2006 The Authors
Journal compilation 2006 Blackwell Verlag, Berlin
Accepted on 19 July 2006
J Zool Syst Evol Res doi: 10.1111/j.1439-0469.2006.00382.x
1
Division of General Human Genetics, Department of Medical Genetics, Institute of Human Genetics, University of Tübingen,
Tübingen, Germany; 2Department of Wildlife Ecology and Management, University of Freiburg, Freiburg, Germany; 3Department
of Experimental Ecology (Biology 3), University of Ulm, Ulm, Germany; 4Department of Zoology, Natural History Museum,
University of Oslo, Oslo, Norway
Female genetic heterogeneity affects the reproduction of great tits (Parus major L.,
1758) in low-quality woodlands
J. Tomiuk1, M. Stauss1, G. Segelbacher2, J. Fietz3, J. Kömpf1 and L. Bachmann4
Abstract
Genetic heterogeneity is considered an important parameter for individual fitness and reproductive success. In 1999 and 2000, we studied the
population genetics of great tit (Parus major L., 1758) in southwestern Germany from two different forest types (deciduous and mixedconiferous), which may significantly differ in prey diversity and/or food supply. Adults of 99 families were genotyped at four enzyme and eight
microsatellite loci, in order to estimate individual heterozygosity. In the mixed-coniferous forest, a significant positive correlation between the
genetic heterogeneity of females and early egg-laying date and clutch size was detected. Early egg-laying date and increased clutch size are
conditions that positively affect the number of fledglings. This effect of individual heterozygosity was not observed in the deciduous woodland.
Maternal genetic heterogeneity, however, did not correlate with fledgling condition, and individual heterozygosity of fathers had no impact on
breeding success in either habitat. The positive effect of female genetic heterogeneity on brood size of great tits in mixed-coniferous forests is
attributed to early egg-laying date, i.e. a maternal effect, rather than to a specific mating strategy that optimizes fitness through an increased
brood size and the quality of offspring.
Key words: Genetic variation – inbreeding avoidance – maternal effects – mating strategy
Introduction
The fundamental meaning of genetic variability for individuals
and populations has been an issue in evolutionary biology at
all times (Dobzhansky 1970). Classical population genetic
models predict a positive association between genetic heterogeneity and fitness for any set of markers (e.g. Ohta 1971;
Charlesworth 1991). Avoidance of inbreeding depression is
one of the main arguments put forward in favour of this
association. Yet, experimental studies have sometimes revealed
contradictory findings (e.g. review by Zouros and Foltz 1987).
In the common mussel (Mytilus edulis L., 1758), for example,
Koehn and Gaffney (1984) found a positive correlation
between heterozygosity and fitness-related characters such as
growth rate, whereas Pierce and Mitton (1982) noticed a
negative effect of heterozygosity on individual fitness of the
tiger salamander Ambystoma tigrinum (Green, 1825). Allozymes and microsatellites are frequently used to assess
heterozygosity and the choice of a particular marker system
is certainly an issue (David 1998; Thelen and Allendorf 2001).
Most microsatellites are considered neutral, although the
structure of some particular microsatellites may be under
selection (Li et al. 2002). Allozymes, however, are essential
components of biochemical pathways. Variation of their
activity and substrate specificity may have a substantial impact
on the fitness of organisms. Allelic variation at such loci may
nevertheless be neutral and merely act as neutral markers of
closely linked fitness loci (Nei and Graur 1984). Combining
both kinds of markers in ecological studies is therefore
considered suitable for the assessment of genetic variation of
individuals (Pujolar et al. 2005).
In Parus species, a diet consisting of a high proportion of
alternative prey types is considered an indicator for suboptimal
habitats (Cowie and Hinsley 1987). For example, the diet of
great tit (Parus major L., 1758) nestlings is less diverse in
J Zool Syst Evol Res (2007) 45(2), 144–150
deciduous forests than in mixed woodlands where the diet of
nestlings includes a high proportion of spiders (Gibb and Betts
1963). Some Parus species, e.g. the blue tit (Parus caeruleus L.,
1758), are better adapted to deciduous forests where individuals show a better breeding performance than those in lowquality habitats (mixed woodlands dominated by coniferous
trees) (Blondel et al. 1987; Cowie and Hinsley 1987; van Balen
and Potting 1990; Stauss 2000; Stauss et al. 2005). Stauss
(2000) found, during a study period of more than 10 years,
that great tit females start laying eggs 3 days earlier in
deciduous forests than in mixed-coniferous forests. The density
of great tit breeding pairs was significantly higher in deciduous
forests (1.73 ± 0.38 pairs ha)1) than in mixed-coniferous
forests (1.04 ± 0.21 pairs ha)1). Furthermore, the average
hatching success was higher in deciduous habitats (90%) than
in mixed-coniferous ones (84%). These findings strongly
support the quality assessment of the two habitat types, i.e.
high-quality habitat (deciduous forest) and low-quality habitat
(mixed-coniferous forest).
In 1999 and 2000, in particular, the effect of genetic
heterogeneity of breeding great tits on fitness-related brood
parameters in mixed-coniferous and deciduous woodlands was
focussed. The association between genetic variability of
breeding great tit individuals and their reproductive success
was analysed. Such correlations have previously been reported
for blue tits. In this species, high genetic variability of females
was associated with an increased brood size, and paternal
genetic heterogeneity was associated with increased fledging
success and a higher number of sired recruits (Foerster et al.
2003). It was also found that genetic heterogeneity of great tit
females has an impact on their reproduction in mixedconiferous woodlands, an effect that was neither observed in
deciduous forests nor for paternal genetic variability. The
significant association between female genetic heterogeneity
Maternal genetic heterogeneity and reproduction of Parus major
and some brood parameters of great tits in mixed-coniferous
forests is considered as a maternal effect.
Materials and Methods
Study area
Great tit (P. major L., 1758) populations were studied in three forests
near Tübingen, southwestern Germany (4833¢N, 900¢E). A study plot
of 35 ha was dominated by 60% coniferous trees, e.g. scots pines
(Pinus sylvestris L., 1753) and spruces (Picea abies L., 1753). Two
study plots (9 and 16 ha) in the same forest consist of 67% beeches
(Fagus sylvatica L., 1753) and 21% oaks (Quercus robur L., 1753). For
more detailed information, see Stauss et al. (2005). The data from the
two deciduous plots were pooled, because there were no significant
differences in any of the estimated parameters (Wilcoxon rank sum
test).
The data presented here were obtained during a long-term population biological study of great tits and blue tits (P. caeruleus) from
1990 to 2004 (Stauss 2000; Stauss et al. 2005). In the course of the
study, 173 nest boxes were installed in the deciduous forest and 236
nest boxes in the mixed woodland. The nest boxes were arranged in a
30 m · 30 m grid. Nests were checked regularly during the breeding
seasons. Reproductive parameters such as laying date, clutch size and
the number of hatchlings and fledglings were recorded. Adults and
fledglings were weighed 14–16 days after hatching, i.e. 1 or 2 days
before the nestlings fledged. In 1999, 17 females, 16 males and 17
families from the mixed forest and 28 females, 29 males and 29 families
from the deciduous forest were analysed. In 2000, the sample consisted
of 22 females, 23 males and 23 families from the mixed forest and 30
females, 29 males and 30 families from the deciduous forests. Roughly,
one third of the adult birds monitored in 2000 were already breeding in
1999. Eight identical breeding pairs (five in the coniferous and three in
the mixed forest) were noticed in both years. Another three female
yearlings were recruits in the mixed woodland in 2000.
Genetic variability
During the breeding seasons in 1999 and 2000, blood (about 50 ll) was
sampled through tapping the Vena ulnaris. Blood was stored in 250 ll
EDTA buffer (1 mM, pH 7.4) in plastic vials and frozen until further
processing. Approximately, 150 ll diluted blood was used for DNA
isolation using the Qiagen DNA Blood Mini Kit (Qiagen, Hilden,
Germany).
Allelic variation within 99 families was studied. In both years, 96
males and 98 females were successfully genotyped at up to eight
microsatellite loci: Pk-12 (GenBank accession no. AF041466), Mcy-4
(Double et al. 1997), Pocc-6 and Pocc-8 (Bensch et al. 1997), Pat-14
and Pat-43 (Galbusera et al. 2000) and Gf-4 and Gf-6 (Petren 1998).
The four microsatellite loci, Pk-12, Pat-14, Pat-43 and Pocc-8, were
analysed by polyacrylamide gel electrophoresis and silver staining, and
the four microsatellites, Mcy-4, Pocc-6, Gf-4 and Gf-6, were scored by
fragment-length analysis on an ABI-310 automatic sequencer (Applied
Biosystems, Foster City, CA, USA). Approximately, 100 ll diluted
blood was used for the electrophoretic analyses of three esterase
isozymes (EST-1, EST-2, EST-3, E.C. 3.1.1.1) and phosphoglucoisomerase (PGI, E.C. 5.3.1.9), as described in Stauss et al. (2003) and
Driesel et al. (2004).
Statistical analysis
The genetic heterogeneity of individuals was estimated as the observed
relative proportion of heterozygous loci per individual.
Standardization of reproductive parameters
The brood parameters egg-laying date, hatching date, number of
fledglings, total brood mass and body mass of fledglings differed
significantly between the breeding seasons 1999 and 2000 (Fig. 1,
p < 0.027; see also Table S1). For eliminating year effects (not
relevant in this study), the data set per year was standardized to the
145
mean ¼ 0 and the standard deviation ¼ 1. After standardization, the
observed values of all parameters were close to a normal distribution
(Shapiro–Wilks test: 0.020 £ p £ 0.710, UNIVARIATE procedure;
SAS 2003).
The standardized brood parameters were tested for normality
(Shapiro–Wilks test, UNIVARIATE procedure; SAS 2003) and
homogeneity of variances between habitats and years (Levene’s test,
t-test procedure; SAS 2003). Analyses of variance [general linear
models (GLM) procedure and GENMOD procedure for binomially
distributed dependent variables; SAS 2003] and regression models
[REG procedure and non-linear regression analysis (NLIN) procedure;
SAS 2003] were applied to parameters such as egg-laying date, clutch
size, hatching date, number of hatchlings, number of fledglings, the
mean body mass of fledglings and the total fledging mass, in order to
study the impact of habitat quality and parental heterozygosity on the
reproductive success of breeding pairs. Pearson’s correlation coefficients were calculated for male and female heterozygosity and brood
parameters (CORR procedure; SAS 2003). For these analyses,
individual genetic heterogeneity values were logarithmically transformed. For all tests, a significance level of 5% was accepted.
Results
Individual genetic heterogeneity within and between groups
The average degree of individual heterozygosity (relative
proportion of heterozygous loci per individual) was determined for adult great tit males and females separately for both
habitat types and years (Fig. 2). The observed heterozygosity
values did not differ significantly between sexes (p ¼ 0.726). In
a subsequent analysis using the GLM procedure (SAS 2003),
no significant differences between years in both habitat types
(Hfemale: p > 0.573; Hmale: p > 0.559) and between habitat
types in both years (Hfemale: p > 0.074; Hmale: p > 0.540)
could be detected. Furthermore, the population genetic analyses showed fairly homogeneous genetic structures (allele and
genotype frequencies) across habitat types within years (Blank
et al. unpublished data).
Correlation of brood parameters
Most brood parameters are closely correlated to each other in
both habitat types (see Table S2). Yet, correlation analyses
points to some differences depending on the habitat type.
There was a significant correlation between egg laying and
clutch size in the mixed-coniferous habitat (p ¼ 0.008) but not
in the deciduous habitat (p ¼ 0.064). In the deciduous but not
in the mixed-coniferous woodland, early egg-laying date and
hatching results in fledglings with high individual body mass
(p < 0.001). Egg-laying date is the starting point of the
measurements of breeding success. Its overall importance for
reproduction was therefore studied in more detail.
Egg-laying date and reproductive success
Egg-laying date is known to have a major effect on brood
parameters (e.g. Verhulst and Tinbergen 1991; Nilsson 1999;
Hansson et al. 2000; Wardrop and Ydenberg 2003). Using the
framework of generalized linear models in the analysis of
variance (GLM procedure; SAS 2003), it was tested whether
the time of egg laying had significant effects on clutch size and
hatching date. Subsequently, significant effects of clutch size
on the number of hatchlings were tested, afterwards significant
effects of the number of hatchlings on the number of fledglings
were tested, and finally significant effects of the number of
fledglings on the total and mean body mass of fledglings were
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin
146
Tomiuk, Stauss, Segelbacher, Fietz, Kömpf and Bachmann
Fig. 1. Brood parameters of great tits in the mixed-coniferous and deciduous woodlands in the breeding seasons of 1999 and 2000. Boxes and
solid lines in boxes represent mean ± SD, the broken lines indicate the median and the whiskers show the range of variation. The sample sizes are
given within the boxes
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin
Maternal genetic heterogeneity and reproduction of Parus major
147
Table 1. Analyses of variance and covariance (GLM procedure; SAS
2003). The effects of habitat type and egg-laying date as covariates on
clutch size, hatching date and fledging success, of clutch size on the
number hatchlings, of the number of hatchlings on the number of
fledglings and of the number of fledglings on the total and mean body
mass of fledglings were estimated
Source
Fig. 2. Genetic heterogeneity of female and male great tits in deciduous and mixed-coniferous forests in 1999 and 2000. Boxes and solid
lines in boxes represent mean ± SD, the broken line indicates the
median and the whiskers show the range of variation. The sample sizes
are given within boxes
tested. As can be seen from Table 1, there is a dominant effect
of the egg-laying date on clutch size (p ¼ 0.026) and hatching
date (p < 0.001). The other downstream brood parameters
were mainly affected by the respective preceding brood
parameters. Table 1 shows that the habitat-specific effect of
female genetic heterogeneity on the number of offspring and
their quality is mediated through early egg-laying date.
Paternal heterozygosity and reproductive success
Correlation of individual heterozygosity of fathers and breeding success was detected in neither habitat type.
Female heterozygosity and reproductive success
The analyses of variance (GLM procedure; SAS 2003) revealed
a significant effect of female heterozygosity, egg-laying date
and habitat on clutch size (Table 1). Therefore, the female
heterozygosity was correlated with egg-laying date and clutch
size for both habitats separately (Pearson’s correlation coefficient, CORR procedure; SAS 2003). As can be seen from
Fig. 3, egg-laying date is significantly correlated with female
heterozygosity in the mixed-coniferous habitat (F1,35 ¼ 11.42,
p ¼ 0.002). Consistently, clutch size is also significantly
correlated with female genetic heterogeneity (F1,35 ¼ 6.49,
p ¼ 0.015). In the deciduous forest, neither egg-laying date nor
clutch size was significantly correlated to female heterozygosity
(see also Table S3).
Female heterozygosity and egg-laying date
The correlation of female heterozygosity, egg-laying date and
habitat type was now analysed in more detail. A linear
correlation of female heterozygosity on egg-laying date did not
strongly fit the data (model: F3,89 ¼ 2.78, p ¼ 0.045, GLM
procedure; SAS 2003). The dependency of egg-laying date on
female heterozygosity could be much better explained by a
model assuming an increasing negative effect of female
homozygosity on egg-laying date in the mixed-coniferous
habitat and random effects in the deciduous habitat (Fig. 3).
To achieve this, heterozygosity values of the females in the
mixed-coniferous habitat were logarithmically transformed
and an NLIN procedure (SAS 2003) was applied to the data
df
Clutch size
Model
4
Error
88
Habitat
1
Egg-laying date
1
1
Hfemale
1
Hfemale (habitat)
Hatching date (days after 1 April)
Model
4
Error
88
Habitat
1
Egg-laying date
1
1
Hfemale
1
Hfemale (habitat)
Number of hatchlings
Model
4
Error
88
Habitat
1
Clutch size
1
1
Hfemale
1
Hfemale (habitat)
Number of fledglings
Model
4
Error
86
Habitat
1
Number of hatchlings
1
1
Hfemale
1
Hfemale (habitat)
Total brood mass (g)
Model
4
Error
86
Habitat
1
Number of fledglings
1
1
Hfemale
1
Hfemale (habitat)
Mean body mass of fledglings (g)
Model
4
Error
86
Habitat
1
Number of fledglings
1
1
Hfemale
1
Hfemale (habitat)
Fledging success (fledglings per egg)
Model
6
Error
84
Year
1
Habitat
1
Year · habitat
1
Egg-laying date
1
1
Hfemale
1
Hfemale (habitat)
MS
F
2.96
0.875
5.986
4.515
0.007
5.245
3.38
0.013
6.82
5.16
0.01
6.00
0.011
0.026
0.929
0.016
19.446
0.113
0.423
70.806
0.394
0.374
171.94
<0.001
3.74
626.06
3.48
3.30
0.056
<0.001
0.065
0.073
16.675
0.273
1.082
55.716
0.223
0.943
61.00
<0.001
3.96
203.81
0.82
3.45
0.050
<0.001
0.368
0.067
11.288
0.485
0.047
40.051
0.556
0.008
23.30
<0.001
0.10
82.66
1.15
0.02
0.756
<0.001
0.287
0.900
19.476
0.106
0.046
75.185
0.111
0.032
184.04
<0.001
0.44
710.47
1.05
0.31
0.511
<0.001
0.308
0.581
0.933
0.983
2.438
0.991
0.383
1.723
0.95
0.440
2.48
1.01
0.39
1.75
0.119
0.318
0.534
0.189
4.26
<0001
10.06
1.50
5.40
4.05
0.58
1.04
0.002
0.225
0.023
0.047
0.450
0.311
0.078
0.018
0.185
0.028
0.099
0.074
0.011
0.019
p
df, degree of freedom; MS, mean squares (type III); F, F-value; p, type
I error. Significant effects are given in bold.
(model:
F2,91 ¼ 5.10,
p ¼ 0.017;
coniferous
forest:
slope ¼ )1.383 ± 0.483, intercept ¼ )1.125 ± 0.369; deciduous forest: mean ¼ 0.130 ± 0.126 for standardized values).
The fledging success was also tested in terms of the number
of fledglings per egg (Dhondt et al. 1990) as a response to
habitat type, egg-laying date and hatching date, and in terms
of female heterozygosity with generalized linear models where
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin
148
Fig. 3. Association between female genetic heterogeneity and egglaying date in the low-quality habitat (mixed coniferous; a) and highquality habitat (deciduous; b). A non-linear model explained the data
more adequately than a linear model. The female genetic heterogeneity
values in the low-quality habitat were therefore logarithmically
transformed (mixed-coniferous forest: r ¼ )0.496, F1,35 ¼ 11.42,
p ¼ 0.002; deciduous forest: r ¼ )0.095, F1,54 ¼ 0.21, p ¼ 0.648)
the dependent variable is binomially distributed (GENMOD
procedure; SAS 2003). The analysis of the reduced
model revealed again significant temporal effects (egg-laying
and -hatching dates) on fledging success (v2 > 4.19, df ¼ 1,
p < 0.047) but no effect of the genetic heterogeneity of
females (Table 1; see also Table S3).
Discussion
In the present study, a habitat-specific effect of maternal
genetic heterogeneity on reproduction rate of great tits in
mixed-coniferous forests was found. The major fitness
parameters in birds is the number of fledglings, but also
their body mass, as it is closely correlated with fledgling
survival to the next breeding season (Lindén et al. 1992;
Slagsvold et al. 1995). In evolutionary terms, it would thus be
reasonable if selection would operate on these brood parameters in order to optimize fitness. Yet, some reproductive
characters are closely correlated to each other (see Table S2)
and this may cause counteracting effects on fitness. The egglaying date and the correlated clutch size may also be affected
by environmental conditions that are not primarily determined by the habitat type (e.g. temperature), whereas habitat
Tomiuk, Stauss, Segelbacher, Fietz, Kömpf and Bachmann
structure may have larger impact on the survival of nestlings
after their hatching. It is, for example, very likely that the
number of fledglings and their individual body mass are
determined by parental feeding abilities according to the
resources provided by the habitat (see Slagsvold and Lifjeld
1990; Stauss et al. 2005).
It is thus interesting that egg-laying date and clutch size,
two parameters that may subsequently affect the number and
the individual body mass of fledglings, correlate with female
genetic heterogeneity of great tits in the low-quality habitat,
whereas the number and the individual body mass of
fledglings are not directly depending on the genetic heterogeneity of females (Table 1). Under suboptimal ecological
conditions, high genetic heterogeneity of great tit females may
indirectly result in a higher number of offspring that may
result in large broods with a low quality of fledglings. The
lacking association between paternal genetic heterogeneity
and reproductive success of great tits may indicate that the
feeding effort of males for their brood is less crucial.
Summarizing the association between female genetic heterogeneity and brood size is therefore attributed to a maternal
effect rather than to a specific improvement of offspring
fitness through an evolutionary strategy that evolved to
increase nestling quality. Foerster et al. (2003) noted that
individual heterozygosity affects survival of 1-year-old
females to the next season. The observed correlation between
female genetic heterogeneity and egg-laying date in the lowquality habitat is consistent with the results of Foerster et al.
(2003) and may also indicate an increased survival of
genetically heterogeneous females from one breeding season
to the next. The fact that seven of eight female recruits have
an individual genetic heterogeneity above the population
mean supports this conclusion.
Although the evaluation of habitat quality may be a matter
of debate and may bias the results (there may be patches of
high quality in the low-quality habitat and vice versa and
environmental effects may be obscured and not detectable by
statistical methods), this study illustrates that environmental
pressure on P. major differs between mixed forests and
deciduous woodlands. This is in accordance with the results
obtained by Mänd et al. (2005) and Sanz (2001), suggesting
that great and blue tits prefer deciduous forests to coniferous
forests.
In this study, it was found that the relatedness of breeding
pairs and the expected genetic heterogeneity of their brood
(given the parental genotypes) had no significant effect on the
reproductive success of great tits in low-quality habitat. Thus,
the results do not support the hypothesis that individuals
select mating partners that signal suitable genotypes for high
genetic heterogeneity of broods. Nevertheless, it is believed
that inbreeding avoidance is the easiest and most efficient
mating strategy in order to optimize offspring fitness through
increasing their average genetic heterogeneity. Of course,
mating strategies may also increase heterozygosity, given that
females choose optimal mates. Yet, such a scenario is only
possible under strict assumptions, because advantageous
genetic-wide heterogeneity is difficult to maintain over generations.
Acknowledgements
We thank Jutta Calgéer, Kristin Calgéer and Jochen Blank for their
assistance in the field. This work was supported by a grant from the
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin
Maternal genetic heterogeneity and reproduction of Parus major
German Research Foundation No. DFG to 151/2-1. GS was supported by a grant from the Max Planck Institute for Ornithology, JT was
supported by a grant from the German Academic Exchange Service
DAAD 13/PPP-N1, and LB was supported by a grant from the
Research Council of Norway (ÔNational Centre for BiosystematicsÕ,
146515/420). We are grateful to T. Schenck and P. Galbusera for
providing technical assistance.
Zusammenfassung
Der Reproduktionserfolg von Kohlmeisenweibchen (Parus major L.,
1758) wird in Wäldern mit geringer Ressourcenqualität von ihrer
genetischen Heterogenität mitbestimmt
Individuelle Fitness und reproduktiver Erfolg werden oftmals in einem
engen Zusammenhang mit genetischer Heterogenität gesehen. In den
Jahren 1999 and 2000 untersuchten wir Kohlmeisenpopulationen
(Parus major L., 1758) in süddeutschen Laub- und Nadelmischwäldern. Beide Waldformen können sich bzgl. der Futterdiversität und
Futterverfügbarkeit stark unterscheiden. Die Alttiere von 99 Familien
wurden für vier Enzym- und acht Mikrosatellitenloci genotypisiert, um
die individuelle Heterozygotie abzuschätzen. Im Nadelmischwald fand
sich eine signifikante positive Korrelation zwischen der individuellen
Heterozygotie der Weibchen und Legedatum sowie Gelegegröße. Ein
frühes Legedatum und ein größeres Gelege haben einen positiven
Effekt auf die Anzahl von Jungtieren. Ein solcher Effekt konnte im
Laubwald allerdings nicht beobachtet werden. Weiterhin bestand kein
Zusammenhang zwischen maternaler genetischen Heterogenität und
der Masse der Jungtiere, ebenso hatte die väterliche genetische
Heterogenität in beiden Waldformen keinen signifikanten Einfluß auf
den Bruterfolg. Der positive Effekt mütterlicher genetischer Heterogenität auf die Zahl der Nachkommen von Kohlmeisen im Nadelmischwald steht in engem Zusammenhang mit dem Legedatum, d.h.
ein maternaler Effekt erklärt eher die beobachteten Zusammenhänge
als eine spezifische Paarungsstrategie, die sich entwickelte und zur
Fitnessoptimierung führte.
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AuthorsÕ addresses: Jürgen Tomiuk, Michael Stauss and Jost Kömpf,
Division of General Human Genetics, Department of Medical
Genetics, Institute of Human Genetics, University of Tübingen,
Wilhelmstrasse 27, D-72074 Tübingen, Germany. E-mail: juergen.
tomiuk@uni-tuebingen.de, jost.koempf@uni-tuebingen.de, m-stauss@
gmx.de; Gernot Segelbacher, Department of Wildlife Ecology and
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin
150
Management, University of Freiburg, Tennenbacher Strasse 4,
D-79085 Freiburg, Germany. E-mail: gernot.segelbacher@wildlife.
uni-freiburg.de; Joanna Fietz, Department of Experimental Ecology
(Biology 3), University of Ulm, Albert-Einstein-Allee 11, D-89069
Ulm, Germany. E-mail: joanna.fietz@t-online.de; Lutz Bachmann,
Department of Zoology, Natural History Museum, University of
Oslo, P.O. Box 1172 Blindern, N-0318 Oslo, Norway. E-mail: lutz.
bachmann@nhm.uio.no
Supplementary Material
The following supplementary material is available for this
article online:
Table S1. The mean values, standard deviations and the
sample sizes of the brood parameters are listed
Tomiuk, Stauss, Segelbacher, Fietz, Kömpf and Bachmann
Table S2. The pairwise correlation analyses between brood
parameters (egg-laying date, clutch size, hatching date, number
of hatchlings, number of fledglings, total brood mass and
mean body mass of fledglings are given
Table S3. Pearson’s correlation coefficients of female genetic
heterogeneity and three standardized brood parameters (egglaying date, clutch size and fledging success) of great tits in the
mixed-coniferous and deciduous forests are listed
This material is available as part of the online article from
http://www.blackwell-synergy.com
2006 The Authors J Zool Syst Evol Res (2007) 45(2), 144–150
Journal compilation 2006 Blackwell Verlag, Berlin