Biological Journal of the Linnean Society, 2002, 75, 437–452. With 4 figures
Genetic differentiation between Australian and North
American populations of the monarch butterfly Danaus
plexippus (L.) (Lepidoptera: Nymphalidae): an
exploration using allozyme electrophoresis
JILL M. SHEPHARD1*, JANE M. HUGHES1 and MYRON P. ZALUCKI2
1
Genetics Laboratory, Australian School of Environmental Studies, Griffith University-Nathan
Campus, Kessels Road, Brisbane, Queensland, Australia, 4111
2
Department of Zoology and Entomology, The University of Queensland, Brisbane, Australia, 4072
Received 7 June 2001; accepted for publication 29 November 2001
Allozyme analysis was used to address the question of the source of the Australian populations of the monarch butterfly Danaus plexippus (L.). The study had three major aims: (1) To compare the levels of diversity of Australian
and Hawaiian populations with potential source populations. (2) To determine whether eastern and western North
American populations were sufficiently divergent for the Australian populations to be aligned to a source population. (3) To compare the differentiation among regions in Australia and North America to test the prediction of
greater genetic structure in Australia, as a consequence of reduced migratory behaviour. The reverse was found,
with FST values an order of magnitude lower in Australia than in North America. Predictably, Australian and
Hawaiian populations had lower allelic diversity, but unexpected higher heterozygosity values than North
American populations. It was not possible to assign the Australian populations to a definitive source, although
the high levels of similarity of Australian populations to each other suggest a single colonization event. The possibility that the Australian populations have not been here long enough to reach equilibrium is discussed. © 2002
The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452.
ADDITIONAL KEYWORDS: allozyme – bottleneck – colonization – F-statistics – genetic structure – migration.
INTRODUCTION
The study of genetic variation and colonization events
has an important place in understanding the processes
of speciation (Slatkin, 1987; Coyne, 1992; Palumbi,
1992; Green et al., 1996), genetic differentiation among
subdivided populations (Ross, 1983; Baker & Moeed,
1987; Whitlock & McCauley, 1990; Gleeson, 1995), and
aspects of conservation biology (Briscoe et al., 1992;
Willis & Wiese, 1993; Stockwell et al., 1996).
Studies addressing the role of founder effects on
population structure have mostly been on species in
which the origin, number of founders and initial
founding location are known. Typically these involve
species deliberately introduced, or translocations for
*Corresponding author.
E-mail: [email protected]
some anthropogenic, conservation or biological control
purpose (Easteal, 1982; Parkin & Cole, 1985; St Louis
& Barlow, 1988), where knowledge of the source
population, founding site and number of founders
makes it possible to test the validity of bottleneck
models (Easteal, 1982, 1988).
A bottleneck and founder effect (Mayr, 1942) occurs
when a large randomly mating population is reduced
to a small number of individuals for at least one generation (Allendorf, 1986), as often occurs in colonization. Whilst the initial effect of a founder event is a
reduction in population size, the degree to which the
underlying genetic structure may be affected depends upon the number of founder individuals which
contribute directly to the next generation; that is,
the effective population size (Ne) of the founding
population (Chakraborty & Nei, 1977; Hodson, 1992;
Stockwell et al., 1996).
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
437
438
J. M. SHEPHARD ET AL.
A small Ne determines directly the loss of genetic
diversity in the new founding population, such that
the existence of a bottleneck, and its relative severity,
may be estimated by comparing the average heterozygosities of the source and founder populations
(e.g. St Louis & Barlow, 1988). A reduction in heterozygosity of the founding population is considered
indicative of a bottleneck (Chakraborty & Nei, 1977).
However, heterozygosity is influenced by both bottleneck size and duration, with bottlenecks of short duration having little effect on heterozygosity (Stockwell
et al., 1996). Serial colonization events, as occur with
a progressive range expansion, should show progressive loss of genetic diversity isolation-by-distance from
the source (Green et al., 1996), with increasing population structure depending upon the degree of gene
flow experienced between local populations (Slatkin,
1994). High rates of gene flow among populations
subject to random mating results in decreased levels
of genetic structuring, whereas physical distance or
obstructions to movement are likely to lead to genetic
differentiation and structuring (Eanes & Koehn, 1978;
Thorpe & Solé-Cava, 1994).
The monarch butterfly’s range has greatly expanded
from North America and now encompasses numerous
Pacific Islands and Australia. A number of hypotheses
have been developed to explain this range expansion
(see, for example, Scudder & Gulick, 1875; Walker,
1914; Vane-Wright, 1993).
Here we address the degree of genetic differentiation in the monarch butterfly across its range. We
wish to infer from allelic variation the likely colonization history of monarchs. We make comparisons between the eastern and western populations in North
America, Hawaii and a number of sample regions
within Australia. Additionally we survey the degree of
genetic structuring within Australia on a larger scale
than has been addressed previously (e.g. Hughes &
Zalucki, 1984; Zalucki et al., 1987). Given the apparent reduction in migratory behaviour of Australian
populations (James, 1993), levels of genetic differentiation among major population centres is expected
to be greater than among eastern North American
populations.
COMPARATIVE ECOLOGY OF THE AMERICAN AND
AUSTRALIAN POPULATIONS
The supposed absence of a long-range large-scale
cyclic migration in the Australian monarch draws the
primary distinction between the Australian and
American populations (James, 1993; Kitching &
Scheermeyer, 1993). Details of the monarch migrations in North America have been comprehensively
reviewed by Brower (1995, 1996). Two major population centres exist in North America, one on the pacific
coast, usually referred to as the western population,
the other in the eastern-central states, the gulf coast
and Mexico (Eanes & Koehn, 1978), often referred to
as the eastern population (Fig. 1). Both populations
are known for their large overwintering aggregations.
The eastern population over-winters in very large
aggregations at a limited number of sites in Mexico
(Calvert & Brower, 1986). The western population
over-winters at over 40 known coastal sites ranging in
size from a few thousand to a few million individuals
(Lane, 1993). The two populations are subdivided by
the Rocky Mountains and are thought to be geographically isolated (Brower & Boyce, 1991; Brower,
1996).
Since the early 1870s, D. plexippus has colonized
most parts of eastern Australia, the Adelaide area and
a small portion of Western Australia (Zalucki, 1986;
James, 1993). There is a temperature-induced behavioural distinction among the Australian populations
in that the majority of Queensland populations breed
continuously throughout the year, whilst a range
contraction occurs from southern Queensland and
northern New South Wales with the onset of autumn,
leading to the development of three eastern population centres: the southern Queensland/Northern
New South Wales coastal strip extending up in to the
tropics, the Sydney Basin/Hunter Valley region, and
the Adelaide area (James, 1979; James, 1993; Zalucki
& Rochester, 1999).
James (1993) found long-distance autumn migrations in the New South Wales region of up to 380 km.
However, there is little evidence for a regular longdistance movement of the monarch comparable with
the North American phenomenon (James, 1993;
Kitching & Scheermeyer, 1993; Dingle et al., 1999).
A number of patterns could be expected for the
genetic structure of D. plexippus within Australia,
and between Australia, North America and the
Pacific Islands (e.g. Hawaii). If the colonization of
D. plexippus across the Pacific is due to a rapid
range expansion in stepping-stone fashion, then
an isolation-by-distance effect would be expected,
with Hawaiian and Australian populations showing a marked and progressive decrease in allelic
diversity and some loss of heterozygosity relative to
North America. Similarly over a longer period, island
hopping, involving sequential colonization and local
population growth, may increase the chance of founder
sizes being relatively large, therefore improving the
potential for repeated or multiple colonization events
with little loss of allelic diversity, and a consequent
reduction in differentiation between sample locations.
Alternatively, depending on the number of founder
individuals, there may be strong evidence to suggest
a severe bottleneck in either the Hawaiian or
Australian populations. Such bottlenecking would be
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
GENETIC VARIATION IN THE MONARCH BUTTERFLY
439
Figure 1. Map of sampling sites for Danaus plexippus from Australia, Hawaii and North America, including summer and
winter ranges. In each case ranges extend to the coast (Based on records from Zalucki, 1986.). The sites are as follows: 1.
Kalamazoo, 2. San Luis Obispo, 3. Santa Barbara, 4. San Diego, 5. Michoacan, 6. Hawaii, 7. Bracewell, 8. Marsh Road, 9.
Kroombit, 10. Boondall, 11. Beenleigh, 12. Mt Crosby, 13. Monkerai, 14. Watagan, 15. St Albans.
indicated by a significant reduction in heterozygosity,
loss of rare alleles and a high level of differentiation
between populations.
It has been suggested that the Australian monarch
is derived from the eastern North American population (Kitching et al., 1993). It seems reasonable to
assume this was the case for the Hawaiian population
also. If so, then Australian and Hawaiian butterflies
will display allelic patterns derivative of the eastern
North American populations. Alternatively, founder
individuals may have originated from the western
North American population. Detection of this will
be dependent upon whether the eastern and western
populations display distinct allelic ‘signatures’.
MATERIAL AND METHODS
STUDY
SITES AND SAMPLE COLLECTION
Butterflies (N = 1194) were collected at a total of
15 sites from Australia, North America and Hawaii.
In Australia, sites were chosen from three regional
centres within the monarch’s eastern range (Table 1).
These centres were approximately equidistant and
separated geographically by an average of 450 km
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
440
J. M. SHEPHARD ET AL.
Table 1. Site and regional groupings used for data analysis, including sampling locations and details for collection date,
sample size (N), sex ratio and population status at each site
Region
Site
Location
Beenleigh
Boondall
153°12¢-E; 27°43¢-S
153°04¢-E; 27°21¢-S
Mt Crosby
Sydney
Rockhampton
Collection
date
N
% female
Site type
100
100
50
36
Continuously breeding
Continuously breeding
152°48¢-E; 27°32¢-S
18.01.96
19.01.96 &
25.02.96
07.03.96
100
21
Continuously breeding
Watagan
St Albans
Monkerai
151°11¢-E; 33°02¢-S
150°59¢-E; 33°15¢-S
151°52¢-E; 32°16¢-S
23.04.96
24.04.96
26.04.96
55
100
100
4
36
40
Potential transient roost
Continuously breeding
Continuously breeding
Kroombit
Marsh Road
Bracewell
151°00¢-E; 24°10¢-S
151°10¢-E; 24°10¢-S
150°55¢-E; 23°52¢-S
17.02.96
02.10.96
03.10.96
100
100
100
30
23
33
Continuously breeding
Continuously breeding
Continuously breeding
North America
Mexico
Michoacan
101°38¢-E; 19°30¢-N
–.03.96
100
51
Overwintering
Kalamazoo
Kalamazoo
85°36¢-E; 42°17¢-N
01.08.96
52
52
Summer
California
San Diego
Santa Barbara
San Luis
Obispo
117°10¢-E; 32°45¢-N
34°25¢-N; 119°53¢-W
35°25¢-N; 120°51¢-W
32°57¢-N; 117°15¢-W
–.08.96
18.02.98
25.11.97
50
55
55
52
33
55
Overwintering
Overwintering
Overwintering
Hawaii 1
Hawaii 2
21°18¢-N; 157°49¢-W
21°18¢-N; 157°49¢-W
1997
1999
27
21
41
71
Continuously breeding
Continuously breeding
Australia
Brisbane
Hawaii
Hawaii
(Fig. 1). Three subsamples, each from a patch of the
foodplant (Asclepias spp.), were obtained within each
region. Every effort was taken to sample patches
hosting reproductively active populations, and the
majority contained adults, larvae and eggs (Table 1).
Similarly, samples were obtained from three regional centres in North America, and from Honolulu
and nearby settlements in the Hawaiian Island group
(Table 1). Within North America, two sites are ‘representative’ of the eastern monarch population at
different stages of the species’ seasonal phenology:
a sample from the summer breeding range at
Kalamazoo, and a sample from the Sierra Chichua
(Michoacan) overwintering site in Mexico. It was
only possible to replicate sites within California, with
samples taken from overwintering aggregations at
San Diego County, Morro Bay in San Luis Obispo
County and Ellwood Park in Santa Barbara County
(Table 1).
Within Australia, sampling times and conditions
were standardized to control for any genotype frequency bias that may be associated with different
activity times and weather conditions (see Zalucki
et al., 1987; Carter et al., 1989). Individuals were kept
alive on ice in the field, and then either transferred
straight to a -80 °C freezer, or snap frozen in liquid
nitrogen, and then kept in a -80 °C freezer until
required for electrophoresis.
With the exception of one sample from California,
North American and Hawaiian samples were transported live as adults to Australia where they were
immediately frozen at -80 °C and stored prior to electrophoresis. Samples from San Diego County were
received as pupae and were bred through in the
laboratory; newly-emerged individuals were frozen at
-80 °C until required.
ELECTROPHORETIC ANALYSIS
Each site was screened for 19 enzymes of which 13 displayed variation. Five of these were difficult to interpret and were not used. Similarly, aconitate hydratase
(ACON) was dropped from all sites as numerous deviations from Hardy–Weinberg proportions suggested
either misreading of plates or some form of selection
affecting the locus
The remaining seven enzymes were considered
polymorphic, based on the criterion of the most
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
GENETIC VARIATION IN THE MONARCH BUTTERFLY
441
Table 2. Enzyme systems and Electrophoretic Running Systems
Enzyme and EC No.
Locus scored*
No. alleles
Quaternary
structure
Buffer†
Tissue
Migration
b-hydroxybutyric acid 1.1.1.30
Mannose phosphate isomerase 5.3.1.8
Peptidase D 3.4.11 or 13
Glucose phosphate isomerase 5.3.1.9
Phosphoglucomutase 2.7.5.1
Aspartate amino transferase 2.6.1.1
Isocitric dehydrogenase 1.1.1.42
Hbdh-1
Mpi-1
PepD-2
Pgi-1
Pgm-2
Aat-1
Idh-1
8
3
6
7
5
4
5
Dimeric
Monomeric
Dimeric
Dimeric
Monomeric
Dimeric
Dimeric
TG 8.5
TC 7.0
TC 7.0
TG 8.5
TG 8.5
TC 7.0
TC 7.0
Abdomen tip
Head
Head
Head
Head
Head
Head
Cathodal
Anodal
Anodal
Anodal
Anodal
Anodal
Anodal
* Loci allocated position in relation to the anodal margin of the plate. Accordingly locus closest to this margin was given
the designation ‘1’.
†
Buffer recipes are as follows: Tris Citrate pH 7.0, 75 mM – 90.8 g Trizma base, 50.6 g citric acid to 10 L of DDH2O;
Tris Glycine pH 8.5, 50 mM – 30 g Trizma base, 128.8 g Glycine to 10 L of DDH2O.
common allele occurring at a frequency of less than
0.99, and were retained. Mannose phosphate isomerase (MPI) was later dropped from the North
American and Hawaiian analyses due to scoring
difficulties. Aspartate aminotransferase (AAT) was
monomorphic across all Australian sites and Hawaii,
but was retained as it was polymorphic in the North
American samples.
Electrophoresis was performed using cellulose
acetate plates (Titan III, Helena Laboratories, TX)
with methods adapted from Hebert and Beaton (1993;
see Table 2). A single reference sample was included
on each plate for scoring purposes and the American,
Hawaiian and Australian samples were calibrated
using check gels to ensure consistency of scoring.
STATISTICAL ANALYSIS
Data were analysed using BIOSYS-1 (Swofford &
Selander, 1989; Release 1.7). Allele frequencies and
single locus heterozygosity estimates were calculated
for each population. All populations were tested for
conformance to Hardy–Weinberg expectations using
Levene’s (1949) correction for small sample size. The
Australian and American samples were analysed at
two levels: site and region (Table 1). Regional data contained the cumulative information of sites for that
region. Mexico and Kalamazoo were considered at the
site level for the purposes of analysis within North
America only. Further analyses were made only at the
regional level. The small number of individuals from
Hawaii negated any form of internal analysis, and the
sample was considered at the regional level only.
Accordingly, comparative analyses between Australia,
America and Hawaii are discussed at the regional
level.
At all levels of analysis, Wright’s (1951) F-statistics
were used to calculate population genetic structure fol-
lowing the method of Weir & Cockerham (1984). This
method is thought to perform best with moderate-tolarge levels of gene flow, and equal and reasonably
large sample sizes (Slatkin & Barton, 1989; Roderick,
1996). Slatkin & Barton (1989) caution that with high
levels of gene flow this method may overestimate the
effective number of migrants per generation (Nem) in
that it conservatively estimates FST.
Levels of gene flow were estimated using the equation Nem ª 0.25 (1/FST – 1). This has been shown to be
appropriate when applied to either the infinite island
model, in which gene flow amongst near and far
populations occurs with equal probability, or the
stepping-stone model, in which gene flow only occurs
between adjacent populations (Slatkin & Barton,
1989; Peterson, 1996). Gene flow estimates were
calculated at site and regional levels.
FIS values were calculated by BIOSYS-1. FST values
were tested using the formula of Waples (1987). Mean
values of FST and standard errors were calculated using
a jackknife procedure (Weir & Cockerham, 1984).
Additionally, Australian samples were analysed
hierarchically (see Table 1), such that FST values
were calculated to measure the degree of population
subdivision within regions, and the degree of division
among regions for each locus. These were labelled FSR
and FRT, respectively. This procedure was not possible
with the American samples due to the unbalanced
sample design.
Pairwise FST tests and UPGMA cluster analysis
(Nei’s 1978) were performed to estimate the degree
of differentiation between regions. Cluster analysis
was performed at the site level within the Australian
analysis. UPGMA cluster analysis was compared
with Neighbour-Joining Trees generated using MEGA
(Kumar et al., 1993). No appreciable differences
were found and only results of the UPGMA analysis
are presented.
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
442
J. M. SHEPHARD ET AL.
RESULTS
GENETIC
VARIABILITY AT EACH SITE
Mean sample size per locus ranged from 27 to 100 for
the populations examined (Table 3), with 38 alleles
found across all sites (see Appendix). Of the six loci
analysed for all sites, North America had 35 alleles
and Hawaii and Australia 18 each. Mpi was not scored
for the North American and Hawaiian sites, an additional three alleles were recorded at the Mpi locus in
Australia making its allele total 21.
San Luis Obispo and Santa Barbara had the greatest mean number of alleles per locus; more than all
other sites except Mexico and Kalamazoo (Table 3).
San Diego was the only North American site to display
a similar number of alleles to either Australia or
Hawaii. Overall, the North American sites showed a
significantly greater number of alleles per locus than
the Australian and Hawaiian populations (t = 5.829,
P = 0.0001).
A single allele at Pgi and two alleles at Idh were
found in Australia but not found in Hawaii (Figs 2 and
3). In all instances these alleles occurred across the
North American sites. With the exception of the ‘G’
allele at the Hbdh locus, alleles absent from Australia
had a frequency of less than 7.5% in North America.
Similarly, alleles at Pgi and Hbdh found in Hawaii
were absent from the Australian sample. These alleles
were all found in at least two sites in North America.
Aat was fixed in the Hawaiian and Australian sites but
showed a small degree of variability in four of the five
North American samples. Allele frequencies at all sites
are given in the Appendix.
The presence of alleles in Australia not found
in Hawaii may have been the result of the small
Hawaiian sample size. However, with the exception of
a single allele, subsequent electrophoresis of a further
21 Hawaiian butterflies (see Appendix) replicated the
existing allele frequencies. This allele, corresponding
to allele ‘F’ at the PepD locus, had a relatively low
frequency (0.08), suggesting the absence of the remaining alleles in Hawaii was not solely the result
of sample size.
Mean heterozygosity ranged from 0.353 (± 0.083)
in Mexico to 0.427 (± 0.092) at Bracewell in the
Rockhampton region (Table 3). Mean heterozygosity
levels were consistently larger among the Australian
populations, and in Hawaii, than in North America
(t = 4.467, P = 0.0006). With the exception of San
Diego, the North American samples were characterized by a high proportion of low frequency alleles. This
uneven spread of alleles may be responsible for the
perceived reduction in genetic diversity and heterozygosity (Allendorf, 1986; Vrijenhoek, 1989). In contrast,
the Australian and Hawaiian sites have a lower
number of allelic variants at fairly even frequencies
contributing to comparable and unexpectedly high
heterozygosity values.
DEVIATIONS
FROM
HARDY–WEINBERG
EQUILIBRIUM
Among the Australian sites, Hbdh was the only
locus for which there were no significant deviations
from Hardy–Weinberg equilibrium (Table 4). Of a total
of ten significant FIS values, 80% indicated varying
Table 3. Genetic variability in all populations (values in parentheses are standard errors)*
Population
Mean sample size per locus
Mean no. alleles per locus
Mean heterozygosity†
Beenleigh
Boondall
Mt Crosby
Watagan
St Albans
Monkerai
Kroombit
Marsh Road
Bracewell
Michoacan
Kalamazoo
San Diego
Santa Barbara
San Luis Obispo
Hawaii
99.1
99.4
100.0
54.4
99.9
99.1
99.9
99.0
99.4
98.5
51.8
49.2
54.8
51.5
27.0
2.9
3.0
2.7
2.6
2.9
2.9
2.9
2.6
2.6
4.7
4.0
3.0
4.8
4.8
3.0
0.421
0.404
0.398
0.388
0.387
0.397
0.402
0.401
0.427
0.353
0.388
0.372
0.358
0.380
0.406
(0.5)
(0.4)
(0.0)
(0.2)
(0.1)
(0.6)
(0.1)
(0.4)
(0.4)
(1.1)
(0.2)
(0.7)
(0.2)
(3.3)
(0.0)
(0.4)
(0.5)
(0.4)
(0.3)
(0.4)
(0.5)
(0.5)
(0.3)
(0.3)
(0.6)
(0.6)
(0.7)
(0.4)
(0.7)
(0.5)
(0.085)
(0.086)
(0.083)
(0.085)
(0.083)
(0.084)
(0.084)
(0.085)
(0.092)
(0.083)
(0.097)
(0.094)
(0.082)
(0.090)
(0.114)
* Australian populations are calculated using 7 loci, American populations are calculated using 6 loci.
†
Hardy–Weinberg expected.
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
GENETIC VARIATION IN THE MONARCH BUTTERFLY
443
N
N
N
N
N
N
N
Figure 2. Allele frequencies and sample sizes at the Pgi-1 locus from regions within Australia, Hawaii and North America.
Low frequency alleles are identified using leader lines. The exact frequencies for these are given in Appendix 1. The regions
are labelled as follows: CAL = California, MEX = Mexico, KAL = Kalamazoo, HAW = Hawaii, ROC = Rockhampton, BRIS
= Brisbane, SYD = Sydney.
degrees of heterozygote deficiency; a result far
greater than that expected by chance alone (Zar,
1984). For Hawaii there were no deviations from
Hardy–Weinberg expectations (Table 4). In the North
American sites, only one sample showed a significant
deviation from Hardy–Weinberg expectation, a result
that could have been expected through chance (Zar,
1984).
THE
PRESENCE OF GENETIC STRUCTURING
WITHIN
AUSTRALIA
Hierarchical F-statistics indicated little genetic structure either between or within regions. Mpi was the
only locus to display any significant within-region differentiation (P < 0.001) (Table 5). This structure was
lost when comparing between regions (Table 5).
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
444
J. M. SHEPHARD ET AL.
N
N
N
N
N
N
N
Figure 3. Allele frequencies and sample sizes at the Idh-1 locus from regions within Australia, Hawaii and North America.
Low frequency alleles are identified using leader lines. The exact frequencies for these are given in Appendix 1. The regions
are labelled as follows: CAL = California, MEX = Mexico, KAL = Kalamazoo, HAW = Hawaii, ROC = Rockhampton, BRIS
= Brisbane, SYD = Sydney.
Similarly, Mpi was the only locus to display a significant FST value. FST values at each locus, and jackknifed
estimates of overall differentiation, suggested very
little genetic structure (Mean FST = 0.004 ± 0.0019).
At each locus the most common allele was consistent among sites, with alternate alleles occurring
at similar frequencies across all sites. Pep D was an
exception to this, being the only locus to display a
rare allele not shared across all sites. Aat was fixed at
all Australian sites (see Appendix). Removal of Mpi
from the analysis had very little effect on overall
genetic structure, producing an FST value of 0.0043
(± 0.002).
Cluster analysis using Nei’s (1978) unbiased genetic
distance produced a shallow tree with a relatively
random association of sites (Fig. 4). This, and the very
high levels of estimated gene flow revealed through
regional pairwise FST comparisons (Table 6), are
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
GENETIC VARIATION IN THE MONARCH BUTTERFLY
445
Table 4. The Fixation Index (FIS) within each population sampled at seven polymorphic loci. The total number of loci
examined varies according to region
Site
Locus PGI
PGM
IDH
PEP D
HBDH
MPI
AAT
Beenleigh
Boondall
Mt Crosby
Watagan
St Albans
Monkerai
Kroombit
Marsh Road
Bracewell
Michoacan
Kalamazoo
San Diego
Santa Barbara
San Luis Obispo
Hawaii
-0.084
0.000
0.051
-0.006
0.008
-0.044
-0.054
-0.194 ***
-0.120
0.006
-0.013
0.176
0.195
-0.477***
-0.070
0.087
-0.020
-0.115
0.124
0.000
-0.006
0.001
0.038
-0.188 *
-0.011
-0.051
-0.026
0.030
0.068
-0.143
0.190 ***
0.054
0.010
-0.005
0.052
0.087
-0.072
0.031
0.003
-0.092
-0.087
-0.149
-0.062
-0.123
-0.080
0.176 *
0.181 *
0.123
0.111
0.106
0.101
0.039
0.064
0.291 *
-0.072
-0.265
0.032
-0.028
0.100
-0.210
0.036
0.082
0.110
-0.100
0.040
-0.490
0.023
0.023
-0.065
-0.164
0.071
0.170
0.039
-0.106
-0.137
0.321
0.163
0.064
-0.123
0.020
0.095
0.198
0.318
0.077
–
–
–
–
–
-
***
*
*
***
-0.047
-0.010
–
-0.038
-0.040
-
*P < 0.05, **P < 0.01, ***P < 0.001.
Table 5. FST values calculated at all levels of analysis. Hierarchical F-statistics for the Australian analysis are calculated
within each region (FSR) and between regions (FRT). Mean values are jackknifed estimates. Values in parentheses are standard deviations. Numbers in italics are gene flow estimates (Nem)
Loci
PGI
PGM
IDH
PEP D
HBDH
MPI
AAT
Mean
0.000
0.002
-0.0015
166.42
0.012***
0.000
0.0139***
17.74
-
0.004 (0.0019)
62.25
Australia
FSR
FRT
FST
Nem
0.000
0.003
0.0025
99.75
0.001
0.002
0.0035
71.18
0.001
0.000
0.0001
2499.75
0.001
0.004
0.0045
55.31
North
America
FST
Nem
0.0197***
12.44
0.0358***
6.73
0.0073
33.97
0.0432***
5.54
0.0051
48.77
–
0.0079***
2.91
0.0247 (0.00726)
9.87
Regional
(Australia,
Hawaii &
N. America)
FST
Nem
0.0784***
2.94
0.0181***
13.56
0.0345***
6.99
0.0207***
11.83
0.0092***
26.92
-
0.0287***
8.46
0.0365 (0.01643)
6.77
*P < 0.05, **P < 0.025, ***P < 0.001.
consistent with a lack of geographical structure in
Australia.
GENETIC
DIFFERENTIATION AMONG
AMERICAN
SITES
Small but significant FST values were obtained at four
of the six loci analysed for the American sites. These
ranged from 0.0073 to 0.0358 (Table 5). Pairwise FST
comparisons between sites suggested fairly limited
genetic structure, with the least estimated gene flow
occurring between San Diego and all other populations
(Table 7). Surprisingly, the greatest gene flow was
found between the eastern population of Kalamazoo
and the west coast population, Santa Barbara. The
similarity between these populations was many magnitudes greater than between Santa Barbara and its
nearest geographical neighbours. Whilst the degree of
inferred gene flow between the North American sites
was less than that found within Australia, it was
insufficient to suggest any strong degree of structure.
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
446
J. M. SHEPHARD ET AL.
STRUCTURE AT
A
THE REGIONAL LEVEL THROUGHOUT
MONARCH’S
THE
B
Figure 4. Results of UPGMA analysis. A. Genetic relationship between the Australian sites (unweighted pair
group method) using Nei’s (1978) unbiased genetic distance. Sites within the same region are denoted by shaded
boxes (cophonetic correlation = 0.664). B. Analysis at the
regional level using Nei’s unbiased genetic distance and
unweighted pair group method (cophonetic correlation =
0.908).
RANGE
Significant subdivision among populations was found
at all loci examined at the regional level (Table 5).
With the exception of Pgm and Pep D, regional comparisons indicated a significant increase in structure
at all loci when compared to estimates within North
America only (Table 5). Nonetheless, a marked degree of differentiation is apparent at the regional level
when compared with either the Australian or North
American samples independently (Table 5).
The mean jackknifed FST estimate for North America
is many orders of magnitude greater than the result
for Australia. This is not seen when comparing North
America to the regions, suggesting that the overall
degree of differentiation may be strongly influenced by
structure within the North American sample (Table 5).
Regional pairwise FST comparisons, with high levels
of gene exchange between Mexico and Kalamazoo, and
amongst the Australian regions (Table 6) reinforces
the historically accepted relationships between the
populations. The structure between Hawaii and Australia is comparable to the degree of structure found
between Hawaii and North America. The high level of
inferred gene flow found at the site level (Table 7)
between Kalamazoo and Santa Barbara is replicated
at the regional level (FST = 0.0026 ± 0.005), and is reinforced using cluster analysis based on Nei’s (1978)
genetic distance (Fig. 4B).
DISCUSSION
Our study had three major aims. The first was to
compare the levels of diversity of Australian and
Table 6. Pairwise FST and gene flow (Nem) estimates between all regions. FST values are below the diagonal, Nem
estimates are above the diagonal. Both are calculated from jacknifed estimates. Values in parentheses are standard
deviations
Mexico
Kalamazoo
California
Hawaii
Brisbane
Sydney
Rockhampton
Mexico
Kalamazoo
California
0.0141
(0.007)
0.0163
(0.006)
0.0642
(0.038)
0.0964
(0.044)
0.0829
(0.025)
0.0794
(0.04)
17.48
-
15.09
95.90
3.644
5.46
2.34
3.78
2.77
4.31
2.90
4.89
0.0026
(0.005)
0.0438
(0.041)
0.0620
(0.038)
0.0548
(0.022)
0.0486
(0.035)
-
4.45
3.37
4.48
4.68
3.40
3.74
5.38
-
20.41
63.85
0.0121
(0.007)
0.0039
(0.001)
-
30.61
0.0081
(0.008)
-
0.0532
(0.04)
0.0609
(0.035)
0.0528
(0.023)
0.0507
(0.033)
Hawaii
0.0684
(0.036)
0.0626
(0.022)
0.0444
(0.024)
Brisbane
Sydney
Rockhampton
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
GENETIC VARIATION IN THE MONARCH BUTTERFLY
447
Table 7. Pairwise FST and gene flow (Nem) estimates between the American regions. FST values are below the diagonal,
Nem estimates are above the diagonal. Both are calculated from jacknifed estimates. Values in parentheses are standard
deviations
Michoacan
Kalamazoo
San Diego
Santa Barbara
San Luis Obispo
Michoacan
Kalamazoo
0.0141
(0.0377)
0.0669
(0.0285)
0.0036
(0.004)
0.0209
(0.0158)
17.48
0.0266
(0.01074)
0.0024
(0.003)
0.0193
(0.0095)
Hawaiian populations with potential source populations in North America. We had predicted that Australian and Hawaiian populations would have lower
diversity than the source populations, especially if
they had arisen from a single, or stepping-stone colonization event. The second aim was to determine
whether the genetic signatures of North American
populations were sufficiently distinct to be able to
assess the likely origin of Australian and Hawaiian
populations. The third aim was to examine genetic
variation among Australian populations and to
compare it with variation among North American
populations. Because the Australian populations do
not undergo strong and large-scale annual cyclical
migration, we had predicted that they would show
more genetic structure than the North American
populations.
Although mean number of alleles per locus was
lower for Australian than North American populations, levels of heterozygosity were not. In fact,
heterozygosity values were significantly greater in
Australian and Hawaiian populations than in North
American populations. Simulation studies have shown
that heterozygosity does not necessarily decline as a
result of a bottleneck, especially if the population
increases rapidly immediately afterwards (Nei et al.,
1975). Population explosions may have occurred on
some Pacific islands following the monarch’s introduction (Walker, 1914).
The observation of an increase in heterozygosity
is a little surprising, although a similar result was
reported by Leberg (1992) from an experimental
manipulation of population sizes in mosquito fish
Gambusia holbrooki. He suggested that the increase,
which was only recorded in some populations, was an
effect of previously rare alleles reaching the new
populations by chance and rising to quite high frequencies by genetic drift. Even though population
San Diego
3.487
9.15
Santa Barbara
San Luis Obispo
69.19
103.92
11.712
12.70
6.99
0.0345
(0.0167)
0.0587
(0.0189)
4.01
12.44
0.0197
(0.0166)
-
sizes currently appear to be large, they were likely
to be small for a number of generations after the
original colonization event.
Nei et al. (1975) predict that population bottlenecks
will have a larger effect on allelic diversity than heterozygosity. As expected, the number of alleles per
locus was lower for Australian populations than North
American populations. This is because it is rare alleles
that are usually lost during colonization with a subsequent transient population bottleneck. This effect
is seen in the San Diego sample, which was from a
population that had been through a single generation
in the laboratory. A bottleneck, in terms of a limited
number of successful adults, also appears to have
reduced the number of alleles per locus but not
affected the heterozygosity in this laboratory
population.
The genetic differences between eastern and
western North American samples are not sufficient
for us to propose the likely origin of the Hawaiian
and Australian populations. The similarity between
California and Kalamazoo was unexpected (Brower
& Boyce, 1991), and suggests at least some movement
of individuals between the two populations. The similarly low levels of differentiation between Kalamazoo
and Mexico are consistent with the view that they represent parts of the same population (Brower, 1996).
The results clearly demonstrate, however, that the
three Australian regions are more similar to each
other than to Hawaii or to North American regions
and, with one exception, share identical alleles. This
suggests that they are the result of a single colonization event, but does not indicate the specific origin of
the colonists.
It may be possible to infer details of the process of
colonization by looking at individual alleles and their
distribution across sites. Across the six loci analysed
for all sites, 35 alleles were detected. All of these
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
448
J. M. SHEPHARD ET AL.
alleles occurred in at least one North American site;
16 alleles occurred in North America, but not in
Australia. Similarly 17 alleles occurred in North
America that were not found in Hawaii. These were
not the same alleles in all cases. Hawaii had three
alleles not present in Australia, and Australia had four
alleles that were not present in Hawaii. This allele distribution is consistent with Australian and Hawaiian
populations having originated from North America. It
also suggests that the Hawaiian and Australian populations may have resulted from different colonization events. If Hawaii represented a stepping stone
to Australia then alleles present in Australia would
be expected to be present in Hawaii.
The deviations from Hardy–Weinberg proportions at
the Mpi locus at four of the nine sites may have been
due to selection acting against one or more heterozygotes, the presence of null alleles or the mis-scoring
of plates. Selection has been suggested to affect allele
frequencies at other loci in Queensland monarch
populations (Hughes & Zalucki, 1993). Because neutrality is assumed when making assessment of gene
flow from FST values (Slatkin, 1987), and because Mpi
was the only locus showing significant FST values, we
recalculated FST values without Mpi. The overall conclusion did not change. There is very little genetic
structure in the Australian monarch population and
no tendency for nearby populations to be more similar.
When overall FST values are compared between Australia and North America, the North American values
are about an order of magnitude larger. This is not
due to separation of eastern and western populations,
which might have been expected (Brower, 1996). In
fact, Kalamazoo and Santa Barbara, which represent
different sides of the country, were the most similar
and almost all pairwise FST values were an order of
magnitude larger than the mean for Australia of
0.004.
There are three possible explanations for these
results. First, there may be higher levels of gene flow
between localities in Australia than in North America.
This would be unexpected, given the migratory behaviour in North America compared to minor seasonal
range expansions and contractions in Australia
(Zalucki, 1983). A second, and possibly more likely
explanation, is that the Australian populations have
only been here for about 130–150 years and have not
yet reached equilibrium. The calculation of Nem from
FST assumes that the population has reached equilibrium between increasing divergence among subpopulations due to genetic drift, and a decrease in
divergence due to migration (Wright, 1951). The time
it takes to reach equilibrium depends on effective
population size, migration rate and generation time.
Higher migration rates shorten the time to reach equilibrium and higher values of Ne lengthen the time
(Crow & Aoki, 1984). Population sizes of monarchs
currently appear to be very large. There are roughly
12 generations per year (Zalucki, 1982), so the
Australian populations have only had between 1200
and 2000 generations to reach equilibrium. Possibly
the use of mitochondrial DNA, which is expected to
reach equilibrium roughly four times faster than nuclear DNA, due to its fourfold smaller effective population size (Birky et al., 1989) could be used to resolve
this issue.
A third possibility that cannot be ruled out is
that the loci that we have examined are influenced by
selection. For selection to explain the relatively small
differences among Australian populations, all loci
would have to be effected by some form of stabilizing
selection, keeping allele frequencies constant and
heterozygosities relatively high. This seems unlikely,
although the suggestion that selection can keep allele
frequencies constant is not new (Karl & Avise, 1992).
In addition, selection has been suggested to contribute
to the maintenance of variation at the Pgi locus in this
species (Hughes & Zalucki, 1993). Obviously, if a locus
is affected by selection, inferring levels of dispersal
from FST values is not valid. The best way to assess the
importance of selection would be to compare results
using neutral microsatellite markers.
ACKNOWLEDGEMENTS
We thank Mia Hillyer, Chris Marshall, Jon Marshall,
David Hurwood, Justine Smith, Yaramah Zalucki
and Kaye Earnshaw for assistance with field collection in Australia. Amanda Hedin, Chris Hanlon,
Tim Payne, Kingston Leong, Eneida Montesinos,
David Marriot and Andrew Taylor for help with the
Northern Hemisphere collections. This work was
funded by Jane Hughes and Myron Zalucki. Collecting trips to the USA by MPZ were supported in part
by UQ travel grants. We thank DAS Smith and an
anonymous reviewer for helpful comments.
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ALLELE
FREQUENCIES AND HETEROZYGOSITY VALUES AT ALL SITES
Sites
Been
Boon
Mt Cr
Watag
St Alb
Monk
Kroom
Marsh
Brace
Mex
San D
San L
SantaB
Kz
Hawaii 1
Hawaii 2
PGI
(N)
A
B
C
D
E
F
G
H*
98
0.000
0.000
0.505
0.000
0.347
0.148
0.000
0.653
99
0.000
0.000
0.505
0.000
0.303
0.192
0.000
0.616
100
0.000
0.000
0.500
0.000
0.290
0.210
0.000
0.590
54
0.000
0.000
0.454
0.000
0.370
0.176
0.000
0.630
99
0.000
0.005
0.429
0.000
0.394
0.172
0.000
0.626
96
0.000
0.000
0.391
0.000
0.385
0.224
0.000
0.677
100
0.000
0.000
0.430
0.000
0.345
0.225
0.000
0.680
97
0.000
0.000
0.407
0.000
0.371
0.222
0.000
0.773
99
0.000
0.000
0.465
0.000
0.283
0.253
0.000
0.717
94
0.005
0.027
0.160
0.074
0.697
0.032
0.005
0.479
46
0.000
0.000
0.272
0.000
0.728
0.000
0.000
0.326
35
0.014
0.043
0.343
0.029
0.486
0.071
0.014
0.943
54
0.028
0.028
0.167
0.028
0.713
0.037
0.000
0.370
51
0.020
0.000
0.235
0.020
0.676
0.049
0.000
0.490
27
0.000
0.000
0.111
0.000
0.444
0.407
0.037
0.667
20
0.000
0.000
0.250
0.000
0.475
0.25
0.000
0.649
PGM
(N)
A
B
C
D
E
H*
99
0.000
0.288
0.354
0.359
0.000
0.606
100
0.000
0.330
0.325
0.345
0.000
0.680
100
0.000
0.290
0.350
0.360
0.000
0.740
55
0.000
0.291
0.345
0.364
0.000
0.582
100
0.000
0.250
0.430
0.320
0.000
0.650
100
0.000
0.275
0.450
0.275
0.000
0.650
100
0.000
0.305
0.395
0.300
0.000
0.660
100
0.000
0.280
0.455
0.265
0.000
0.620
100
0.000
0.250
0.380
0.210
0.000
0.700
100
0.120
0.450
0.355
0.065
0.010
0.660
48
0.000
0.188
0.458
0.354
0.000
0.646
54
0.019
0.472
0.380
0.130
0.000
0.574
55
0.027
0.400
0.455
0.118
0.000
0.600
52
0.000
0.404
0.394
0.202
0.000
0.673
27
0.000
0.389
0.389
0.222
0.000
0.741
21
0.000
0.29
0.45
0.26
0.000
0.646
AAT
(N)
A
B
C
D
H*
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
55
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.000
1.000
0.000
0.000
100
0.000
0.045
0.955
0.000
0.099
50
0.000
0.000
1.000
0.000
0.000
55
0.000
0.036
0.955
0.009
0.091
55
0.018
0.018
0.945
0.018
0.109
52
0.010
0.010
0.990
0.000
0.019
27
0.000
0.000
1.000
0.000
0.000
21
0.000
0.000
1.000
0.000
0.000
IDH
(N)
A
B
C
D
E
H*
100
0.000
0.100
0.790
0.085
0.025
0.290
100
0.000
0.090
0.845
0.055
0.010
0.260
100
0.000
0.080
0.780
0.100
0.040
0.370
54
0.000
0.111
0.806
0.083
0.000
0.333
100
0.000
0.095
0.780
0.115
0.010
0.350
100
0.000
0.065
0.790
0.145
0.000
0.320
100
0.000
0.065
0.815
0.120
0.000
0.340
100
0.000
0.090
0.835
0.075
0.000
0.280
100
0.000
0.065
0.805
0.130
0.000
0.330
100
0.000
0.005
0.885
0.050
0.060
0.230
50
0.000
0.000
0.870
0.130
0.000
0.260
55
0.000
0.000
0.855
0.064
0.082
0.291
55
0.000
0.009
0.927
0.055
0.009
0.145
52
0.010
0.000
0.904
0.077
0.010
0.192
27
0.000
0.074
0.926
0.000
0.000
0.148
21
0.000
0.000
1.000
0.000
0.000
0.000
451
Locus
GENETIC VARIATION IN THE MONARCH BUTTERFLY
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
APPENDIX
452
Continued
Sites
© 2002 The Linnean Society of London, Biological Journal of the Linnean Society, 2002, 75, 437–452
Locus
Been
Boon
Mt Cr
Watag
St Alb
Monk
Kroom
Marsh
Brace
Mex
San D
San L
SantaB
Kz
Hawaii 1
Hawaii 2
PEP D
(N)
A
B
C
D
E
F
H*
100
0.000
0.005
0.745
0.000
0.100
0.150
0.340
100
0.000
0.005
0.745
0.005
0.125
0.120
0.340
100
0.000
0.000
0.755
0.000
0.100
0.145
0.350
54
0.000
0.000
0.833
0.000
0.083
0.083
0.259
100
0.000
0.000
0.825
0.000
0.055
0.120
0.270
100
0.000
0.010
0.805
0.005
0.060
0.120
0.300
100
0.000
0.005
0.760
0.005
0.100
0.130
0.380
98
0.000
0.000
0.776
0.000
0.148
0.077
0.347
100
0.000
0.000
0.705
0.000
0.100
0.035
0.300
96
0.000
0.068
0.854
0.016
0.057
0.005
0.281
50
0.010
0.130
0.620
0.200
0.010
0.030
0.540
55
0.000
0.018
0.855
0.073
0.027
0.027
0.236
55
0.000
0.109
0.782
0.036
0.064
0.009
0.382
52
0.019
0.019
0.683
0.038
0.048
0.019
0.442
27
0.000
0.130
0.759
0.019
0.093
0.000
0.481
19
0.000
0.080
0.420
0.320
0.110
0.08
0.696
HBDH
(N)
A
B
C
D
E
F
G
H
H*
100
0.000
0.000
0.000
0.210
0.000
0.790
0.000
0.000
0.320
100
0.000
0.000
0.000
0.215
0.000
0.785
0.000
0.000
0.310
100
0.000
0.000
0.000
0.205
0.000
0.795
0.000
0.000
0.290
55
0.000
0.000
0.000
0.273
0.000
0.727
0.000
0.000
0.436
100
0.000
0.000
0.000
0.250
0.000
0.750
0.000
0.000
0.360
100
0.000
0.000
0.000
0.220
0.000
0.780
0.000
0.000
0.360
99
0.000
0.000
0.000
0.258
0.000
0.742
0.000
0.000
0.374
99
0.000
0.000
0.000
0.258
0.000
0.742
0.000
0.000
0.374
100
0.000
0.000
0.000
0.270
0.000
0.730
0.000
0.000
0.420
100
0.000
0.000
0.000
0.235
0.000
0.735
0.025
0.005
0.470
51
0.010
0.000
0.000
0.137
0.000
0.755
0.098
0.000
0.333
55
0.009
0.009
0.009
0.136
0.018
0.764
0.055
0.000
0.436
55
0.000
0.009
0.018
0.182
0.018
0.727
0.045
0.000
0.418
52
0.000
0.010
0.000
0.279
0.000
0.683
0.029
0.000
0.423
27
0.000
0.000
0.019
0.296
0.000
0.556
0.130
0.000
0.667
21
0.000
0.000
0.000
0.350
0.000
0.550
0.090
0.000
0.567
MPI
(N)
B
C
D
H*
97
0.201
0.598
0.201
0.381
97
0.113
0.655
0.232
0.423
100
0.035
0.755
0.210
0.360
54
0.074
0.769
0.157
0.426
100
0.055
0.775
0.170
0.360
98
0.046
0.704
0.250
0.398
100
0.045
0.745
0.210
0.320
99
0.030
0.672
0.298
0.313
97
0.031
0.768
0.210
0.340
-
-
-
-
-
-
*Heterozygosity value is the direct count estimate; results for Hawaii 2 are not included in the analysis.
J. M. SHEPHARD ET AL.
APPENDIX