furthermore, increased growth rate seems to contribute even more to the cost of

producing tail feathers than increased tail length, particularly increased growth rate in the early phase of

feather formation. The fault bar score (a measure of the absolute amount of fault bars) was greater in the

late (last formed) half of the feather than in the early. Final tail length was weakly but significantly

positively related to body condition, suggesting that tail length may serve as a male quality advertisement

in the context of female mate choice.

Acknowledgements I want to thank my supervisor at the University of Gothenburg, Professor Staffan Andersson, who

introduced me to this study species and has helped me throughout the entire project with everything from

statistics and interpreting the results to critical review of the report. I would also like to thank Calum

Ninnes, one of Staffan’s PhD students at the University of Gothenburg, for supplying me with the feather

samples and helping me out with the measurements.

13

References Articles and literature Andersson, M. (1982). "Female choice selects for extreme tail length in a widowbird." Nature

299(5886): 818-820.

Andersson, S. (1992). "Female preference for long tails in lekking Jackson's widowbirds:

experimental evidence." Animal Behaviour 43(3): 379-388.

Andersson, S. (1994). "Costs of Sexual Advertising in the Lekking Jackson's Widowbird." The

Condor 96(1): 1-10.

Fisher, R. A. (1930). The Genetical Theory of Natural Selection. Clarendon Press, Oxford.

Fry, C. H., Keith, S (2004). The Birds of Africa Vol. VII., Christopher Helm, London.

Grubb, T. C. (1989). "Ptilochronology: Feather Growth Bars As Indicators of Nutritional Status."

Auk 106(2): 314-320.

James R. King, M. E. M. (1984). "Fault Bars in the Feathers of White-Crowned Sparrows: Dietary

Deficiency or Stress of Captivity and Handling?" Auk 101(1): 168-169.

Riddle, O. (1908). "The Genesis of Fault-Bars in Feathers and the Cause of Alternation of Light

and Dark Fundamental Bars." Biological Bulletin 14(6): 328-370.

Sarah R Pryke, S. A. (2003). "Carotenoid-based epaulettes reveal male competitive ability:

experiments with resident and floater red-shouldered widowbirds." Animal Behaviour 66(2): 217-

224.

Sarah R. Pryke, S. A. (2001). "SEXUAL SELECTION OF MULTIPLE HANDICAPS IN THE

RED-COLLARED WIDOWBIRD: FEMALE CHOICE OF TAIL LENGTH BUT NOT

CAROTENOID DISPLAY." Evolution 55(7): 1452-1463.

Sarah R. Pryke, S. A. (2002). "A generalized female bias for long tails in a short–tailed

widowbird." Philosophical Transactions of the Royal Society B: Biological Sciences 269(1505 ):

2141-2146.

Staffan Andersson, M. A. (1994). "Tail Ornamentation, Size Dimorphism and Wing Length in the

Genus Euplectes (Ploceinae)." Auk 111(1): 80-86.

Web sites

BirdLife (2013). "BirdLife Intenational." Retrieved 24/5, 2013, from http://www.birdlife.org

GoogleMapMaker (2013). "Iringa region, Tanzania." Retrieved 24/5, 2013, from http://goo.gl/Sq7dj

14

Appendix 1. Fault bar definitions:

Class 1: If the fault bar was found on only one side of the rachis and it went through less than half the

way across the barbs of one side of the rachis, or if found on both sides of the rachis and the sum of the

length of the fault bar fragments on both sides was less than half the way across the barbs of one side of

the rachis, then it fell into this class.

Class 2: If the fault bar was found on only one side of the rachis and it went through at least half the way

across the barbs of one side of the rachis or if found on both sides of the rachis and the sum of the length

of the fault bar fragments on both sides was equal to or greater than half way across the barbs of one side

of the rachis, but less than half way across on both sides (i.e. less than 1 1/2 way across the whole feather

width), then it fell into this class.

Class 3: If the fault bar went all the way across the whole feather width or if the sum of the fault bar

fragments on both sides was greater than half way across on both sides (i.e. more than 1 1/2 way across

the whole feather width), then it fell into this class.