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Population Ecology ISSN 1438-3896Volume 53Number 3 Popul Ecol (2011) 53:421-427DOI 10.1007/s10144-011-0271-8
Mating in the rain? Climatic variance forpolyandry in the honeybee (Apis melliferajemenitica)
Mogbel A. A. El-Niweiri & RobinF. A. Moritz
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ORIGINAL ARTICLE
Mating in the rain? Climatic variance for polyandryin the honeybee (Apis mellifera jemenitica)
Mogbel A. A. El-Niweiri • Robin F. A. Moritz
Received: 25 July 2009 / Accepted: 27 April 2011 / Published online: 21 May 2011
� The Society of Population Ecology and Springer 2011
Abstract We tested the impact of colony density and
climatic conditions on the level of queen polyandry in
different wild populations of the honeybee (Apis mellifera
jemenitica). We identified the mating frequency of queens
by genotyping worker offspring (n = 672) of 28 wild
colonies with microsatellite DNA markers. The popula-
tions sampled in different climatic regions in Sudan
showed a high variance for the queen mating frequency
ranging from 9 to 23 estimated matings with an average
of 14.00 ± 3.94 (13.16 ± 4.87 effective matings). The
degree of polyandry was highly significantly correlated
with the rainfall in the various regions. In general, more
rainfall resulted in lower mating frequencies. Polyandry did
not correlate with colony density or with genetic diversity
of the local sample populations. This suggests that varia-
tion in polyandry in wild honeybee populations of Sudan is
primarily driven by climatic differences among ecosystem
variation rather than by the absolute or effective local
honeybee population size.
Keywords Colony density � Ecosystems �Microsatellite DNA � Queen mating
Introduction
A large suite of theoretical and empirical studies has
focused on the evolution of extreme polyandry of social
insect queens and on the underlying ultimate adaptive
mechanisms (reviewed in Crozier and Fjerdingstad 2001).
However, much less interest has been paid to the proximal
factors such as climate and habitat and their influence in
queen mating behaviour. The levels of polyandry have
been best studied in queens of the western honeybee (Apis
mellifera L.). The number of drone mates per queen can
vary dramatically, ranging from single mating under the
extreme conditions of the North Sea Islands (Neumann
et al. 1999a) to up to 45 males per queen in South African
populations (Neumann and Moritz 2000; Moritz et al.
1995, 1996). Since A. mellifera queens have not only a high
mean but also a high variance for the number of mates,
they provide an excellent test system to study proximate
factors affecting multiple matings. Virgin A. mellifera
queens start mating when they are about 1 week old
(Ruttner 1988). After a few orientation flights the queens
fly to a drone congregation area (DCA), where they mate
on the wing with many drones (Koeniger and Koeniger
1991). Depending on the flight conditions, they may
embark on several mating flights to eventually have an
average of more than ten matings (Schluns et al. 2005).
Successful mating flights very strongly depend on envi-
ronmental factors, such as wind speed and temperature
(Alber et al. 1955). Previous studies (Kraus et al. 2005)
seem to indicate that honeybees of temperate regions (e.g.,
A. m. carnica and A. m. ligustica) have lower levels of
polyandry than honeybees of tropical and subtropical
regions (A. m. capensis, A. m. scutellata). Particularly
conspicuous are the significant differences in the level of
polyandry between African and European populations
M. A. A. El-Niweiri (&) � R. F. A. Moritz
Institut fur Biologie, Molekulare Okologie,
Martin-Luther-Universitat Halle-Wittenberg,
Hoher Weg 4, 06099 Halle/Saale, Germany
e-mail: mogbel.el-niweiri@zoologie.uni-halle.de
R. F. A. Moritz
e-mail: r.moritz@zoologie.uni-halle.de
M. A. A. El-Niweiri
Apiculture Research Unit, National Centre for Research,
Mohammad Najeeb Street, 6096 Khartoum, Sudan
123
Popul Ecol (2011) 53:421–427
DOI 10.1007/s10144-011-0271-8
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(Kraus et al. 2004). Whereas queens of African honeybees
mate with up to 41.3 ± 15.6, these numbers are much
lower in Europe, where queens mate only with 23.4 ± 7.8
males. There may be various reasons for these differences
in mating behaviour between African and European
honeybees, including the following non-exclusive
mechanisms:
1. Mating frequencies are subspecies specific
Genetic variance has been shown to be important for
mating frequency (Kraus et al. 2005), and hence queens of
different subspecies might have genetically encoded dif-
ferent degrees of polyandry.
2. Mating frequency depends on population size
Queens in high-density populations may more readily
find mates than queens in low-density conditions. Drone
availability has been shown to be an essential factor for
successful mating, and a lack of drones can drastically
reduce the number of multiple queen matings (Neumann
et al. 1999b). Indeed population densities of European
honeybee populations are typically much lower than those
in Africa (Jaffe et al. 2009).
3. Mating frequency is affected by climatic factors
Weather conditions are extremely important for suc-
cessful mating (Lensky and Demter 1985; Neumann et al.
1999a). Hence, a climate with many sunny days and good
mating flight conditions might facilitate high mating fre-
quencies. Rainy or cloudy days and strong winds prevent
mating flights of both queens and drones (Alber et al. 1955;
Lensky and Demter 1985).
Clearly all three factors are highly confounded because
different subspecies are adapted to extremely different
climates and occur at very different densities (Jaffe et al.
2009). To extract the impact of climate factors and popu-
lation density on mating biology, it is necessary to test
populations within the same subspecies. Moreover, it is
important to measure both population density and climate
in the tested populations to differentiate between the
impacts of both factors on the mating frequency. Finally,
for obtaining meaningful data within the context of evo-
lutionary biology and adaptive behaviour, it is important to
test wild populations that are independent of apicultural
practice. In this study we used wild honeybees of Sudan as
a test case. They are distributed over a vast area covering
2.5 million km2 extending from about 3�N to 22�N and
from 22�E to 38�E. This area comprises most diverse
habitats, ranging from desert to tropical rainforest with
extremely different climatic conditions. Apiaries with
managed colonies are rare in Sudan, and the majority of the
honeybee population occurs in the wild (El-Niweiri and
Moritz 2010).
Materials and methods
Population densities in wild populations can be easily
assessed by genotyping the offspring of queens mated in the
wild and inferring the number of colonies that produced the
siring drones using DNA-microsatellite paternity test (Moritz
et al. 2003). This sampling procedure and analytical setting
allows for extracting the impacts of population density and
climatic factors on the mating biology of honeybee queens.
Sample collection
Twenty-eight wild colonies were detected in seven differ-
ent locations (4 colonies per km2 in each location) com-
prising in a wide variety of habitats (Fig. 1). From each
colony at least 24 worker bees (or pupae if available) were
sampled per colony and stored in ethanol until DNA pro-
cessing. Meteorological data were obtained from Sudan
Meteorological Authority.
PCR amplification
DNA was extracted from 24 workers per colony with routine
methods (Walsh et al. 1991) and genotyped with at five tightly
linked polymorphic microsatellite loci on chromosome 13
(HB5, HB7, HB10, HB15, SV240, Solignac et al. 2003) using
an automated DNA sequencer (Megabace 1000, Amersham).
The queen and siring drone genotypes were inferred from the
worker genotypes by Mendelian inference (Moritz et al. 2007).
Population structure and colony density
The numbers of drone producing colonies were inferred
from the genotypes of the siring males yielding an excep-
tionally robust estimate of the actual number of colonies in
the population. These numbers were corrected for the
sample size according to Cornuet and Aries (1980). Colony
densities were calculated based on the queens’ flight mat-
ing distance as in Moritz et al. (2007).
The genotype data of the inferred drones were analyzed
using the Excel Microsatellite Toolkit of Park (2001). The
expected heterozygosities HE (Nei 1987) were calculated
from the drone allele frequencies of the seven subpopula-
tions as a measure of genetic diversity. Deviations from
Hardy–Weinberg equilibrium were estimated with FSTAT
(Goudet 1995) version 2.9.3.2. Fisher’s exact test for genic
differentiation was performed using GENEPOP version 3.1
(Raymond and Rousset 1995).
Polyandry and colony structure
We used three parameters to calculate the mating fre-
quency: the number of observed matings, ko, underestimates
422 Popul Ecol (2011) 53:421–427
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the actual number of matings due to the finite sample size
(Cornuet and Aries 1980), the actual (estimated) number of
matings, ke, as given in Neumann and Moritz (2000), to
correct for differences in sample sizes. We calculated the
number of effective males, me (Pamilo 1993), which is
based on the intracolonial relatedness among workers. The
non-detection error (the probability to find two drones
randomly sharing an identical genotype at all loci) was
calculated based on the overall population allele frequen-
cies (Boomsma and Ratnieks 1996).
Results
The average expected heterozygosities HE across the five
tested loci estimated from the drone genotypes ranged from
0.64 ± 0.04 in Bahr el Jebel to 0.78 ± 0.15 in the Kassala
population. Fisher’s exact test across all populations
showed a significant genic differentiation at all tested loci
(P \ 0.0001, Table 1).
The tested queens showed a high level of polyandry
ranging from 9.00 to 23.00 with an average of
14.00 ± 3.94 estimated numbers of matings per queen with
low non-detection errors (\0.01, Table 2).
The independent comparison analyzing of the environ-
mental variables with the degree of polyandry showed that
the variance among locations was however considerable
and we found a significant correlation of the mating fre-
quency with annual rainfall (R2 = 0.25, P = 0.003,
Fig. 2b). However, no significant correlation was observed
between polyandry and annual mean temperature (R2 = 0.
004, P = 0.68, Fig. 3a).
Partial correlation analysis (Wessa 2008) was also used
to find out the correlation between the two variables mating
frequency and annual rainfall after removing the effects of
other variables (colony density and temperature). The
partial correlation (-0.50) found to be equivalent to the
original correlation (-0.49) in magnitude and sign when
controlling for colony density, suggesting that colony
density has no effect on the original correlation between
mating frequency of honeybees and annual rainfall in
Sudan (Table 3). Moreover when temperature is controlled
through partial correlation, the correlation of mating fre-
quency of honeybees with annual rainfall does not differ-
entiate from the partial correlation. This indicated that even
controlling for temperature and colony density, the control
variables have no effect and there is still significant cor-
relation of mating frequency with rainfall (Tables 3, 4).
Kassala
Khartoum
Gezira
White Nile
Blue Nile
Kordofan
Bahr el Jebel
Semi desert
Dry savannah
Wet savannah & forest
300 (km)
N
0
Fig. 1 Map of Sudan (Map
Library) showing the sampling
sites of seven different locations
where four wild colonies each
were spotted and sampled. The
sample locations cover a wide
variety of habitats ranging from
wet tropical forest in the south
to desert in the north
Table 1 Estimates of the base population genetic parameters:
expected heterozygosity (HE) and colony density (as estimated from
the genotypes of the siring drones), in the test set of 5 loci at the
sample locations
Location Colony density (colonies/km2) HE
Kassala 11.80 0.77
Khartoum 12.20 0.79
Gezira 10.00 0.79
White Nile 9.40 0.72
Blue Nile 16.10 0.81
Kordofan 17.20 0.71
Bahr el Jebel 16.00 0.70
13.24 0.76
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Similarly, the wild colony density (estimated after
excluding managed colony) was highly variable at the seven
sample locations ranging from 9.40 colonies/km2 at the
White Nile to 17.20 colonies/km2 in Kordofan (Table 1).
There was neither a significant correlation between poly-
andry and colony density (R2 = 0.013, P = 0.65, Fig. 3b)
nor between annual mean temperature and colony density
(R2 = 0.005, P \ 0.79, Fig. 4a). However, we did find a
significant correlation between colony density and rainfall
(R2 = 0.45, P \ 0.001, Fig. 4b).
Discussion
The high gene diversities of the honeybee populations in
Sudan are well in line with other African populations
(Estoup et al. 1995; Franck et al. 1998, 2001). They are
probably a direct result of the extreme migratory behaviour
which is a typical characteristic of many African honeybee
subspecies (Fletcher 1978; Hepburn and Radloff 1998)
including A. m. jemenitica (Rashad and EL-Sarrag 1978).
Jaffe et al. (2009) showed that migratory behaviour of
Table 2 Estimates of the
observed and estimated level of
polyandry calculated from
different four colonies in each
location
Location Colony number ko observed matings ke estimated matings
Kassala 1 13.00 17.00
2 12.00 15.00
3 14.00 20.00
4 15.00 23.00
Mean ± SD 13.50 ± 1.29 18.75 ± 3.50
Khartoum 1 14.00 20.00
2 13.00 17.00
3 10.00 12.00
4 13.00 17.00
Mean ± SD 12.50 ± 1.13 16.50 ± 2.25
Gezira 1 11.00 13.00
2 11.00 13.00
3 15.00 23.00
4 11.00 13.00
Mean ± SD 12.00 ± 2.00 15.50 ± 4.50
White Nile 1 12.00 15.00
2 9.00 10.00
3 10.00 12.00
4 12.00 15.00
Mean ± SD 10.75 ± 1.50 13.00 ± 2.45
Blue Nile 1 9.00 10.00
2 8.00 9.00
3 10.00 12.00
4 11.00 13.00
Mean ± SD 9.50 ± 1.29 11.00 ± 1.82
Kordofan 1 12.00 15.00
2 8.00 9.00
3 11.00 13.00
4 8.00 9.00
Mean ± SD 9.75 ± 2.06 11.50 ± 3.00
Bahr el Jebel 1 11.00 13.00
2 8.00 9.00
3 11.00 13.00
4 10.00 12.00
Mean ± SD 10.00 ± 1.41 11.75 ± 1.89
Total 28
Mean 11.14 14.00
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African honeybees resulted in almost complete yearly
turnovers of entire wild A. m. scutellata populations in the
South African Highveld.
The tested queens had mated at the average with
14.00 ± 3.94 males revealing a considerable variance for
the degree of polyandry. The mating number was highly
significantly correlated with rainfall but neither with pop-
ulation density, nor with temperature. The desert regions
in the north cover about one-third of entire country,
with only very irregular rain fall (0–50 mm per year).
The semi-desert region is slightly richer in vegetation due
to 50–300 mm rainfall per year, followed by the dry
savannah region with an annual rainfall of 300–500 mm
per year and a dry season between 4 and 6 months. Further
in the south of Sudan is a wet savannah region with annual
rainfalls between 500 and 1000 mm. Finally, the most
southern vegetation belts are dense forests with annual
rainfalls of 1000–1600 mm resulting in thick vegetation
(Walter 1970; van Chi-Bonnardel 1973; Rudloff 1981).
Given the rich forage potential for honeybees in the wet
regions and the potential significance of nutritional
resources for honeybee fitness it seems not surprising that
wet regions provide favourable climate for the bees in
general. Indeed, colony density was positively correlated
with mean rainfall suggesting that conditions for honeybee
colonies are much better in the south then in the north of
Sudan. Since the production of drones is costly requiring
plenty of forage both pollen and nectar (Winston 1987) this
gradient in colony density seems highly plausible. Rich
forage is not necessarily expected to be abundant in desert
regions. Our results are therefore in agreement with Jaffe
et al. (2009) who showed that higher densities are typically
found in the subtropical rather than in the dry savannahs
and deserts of Africa.
A high local colony density has been shown to enhance
the numbers of drones in a congregation area and low
0
5
10
15
20
25
0 500 1000 1500
Pol
yand
ry (
k e)
Annual mean rainfall (mm)
0
5
10
15
20
25
0 5 10 15
Pol
yand
ry (
k e)
Rainfall per day
(a)
(b)
Fig. 2 The factors that showed significant correlation with estimated
number of polyandry. Estimated polyandry (y-axis), rain fall per day
(a) and annual rainfall (b)
(a)
(b)
Pol
yand
ry (
k e)
Annual mean temperature (C°)
0
5
10
15
20
25
0 5 10 15
Pol
yand
ry (
k e)
Poulation density (col/km2)
0
5
10
15
20
25
25 30 35 40
30
20
30
Fig. 3 Annual mean temperature (a) and population density (colo-
nies/km2) (b) showed no significant correlation with the estimated
polyandry (y-axis)
Table 3 The partial correlation of mating frequency of honeybees
and annual rainfall when controlling for colony density
Pearson product moment partial correlation—ungrouped data
Statistic Value
Correlation R (xy) -0.50
Partial correlation R (xy.z) -0.49
Correlation R (xz) -0.11
Partial correlation R (xz.y) -0.01
Correlation R (yz) 0.22
Partial correlation R (yz.x) 0.58
x = mating frequency, y = rainfall, z = colony density
Table 4 The partial correlation of mating frequency of honeybees
and annual rainfall when controlling for temperature
Pearson product moment partial correlation—ungrouped data
Statistic Value
Correlation R (xy) -0.50
Partial correlation R (xy.z) -0.51
Correlation R (xz) -0.05
Partial correlation R (xz.y) 0.19
Correlation R (yz) 0.23
Partial correlation R (yz.x) 0.29
x = mating frequency, y = rainfall, z = temperature
Popul Ecol (2011) 53:421–427 425
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colony density caused very low mating frequencies
(Neumann et al. 1999b). Moreover, polyandry may be
associated with the number of drones in the congregation
area (Baudry et al. 1998). However, in our study we found
no significant correlation between colony density and
polyandry. Kraus et al. (2003) showed that not only the
colony density but also the quality of a drone producing
colony is important for the male mating success, but then
again we would expect the better foraging conditions in the
wetter regions of the country. Hence other factors than
colony density, colony vitality or local drone availability
must have driven the correlation between rainfall and
polyandry. Since virgin A. mellifera queens mate on the
wing, mating is highly dependant on local weather condi-
tions. Honeybee queens only fly out on sunny, warm days
to a ‘‘drone congregation area’’ to mate with many drones
(Ruttner 1988). If the weather holds, she may return to the
DCA for several days until she is fully mated (Schluns
et al. 2005). Whenever the weather is unsuitable due to
rainfall, cold or wind there will be no mating flights, nei-
ther of queens nor of drones (Lensky and Demter 1985).
Poor weather will inevitably reduce the number of mating
flights opportunities and hence not enhance the number of
successful matings. From this perspective, it may not be so
surprising to see the degree of polyandry to be negatively
correlated with average daily rainfall in our study. Optimal
mating flight conditions are more often found in the much
more sunny and hot climate of central and northern Sudan.
It may thus well be that local climatic mating flight con-
ditions are more important for determining the degree of
polyandry rather than overall regional ecosystem qualities
for colony vitality. If we were highly speculative evolu-
tionary biologists we would perhaps argue that the
increased mating frequency in the poorer (=dryer) habitats
reflects an adaptive increase in intracolonial genetic vari-
ance. Indeed intracolonial genetic variance has repeatedly
been invoked to explain the evolution of multiple mating in
honeybees (Wilson 1971; Crozier and Pamilo 1996).
Regrettably, we feel that this conclusion would stretch our
empirical data and see the more proximate explanation of
less rainy days which facilitate multiple matings as more
parsimonious at this stage. There won’t be many queens
Pop
ulat
ion
dens
ity (
col/k
m2 )
Mean temperature (C°)
0
2
25 28 34 403731
(a)
(b)
Pop
ulat
ion
dens
ity (
col/k
m2 )
0
8
10
14
16
18
0 200 400 1000
Mean rainfall (mm)
4
6
20
12
14
1400
20
16
18
10
8
600 800 1200
6
4
2
12
Fig. 4 The correlation between
colony density and weather
(temperature and rain).
Population density (colonies/
km2) is not correlated with
annual mean temperature (a) but
positively correlated with rain
fall (b)
426 Popul Ecol (2011) 53:421–427
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and drones that will make it to the DCA to mate in the rain
(Alber et al. 1955).
Acknowledgments Financial support was granted to MAAEN by
the National Centre for Research, Khartoum, Sudan and German
Academic Exchange Service (DAAD) fellowship and the Europe
Strategic Research Project BEE SHOP (RFAM).
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