59
Genetica 101: 59–66, 1997.
c 1997 Kluwer Academic Publishers. Printed in the Netherlands.
Allozyme variation in Parnassius mnemosyne (L.) (Lepidoptera) populations
in North-East Hungary: variation within a subspecies group
Emese Meglécz1 , Katalin Pecsenye1 , László Peregovits2 & Zoltán Varga1
1
Department of Evolutionary Zoology and Human Biology, Kossuth Lajos University, Debrecen H-4010, Egyetem
tér 1., Hungary; 2 Hungarian Natural History Museum, Department of Zoology, Budapest H-1088, Baross u. 13.,
Hungary
Received 17 September 1996 Accepted 15 April 1997
Key words: allozyme frequencies, genetic drift, heterozygote deficiency, Lepidoptera, Parnassius mnemosyne
Abstract
Allozyme polymorphism was studied in 11 Parnassius mnemosyne (Linnaeus, 1758) populations in North-East
Hungary. Significant departures from Hardy-Weinberg equilibrium were observed in several cases due to heterozygote deficiency. Genetic variability did not display geographical pattern; the level of genetic differentiation was
similar between adjacent populations and between populations originating from different geographical regions.
Even a completely isolated population was not differentiated markedly from the others. Thus, genetic drift can be
expected as the main evolutionary force acting in the populations.
Introduction
Conservation of biological diversity at different levels
is an increasingly important task in the face of massive destruction and fragmentation of natural habitats
(Soulé, 1986). To develop a proper conservation strategy for a particular species, it is important to have
information both on the genetic diversity and on the
ecological characteristics of the species in question.
The main goal of this study was to investigate genetic diversity in populations of the butterfly Parnassius
mnemosyne (Linnaeus, 1758), which is highly endangered in Northern and Central Europe (Heath, 1981)
and included in the list of the Bern Convention on the
protected species. In Hungary, this species still occurs
in strong populations. Nevertheless, several populations are isolated and at least potentially threatened,
hence the species is protected and included in the Red
Data Book of Hungary (Rakonczay, 1990). The investigated populations (Figure 1) originated from the marginal area of the distribution of the P. mnemosyne ariovistus (Fruhstorfer, 1907) subspecies group, which is
widely distributed in the Northern Carpathians (Zelny,
1956; Varga, 1993).
Parnassius mnemosyne is a specialized Kstrategist; females can mate only once and they lay
about 50 eggs dispersed over a large area (Weideman, 1986). This species requires structured habitats;
larvae feed on Corydalis cava and C. solida, which
occur in humid, deciduous forests, while imagoes prefer clearings for mating and feeding. After the last
glacial period, the investigated area was continuously
covered with forest until the appearance of Neolithic
culture approximately 6000 years ago (Willis et al.,
1997). As a consequence of human activities, extensive deforestation occurred in the valleys, resulting in
the separation of the forested area of the Aggtelek karst
(Figure 1: pops. 1–2), Bükk mountains (Figure 1: pops.
3–10), and the hardwood gallery forests of the Tisza
region (Figure 1: pop. 11). The largest continuous
woodland in northeast Hungary remained on the Bükk
plateau (Figure 1: pops. 3, 4, 8, 9) until recent clearfellings approximately 200 years ago. Concurrently,
the extreme fragmentation of gallery forests due to the
control of Tisza river and its tributaries (i.e., altering
the river bed by cutting of its curves) resulted in the
isolation of the Sajólád forest (Figure 1: pop. 11).
The aim of our work was to answer the following questions: Does genetic substructuring exist in the
60
east Hungary (Figure 1; 47.8–48.5 N, 20 –21 E).
Two populations were sampled in the karstic area of
Aggtelek (Nagyoldal, pop. 1; Ménes valley, pop. 2;
altitude: 400–500 m). Eight samples originated from
the Bükk mountains: four from the plateau and its
edge (Lusta valley, pop. 3; Bányahegy, pop. 4; Gyertyán valley, pop. 8; Hollóstető, pop. 9; altitude: 500–
800 m) and four from the foreground of the mountains
(Vöröskő, pop. 5; Odorvár, pop. 6; Hór valley, pop.
7; Bükkszentlászló, pop. 10; altitude: 400–500 m).
Odorvár, Hór valley, Gyertyán valley, and Hollóstető
are situated along valleys directly connected to each
other. The last sample originated from an isolated population in Sajólád (pop. 11; approx. altitude: 100 m).
This single population was also considered to represent
a separate region because it has no connection to any
other population.
Imagoes were collected after the egg laying period
in late May, 1994 and stored at 20 C until electrophoresis. Sample sizes varied between 16 and 67,
according to the size of the populations.
Enzyme assay
Figure 1. Sampling localities of Parnassius mnemosyne in northeast Hungary. Aggtelek karst: Nagyoldal (1), Ménes valley (2),
Bükk mountains: Lusta valley (3), Bányahegy (4), Vöröskő (5),
Odorvár (6), Hór valley (7), Gyertyán valley (8), Hollóstető (9),
Bükkszentlászló (10), Sajólád (11).
investigated area? Is there still a large continental population in the Bükk mountains with metapopulation
structure or has it already been fragmented to separate populations due to habitat fragmentation? What is
the main evolutionary force affecting allozyme variation in the populations: limited migration resulting in
geographic pattern of genetic differentiation or genetic drift due to small population sizes yielding random
pattern in genetic variation?
Materials and methods
Sample collection
In order to avoid difficulties in notation we refer to the
entities that were sampled as ‘populations’.
Samples were collected from 11 Parnassius
mnemosyne populations in three regions of north-
Eight loci were examined in all samples: glutamateoxalacetate trasaminase (Got), -glycerophosphate
dehydrogenase (Gpdh), hexokinase (Hk), isocitrate
dehydrogenase (Idh), malate dehydrogenase (Mdh),
phosphoglucose isomerase (Pgi), phosphoglucomutase (Pgm), and superoxide dismutase (Sod). Thoraxes
and abdomens were homogenized in 5 l/mg extraction
buffer. Electrophoresis was carried out on horizontal
starch gel slabs using different buffer systems. Several individuals were run at least twice to check the
repeatability of the banding patterns. The extraction
buffers, the electrophoretic buffer systems and conditions, together with the staining solutions used for each
enzyme, are given in Appendix 1.
Data analyses
Genotype and allele frequencies were calculated on
the basis of the banding patterns. The Markov chain
method was used to estimate the exact Hardy-Weinberg
probability without bias (Guo & Thompson, 1992). An
exact test for population differentiation (Raymond &
Rousset, 1995a) was conducted to test for independence of the allelic composition of the various populations. Genetic differentiation between populations was
also analyzed by Wright’s F-statistics: the total genetic variability (FIT ) was partitioned into within (FIS )
61
Table 1. Results of Hardy-Weinberg tests
Pops.
1
2
3
4
5
6
7
8
9
10
11
Pgm
N
H-W
FIS
53
D
0.189
17
D
0.312
50
D
0.047
49
D
0.042
16
D
0.304
23
D
0.407
16
D
0.514
49
E
0.155
40
D
0.042
30
E
0.016
42
D
0.141
Pgi
N
H-W
FIS
59
E
0.126
20
E
0.027
33
D
0.061
33
E
0.005
17
D
0.175
28
D
0.116
13
D
0.319
48
D
0.036
44
D
0.014
31
D
0.269
45
E
0.038
Hk
N
H-W
FIS
57
D
0.237
16
D
0.211
53
D
0.381
43
D
0.355
14
D
0.594
25
D
0.473
16
D
0.610
48
D
0.597
44
D
0.173
25
D
0.258
38
D
0.114
N: sample sizes; H-W: departures from Hardy-Weinberg equilibrium; E: heterozygote excess; D: heterozygote deficiency; FIS : the size
of the departure of heterozygote frequency from the Hardy-Weinberg expectation.
significant at 0.001 level, significant at 0.01 level, significant at 0.05 level.
and between (FST ) population variation (Weir, 1990).
Average FST values were used to estimate the magnitude of gene flow by calculating the product of the
effective population size and the migration rate (Ne m)
(Slatkin & Voelm, 1991). Multilocus estimates of the
number of migrants (Ne m) were calculated according
to Slatkin (1985) and Slatkin and Barton (1989). Correlation between FIS values and empirical population
sizes were tested by Spearman rank correlation test.
Populations were grouped into three regions on the
basis of their geographic location (Aggtelek region,
Bükk region, and Sajólád). In a hierarchical gene
diversity analysis (Wright, 1978), the total betweenpopulation variation (FPT ) is proportioned into differentiation within (FPR ) and between regions (FRT ).
Allele frequencies were used to estimate arc genetic
distances (Cavalli-Sforza & Edwards, 1967) and an
UPGMA dendrogram was constructed on the basis of
these data (Sneath & Sokal, 1973).
As the presence of null alleles cannot be completely excluded, we included null alleles and corrected the
allele frequencies assuming Hardy-Weinberg equilibrium (Brookfield, 1996). With this new data set we
performed an exact test for population differentiation,
calculated genetic distances and constructed a dendrogram, as described above.
Genepop, version 1.0 (Raymond & Rousset,
1995b) was used to perform the Hardy-Weinberg test,
the exact test for population differentiation and generate an estimate of Ne m based on the private allele
method; FSTAT, version 1.2 (Goudet, 1995), to com-
pute F-statistics; Biosys-1, Release 1.7 (Swofford &
Selander, 1981), to calculate hierarchical F-statistics,
genetic distances and to construct a dendrogram.
Results
Three of the eight loci were polymorphic using the criterion that the frequency of the most abundant allele
is less than 0.95 (Hk, Pgm, Pgi). Additionally, rare
alleles were observed at Gpdh and Idh. Allele frequencies are shown in Appendix 2. Statistical analyses
were based on the data at these five loci.
Significant Hardy-Weinberg disequilibrium was
observed at Hk and Pgm in many populations, but
there was no apparent pattern (Table 1), i.e., (i) neither
Hk nor Pgm were in disequilibrium across all populations; (ii) six populations were in equilibrium at one
of these two loci but not at the other. FIS values also
showed significant heterozygote deficiency in many
cases (Table 1). The results of the two tests were mostly parallel; when FIS values proved to be significant
at a given locus, the populations were generally not at
Hardy-Weinberg equilibrium.
Table 2 summarizes the results of the F-statistics
(Weir, 1990). The overall FIT value showed a relatively
high level of genetic variability, much of which could
be ascribed to the within-population variation. However, there was also significant variation between populations. Based on the average value of fixation indices
(FST = 0.064) we calculated an indirect estimate of
62
Table 2. Summary of F-statistics. FIS measures the
genetic variability within populations, FST measures
the genetic variability among populations, FIT measures the total genetic variability
Locus
FIS
FIT
FST
Pgm
Pgi
Hk
Idh
Gpdh
0.109
0.062
0.337
0.002
0.003
0.140
0.092
0.415
0.000
0.000
0.034
0.032
0.118
0.002
0.004
Mean
0.172
0.225
0.064
Table 3. Cavalli-Sforza and Edwards (1967) arc genetic
distances averaged by regions. Ranges in parentheses
Region
No. of
pops.
Aggtelek
Bükk
Aggtelek
2
Bükk
8
Sajólád
1
0.202
(0.202–0.202)
0.181
(0.135–0.248)
0.173
(0.168–0.177)
0.132
(0.090–0.184)
0.142
(0.089–0.190)
gene flow (Ne m = 3.66). Ne m estimate was also low
(1.69) on the basis of the private allele method.
The larger proportion of the total diversity among
populations (FPT = 0.055) could be attributed to the
variation within regions (FPR = 0.058). Little differentiation was observed between regions (FRT = 0.003).
Cavalli-Sforza and Edwards (1967) genetic distances between pairs of populations are shown in
Appendix 3. The average genetic distances within
regions were similar or even higher than those aver-
Table 4. Exact test for population differentiation
Locus
Pgm
Pgi
Hk
Idh
Gpdh
Populations from Bükk
All populations
k
4
3
3
2
2
k
5
3
3
2
2
Exact prob.
0.000
0.000
0.000
0.489
1.000
Exact prob.
0.000
0.000
0.000
0.374
0.857
k: number of alleles. significant at 0.001 level.
aged between regions, indicating that the differentiation between regions was not stronger than between
populations within a region (Table 3). The dendrogram
constructed on the basis of genetic distances showed a
similar pattern (Figure 2). Populations from the same
region were not clustered into a single branch. Even the
four directly connected populations in the Bükk mountains (Odorvár, pop. 6; Hór valley, pop. 7; Gyertyán
valley, pop. 8; Hollóstető, pop. 9) appeared in different
branches.
A similar pattern was obtained from the results of
the exact test for population differentiation (Table 4).
Allele frequencies were highly heterogeneous among
populations at all polymorphic loci. The heterogeneity of gene frequencies among the eight Bükk mountain populations was similar to that observed across all
populations. This finding again indicated significant
heterogeneity within regions and a lower level of differentiation between regions. Results of the analyses
performed on the corrected allele frequencies for null
alleles were consistent with those obtained using the
originally observed genotype frequencies.
Discussion
Figure 2. Dendrogram constructed on the basis of Cavalli-Sforza
and Edwards (1967) arc genetic distances. I. Aggtelek karst, II. Bükk
mountains, III. Sajólád.
The traditional conservation approach has been to protect and manage habitat islands as reserves for the
endangered species. This approach assumes the existence of a single homogenous and isolated population
in the habitat patch. Consequently, the traditional question for conservation has been the minimal size of a
viable population (Hanski, 1997). On the other hand,
habitat fragmentation has become a widespread phenomenon, one which has resulted in subdivided populations. It has long been recognized that population
subdivision has a great influence on the maintenance
and loss of genetic variation (Wright, 1978; Nei, 1975).
Because genetic variation is of particular importance
63
to conservation strategies it is essential to study the
structure of the genetic variation in the populations
of endangered species. In this study, we investigated the consequences of habitat fragmentation on P.
mnemosyne populations. We were equally interested
in the structure of the within- and between-population
variation to obtain a general view on the status of the
Hungarian populations of this species.
Hardy-Weinberg equilibrium is routinely tested in
natural populations but significant deviations have been
found in only a few butterfly species (Goulson, 1993;
Nève, 1996; Smith et al., 1993; Watt, 1983). In Parnassius mnemosyne populations, we found an overall
heterozygote deficiency, which often resulted in significant Hardy-Weinberg disequilibrium. There are four
possible explanations for heterozygote deficiency: (i)
underdominant selection, i.e., heterozygote disadvantage; (ii) inbreeding; (iii) presence of null alleles; and
(iv) subdivision of the populations.
(i) In models with constant fitness, underdominant selection does not lead to stable polymorphism
(Wright, 1969). Nevertheless, frequency-dependent
models can describe stable equilibrium (Clarke &
O’Donald, 1964). If environmental factors affecting
allele frequencies are similar in all populations, the
magnitude of heterozygote deficiency should be similar too. Although neither Hk nor Pgm showed consistent heterozygote deficiency across all populations,
we cannot exclude the possibility of underdominant
selection as we do not know whether environmental
factors were homogeneous across the investigated populations.
(ii) Inbreeding affects all loci similarly, hence, FIS
values should be similar at all loci in a given population. We did not observe such a pattern in any population, yet we cannot exclude the possibility of inbreeding as a consequence of seriously reduced population
size due to a recent bottleneck. Parnassius mnemosyne
females are far less numerous than males (in preliminary mark-release-recapture studies we found that 25–
30% of the individuals are females) and they mate only
once. Therefore, it is possible that under unfavorable
conditions, only a few pairs produce the next generation, which could lead to heterozygote deficiency.
Spearman rank correlation tests indicated a significant
increase in FIS values with decreasing empirical population size for Pgi and Pgm (Pgi: rs = 0.582, P < 0.05;
Pgm: rs = 0.566, P < 0.05) supporting the possibility
of inbreeding. It is, however, remarkable that the Pgi
locus does not show significant heterozygote deficiency. Pgi is one of the few loci where allelic frequencies
are known to correlate with environmental factors, presumably due to selection (Zanglerl & Bazzaz, 1984).
Watt has shown in Colias that heterozygote excess is
maintained by overdominant selection at Pgi (Watt,
1983; Watt, Cassin & Swan, 1983). In our case, it
is possible that overdominance opposed inbreeding,
which resulted in genotypic frequency distributions
close to Hardy-Weinberg expectations.
(iii) Although the presence of null alleles cannot be
excluded, the fact that the frequency of the presumed
null alleles increased with decreasing population size
(see the results of rank correlation test) makes this
explanation unlikely.
(iv) Heterozygote deficiency in a subdivided population is the consequence of random processes
(Wahlund effect). Hence, we would expect to observe
a random pattern across loci and populations. The fact
that our FIS values were not consistent across populations or across loci suggests that the heterozygote
deficiency we observed may be a consequence of population subdivision.
At this time, none of the four explanations can be
rejected unambiguously, and further investigations are
required.
The different analyses on the hierarchical structure
of the investigated P. mnemosyne populations (average genetic distances, dendrogram, hierarchical Fstatistics, and test for population differentiation for
different data sets) generated similar results. Populations are genetically differentiated, but not according
to geographical proximity, i.e., populations in different
regions do not differ to a greater extent than populations
in the same region. In theory, the lack of geographic
pattern in genetic variation can be the consequence of
three different evolutionary forces: (i) intensive migration between regions; (ii) similar effects of selection in
all regions; (iii) genetic drift. Both intensive migration
and selection should result in homogeneous allele frequencies across populations. On the other hand, genetic drift would lead to heterogeneity in frequencies. The
highly significant differences in allele frequencies at
the polymorphic loci suggest that the main evolutionary force acting on allozyme polymorphism in these
populations is genetic drift. Thus, we can assume that
the effective population sizes are rather small and there
is little migration even between adjacent populations.
In spite of the small geographic scale used in this
study, the observed level of genetic differentiation
among P. mnemosyne populations is much higher than
in other Lepidoptera species (Bossart & Scriber, 1995;
Costa & Ross, 1994; Peterson, 1995). Our values are
64
comparable to those reported for species of low agility
such as Helix aspersa (FST = 0.13; Selander & Kaufman, 1975) and Euphydryas butterflies (FST ranges
from 0.09 to 0.12 in McKechnie, Ehrlich & White,
1975).
The level of genetic differentiation between the
completely isolated Sajólád population and the other
populations does not differ from that observed among
populations in general. Again this suggests that there is
no correlation between geographic distance and population differentiation. Consequently, we can conclude
that the eight samples from the Bükk mountains cannot be considered as coming from a single continental population with a fairly homogeneous gene pool.
Rather these samples represent separate populations.
In spite of the short distances between populations,
inter-migration seems to be restricted.
The genetic structure of Parnassius mnemosyne
populations has also been investigated in Southern
France (Napolitano, Geiger & Descimon, 1988; Descimon & Napolitano, 1993; Napolitano & Descimon,
1994). Here it was found that P. mnemosyne exists as
a large continental population with a relatively high
migration rate between different localities, but with
decreased gene flow among the peripheral colonies.
Our observations are in good agreement with their
results on the peripheral populations. We conclude that
the total investigated area in the Carpathian basin actually belongs to the marginal territory of the distribution
of the P. mnemosyne ariovistus subspecies group.
Acknowledgements
We thank Ward Watt (Stanford University), Kjetil Hindar (Norwegian Institute for Nature Research), and an
anonymous reviewer for significant comments on the
manuscript. This work was supported by OTKA 3179,
OTKA F-016688, OTKA 6067.
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Appendix 1
The extraction buffer contained 0.01M Tris-HCl, 1mM
EDTA, 1% saccharose, 6mM DTT pH = 7.5. The
buffer systems and electrophoretic conditions were as
follows:
Buffer system I: Tris-citrat buffer, pH = 7.0 (Shaw &
Prasad, 1970). Run for 5.5 h at 50mA. Buffer system
II: Boric acid-NaOH buffer, pH = 8.0 (Shaw & Prasad,
1970). Run for 6 h at 40 mA. Buffer system III: electrode buffer: 0.01 M Tris, 0.075M glycine, pH = 8.3,
gel buffer: 0.1 M Tris-HCl, pH = 8.9. Run for 8 h at
300 V.
Staining solutions (100 ml for one slice):
GPDH (EC 1.1.1.8): Buffer syst. I., staining solu-
tion: 200 mg -glycerophosphate, 10 ml 1 M Tris
(pH = 8.5), 1 ml 0.1 M EDTA, 25 mg NAD, 15 mg
NBT 1 mg PMS. GOT (EC 2.6.1.1): Buffer syst. II.,
staining solution: 640 mg DL-asparatic acid, 88 mg ketoglutaric acid, 60 mg pyridoxal 5-phosphate, 10 ml
2 M Tris (pH = 8.0), 100 mg Fast blue B salt. IDH
(EC 1.1.1.42): Buffer syst. I., staining solution: 70 mg
DL-isocitric acid, 5 ml 2 M Tris (pH = 8.3), 1 ml
0.1 M EDTA, 15 mg NADP, 15 mg NBT, 1mg MgCl2 ,
1 mg PMS. MDH (EC 1.1.1.37): Buffer syst. I., staining solution: 150 mg DL-malic acid, 10 ml 1 M Tris
(pH = 8.5), 1 ml 0.1 M EDTA, 25 mg NAD, 15 mg
NBT 1 mg PMS. SOD (EC 1.15.1.1): Buffer syst.II.,
staining solution: 10 ml 1 M Tris (pH = 8.5), 1 ml
0.1 M EDTA, 15 mg NBT 1.5 mg PMS. Incubation
was in light.
Agar overlay method: 144 mg agar-agar in 10 ml water
was added to 10ml staining solution. HK (EC 2.7.1.1):
Buffer syst. I. staining solution: 35 mg ATP, 70 mg
glucose, 100 mg galactose, 15 mg NADP, 15 mg NBT,
1mg MgCl2 , 0.1 ml 0.1 M EDTA, 0.5 ml 2 M Tris
(pH = 8.0), 12 u. glucose-6-phosphate dehydrogenase, 3 mg PMS. PGI (EC 5.3.1.9): Buffer syst. I.,
staining solution: 12 mg fructose-6-phosphate, 13 mg
NADP, 7 mg NBT, 1 mg MgCl2 , 0.5 ml 2 M Tris
(pH = 8.0), 4 u. glucose-6-phosphate dehydrogenase,
2 mg PMS. PGM (EC 2.7.5.1): Buffer syst. I., staining
solution: 80 mg glucose-1-phosphate, 15 mg NADP,
15 mg NBT, 1 mg MgCl2 , 0.1 ml 0.1 M EDTA, 0.5 ml
2 M Tris (pH = 8.0), 5 u. glucose-6-phosphate dehydrogenase, 3 mg PMS.
66
Appendix 2
Allele frequencies at five investigated loci in all 11 populations
Pops.
1
2
3
4
5
6
7
8
9
10
11
Pgm
A
B
C
D
E
0.009
0.557
0.330
0.104
0.000
0.029
0.500
0.265
0.088
0.118
0.120
0.680
0.150
0.050
0.000
0.082
0.786
0.133
0.000
0.000
0.125
0.594
0.250
0.031
0.000
0.043
0.783
0.174
0.000
0.000
0.000
0.625
0.344
0.031
0.000
0.031
0.796
0.082
0.092
0.000
0.063
0.613
0.188
0.138
0.000
0.033
0.683
0.283
0.000
0.000
0.167
0.548
0.286
0.000
0.000
Pgi
A
B
C
0.110
0.881
0.008
0.050
0.950
0.000
0.333
0.667
0.000
0.242
0.742
0.015
0.147
0.794
0.059
0.196
0.750
0.054
0.115
0.731
0.154
0.125
0.750
0.125
0.159
0.727
0.114
0.145
0.645
0.210
0.178
0.822
0.000
Hk
A
B
C
0.272
0.684
0.044
0.813
0.188
0.000
0.698
0.302
0.000
0.651
0.302
0.047
0.536
0.464
0.000
0.920
0.080
0.000
0.813
0.188
0.000
0.469
0.521
0.010
0.682
0.318
0.000
0.560
0.440
0.000
0.566
0.434
0.000
Idh
A
B
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
0.989
0.011
1.000
0.000
1.000
0.000
Gpdh
A
B
1.000
0.000
1.000
0.000
1.000
0.000
0.991
0.009
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
1.000
0.000
Appendix 3
Matrix of Cavalli-Sforza and Edwards (1967) arc genetic distances
Pops.
1
2
3
4
5
6
7
8
9
10
2
3
4
5
6
7
8
9
10
11
0.202
0.185
0.182
0.135
0.248
0.198
0.138
0.166
0.181
0.168
—
0.170
0.188
0.169
0.179
0.171
0.203
0.166
0.215
0.177
—
0.097
0.111
0.138
0.180
0.154
0.126
0.174
0.104
—
0.111
0.112
0.163
0.139
0.144
0.133
0.104
—
0.153
0.140
0.108
0.090
0.096
0.089
—
0.119
0.184
0.149
0.147
0.161
—
0.154
0.116
0.112
0.190
—
0.096
0.125
0.177
—
0.127
0.161
—
0.152