Age-related improvement in reproductive performance in a
long-lived raptor: a cross-sectional and longitudinal study
Julio Blas, Fabrizio Sergio and Fernando Hiraldo
J. Blas, F. Sergio (fsergio@ebd.csic.es) and F. Hiraldo, Dept of Conservation Biology, Estación Biológica de Doñana, C. S. I. C. Avda. Ma Luisa
s/n, Pabellón del Perú, Apdo 1056, ES-41013 Sevilla, Spain.
In numerous iteroparous species, mean fecundity increases with age. Such improvement has been explained by: a)
progressive removal of inferior breeders from the breeding population (selection-hypothesis); b) delayed breeding of
higher-quality phenotypes (delayed-breeder-hypothesis); c) longitudinal enhancement of skills associated with age per se
(age-hypothesis); d) progressive improvement in the capability to conduct specific tasks facilitated by accumulated
experience (breeding-experience-hypothesis); and e) increasing parental investment promoted by declining residual
reproductive values (restraint-hypothesis). To date, there have been few comprehensive tests of these hypotheses. Here, we
provide such a study using a long-term dataset on a long-lived raptor, the black kite Milvus migrans (maximum lifespan
23 yr). Kites delayed breeding for 1—7 yr and all measures of breeding performance increased linearly or quadratically up
to 11 yr of age. There was no support for the delayed-breeder-hypothesis: superior phenotypes did not delay breeding
longer. Superior breeders were retained longer in the breeding population, consistent with the selection-hypothesis. All
measures of breeding performance increased longitudinally within individuals, supporting the age-hypothesis, while some
of them increased with accumulated previous experience, supporting the breeding-experience-hypothesis. Some analyses
suggested the existence of trade-offs between reproduction in the early years of life and subsequent survival, partially
supporting the restraint-hypothesis. The pattern of age-related improvements in breeding rates observed at the
population-level could be ascribed to the combined effect of the progressive removal of inferior phenotypes from the
breeding population and the individual-level lack of specific skills which are progressively acquired with time and
experience. It was also compatible with a longitudinal increase in reproductive investment. Results from previous studies
suggest that different mechanisms may operate in different species and that age-related improvements in reproduction
may be frequently promoted by the complex interplay between longitudinal improvements and changes in the relative
frequency of productive phenotypes in the breeding population.
Age-related variation in offspring production is a widespread pattern among iteroparous animals (Roff 1992,
Stearns 1992). At the population level, changes in breeding
performance generally follow a predictable age-related
pattern which can be subdivided into four potentially
progressive stages: 1) delayed onset of first breeding; 2)
longitudinal increases in productivity along successive
breeding episodes; 3) a fecundity-plateau in the middlelate stages of the life-cycle; and 4) a decline in fecundity
among the older age classes (Newton 1989, Forslund and
Pärt 1995, Martin 1995, Berube et al. 1999, Newton and
Rothery 2002).
In vertebrate taxa, the widely demonstrated age-related
improvements in reproduction recorded during the early
stages of life can be explained by five main hypotheses
which generate different sets of predictions regarding intraand inter-individual variation in breeding success (details in
Table 1). These five hypotheses are not always mutually
exclusive and, in some cases, they share common predictions (Table 1). 1) The selection hypothesis proposes that
age-related increases in breeding performance observed at
the population level are a consequence of the progressive
disappearance of individuals of lower phenotypic quality
(disappearance of poor breeders). This leads to variation in
mean reproductive output across age classes (Saether 1990,
Forslund and Pärt 1995, Laaksonen et al. 2002, Moyes
et al. 2006).
2) The delayed breeder hypothesis states that a staggered
incorporation of good breeders into the reproductive pool
may explain the initial age-related increases in breeding
performance (Hamann and Cooke 1987, Lessells and Krebs
1989, Perdeck and Cave 1992).
3) The age hypothesis postulates an increase in reproductive output at the individual-level, resulting from
progressive improvements in different skills not necessarily
directly related to reproduction, but with a positive impact
Table 1. Hypotheses explaining age-related improvements in breeding performance and their outcome predictions.
Hypothesis
Age-improvements in
reproduction caused by:
1. Selection
Progressive disappearance
of poor breeders from the
population
2. Delayed breeder
3. Age
High quality individuals
delay breeding more than
lower quality ones
Age per se improves skills
that in turn enhance
reproduction
Predictions
5. Restraint
Increasing experience
(rather than age per se)
promotes breeding skills
which enhance
reproduction
Progressively larger
terminal investment
Explanatory variables in
GLMMa
Age at last reproductione
Body size
Sex
Body size xsex
Yearf
Sex
Age
Age at last reproduction
Age of first breeding
Yearf
Individual identityf
Sex
Age
Age of first breeding
No. of fledged young in
first breeding attempt
Body size
Sex
Body size xsex
Yearf
Sex
Age
Age of first breeding
Breeding experience
Yearf
Individual identityf
-j
193 (105, 88)
Sex
Age of first breeding
Sex xage of first breeding
Sex
Age
Age of first breeding
Breeding experience
Yearf
Individual identityf
Sex
Age
Age of first breeding
Breeding experience
Yearf
Individual identityf
Sex
Age
Age of first breeding
No. of fledged young in
first breeding attempt
171 (94, 77)
1a
Higher quality individuals
drop out of breeding
population later
1b
Superior breeders g are
retained longer than inferior
breeders in the breeding
population
Number of fledged youngh
1c
Survival increases with
increasing reproductive
output in the early stages of
life (opposite of 5a)
Survival probabilityi
2a
Higher quality d individuals
enter the breeding population
progressively later
Age of first breedinge
2b
Delayed breeders show
Number of fledged youngh
better reproductive output than
non-delayed breeders of similar
age (opposite of 4b)
3a
Reproductive output
increases longitudinally within
individuals
The reproductive output of the
first breeding attempt is higher
in older individuals
Reproductive output
increases with experience,
while controlling for age
—j
4b
Delayed breeders show lower
reproductive output than
non-delayed breeders of
similar age (opposite of 2b)
Number of fledged youngh
5a
Survival declines with
Survival probabilityi
increasing reproductive
output in the early stages of life
(opposite of 1c)
3b
4. Breeding experience
d
4a
nb
Dependent variable in
GLMMa
No of fledged young in first
breeding attempth
Number of fledged youngh
264 (135, 129)
Supportedc
*
145 (74, 71)
56 (28, 28)
401 (211, 190)
*
401 (211, 190)
*
401 (211, 190)
*
145 (74, 71)
Table 1 (Continued)
Hypothesis
a
Predictions
Age-improvements in
reproduction caused by:
Dependent variable in
GLMMa
5b
Survival increases with age of
first breeding (i.e. is higher for
delayed breeders)
Survival probabilityi
5c
Longevity increases with age of
first breeding (i.e. is higher for
delayed breeders)
Longevityk
Explanatory variables in
GLMMa
Sex
Age
Age of first breeding
No. of fledged young in
first breeding attempt
Age of first breeding
nb
Supportedc
145 (74, 71)
*
51 (27, 24)
*
Explanatory and dependent variables employed in the GLMM models used to test the predictions of the hypotheses (see Methods).
Sample size of the GLMM model. In parentheses are the sample sizes for males and females, respectively.
Symbol legend: * =the prediction was supported by the results of this study.
d
In this prediction, ‘‘individual quality’’ is assessed independently of the breeding performance of the individual and may be measured as body size, body condition, plumage brightness or other
independent measures decided on the basis of previous knowledge of the study system. This has the advantage of avoiding circular arguments.
e
GLMM with normal errors and an identity link function.
f
Random factor in the GLMM.
g
This prediction focuses directly on the breeding performance of the individual in previous years. ‘‘Superior breeders’’ are those that have already demonstrated to be so in previous breeding seasons.
h
GLMM with Poisson errors and an logarithmic link function.
i
Tested by means of a Cox regression (see Methods).
j
Tested by means of Friedman’s repeated measures ANOVA (see Methods).
k
Tested by means of a non-parametric correlation (see Methods).
b
c
on it (e.g. foraging efficiency, access to resources or social
dominance; Desrochers 1992, Gilchrist et al. 1994, Catry
and Furness 1999).
4) The breeding experience hypothesis proposes that,
independently of age, the actual performance of a reproductive attempt generates critical skills in breeding tasks
(e.g. nest construction, incubation or chick rearing) that
may improve future breeding success (Pyle et al. 1991,
Fowler 1995, Chichon 2003).
Finally, the reproductive improvements postulated at the
individual-level may not only respond to abilities acquired
through age and experience, but rather represent voluntary
restraint. 5) Such restraint hypothesis links both the agerelated increase in productivity and the delayed age of first
breeding to longitudinal changes in reproductive investment (Curio 1983, Reid 1988, Green 1990, Tavecchia et al.
2001, 2005). This hypothesis assumes a trade-off between
current investment in reproduction and future survival or
fecundity. As individuals age, a decline in their residual
reproductive value primes gradual increases in their reproductive effort leading to improvements in reproduction.
Overall, hypotheses 1 and 2 employ a cross-sectional
approach to examine the population-level appearance and
disappearance of phenotypes of different quality, while
hypotheses 3—5 focus on longitudinal improvements in
performance within individuals. To date, most of the tests
of the five hypotheses were conducted on the smaller,
shorter-lived species of a few taxonomic groups or tested
only some of the hypotheses and not others (reviews in
Saether 1990, Forslund and Pärt 1995, see for example
Chichon 2003, Reid et al. 2003, Balbontı́n et al. 2007,
Hatch and Westneat 2007 and references therein). Here, we
provide a comprehensive test of the five hypotheses by
means of a long-term cross-sectional and longitudinal study
on a long-lived bird of prey, the black kite Milvus migrans.
To date, detailed studies on age-related reproduction in
raptors have been few and were mainly conducted on
smaller-sized, shorter-lived species (Pietiänen 1988, Espie
et al. 2000, Laaksonen et al. 2002, Newton and Rothery
2002, Arroyo et al. 2007). Furthermore, only a handful of
these studies have tested hypotheses on longitudinal
improvements in breeding rates (Espie et al. 2000,
Laaksonen et al. 2002, Newton and Rothery 2002).
Methods
population was stable during the study period at around
500 breeding pairs. Breeding and natal dispersal distances
are short (median 302 and 4800 m respectively) and
extensive surveys strongly suggest the absence of emigration
to other populations (Forero et al. 1999, 2002).
Field procedures
In all analyses, we employ reproductive data collected
exclusively between 1989 and 1999. However, ringing
activities started earlier in the following staggered manner:
since 1964, as many nestlings as possible have been marked
every year with metal rings. Since 1986, the nestlings were
also marked with a white plastic ring with a black, threecharacter alphanumeric code, which can be read by
telescope without disturbing the birds. In addition, since
1986, we used cannon nets and padded leg-hold traps
throughout the study area to capture and mark adults with
metal and plastic rings. Many of these birds had been metalbanded as nestlings before 1986, which subsequently
allowed us to sample the breeding performance of all the
age classes in the population. For each trapped adult we also
measured body mass to the nearest 5 g, tarsus length to the
nearest 0.1 mm, and wing length and tail length to the
nearest 1.0 mm. Overall, up to 2000, 2367 nestlings were
marked only with metal bands, and 4257 nestlings plus
1076 adults were marked with both metal and plastic
bands.
Since 1989, territories were searched intensively for
banded kites, for a total of over 3000 individual detections.
When a marked bird was detected on a territory, the area
was visited several times to locate its nest, to assess whether
laying took place and to record clutch size and the number
of chicks raised to fledging age (40—45 d old). Pairs were
classified as laying or non-laying only when their nests
could be checked weekly during the incubation period. This
ensured that we did not classify as non-laying females those
that actually laid eggs but lost their clutch soon afterwards.
In addition, when nests were located high on trees and the
time for climbing them was judged to be excessive, visits
were avoided altogether or minimized during the incubation and hatching period in order to avoid excessive
disturbance. For these reasons, sample size varies somewhat
between analyses. Individuals were sexed by molecular
analysis of a blood sample (Ellegren 1996) or by multiple
observations of copulation behaviour.
Study area
The study was conducted in a 430 km2 plot located in
Doñ ana National Park (south-western Spain). The landscape was mainly characterized by seasonally flooded
marshland, scrublands, grasslands, and mobile sand dunes
along the sea shore (see Forero et al. 1999, 2002 for details).
Study species
The black kite is a migratory, medium-sized raptor. The
maximum recorded lifespan is 23 yr (unpubl.). Sex roles are
asymmetric during reproduction, with females performing
most of the incubation and brooding while males provide
most of the food for their mates and nestlings. The
Estimates of individual quality, breeding
performance, age of first and last breeding,
experience and longevity
As in other raptorial species, previous analyses on this
population have demonstrated an association between
breeding output and large female size or small male size
(Sergio et al. 2007b and references therein). Therefore, we
used body size as an estimate of individual quality, as
expressed by the breeding potential of an individual (n =
53—70 individuals, depending on the analysis, see Results).
Because univariate metrics have been criticized as measures
of body size, we estimated size by means of the first axis
(PC1, hereafter ‘‘body size’’) of a principal components
analysis (Tabachnick and Fidell 1996) built using tarsus,
wing and tail length (Rising and Somers 1989, Freeman
and Jackson 1990). The PC1 explained 62% of the
variation in size and had high positive loadings for wing
length (r =0.87), tarsus length (0.52) and tail length (0.68).
Breeding performance was expressed as: a) the probability of laying eggs (0 =does not lay any eggs; 1 =lays
eggs); b) clutch size, defined as the number of eggs laid by a
breeding individual (i.e. one that managed to lay at least
one egg); and c) the number of fledged young, defined as
the brood size of a nest at fledging age, including zerocounts (i.e. pairs that failed to raise any chicks to fledging
age). We defined as age of first breeding the age when an
individual first laid eggs, and as age of last breeding the age
when an individual disappeared from the breeding pool of
the population. An individual was estimated to have been
removed from the breeding population when it was not
observed anymore to hold a territory for three consecutive
years. Because re-sighting probability is virtually one in this
population (Forero et al. 1999), the probability that an
individual could escape detection for three consecutive years
is considered very remote (estimated at 0.001 based on
Forero et al. 1999). Furthermore, no individual has been
observed to re-enter the breeding pool of the population
after two consecutive years of absence (unpubl.). Experience
was measured as the number of successful reproductions (at
least once chick raised to fledging) accumulated until the
current breeding attempt (range 1—6). Longevity was
available for a sample of 51 marked birds found dead
during the course of the study.
Statistical analyses and hypothesis testing
In our population, gradual declines in breeding performance were observed after the age of 11 yr (Blas 2002).
However, because many of the processes that promote agespecific declines in reproductive performance differ from
those that generate age-structured improvements, senescence will be analysed in detail elsewhere. Therefore, the
reproductive attempts of individuals older than 11 yr were
excluded from all the analyses. To describe the general
pattern of age-related improvements in reproduction, we
built a generalized linear mixed model (GLMM, Littel et al.
1996) with year (as a random factor), individual identity (as
a random factor), age, ageˆ2, sex and the interaction of age
and sex as explanatory variables and the probability of
laying eggs, clutch size or the number of fledged young as
dependent variables (n =409—719 breeding attempts depending on the dependent variable employed in the
analysis, see Table 2 for details).
We tested predictions 1a—b, 2a—b, 3b and 4a—b
(explained in Table 1) by means of GLMMs. Details on
explanatory and dependent variables, sample sizes and
model structure for all GLMMs are shown in Table 1.
To test the predictions of the selection hypothesis and of the
delayed breeder hypothesis, we followed the recommendations by van der Pol and Verhulst (2006) and built a
GLMM with year (as a random factor), individual identity
(as a random factor), age, ageˆ2, sex, age of first breeding
and age at last breeding as explanatory variables and the
number of fledged young as dependent variable. Under this
approach, age of first breeding and age of last breeding are
left in the model independently of their effect, in order to
test for within-individual age effects in the presence of a
selective effect (progressive incorporation or disappearance
of phenotypes of different quality). Applications of this
approach can be found in Nussey et al. (2006, 2008) and
Balbontı́n et al. (2007).
To explore the survival consequences of delayed breeding
and its associated reproductive success (prediction 1c, 5a
and 5b of Table 1), we related the probability of survival to
the age of first breeding and to the number of fledglings
produced in the first breeding attempt by means of a
backward stepwise Cox regression (Cabezas et al. 2007) that
accounted for age as a covariate (n =145 individuals
available for analysis). To be conservative, we assumed
that death occurred after three consecutive years lacking
re-sightings.
Table 2. GLMM regressions testing the linear and quadratic effects of age on: (a) the probability of laying eggs (n =247 males and 271
females); (b) clutch size (n =201 males and 208 females); and (c) the number of fledged young per territorial pair (n =353 males and 366
females) in a population of black kites in Doñ ana National Park (Spain). Random factors (year and individual identity) are only shown when
their effect was significant.
Variable
Parameter estimate9SE
F
p
0.6990.23
—0.0490.02
—0.8190.66
8.77
6.61
—
0.003
0.033
—
7.85
—
0.006
—
15.43
8.06
3.41c
—
B0.0001
0.005
0.003
—
a
(a) Dependent variable: probability of laying eggs (n =518)
Age
Age2 (quadratic effect)
Intercept
(b) Dependent variable: clutch size (n =409)b
Age
Intercept
(c) Dependent variable: number of fledged youngc (n =719)b
Age
Age2 (quadratic effect)
Individual identityd
Intercept
a
0.0290.005
0.6890.04
0.3890.10
—0.0290.007
0.2190.06
—1.9490.31
GLMM logistic regression with binomial errors and a logit link function (Littel et al. 1996).
GLMM multiple regression with Poisson errors and a logarithmic link function (Littel et al. 1996).
c
Number of fledged young per territorial individual: includes individuals which failed to raise any chick to fledging age (i.e. with zero fledged
young).
d
Random effect, tested by means of a Z-test (Littel et al. 1996).
b
Unavoidably, we could not sample the longitudinal
breeding performance of each individual for all ages (e.g.
because some individuals died before others, or because
breeding output could not be recorded in all years). For this
reason, we tested prediction 3a (Table 1) of longitudinal
improvements in breeding performance in two ways.
a) Firstly, we used Friedman’s repeated measures ANOVA
(Siegel and Castellan 1988) to compare the breeding output
of the same individual across the age classes 2—4, 5—7 and
8—11 yr old (n =15—43 individuals, details in Fig. 2). b)
Secondly, for each individual that was checked for
reproduction in at least 6 yr of its life, we correlated
breeding output with age (n =16—42 individuals, details in
the Results section) and then assessed the preponderance of
positive correlations (rs > 0.1) by means of a binomial test
(Siegel and Castellan 1988). Finally, prediction 5c (Table 1)
was tested by correlating the age of first breeding with the
longevity of 51 individuals by means of Spearman correlation coefficient (Siegel and Castellan 1988).
All stepwise models were built through a backward
procedure where the least significant terms or interactions
were sequentially removed until obtaining a minimal
adequate model that only retained significant effects at
the 5% probability level (McCullagh and Nelder 1989,
Crawley 1993). All tests are two-tailed, statistical significance was set at a B 0.05, and all means are given 91 SE.
Results
Age of first breeding and pattern of age-related
improvement in reproduction
The mean age of first breeding was 3.590.1 yr (range 1—7,
n =171), with no significant difference between the sexes
(t169 =1.63, p =0.10). Most individuals initiated breeding
within their first four years of life (83% of the cases), and
only sporadically beyond five years of age (4%). All
measures of breeding performance examined increased
linearly or quadratically with age (Table 2, Fig. 1).
Selection hypothesis
Body size, sex and their interaction did not enter the
GLMM with the age when an individual disappeared from
the breeding population as the dependent variable, lending
no support to prediction 1a (all F 52.99, n =37 males and
33 females, all p >0.05). There was instead support for
prediction 1b: the age of last breeding was a predictor of
breeding performance, while controlling for age and age of
first breeding (Table 3). Therefore, for both sexes, superior
breeders were removed progressively later from the breeding
population. Finally, there was no support for prediction 1c:
the reproductive output in the first breeding attempt did
not affect subsequent survival probability (Cox regression,
Wald x21 = 0.33, p =0.56).
Figure 1. Progressive improvement in mean (9 SE) breeding
performance with age in a cross sectional analysis conducted on a
black kite population studied in Doñ ana National Park (Spain).
(a) Mean probability of laying eggs (n =247 males and 271
females); (b) mean clutch size (n =201 males and 208 females); (c)
mean number of young raised to fledging age (n =353 males and
366 females).
Delayed breeder hypothesis
Body size, sex and their interaction did not enter the
GLMM with the age of first breeding as the dependent
variable, lending no support to prediction 2a (all F 51.25,
n =28 males and 27 females, all p >0.05). When
controlling for age, delayed breeding led to poor
Table 3. GLMM regression (with Poisson errors and a logarithmic
link function) testing the effect of sex, age, age of first breeding and
age of last breeding on the number of fledged young (n =135 males
and 129 females) in a population of black kites in Doñ ana National
Park (Spain). Random factors (year and individual identity) are only
shown when their effect was significant. Age of first breeding and
age of last breeding were retained in the model even if their effect
was not significant, in order to test for within-individual age effects
in the presence of a selective effect (Nussey et al. 2006, 2008, van
der Pol and Verhulst 2006, Balbontı́n et al. 2007). Percentage
explained deviance =20.8%.
Variable
Age
Age of first breeding
Age of last breeding
Individual identitya
Intercept
a
Parameter estimate9SE
F
p
0.0390.01
—0.0190.03
0.0290.001
0.0290.01
0.0290.15
9.60
0.16
4.35
2.07a
—
B0.01
ns
B0.05
B0.05
—
Random effect, tested by means of a Z-test (Littel et al. 1996).
subsequent reproductive performance (opposite of prediction 2b, Table 4).
x21 B0.10, p >0.05). On the contrary, there was no support
for prediction 3b, because the reproductive output of the
first breeding attempt was unrelated to age (GLMM, B =
0.0290.07, F153 =2.56, p =0.11).
Breeding experience hypothesis
When age, previous experience and the age of first
breeding were simultaneously taken into account (prediction 4a), clutch size was exclusively related to experience,
the number of fledged young was positively related to both
age and experience and negatively related to the age of first
breeding, while no variable entered the stepwise model
with the probability of laying eggs as the dependent
variable (Table 3, Fig. 3). The negative effect of the age of
first breeding on the number of fledged young while
statistically controlling for age (Table 4c) also supported
prediction 4b.
Restraint hypothesis
Age hypothesis
There was support for prediction 3a. Firstly, on average and
independently of sex, all measures of breeding performance
increased longitudinally through life (Fig. 2), but the
effect was significant for the number of fledged young
(Friedman’s repeated measures ANOVA: x22 =12.2,
p =0.002), marginally significant for clutch size (x22=
5.1, p =0.08) and not significant for the probability of
laying eggs (x22 =3.3, p =0.20). Secondly, for individuals
checked for reproduction at least six times, there was a
significant preponderance of positive correlations for the
probability of laying eggs (22 positive correlation coefficients out of 31; binomial test: p =0.031), for clutch size
(14 of 16; p =0.004) and for the number of fledged young
(31 of 42; p =0.003). There was no difference between the
sexes in the proportion of positive correlations for all the
three estimates of breeding performance examined (all
There was no effect of the reproductive output in the first
breeding attempt on subsequent survival probability, which
did not support prediction 5a (Cox regression, Wald x21 =
0.33, p =0.56). However, predictions 5b and 5c were
supported: survival increased with the age of first breeding
(B =0.5390.15, Wald x21 =11.9, p B0.001; —2 log likelihood =460.2, Global Score Wald x12 =12.3, p B 0.001),
while longevity was positively associated with the age of first
breeding (rs =0.44; n =51, p =0.001).
Discussion
As with previous studies on other raptorial species
(Pietiänen 1988, Espie et al. 2000, Laaksonen et al.
2002, Newton and Rothery 2002, Arroyo et al. 2007)
and birds in general (Saether 1990, Martin 1995), agerelated reproductive rates in our population showed a
Table 4. GLMM regressions testing the effect of age, previous breeding experience and age of first breeding on: (a) the probability of laying
eggs (n =149 males and 141 females); (b) clutch size (n =112 males and 112 females); and (c) the number of fledged young (n =211 males
and 190 females) in a population of black kites in Doñ ana National Park (Spain). Random factors (year and individual identity) are only
shown when their effect was significant.
Variable
(a) Dependent variable: probability of laying eggs (n =290)
No variable entered the model
(b) Dependent variable: clutch size (n =224)b
Breeding experience
Intercept
Parameter estimate 9 SE
(c) Dependent variable: number of fledged youngc (n =401)b
Age
Age of first breeding
Breeding experience
Individual identityd
Intercept
a
F
p
24.17
—
B0.0001
—
a
0.0890.02
0.7290.02
0.5890.24
—0.4190.16
0.2890.15
0.5390.20
—1.9490.31
14.47
4.51
7.58
2.54c
—
0.0002
0.034
0.006
0.005
—
GLMM logistic regression with binomial errors and a logit link function (Littel et al. 1996).
GLMM multiple regression with Poisson errors and a logarithmic link function (Littel et al. 1996).
c
Number of fledged young per territorial individual: includes individuals which failed to raise any chick to fledging age (i.e. with zero fledged
young).
d
Random effect, tested by means of a Z-test (Littel et al. 1996).
b
Figure 3. Progressive improvement in mean (9SE) reproductive
performance with breeding experience in a black kite population
studied in Doñ ana National Park (Spain). Breeding experience was
measured as the number of successful reproductions (at least once
chick raised to fledging) accumulated until the current breeding
attempt.
Figure 2. Progressive improvement in mean (9SE) breeding
performance with age in a longitudinal analysis conducted on a
black kite population studied in Doñ ana National Park (Spain).
The data refer to individuals which were repeatedly sampled at
least twice within each of three main periods of their life
(corresponding to age classes 2—4; 5—7, and 8—11 yr old). Mean
values were used for the repeated measures analyses: for example, if
an individual was sampled when 6 and 7 yr old, the mean of the
two breeding attempts was used to characterise its performance in
the age-class 5—7. (a) Mean probability of laying eggs (n =38; 19
males and 19 females); (b) mean clutch size (n =15; 8 males and 7
females); (c) mean number of young raised to fledging age (n =43;
21 males and 22 females).
typical pattern of deferred breeding early in life followed
by gradual increases in productivity (see also Sergio et al.
2009). Of the five hypotheses we tested to explain this
pattern, four received at least partial support while the fifth
was rejected. Our results indicate that multiple factors such
as age, experience and selection against inferior breeders
may account for the observed increase in reproductive
success with age.
In particular, of the five tested hypotheses, there was no
support for the delayed breeder hypothesis. If anything,
high breeding performance was associated with an early age
of first breeding, running contrary to the main expectation
of this hypothesis. On the contrary, there was some support
for the selection hypothesis: superior breeders persisted
longer within the breeding pool of the population. This
suggested the existence in the population of superior
phenotypes capable of maintaining high levels of reproduction for a longer time-span and inferior phenotypes
characterised by lower breeding rates and shorter reproductive careers. Overall, this hypothesis has been supported by
some studies (Coulson and Porter 1985, Nol and Smith
1987, Wooller et al. 1990), but not by others (Forslund and
Larsson 1992, Perdeck and Cave 1992, Hepp and
Kennamer 1993, Wheelwright and Schultz 1994, Wiebe
and Martin 1998, Balbontı́n et al. 2007, Hatch and
Westneat 2007). Some authors have suggested that the
selection hypothesis may be more relevant for short-lived
species, characterised by high mortality rates which translate
into marked declines in the frequency of poor-performers in
older age-classes (Newton 1989, Forslund and Pärt 1995).
However, there is increasing evidence that such mechanisms
may be operating also in longer-lived species (Wooller et al.
1990, Espie et al. 2000, Laaksonen et al. 2002, Reid et al.
2003, Tavecchia et al. 2005, Moyes et al. 2006).
Our results were also consistent with the age and
experience hypotheses, where age-related improvements in
reproductive rates are promoted by chronological age per se
and by accumulation of previous breeding experience,
respectively. Chronological age may progressively enhance
the social dominance, foraging capabilities and the level of
resource acquisition of an individual through life, while
accumulated experience may improve breeding skills
through previous practice and through enhanced familiarity
with the territory and the partner. All these factors may be
important in our population for the following five reasons.
1) Age per se was shown to promote earlier arrival dates
from the spring migration, with positive cascading effects
on the quality of the territory occupied, the time available
to accumulate reserves for breeding, the precociousness of
laying date and the final breeding output of an individual
(Sergio et al. 2007a, b, 2009). 2) Older individuals were
shown to be dominant over younger ones in physical
contests over territories, which suggested a link between age
and social dominance, which may ultimately translate into
higher reproduction (Sergio et al. 2007a, 2009). 3) Age may
promote improvements in feeding skills (Wunderle 1991),
which in turn may promote higher breeding rates (MacLean
1986). Previous studies from this and other black kite
populations suggest a close link between territory quality,
foraging proficiency, nestlings’ provisioning rates and
eventual breeding output (Sergio et al. 2003a, b, 2005,
2007a). 4) In our population, kites are site-faithful, and
usually retain territories and partners through life or for
many years (Forero et al. 1999). Experience may increase
the familiarity with the partner, territory and hunting
grounds, with potentially positive repercussions on offspring production, as shown in other species (Hepp and
Kennamer 1992). 5) In this and other kite populations,
inexperienced individuals are known to fail frequently to
build a proper nesting platform, or to take longer to achieve
it than older birds, with negative consequences for
reproduction (Viñ uela 1993, Sergio and Newton 2003).
The capability of nest construction is known to improve
with experience in numerous avian taxa (review in Collias
and Collias 1984). All the above is consistent with the idea
that in this population both chronological age per se and
previous experience may act in concert to generate the
observed pattern of age-structured improvement in breeding rates.
Finally, we found some evidence of a potential trade-off
between a precocious age of first breeding and subsequent
survival and longevity, consistent with the restraint hypothesis and as found in other long-lived animals (Green 1990,
Roff 1992, Pyle et al. 1997, Tavecchia et al. 2001, 2005).
Unfortunately, no direct estimates of parental investment
(e.g. nest attendance, foraging effort) were available to
better test this hypothesis. Furthermore, not all predictions
of this hypothesis were supported and the low mortality
typical of adult kites (unpubl.) should imply a relatively
small decline in residual reproductive value for the age
classes analysed here (2—11 yr old). The idea that young
breeders show reproductive restraint in order to increase
subsequent performance has received little empirical support (Newton 1989, Forslund and Pärt 1995, but see
Pugesek 1981 and Weimerskirch 1992), and it is considered
unlikely that this factor alone could contribute to the
observed age-related improvement in reproduction, at least
so early in life (Forslund and Larsson 1992).
In conclusion, the pattern of age-related improvements
in breeding rates observed in this population could be
ascribed to the combined effect of the progressive removal
of inferior phenotypes from the breeding population and
the individual-level lack of specific skills which are
progressively acquired with time and experience. Studies
on other raptorial species have reported evidence of both
longitudinal increases in performance (Laaksonen et al.
2002, Newton and Rothery 2002) and progressive removal
of inferior breeders (Espie et al. 2000, Laaksonen et al.
2002), the two acting alone or in concert. Such results
suggest that different mechanisms may operate in different
species or populations (Wiebe and Martin 1998) and that
age-related improvements in reproduction may be frequently caused by the complex interplay between longitudinal improvements and changes in the relative
frequency of productive phenotypes in the breeding
population.
Acknowledgements — We thank F. G. Vilches, R. Baos, S. Cabezas,
J. A. Donázar, M. G. Forero, G. Garcı́a, L. Garcı́a, M. Guerrero,
and A. Sánchez for help in the field. R. Baos, J. Balbontı́n, G.
R. Bortolotti, J. A. Donázar, M. G. Forero, W. D. Koenig,
K. Martin, D. Serrano, J. L Tella and an anonymous reviewer
kindly improved earlier drafts of this manuscript. Part of this study
was funded by the research projects PB96-0834 of the Direcció n
General de Investigación Cientı́fica y Tecnológica, JA-58 of the
Consejerı́a de Medio Ambiente de la Junta de Andalucı́a and by
the Excellence Project RNM 1790 of the Junta de Andalucı́a.
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