1 23

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

1 23

Your article is protected by copyright and all

rights are held exclusively by The Society

of Population Ecology and Springer. This e-

offprint is for personal use only and shall not

be self-archived in electronic repositories.

If you wish to self-archive your work, please

use the accepted author’s version for posting

to your own website or your institution’s

repository. You may further deposit the

accepted author’s version on a funder’s

repository at a funder’s request, provided it is

not made publicly available until 12 months

after publication.

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

Author's personal copy

(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

123

Author's personal copy

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

Popul Ecol (2011) 53:421–427 423

123

Author's personal copy

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

424 Popul Ecol (2011) 53:421–427

123

Author's personal copy

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

123

Author's personal copy

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

123

Author's personal copy

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).

References

Alber M, Jordan R, Ruttner F, Ruttner H (1955) Von der Paarung der

Honigbiene. Z Bienenforsch 3:1–28 (in German)

Baudry E, Solingac M, Garnery L, Gries M, Cornuet JM, Koeniger N

(1998) Relatedness among honeybees (Apis mellifera) of a drone

congregation. Proc R Soc B 265:2009–2014

Boomsma JJ, Ratnieks FLW (1996) Paternity in eusocial Hymenop-

tera. Philos Trans R Soc B Biol Sci 351:947–975

Cornuet JM, Aries F (1980) Number of sex alleles in a sample of

honeybee colonies. Apidologie 11:87–93

Crozier RH, Fjerdingstad EJ (2001) Polyandry in social Hymenop-

tera—disunity in diversity? Ann Zool Fenn 38:267–285

Crozier RH, Pamilo P (1996) Evolution of social insect colonies.

Oxford University Press, Oxford

El-Niweiri MAA, Moritz RFA (2010) The impact of apiculture on the

genetic structure of wild honeybee populations (Apis mellifera)

in Sudan. J Insect Conserv 14:115–124

Estoup A, Garnery L, Solignac M, Cornuet JM (1995) Microsatellite

variation in honeybee (Apis mellifera L.) populations: hierarchi-

cal genetic structure and test of the infinite allele and stepwise

mutation models. Genetics 140:679–695

Fletcher DJC (1978) The African bee, Apis mellifera adansonii, in

Africa. Annu Rev Entomol 23:151–171

Franck P, Garnery L, Solignac M, Cornuet JM (1998) The origin of

west European subspecies of honeybees (Apis mellifera): new

insights from microsatellite and mitochondrial data. Evolution

52:1119–1134

Franck P, Garnery L, Loiseau A, Oldroyd BP, Hepburn HR, Solignac M,

Cornuet JM (2001) Genetic diversity of the honeybee in Africa:

microsatellite and mitochondrial data. J Hered 86:420–430

Goudet J (1995) Fstat (version 1.2): a computer program to calculate

f-statistics. J Hered 86:485–486

Hepburn HR, Radloff SE (1998) Honeybees of Africa. Springer,

Berlin

Jaffe R, Dietemann V, Crewe RM, Moritz RFA (2009) Temporal

variation in the genetic structure of a drone congregation area: an

insight into the population dynamics of wild African honeybees

(Apis mellifera scutellata). Mol Ecol 18:1511–1522

Koeniger N, Koeniger G (1991) An evolutionary approach to mating

behaviour and drone copulatory organs in Apis. Apidologie

22:581–590

Kraus FB, Neumann P, Scharpenberg H, van Praagh J (2003) Male

fitness of honeybee colonies (Apis mellifera L.). J Evol Biol

16:914–920

Kraus FB, Neumann P, van Praagh J, Moritz RFA (2004) Sperm

limitation and the evolution of polyandry in the honeybee (Apismellifera L.). Behav Ecol Sociobiol 55:494–501

Kraus FB, Neumann P, Moritz RFA (2005) Genetic variance of

mating frequency in the honeybee (Apis mellifera L.). Insect Soc

52:1–5

Lensky Y, Demter M (1985) Mating flights of the queen honey bee

(Apis mellifera) in a subtropical climate. Comp Biochem Phys A

81:229–241

Moritz RFA, Kryger P, Koeniger G, Koeniger N, Estoup A, Tingek S

(1995) High degree of polyandry in Apis dorsata queens detected

by DNA microsatellite variability. Behav Ecol Sociobiol

37:357–363

Moritz RFA, Kryger P, Allsopp M (1996) Competition for royalty in

bees. Nature 384:522

Moritz RFA, Scharpenberg H, Lattorff HMG, Neumann P (2003) A

technical note for using microsatellite DNA analyses in haploid

male DNA pools of social Hymenoptera. Insect Soc 50:398–400

Moritz RFA, Kraus FB, Kryger P, Crewe RM (2007) The size of wild

honeybee populations (Apis mellifera) and its implications for

the conservation of honeybees. J Insect Conserv 11:391–397

Nei M (1987) Molecular evolutionary genetics. Columbia University

Press, New York

Neumann P, Moritz RFA (2000) Testing genetic variance hypotheses

for the evolution of polyandry in the honeybee (Apis melliferaL.). Insect Soc 47:271–279

Neumann P, Moritz RFA, van Praagh J (1999a) Queen mating

frequency in different types of honeybee mating apiaries. J Apic

Res 38:11–18

Neumann P, van Praagh J, Moritz RFA, Dustmann J (1999b) Testing

reliability of a potential island mating apiary using DNA

microsatellites. Apidologie 30:257–276

Pamilo P (1993) Polyandry and allele frequency differences between

the sexes in the ant Formica aquilonia. Heredity 70:472–480

Park SDE (2001) Trypanotolerance in West African cattle and the

population genetic effects of selection. PhD thesis, University of

Dublin, Ireland

Rashad SE, EL-Sarrag MSA (1978) Beekeeping in Sudan. Bee World

59:105–111

Raymond M, Rousset F (1995) An exact test for population

differentiation. Evolution 49:1280–1283

Rudloff W (1981) World climate. Wissenschaftliche Verlagsgesells-

chaft, Stuttgart

Ruttner F (1988) Biogeography and taxonomy of honeybees.

Springer, Berlin

Schluns H, Moritz RFA, Kryger P (2005) Multiple nuptial flights and

the evolution of extreme polyandry in honeybee queens (Apismellifera L.). Anim Behav 70:125–131

Solignac M, Vautrin D, Loiseau A, Mougel F, Baudry E, Estoup A,

Garnery L, Haberl M, Cornuet JM (2003) Five hundred and fifty

microsatellite markers for the study of the honeybee (Apismellifera). Mol Ecol Notes 3:307–311

van Chi-Bonnardel R (1973) The atlas of Africa. Editions Jeune

Afrique, Paris

Walsh PS, Metzger DA, Higuchi R (1991) Chelex 100 as medium for

simple extraction of DNA for PCR-based typing from forensic

material. Biotechniques 10:506–513

Walter H (1970) Vegetationszonen und Klima. Ulmer, Stuttgart

(in German)

Wessa P (2008) Partial correlation (v1.0.4) in free statistics software

(v1.1.23-r6). Office for Research Development and Education.

http://www.wessa.net/rwasp_partialcorrelation.wasp/

Wilson EO (1971) The insect societies. Harvard University Press,

Cambridge

Winston M (1987) The biology of the honeybee. Harvard University

Press, Cambridge

Popul Ecol (2011) 53:421–427 427

123

Author's personal copy