Sex differences in developmental plasticity and canalization shape population
divergence in mate preferences
Erik I. Svensson1,3, Anna Runemark1,2*, Machteld Verzijden1,* & Maren Wellenreuther1,*
1. Evolutionary Ecology Unit, Department of Biology, Lund University, SE-223 62
Lund, SWEDEN
2. Centre for Ecological and Evolutionary Synthesis (CEES), Department of Biosciences,
University of Oslo, NORWAY
3. Author for correspondence: erik.svensson@biol.lu.se
*. These authors contributed equally. Order of authorship alphabetical.
Supporting Results, Supporting Figures and Supporting Tables
We found no instances of null-alleles and no significant deviations from Hardy-Weinberg
equilibrium in the microsatellite data. Genetic divergence was low and FST-values ranged
from 0 to 0.0227 (Table S3; Fig. S1). Analyses using STRUCTURE showed the highest
support for two clusters. One was the outgroup in France and the other included all south
Swedish populations (Figs. S2-S4). This indicates either recent divergence or high levels of
gene flow between geographically close study populations. The estimated pairwise migration
rate (m) between populations ranged between 1% and 11% (Fig. 2; Table S4). These results
were consistent between runs, although the results have to be interpreted with some caution
given the low genetic divergence between populations. Together, the data suggest a scenario
with low genetic population divergence, presumably due to high gene flow.
To test whether observed behavioral differentiation in male and female mate
preferences between allopatric and sympatric populations (Fig. 3) were due to an effect of
sympatric populations being more genetically close than allopatric ones, we investigated if the
FST-values differed between ecological categories. We first tested if FST-values were higher
1
between allopatric-sympatric population pairs than between population pairs within each
ecological category, which we could reject (F1,19=0.37; P=0.55; Fig. S5A).
Next, we divided the population pairs into three ecological categories and
pairwise comparisons: allopatric vs. sympatric, allopatric vs. allopatric and sympatric vs.
sympatric (Fig. S5B). The divergence between populations between ecological categories
(allopatric-sympatric pairwise comparisons) was not significantly higher than that within
ecological categories (allopatric-allopatric and sympatric-sympatric pairwise comparisons;
F2,18=1.00; P=0.39; Fig. S5B).
We further tested whether our pairwise gene flow estimates within ecological
categories (allopatric-allopatric and sympatric-sympatric pairwise population comparisons)
exceeded that between ecological categories (allopatric-sympatric pairwise population
comparisons). We found no significant differences in estimated gene flow between these
categories (Fig. 2: F1,40=1.27; P=0.27; Fig. S6A). Neither did we find significant differences
between categories when these population pairs were divided into three categories (allopatricsympatric, allopatric-allopatric, sympatric-sympatric; F2,39=2.97; P=0.063; Fig. S6B).
2
Figure S1 Molecular genetic differentiation measured as pair-wise FST-values between all
southern Swedish populations. The color indicates the FST-values. Allopatric populations are
denoted by A and sympatric populations by S. As the FST-values are pair-wise properties this
is a symmetric matrix. The values on the diagonal are therefore per definition zero as they
refer to genetic differentiation of a population against itself.
3
Figure S2 Structure grouping of individuals for the K with highest support (see e.g. Figs S3S4). The mainly red section (left) consists of the seven study populations in southern Sweden,
whereas the green section shows the outgroup data from the C. splendens population in
France. This graph illustrates the low genetic divergence between the southern Swedish
populations.
4
Figure S3 Estimates of mean of Ln probability of data for successive values of K for all study
populations and the outgroup from France. The highest difference is between K=1 and K=2,
whereas this difference stagnates between K=2 and K=3. This supports K=2.
5
Figure S4 An alternative method to find the K with highest support is the Evanno method
(Evanno et al. 2005) where the difference in Ln(K) between successive K’s is divided by the
standard deviation of Ln(K) is used to find the best K for the data set. The K with the highest
ratio is supported, and the Evanno method hence gives further support to a K of 2, the seven
study populations in south Sweden forming one cluster and the population in France the other
cluster.
6
Figure S5 A) We found no significant differences in FST -values between population pairs
with different ecologies, e.g. allopatric-sympatric or the reverse (AS), and the same ecological
setting (allopatry-allopatry (AA) and sympatry-sympatry (SS); F1,19=0.37; P=0.55). B) There
were no significant differences in FST -values when we divided the population pairs into three
categories (allopatric-sympatric or the reverse, allopatry-allopatry and sympatry-sympatry;
F2,18=1.00; P=0.39). Bars denote 95% confidence intervals.
A.
7
B.
8
Figure S6 We found no significant differences in estimated migration rates between
population pairs with different ecologies, e.g. allopatric-sympatric or the reverse (AS), and the
same ecological setting (Fig. 2: allopatry-allopatry (AA) and sympatry-sympatry (SS);
F1,40=1.27; P=0.27). Below, we have also illustrated the estimated pairwise comparisons when
we used three ecological categories instead of two (as in Fig. 2). There were no significant
differences in estimated migration rates between these three ecological categories (F2,39=2.97;
P=0.063).
9
Table S1 Population abbreviations, population names, allopatry or sympatry, geographic
information, number of female preference trials, number of male preference trials and number
of genetic samples per population.
Abbre-
Population
Allopatry/
Latitude
viation
name
Sympatry
A1
Höje Å:
Allopatric
55.70220
Allopatric
Longitude
Female
Male
Genetic
tests
tests
samples
13.14379
80
30
23
55.94817
13.37418
71
20
18
Allopatric
55.70989
13.51850
46
20
14
Klingavälsån: Allopatric
55.62294
13.62378
67
20
-
Allopatric
56.86250
14.65878
35
-
-
Klingavälsån: Sympatric
55.63790
13.58549
91
39
22
Sympatric
55.65060
13.66987
74
-
23
Sympatric
56.21549
14.75463
65
-
10
Klingavälsån: Sympatric
55.60447
13.65638
-
60
23
-
-
90
Värpinge
A2
Rönne Å:
Stockamöllan
A3
Kävlingeån:
Harlösa
A4
Världs Ände
A5
Helge Å:
Gemla
S1
Naturreservat
S2
Åsumsån:
Omma
S3
Mörrumsån:
Rosendala
S4
Sövdemölla
Outgroup Loire
Allopatric
46.57-
0.051-
outgroup
47.26
2.313
10
Table S2 Statistical test (mixed-model analysis) of sex differences in population divergence
of mate preferences between allopatry and sympatry (Fig. 3C). R-code and statistical output
are provided below, as well as tests for model fit (AIC). “Pop” was a random factor that was
nested within “Ecology” (Model 2) or at the same level as the other factor (Model 1). There
was no significant difference (judged by comparing AIC-scores) between Model 1 and Model
2.
#Non-nested model
library(nlme)
library(lme4)
Model1 <- lme(Normresponse ~ Sex + Ecology + Sex*Ecology,random=~1|Pop,
data=dataset)
summary(Model1)
Linear mixed-effects model fit by REML
Data: dataset
AIC
BIC
logLik
-34.96687 -14.26064 23.48344
Random effects:
Formula: ~1 | Pop
(Intercept) Residual
StdDev:
0.2113623 0.2011628
Fixed effects: Normresponse ~ Sex + Ecology + Sex * Ecology
Value Std.Error DF
t-value p-value
(Intercept)
1.2127862 0.09720384 226 12.476731
SexMale
-0.7087726 0.03927372 226 -18.046992
EcologySympatry
-0.4426535 0.14694450
7 -3.012385
SexMale:EcologySympatry 0.2268260 0.06190037 226
3.664372
Correlation:
(Intr) SexMal EclgyS
SexMale
-0.131
EcologySympatry
-0.662 0.087
SexMale:EcologySympatry 0.083 -0.634 -0.181
Standardized Within-Group Residuals:
Min
Q1
Med
Q3
-3.72674793 -0.60123028 -0.02133273 0.52345999
0.0000
0.0000
0.0196
0.0003
Max
3.49495444
Number of Observations: 237
Number of Groups: 9
anova(Model1)
numDF
(Intercept)
Sex
Ecology
Sex:Ecology
1
1
1
1
denDF
226
226
7
226
F-value p-value
118.2295
417.8671
5.7041
13.4276
<.0001
<.0001
0.0483
0.0003
11
#Nested model
Model2 <- lme(Normresponse ~ Sex*Ecology, random=~Ecology|Pop,
data=dataset)
summary(Model2)
Linear mixed-effects model fit by REML
Data: dataset
AIC
BIC
logLik
-31.42115 -3.812842 23.71057
Random effects:
Formula: ~Ecology | Pop
Structure: General positive-definite, Log-Cholesky parametrization
StdDev
Corr
(Intercept)
0.2420580 (Intr)
EcologySympatry 0.1578728 -0.741
Residual
0.2011371
Fixed effects: Normresponse ~ Sex * Ecology
Value Std.Error DF
t-value p-value
(Intercept)
1.2128304 0.11059872 226 10.966044 0.0000
SexMale
-0.7077184 0.03928952 226 -18.012905 0.0000
EcologySympatry
-0.4431389 0.14111616
7 -3.140242 0.0164
SexMale:EcologySympatry 0.2276168 0.06162961 226
3.693303 0.0003
Correlation:
(Intr) SexMal EclgyS
SexMale
-0.115
EcologySympatry
-0.784 0.090
SexMale:EcologySympatry 0.074 -0.638 -0.188
Standardized Within-Group Residuals:
Min
Q1
Med
Q3
-3.75124524 -0.60029322 -0.02054388 0.53526730
Max
3.51364248
Number of Observations: 237
Number of Groups: 9
anova(Model2)
(Intercept)
Sex
Ecology
Sex:Ecology
numDF denDF F-value p-value
1
226 108.5495 <.0001
1
226 417.6155 <.0001
1
7
6.2033 0.0416
1
226 13.6405 0.0003
#Model fits (AIC-scores) of Model 1 vs. Model 2
AIC(Model1)
[1] -34.96687
AIC(Model2)
[1] -31.42115
#Comparing model fits (AIC-scores) of Model 1 vs. Model 2
anova(Model1,Model2)
Model df
AIC
BIC
logLik
Test
L.Ratio p-value
Model1
1 6 -34.96687 -14.260641 23.48344
Model2
2 8 -31.42115 -3.812842 23.71057 1 vs 2 0.4542781 0.7968
12
Table S3 Matrix of pair-wise FST estimates between study populations in Sweden (note that
the French outgroup population is not included here). Allopatric populations are denoted by A
and sympatric populations by S. Full population names and localities are provided in Table
S1.
A1
A2
A3
S1
S2
S3
S4
A1
0.0000
0.0097
0.0068
0.0000
0.0022
0.0046
0.0027
A2
ns
0.0000
0.0018
0.0134
0.0000
0.0000
0.0097
A3
ns
ns
0.0000
0.0000
0.0033
0.0038
0.0227
S1
ns
ns
ns
0.0000
0.0044
0.0127
0.0104
S2
ns
ns
ns
ns
0.0000
0.0000
0.0157
S3
ns
ns
ns
ns
Ns
0.0000
0.0058
S4
ns
ns
ns
ns
Ns
ns
0.0000
13
Table S4 Pair-wise migration rate estimates (m) for the southern Swedish populations
obtained using BayesAss. The estimates present the mean of the highest probability of the
posterior distribution from ten independent runs. Note that the matrix is not symmetric as the
migration rate from one population to another does not necessarily equal the migration rate
from the second population to the first.
A1
A2
A3
S1
A1
0.68859
A2
0.06826 0.69598 0.06899 0.02231
S2
S3
0.0494 0.06119 0.02277 0.10347 0.01166
0.056
S4
0.0629
0.0135 0.07496
A3
0.0661 0.04525 0.70372 0.03459 0.07388 0.01603 0.06039
S1
0.05178 0.03169 0.03476 0.73824 0.07258 0.01153 0.05943
S2
0.06478 0.06289 0.05954 0.01933
S3
0.05756 0.07174 0.05359 0.02429 0.05036
S4
0.10631
0.0434
0.7036 0.01127 0.07854
0.6888 0.05372
0.067 0.01542 0.03448 0.01109 0.72227
14