doi: 10.1111/j.1420-9101.2003.00680.x
Adaptive allocation of stress-induced deformities on bird feathers
R. JO VANI * & J. B LA S *
*Department of Applied Biology, Estacio´n Biolo´gica de Doñana, Consejo Superior de Investigaciones Cientı´ficas, Sevilla, Spain
Department of Biology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Keywords:
Abstract
birds;
Ciconia ciconia;
fault bar allocation hypothesis;
feathers;
flight;
stress.
Physiological stress during ontogeny is known to cause abnormalities in
keratin structures of vertebrates, but little is known about if and how
organisms have evolved mechanisms to reduce the negative effects of these
abnormalities. Stress experienced during avian feather growth is known to
lead to the formation of fault bars, and thereby to the weakening of feathers
because of shortage and slimming of barbules. Here we propose and test a new
hypothesis (the ‘fault bar allocation hypothesis’) according to which birds
should have evolved adaptive strategies to counteract this evolutionary
pressure. In particular, we predicted and tested the idea that in flying birds,
natural selection should have selected for mechanisms to reduce fault bar load
on feathers with high strength requirements during flight. Data on the growth
of feathers of nestling white storks (Ciconia ciconia) revealed a consistent
allocation of more, and more intense, fault bars in innermost than in
outermost wing feathers as predicted by our hypothesis. Moreover, the same
pattern emerged from feathers of adult storks. We discuss the generality of our
results, and suggest avenues for further investigations in this area.
Introduction
Physiological stress caused by many unpredictable phenomena such as storms, droughts, famine or predation
episodes can lower the fitness of organisms. Not surprisingly, coping with stressors has been a constant driving
force of evolution (Futuyma, 1998; Buchanan, 2000;
Grishkan et al., 2003). In vertebrates, different stressors
are mirrored on growth abnormalities in keratin structures such as beaks, claws, feathers, hairs, hoofs, horns or
nails. This has been known in medicine for a long time in
structures such as nails, where these growth abnormalities have been traditionally associated with episodes of
recent stress produced by disease (Han et al., 2000;
Ciastko, 2002), or intrusive medical treatments (Deliliers
& Monni, 2001; Vassallo et al., 2001). However, although
being the symptoms of some kind of stress, they probably
have a low, if any, effect per se on the fitness of
individuals.
Correspondence: Roger Jovani, Department of Applied Biology, Estació n
Bioló gica de Doñ ana, Consejo Superior de Investigaciones Cientı́ficas,
Avda. Ma Luisa s/n, E-41013 Sevilla, Spain.
Tel.: 34 954 232340; fax: 34 954 621125;
e-mail: jovani@ebd.csic.es
294
Fault bars in birds are common and long known
feather growth abnormalities (Riddle, 1908). Feathers
grow from the follicle collar by the accumulation of
keratin produced internally by keratinocytes prior to
cell death. Fault bars are the result of a variable time
lag on the deposition of keratin (Murphy et al., 1989;
Prum & Williamson, 2001), producing absence and
slimming of barbules, and hence, appearing as narrow
(<2 mm) translucent bands across the feather vane
almost perpendicular to the feather axis. Consequently,
fault bars weaken the feather, increasing the probability of partial or even complete feather breakage along
the fault bar line (Slagsvold, 1982; Newton, 1986;
Machmer et al., 1992). Like the nails of humans, fault
bars have been related to an array of stressors such as
malnutrition (Slagsvold, 1982; Newton, 1986), handling
(King & Murphy, 1984; Murphy et al., 1988), or mechanical stress experienced during feather formation (Murphy
et al., 1989; Negro et al., 1994), leading veterinaries to use
fault bars as a symptom of stress and disease suffered
by captive and wild birds (Ritchie et al., 1994).
However, proximal mechanisms and stressors that
produce fault bars are far from being completely resolved,
and need of further study.
J. EV OL. BIOL. 17 (2004) 294–301 ª 2004 BLACKWELL PUBLISHING LTD
Fault bar allocation in birds
Contrary to other kind of abnormalities in keratin
structures, fault bars could seriously reduce individual
birds’ fitness because of their association with flight
requirements of birds. Once feathers reach their final
length (a matter of weeks or months) they will remain
attached to the body of the bird until the next moult
(a matter of months or years). Although lost feathers are
immediately replaced, broken feathers will be replaced
only in the next moult. Thus, feather damage resulting
from fault bars may seriously reduce wing surface area
for long periods of time. All of this is relevant for bird
fitness because wing load (wing area/body weight) is
crucial for bird flight performance (Pennycuick, 1989),
birds being forced to reduce their weight during natural,
i.e. moult, or experimental reductions of wing area
(Swaddle & Witter, 1997; Lind & Jakobson, 2001; Senar
et al., 2002). Moreover, experimental reduction of wing
area is known to increase energetic demands resulting in
direct fitness costs as reflected in lowered reproductive
success (Mauck & Grubb, 1995; Velando, 2002). Furthermore, fault bars are taxonomically ubiquitous among
wing and body feathers (Duerden, 1909; Murphy et al.,
1988; Machmer et al., 1992; Negro et al., 1994), suggesting a role for fault bars as an important handicap through
the evolutionary history of birds. However, it is surprising that the evolution of mechanisms directed to
counteract the negative effects of fault bars in birds
remains unclear.
Here, we propose and test the hypothesis (‘fault bar
allocation hypothesis’) that birds should have evolved
adaptive strategies for reducing the costs of fault bars.
There is previous evidence for fault bars being more
frequent on tail and body feathers than on flight wing
feathers of birds (e.g. Slagsvold, 1982; Machmer et al.,
1992; Bortolotti et al., 2002), suggesting a differential
allocation of fault bars in feathers depending on their
importance for flying. However, most of the evidence is
circumstantial (e.g. Murphy et al., 1988), and all of the
studies up to date have been carried out at the population
level rather than at the individual level, and often from
feathers grown during different years, being therefore
unsuitable for a test of the ‘fault bar allocation hypothesis’. Hence, using individual data on white storks (Ciconia
ciconia), we tested the prediction that individuals of flying
species should allocate fault bars according to feather
strength requirements during flight. As feather requirements are higher for outermost wing feathers (Corning &
Biewener, 1998) we predicted that these feathers would
have less, and slighter fault bars than the innermost wing
feathers.
sized (c. 3500 g), long-distance migratory bird (Cramp &
Simmons, 1977), and is an appropriate model for this
study because fault bars are easily measured even in the
smallest wing feathers, and because their occurrence
could be potentially shaped by natural selection given the
imminence of long-distance migration shortly after
feather formation. Feathers from nestling and adult
white storks were studied during the breeding season of
2003 at the ‘Dehesa de Abajo’ site (Puebla del Rı́o,
Sevilla, SW Spain; 37°13¢N 6°09¢W), where c. 250 pairs of
the species nest colonially on wild olive trees.
Analyses of nestlings
Fifty nestlings aged between 14 and 57 days were
included in the analyses. From each nestling, we measured the vane portion emerging from the feather sheath
(i.e. where fault bars can be detected) of three feathers
from each one of the main flight feather groups of the left
wing: primaries (hereafter P), primary coverts (PC),
secondaries (S), secondary coverts (SC), scapulars (Sc)
and scapular coverts (ScC, Fig. 1). In this way, we
examined a representative sample of each group of
feathers while minimizing disturbance to the nestlings
and the rest of the colony. Even so, we were forced to
skip recording fault bar occurrence on the last group of
feathers (ScC) in 17 occasions because of time constraints.
Each feather was carefully checked for the presence of
fault bars, categorizing them as light (absence of some
barbules producing a visible discontinuity on the structure of the feather), medium (a narrow, i.e. <1 mm,
translucent line across the feather), or strong (‡1 mm
translucent line across the feather, many times causing
breakage of edge barbs of the feather). The distance (to
the nearest mm) from each fault bar to the tip of the
feather was also recorded.
Primaries
Methods
The study species and population
This study was performed on feathers from both nestling
and adult white storks (C. ciconia). This species is a large
295
Secondaries
Scapulars
Fig. 1 Location of the studied feathers within the left wing of a
nestling white stork. Feathers inspected in nestlings are indicated in
dark grey. Feathers studied in adults are shown in dark and light
grey. Nonstudied feathers are indicated in white.
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R. J O VA N I AND J . B L A S
200
Feather type
PC5
S10
SC10
Sc3
ScC3
175
Feather length (mm)
150
125
100
75
50
25
0
0
25
50
75
100
125
150
175
200
P5 length (mm)
Fig. 2 Length of the exposed portion of growing feathers from
50 nestlings relative to the length of exposed fifth primary feather.
Only the central feather of each type is plotted for clarity. Lines
represent best fitting equations. See text for further details.
proportion of fault bars in feathers was analysed with a
binomial distribution of errors and a logit link function,
and the number of fault bars per feather with a Poisson
distribution of errors and a log link function. Feather
identity (e.g. third primary, second scapular) was fitted
into the model as a factor. Moreover, we used Binomial
tests and Wilcoxon matched-pairs signed-rank tests for
analysing how consistent those general (i.e. population
level) results found in GLMM analyses were at the
individual level. These analyses were conservative since
we also included the 17 nestlings for which we did not
check fault bars on the ScC (the exclusion of these
nestlings from the analyses did not change any of the
results). For clarity, we have analysed the occurrence of
all fault bars together (light, medium and strong), and
strong fault bars separately because of their potential
difference in functional importance. However, light and
medium fault bars separately showed very similar
patterns.
Comparison between adults and nestlings
To properly assess whether individuals differentially
allocate fault bars among feather types, one must
compare portions of feathers that have grown at the
same time at different parts of the given bird. Thus, we
first studied the growth of each feather relative to the
others on the 50 nestlings (Fig. 2). Secondaries were the
latest feathers to be grown whereas PC and SC were
the first to reach their final length (Fig. 2). In this way,
the five youngest nestlings on which the vane of S had
not started to emerge from the sheaths were excluded
from the analysis. Moreover, we selected the first, second
or third order equation best fitting to the data of the
relationship between P5 (i.e. the longest P) and each of
the other 17 feather types (examples in Fig. 2). With
these 17 equations we calculated the length of each
feather when S start growing (left arrow in Fig. 2), and
when PC and SC achieve their final length (right arrow
in Fig. 2). We did it in a conservative way, assuming that
some PC-SC could achieve their final length when P5 is
132 mm long. Thus, from the remaining 45 nestlings, we
discarded those feather portions that were growing at
times when other feathers either had not initiated or had
already finished their growth (i.e. proximal feather parts
that were still growing when PC and SC had stopped
growing; and tip zones of those feathers that were
growing before the vanes of S started to emerge from
their sheaths).
As the occurrence of fault bars in a particular feather is
potentially related to the occurrence of fault bars in the
other feathers of an individual nestling, we considered
feathers as nonindependent units in the analyses. Therefore, nestling identity was used as a random factor in
generalized linear mixed models (GLMMs), using GLIMMIX macro of SAS to control for the different occurrence
of fault bars among nestlings (Littell et al., 1996). The
The study of fault bar allocation in adults involves
technical and ethical considerations because storks moult
during the breeding season (Hall et al., 1987), and the
asynchronous growth of adult feathers (Hall et al., 1987)
precludes any study of such detail as that conducted in
nestlings. Fortunately, freshly moulted adult feathers
accumulate on the ground, and we seized this opportunity by collecting more than 900 adult feathers during
our incursions into the colony in June 2003. Feathers
were later classified in the laboratory according to a
reference feather collection, and feathers that were
clearly different from those studied in nestlings were
excluded, that is, the innermost P (shorter, and less
emarginated, and thus with a probable different flight
function), the innermost S (weaker than the rest of S),
and the first Sc (noticeably smaller than the rest of Sc; see
Fig. 1). Hence, 753 adult feathers were available for the
study of the number and intensity of fault bars (see Fig. 5
for sample sizes of different feather types).
White stork nestlings have been banded with plastic
rings at the study site and many other localities in Spain
(c. 19 000 nestlings) from 1986 onwards. In particular,
during the breeding season that preceded this study, we
ringed 217 nestlings at the study colony (c. 95% of the
fledged storks), and c. 400 nestlings were banded in
nearby stork nests. In this way, based on our periodic
surveys of the study site searching for banded storks from
1 month before we started to collect the adult feathers,
we were able to gather strong evidence supporting that
the collected feathers were from adult storks, as not a
single first year stork was found in the colony from a total
of 53 storks that we read the plastic bands of.
As we sampled nestlings at different growing stages,
many had small feathers, precluding a reliable comparison with fully grown feathers of adults. Thus, we
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Fault bar allocation in birds
10
20
9
8
SC-Sc-ScC
6
5
4
3
2
1
ScC3
ScC4
ScC3
ScC4
Sc3
Sc3
Sc4
Sc2
Sc2
ScC2
SC12
SC12
ScC2
SC10
SC10
Sc4
S12
SC8
S12
SC8
S8
S10
14
PC7
Strong
PC5
P7
5
P5
0
4
All fault bars
7
3
2
0
P-PC-S
1
SC-Sc-ScC
S10
S8
PC7
PC5
PC3
P7
P5
0
P3
Innermost wing feathers were more prone to have at
least one fault bar than outermost wing feathers (GLMM,
F17,697 ¼ 15.56, P < 0.0001; Fig. 3). The proportion of
feathers with fault bars was between 4.4 and 22.2% on
P-PC-S, but it was much higher in SC (between 53.3 and
62.2%) and especially on Sc-ScC (57.8–92.9%; Fig. 3).
Two nestlings had no fault bars along the wing, and
26 had fault bars both on P-PC-S, and on SC-Sc-ScC. All
17 nestlings having only fault bars on one of these
two groups of feathers had fault bars on inner, instead
of outer wing feathers (Binomial test P < 0.0001; Fig. 4
insert).
The number of fault bars also increased towards inner
wing feathers (GLMM, F17,697 ¼ 32.48, P < 0.0001;
Fig. 4). P-PC-S that had fault bars normally had a single
one and never more than three fault bars. However, two
fault bars were common for SC and up to four or five
fault bars were common for Sc and ScC, respectively.
Feather type
Fig. 4 Number of fault bars of any kind (upper box), and only strong
fault bars (lower box) in nestlings. Lines represent fault bars along
the wing of individual nestlings. Median (quartiles) are indicated by
circles. Inserts resume major graphs by showing the number of fault
bars within nestlings on feather types primaries-primary covertssecondaries vs. secondary coverts-scapulars-scapular coverts (ScC).
Broken lines represent those nestlings on which we did not recorded
the occurrence of fault bars on the ScC.
Moreover, almost all nestlings had more fault bars on
inner than on outer wing feathers (Fig. 4; Table 1).
Strong fault bars
100
Percentage feathers with fault bars
0
P-PC-S
7
PC3
Fault bar distribution on nestling wings
40
All
11
P3
Results
12
Number of fault bars
selected those 20 oldest nestlings from the original data
set, which had at least 100 mm of exposed P5. This
ensures that most fault bars occurring on nestling
feathers were recorded, as fault bars typically accumulate
at the tip of the feathers (R. Jovani & J. Blas, unpublished
data).
For statistical analyses we used generalized lineal
models (GLM) with the same distributions of errors and
link functions as described above. In this case, we used
the feather group (e.g. primaries, secondaries), the age
(nestling or adult), and their interaction as the independent variables.
297
90
All
Strong
80
70
60
50
40
30
20
10
ScC4
ScC3
Sc4
ScC2
Sc3
Sc2
SC12
SC10
S12
SC8
S8
S10
PC7
PC5
P7
45 45 45 45 45 28 28 28
PC3
45 45 45 45 45 45 45 45 45 45
P5
P3
0
Feather type
Fig. 3 Proportion of nestling feathers with fault bars. The number of
each type of feather analysed is indicated.
P-PC-S were almost free from strong fault bars (Fig. 3).
However, the proportion of feathers with some strong
fault bar increased from SC to ScC (GLMM,
F17,697 ¼ 9.97, P < 0.0001; Fig. 3). Seventeen nestlings
lacked strong fault bars in any feather, and two had fault
bars both on P-PC-S, and SC-Sc-ScC. Twenty-five of
those 26 nestlings having fault bars only on P-PC-S, or
only on SC-Sc-ScC, had fault bars on inner but not on
outer wing feathers (Binomial test, P < 0.0001; Fig. 4
insert).
Similarly, the number of strong fault bars was
unequally distributed among the wing feathers of nestlings (GLMM, F17,697 ¼ 25.99, P < 0.0001), being higher
in inner wing feathers (Fig. 4). P-PC-S had as much as
one single strong fault bar, SC two, Sc three, and ScC
reached a maximum of five fault bars and median values
up to one strong fault bar. Moreover, almost all nestlings
had equal or higher numbers of strong fault bars on inner
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R. J O VA N I AND J . B L A S
Table 1. Wilcoxon matched-pairs signed-rank tests for examining
the difference on the number of fault bars occurring on feather
types P-PC-S vs. SC-Sc-ScC (see Fig. 1 for the position of the feathers
on the wing) on the 45 nestlings studied. Data refer to the number of
nestlings in each class.
100
90
Chicks
All
Strong
80
70
60
Type of fault bars
P, PC, S < SC, Sc, ScC
P, PC, S ¼ SC, Sc, ScC
P, PC, S > SC, Sc, ScC
Wilcoxon test
Strong
42
3
0
Z ¼ )5.647,
P < 0.0001
27
17
1
Z ¼ )4.530,
P < 0.0001
P, primaries; PC, primary coverts; S, secondaries; SC, secondary
coverts; Sc, scapulars; ScC, scapular coverts.
vs. outer feathers, with only one nestling showing the
opposite pattern (Table 1; Fig. 4 insert).
Percentage feathers with fault bars
50
All
40
30
20
10
0
60
60
60
60
60
24
P
PC
S
SC
Sc
ScC
100
90
Adults
All
Strong
80
70
60
Comparison between adults and nestlings
50
All fault bars
40
As a whole, the proportion of feathers with fault bars was
three times higher in nestlings (43.2%, n ¼ 324) than in
adults (12.9%, n ¼ 753; v32 ¼ 754.76, P < 0.0001), and
this pattern holds true even when controlling for feather
type (GLM, feather type v25 ¼ 277.72, P < 0.0001; age
v21 ¼ 99.27, P < 0.0001).
Although fault bars predominated on inner wing
feathers in both nestlings and adults, a clear age-related
difference occurred; whereas in the nestlings almost all
the feathers with fault bars were SC-Sc-ScC, in the adults
fault bars mainly occurred on Sc-ScC, but not in SC
(GLM, feather type v25 ¼ 277.72, P < 0.0001; age
v21 ¼ 99.27, P < 0.0001; interaction feather type · age:
v25 ¼ 41.07, P < 0.0001; Fig. 5).
As a whole, nestlings showed a higher number of fault
bars (mean ¼ 2.80) than adults (mean ¼ 2.44; Mann–
Whitney U324,753 ¼ 86599.50, P < 0.0001), and this hold
when statistically controlling for feather type (GLM,
feather type v25 ¼ 1054.43, P < 0.0001; age v12 ¼ 117.04,
P < 0.0001).
Inner wing feathers harboured more fault bars than
outer wing feathers both in nestlings and adults (Fig. 5).
However, this increase started on SC in nestlings and in
Sc in adults (GLM, feather type v25 ¼ 1054.43,
P < 0.0001; age: v21 ¼ 117.04, P < 0.0001; age · feather
type v25 ¼ 151.77, P < 0.0001). Moreover, the maximum
numbers of fault bars also increased towards inner wing
feathers in the nestlings (Spearman correlation with the
two maximum values of each feather type rs ¼ 0.812,
n ¼ 12, P < 0.01), but not in the adults (rs ¼ 0.429,
n ¼ 12, n.s.; Fig. 6).
Strong fault bars
The proportion of feathers with strong fault bars was six
times higher in nestlings (9.7%, n ¼ 324) than in adults
30
20
10
0
124
68
256
205
61
39
P
PC
S
SC
Sc
ScC
Feather type
Fig. 5 Proportion of nestling and adult feathers with at least one
fault bar. The number of analysed feathers of each type is indicated.
(1.6%, n ¼ 753; v32 ¼ 1279.48, P < 0.0001), and the
same was found when controlling for feather type in a
GLM analysis (feather type v52 ¼ 134.79, P < 0.0001; age
v21 ¼ 28.32, P < 0.0001). As for the total proportion of
fault bars, the interaction between age and feather type
was also significant in the multivariable analysis (GLM,
feather type v25 ¼ 134.79, P < 0.0001; age v12 ¼ 28.32,
P < 0.0001; feather type · age v52 ¼ 21.63, P < 0.01),
indicating that while in nestlings the proportion of strong
fault bars gradually increased from S up to ScC, this was
displaced one position towards inner wing feathers in
adults, only increasing from SC to Sc, but not from S to
SC (Fig. 5).
Nestlings showed a higher number of strong fault
bars (mean ¼ 0.188) than adults (mean 0.021, Mann–
Whitney U324,753 ¼ 112052.00, P < 0.0001), and this
hold when statistically controlling for feather type
(GLM, feather type v25 ¼ 256.23, P < 0.0001; age
v21 ¼ 46.10, P < 0.0001).
Inner wing feathers had more numerous strong fault
bars both in nestlings and adults (Fig. 6). In nestlings,
strong fault bars showed a clear increase towards ScC, but
in adults Sc was the feather type with more strong fault
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Number of fault bars
Fault bar allocation in birds
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
Chicks
50
59
P
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
All
Strong
54
60
PC
Adults
117 124
P
52
60
S
21
57
7
SC
50
Sc
0
4
ScC
All
Strong
61 69
PC
239
S
256 192 202
SC
32
53
Sc
15 38
ScC
Feather type
Fig. 6 Number of fault bars in nestling and adult feathers. Circle size
represents the number of feathers from one to 16. The number of
feathers with zero fault bars is also indicated.
bars (GLM, feather type v25 ¼ 256.23, P < 0.0001; age
v21 ¼ 46.10, P < 0.0001; age · feather type v25 ¼ 28.45,
P < 0.0001).
Discussion
Our results demonstrate that white stork nestlings
confronted with natural stressors consistently allocated
fault bars on the different wing feathers in a nonrandom
manner. This gives support to our hypothesis of adaptive
allocation of fault bars, because feathers with important
flight function were those showing a lower proportion
and number of both total and strong fault bars. Moreover, despite the intrinsic methodological difficulties in
the study of fault bar allocation in adults, the same
pattern was found on adult feathers, suggesting an
adaptive fault bar allocation strategy in white storks
throughout their lives. Furthermore, the lower number
of fault bars in adults paralleled a movement of the first
feather type with high fault bars values towards inner
wing feathers (Sc) in relation to nestlings (SC), suggesting that fault bar allocation occurs in an hierarchical
manner. This also proves that fault bar occurrence is not
299
dependent of feather strength per se, but rather on feather
location. Previous studies have also found different
occurrence of fault bars on different feather groups
(Machmer et al., 1992), but to our knowledge, this is the
first clear demonstration of the occurrence of fault bar
allocation because feather zones growing at the same
time in the same individuals were compared.
Consistent with previous information (e.g. Slagsvold,
1982), fault bars were more common and stronger in
nestlings than in adults. This could be because nestlings
are forced to grow all feathers in a short time period
while the moult in the adults of the studied species is
much more flexible in timing, and feathers grow asynchronously. It is worth noting, however, that while
extreme numbers of fault bars in nestlings were only
found on inner wing feathers, even some outermost
adult feathers showed a high frequency of fault bars.
Because of fault bar allocation, this finding suggests that
some adults could be suffering even higher physiological
stress than nestlings.
Fault bars have been used as an index of ‘stress’,
‘quality’, or ‘body condition’ in an array of studies in
animal ecology (Bortolotti et al., 2002), conservation
biology (Sodhi, 2002), foraging ecology (Waite, 1990),
or sex allocation (Slagsvold, 1982). Fault bars occurring
on different feather types are typically added to extract a
‘fault bar index’ (Bortolotti et al., 2002), or only fault bars
occurring on one feather type are recorded (Sodhi,
2002). Because fault bar allocation is not random,
information contained in fault bars occurring on different
feathers should not be equivalent, but rather complementary. Therefore, we suggest that the best way of
extracting information from fault bars could be first
exploring fault bar data, and then studying separately
fault bar occurrence on different feather groups, or
weighting fault bar occurrence on different feathers
proportionally to their rarity on the study species.
Our results with storks together with previous evidence (Murphy et al., 1988; Machmer et al., 1992)
suggest that fault bar allocation could be a common
strategy of many flying bird species. However, the ‘fault
bar allocation hypothesis’ predicts that fault bar allocation might be a common strategy in species with high
flight requirements, but may be absent on nonflying
species. Ostriches (Sthrutio camelus) could provide some
insight on this point. Thanks to the economic importance
of ostrich feathers (e.g. dusters, decorative purposes),
farmers have studied the occurrence of fault bars in
ostrich feathers for a long time (Duerden, 1909; Deeming, 1999). Fault bars are common both in wild and
farmed ostriches, and they are equally abundant on wing
and body feathers (Duerden, 1909). This supports our
fault bar allocation hypothesis, because nonflying birds
such as ostriches seem to show a similar propensity of
fault bars on flight and body feathers. Moreover,
although the occurrence of fault bars has also been
related to many external stressors in ostriches (e.g. bad
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weather, inappropriate handling, crowding), some genetic variability in the propensity to develop fault bars has
been detected, and directed captive breeding programmes
have brought some improvements in the quality of
feathers (Petitte & Davis, 1999). Thus, a prerequisite of
our hypothesis, i.e. that there is genetic variability in
fault bar propensity available for natural selection to
operate on, is confirmed by ostrich information.
The potential of fault bars in biological research is still
undervalued. For instance, like tree-ring data (e.g.
Swetnam & Lynch, 1993; Barber et al., 2000), the study
of fault bars from museum bird collections could permit
the reconstruction of the ‘stress history’ of birds during the
last centuries. However, this promising future will benefit
of further work on the proximal mechanisms producing
fault bars (Murphy et al., 1988), the covariation between
fault bars and fitness (e.g. Bortolotti et al., 2002), and
further tests of the ‘fault bar allocation hypothesis’.
Acknowledgments
We are grateful to José Luis Tella for his support. Joaquı́n
Lamas, Judit Smits, Gary Bortolotti, José Luis Tella,
Martina Carrete, Raquel Baos, Isa Luque, Mariola
Martı́n, MaCarmen Roque, Fatima Leó n, Ernesto Fedriani
and especially Juan Manuel Terrero were of great help
on the field. This work improved from discussions and
manuscript revisions from Gary Bortolotti, José Luis
Tella, David Serrano, Juha Merilä , Carlos Rodriguez,
Esperanza Ursú a and Anna Perera. Funds were provided
by the Project B0S2002-00857 of Ministerio de Ciencia y
Tecnologı́a y Fondos Feder, Telefó nica Mó viles S.A. and
Junta de Andalucı́a. JB was supported from a postdoctoral grant from the Spanish Ministerio de Educació n,
Cultura y Deporte.
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Recieved 17 September 2003; revised 4 November 2003; accepted 4
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