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Heredity66 (1991) 181—189
Genetical Society of Great Britain Received 30Apr11 1990
The significance of genetic erosion in the
process of extinction.
I. Genetic differentiation in Salvia pratensis
and Scabiosa columbaria in relation to
population size
R. VAN TREUREN,* R. BIJLSMA,* W. VAN DELDEN* & N. J. OUBORGI
* Department of Genetics, University of Groningen, Kerklaan 30, 9751 NN Haren, and tDepartment of Plant Ecology,
Institute for Ecological Research, P.O. Box 40, 6666 ZG Heteren, The Netherlands
As part of a programme to determine the importance of the loss of genetic variation for the
probability of population extinction, the amount of allozyme variation was determined in 14
populations of Salvia pratensis and in 12 populations of Scabiosa columbaria. Significant correla-
tions were found between population size and the proportion of polymorphic loci (Salvia:
r= 0.619; Scabiosa: r= 0.713) and between population size and mean observed number of alleles
per locus (Salvia: r =0.540; Scabiosa: r = 0.819). Genetic differentiation was substantially larger
among small populations than among large populations: in Salvia GST was 0.181 and 0.115,
respectively, and in Scabiosa 0.236 and 0.101, respectively. The results are discussed in relation to
genetic drift, inbreeding and restricted gene flow.
Keywords: conservation biology, extinction, genetic erosion, population size, Salvia pratensis,
Scabiosa columbaria.
Introduction
Dueto the activities of man, populations of many plant
and animal species have become small, fragmented and
isolated. Research is needed to develop effective
measures for conservation. Until the beginning of the
last decade conservation was mainly the domain of
ecologists, but recently much attention has been
focused on the importance of the population genetic
aspects (Soulé & Wilcox, 1980; Frankel & Soulé, 1981;
Schonewald-Cox et a!., 1983; Soulé, 1986, 1987).
Population genetic theory predicts that, as a con-
sequence of genetic drift and inbreeding, small popula-
tions will have decreased levels of genetic variation.
Even favourable alleles may be lost and the potential to
adapt to a changing environment may be seriously
diminished (Vrijenhoek, 1985). Moreover, inbreeding
results in increased levels of homozygosity which may
cause inbreeding depression (Frankel R., 1983). Both
processes may thus lead to 'genetic erosion', reduce the
fitness of individuals in a population and increase the
chance of the extinction of the population. Ultimately
this may lead to the extinction of the species. The
deleterious effects of genetic erosion in populations,
181
however, can be counteracted by gene flow renewing
the genetic variation.
Because experimental data about the significance of
genetic erosion in extinction are virtually absent, we
started a project to examine these processes in two
plant species in The Netherlands: Salvia pratensis and
Scabiosa columbaria. These species were selected
because: (i) the number of populations has significantly
declined in the last decades, (ii) they occur in both
small and large populations, (iii) both are thought to be
predominantly outbreeding. The research described in
this paper is part of a comprehensive research project
to determine the importance of genetic factors for
population extinction and to develop effective manage-
ment measures that could prevent species from becom-
ing extinct. In this paper we present data on the amount
of allozyme variation and the extent of genetic differen-
tiation in relation to population size.
Materials and methods
Both Salvia pratensis and Scabiosa columbaria are
gynodioecious, protandric perennials and are diploid
with 2n= 18 (Tutin eta!., 1972) and 2n= 16 (Tutin et
182 R. VAN TREUREN ETAL.
a!., 1976), respectively. Salvia occurs in dry, sunny,
calcareous grassland on river dunes and dikes,
Scabiosa in dry, grassy places on calcareous soils. The
number of (1 X 1 km) grid squares in which Salvia and
Scabiosa was observed, declined between 1950 and
1980 from 92 to 78 and from 82 to 52, respectively
(Mennema et a!., 1985). In 1988 only 39 populations
of Salvia and 24 populations of Scabiosa were
recorded (Ouborg eta!., 1989).
The location of the populations examined is given in
Fig. 1. The mean distance between the examined
populations and their nearest neighbouring population
was 4 km for Salvia and 7 km for Scabiosa. Because
both species are pollinated mainly by bees, which are
known to forage within considerably smaller distances
(Levin & Kerster, 1974), gene flow between popula-
tions by means of pollen was expected to be restricted.
Because seeds of both species have no special means of
transport, seed dispersal may even be less important
(Levin & Kerster, 1974).
In 1988, the size of small populations was deter-
mined by counting the total number of flowering indivi-
duals, whereas the size of large populations was
estimated by stratified sampling of square metres and
the subsequent extrapolation to total population area.
Populations were grouped in two distinct size classes
(small and large populations). This classification,
however, was partly arbitrary. Criteria were such that
the difference in population size between the largest
small population and the smallest large population had
to be substantial and that the difference in number of
populations in each size class had to be as small as
possible (Table 1).
Individual plants were sampled in all populations in
1988 by cutting pieces of leaf material. In small
populations as many plants as possible were sampled,
whereas in large populations about 50 individuals were
sampled with regular spacing, using the whole popula-
tion area. The samples were put in plastic bags with a
small amount of water and kept in a portable cooler. In
the laboratory the samples were stored in a refrigerator
(4°C) until the moment of electrophoretic analysis. The
activity of the enzymes remained sufficiently high for at
least 3 weeks. Of the 29 enzyme systems tested for
electrophoresis, 10 showed a sufficiently clear pattern
and were used for genetic analyses (Table 2).
Electrophoreticprocedure
Buffer systems. Tris-citrate pH 7.0, LiOH-borate pH
8.3 and Iris-borate EDTA pH 8.6. Apart from GPI,
lCD and PGD for Salvia, which were performed on
polyacrylamide, electrophoretic analyses were carried
out on starch gels. Electrophoretic methods and
recipes for buffers (except tris-borate EDTA pH 8.6)
and staining solutions (except SORDH) are described
Fig. 1 Location of the examined populations of Salvia pratensis (a) and Scabiosa columbaria (b) in The Netherlands. For
Salvia, the following three locations consisted of two (sub )populations (their interpopulational distances given between
brackets): 1(320 m), c (580 m) and b (160 m).
(a) (b)
030 60km 030 60km
GENETIC DIFFERENTIATION IN RELATION TO POPULATION SIZE 183
Table 1 Examined populations of Salvia and Scabiosa with their abbreviated name
(A), number of flowering (N) and sampled (n) individuals. Populations are grouped
according to size (see text)
Small populations (A) NnLarge populations (A) Nn
SalviaForten 1 ft 5501st o300 49
Forten 2 f2 14 14 Ruitenberg r300 50
Neerijnen n 17 17 Cortenoever 2 c2 310 66
Lexmond 130 20 Wilpse klei w400 50
Hoenwaard h46 34 Bijiand 2 b2 1000 36
Bijiand 1 b1 60 14 Koekoekswaard k1500 60
Cortenoeverl c1 60 10
Piekenwaard p61 43
Scab iosa
Hoenwaard h14 6 Terwolde t200 50
Kwartierse dijk kw 35 25 Wilpse klei wi 200 50
Ruitenberg r90 42 Bemelerberg b300 50
Kannerhei k 100 21 Wolfskop wo 25000 48
Zalk z118 30 01stJulianagroeve
Wrakelberg
ojw
50000
75000
100000
505050
Table 2 Enzymes studied and buffer-systems used for Salvia and Scabiosa
Enzyme Abbreviation E.C. number
Buffer pH
Salvia Scabiosa
Sorbitoldehydrogenase SORDH 1.1.1.14. 8.3 —
Malic enzyme ME 1.1.1.40. 8.3 —
Isocitratedehydrogenase lCD 1.1.1.42. 7.0 —
Phosphogluconate dehydrogenase PGD 1.1.1.44. 7.0 7.0
Peroxidase PEROX 1.11.1.17. 8.6 —
Glutamate—oxaloacetate transaminase GOT 2.6.1.1. 8.3 8.3
Phosphoglucomutase PGM 2.7.5.1. 8.6 8.6
Aconitase ACN 4.2.1.3. —8.6
Triose phosphate isomerase TPI 5.3.1.1. 8.6 8.3
Glucose phosphate isomerase GPI 5.3.1.9. 7.0 7.0/8.6
in Hofman (1988). The recipe of the tris-borate EDTA
buffer-system pH 8.6 was: 12.11 g Tris/1 aquadest
(0.1 M), 1.86 g EDTA/1 aquadest (0.005 M), adjust to
pH 8.6 with boric acid. The staining solution of
SORDH was: 50 ml 0.06 M Tris-HC1 pH 8.1 (7.27 g
Tris/1 aquadest, adjust to pH 8.1 with 25 per cent HC1),
125 mg sorbitol, 20mg NAD, 5 mg MTT, 1 mg PMS,
50 mg pyrazol and 50 mg sodium pyruvate. Because of
the complexity of some enzyme-activity patterns, due
to the presence of a gene duplication (R. Van Treuren
& R. Bijlsma, in preparation), electrophoresis of
Scabiosa for GPI was performed on two buffer
systems. On tris-citrate pH 7.0 electrophoretic mobility
was higher (better separated bands), whereas tris-
borate EDTA pH 8.6 gave a higher resolution (sharper
bands).
Estimation of genetic variation
Toestimate the amount of genetic variation, the follow-
ing measures were calculated: (i) the proportion of
polymorphic loci (P), (ii) the mean observed number of
alleles per locus (A0) and (iii) gene diversity (He). A
locus was considered polymorphic if the frequency of
the most frequent allele was less than 0.99. Gene
diversity and standard genetic distance were computed
184 R. VAN TREUREN ETAL.
according to Nei (1987) in which corrections were
made for small sample sizes.
Results
Enzyme variability is given in Table 3. Because the
allelic variation and number of subunits of Pgd-2 for
Scabiosa was only recently established, the results for
this locus were omitted from the genetic analyses. In
order to determine if the inheritance of the allozymes
was Mendelian, crosses were performed with plants
grown from seeds collected in 1987. Because not all
genotypes were represented in the seed samples, only
the relatively frequent variants could be tested (Table
4). No significant deviation from Mendelian inheri-
tance was found for any of the loci examined. Indepen-
dent segregation was observed for most loci, strong
linkage was only found between Pgd-1 and Gpi-2 of
Scabiosa. Recombination between these loci was
estimated to occur at a frequency of about 6 per cent
(R. Van Treuren & R. Bijisma, in preparation).
To establish the relationship between population
size and the amount of genetic variation, corrections
for differences in sample size were calculated in two
different ways. Firstly, Spearman's rank correlation
Table 3 Enzyme variability of Salvia and Scabiosa. Loci coding for similar enzymes
were numbered in ascendence according to the electrophoretic mobility of their
gene products. Alleles were named according to their relative position to the N
(normal) allele, which was present in every population and which was usually the
most frequent. I was intermediate between S (slow) and N, 12 between N and F
(fast)
Salvia Scabiosa
Locus Isozyme
structure Alleles Locus Isozyme
structure Alleles
Sordh
Me-i
lcd-i
Pgd-i
Pgd-2
Perox
Got-i
Got-2
Pgm-i
Pgm-2
Tpi-i
Tpi-2
Gpi-i
Monomeric
Dimeric
?Dimeric
Dimeric
Monomeric
Dimeric
Dimeric
Monomeric
Monomeric
Dimeric
Dimeric
?
5, NS,11,N
N5, N, F
5, N, F
S,11,N,F
S,11,N,F
S, N, F
S, N, F
S,11,N,12,F
S,11,N
N,FN
Pgd-i
Pgd-2
Pgd-3
Got-I
Pgm-1
Pgm-2
Acn-l
Acn-2
Tpi-i
Tpi-2
Gpi-i
Gpi-2
Gpi-3
Dimeric
Dimeric
Monomeric
Dimeric
Monomeric
?Monomeric
Monomeric
Dimeric
Dimeric
Dimeric
Dimeric
?
5, N, F
S,NS, N5, NS, N, F
NS,N,F
S, N5, N, F
N,FS,N,F
S,I,N,I2,F
N
Table 4 Parental genotypes (P) and genotype numbers in the F1-generation with Chi-square values for the deviation from
Mendelian segregation
Salvia Scabiosa
Locus Pgd-2 Perox Got-i Got-2 Pgm-i Pgm-2 Tpi-1 Pgd-1 Got-i Tpi-i Gpi-i Gpi-2
PNFSN NFNF SNSN SNSN NFNF NNNI2 INNN SNSN SNSN SNSN SNSN NFNF
F1 SN 7
SF 14
NN 9
NF 7
NN1O
NF 11
FF 8
SS 6
SN 20
NN 16
SS 5
SN 15
NN 9
NN 9
NF 13
FF 7
NN22
NI2 15 11N19
NN 18 SS 22
SN 61
NN 24
SS 23
SN 58
NN 26
SS 16
SN 41
NN 12
SS 8
SN 16
NN 10
NN17
NF 40
FF 15
x2 3.541 1.966 4.857 1.138 0.586 1.324 0.027 2.178 0.925 2.913 0.353 1.000
GENETIC DIFFERENTIATION IN RELATION TO POPULATION SIZE 185
C)
0anS
V
0)0000a
C,VC,
C,
Ij°bL,
::
0-IS
(a)
0-619
1-00 10 00 000 lOOC
I-6C
1-45
130
I-IS
1-OC
(b ••••
—f—1T
r0-540
10 00 1000 i00C
0-20
::
005
(c)
•
:
=0-309
I10 100 1000 10000 - 0
PpulQtion size
100 000 10000 100000
Popu'ation size
coefficients were calculated between population size,
sample size and the amount of genetic variation. Sub-
sequently, by keeping sample size constant, the partial
correlation coefficients (Sokal & Rohlf, 1981) between
population size and the amount of genetic variation
were computed. Significant correlations were found
between population size and the proportion of poly-
morphic loci (Salvia: r=0.807, t=4.534, P<0.0005;
Scabiosa: r'0.622, t=2.386, 0.01<P<0.025) and
between population size and the mean observed
number of alleles (Salvia: r=0.570, t=2.303,
0.01 <P< 0.025; Scabiosa: r= 0.653, t=2.584,
0.01 <P< 0.025), although it should be stressed that P
and A0 are not independent measures. However, no
significant correlation was found between population
size and gene diversity (Salvia: r=0.051, t=0.169,
0.4<P; Scabiosa: r0.135, t0.410, 0.3<P<0.4).
Secondly, repeated samples of equal size were taken
from the master file (Salvia: sample size =5; Scabiosa:
Salvia
sample size =6), the number of repetitions in each
population were determined by the original sample
size. Subsequently, the mean values of P, A0 and He
were used in a weighted regression (Fig. 2). Again,
significant positive correlations were found between
the population size and proportion of polymorphic loci
(Salvia: r= 0.6 19, t=2.73, 0.005 <P< 0.01; Scabiosa:
r 0.713, t=3.21, 0.001 <P< 0.005) and between
population size and the mean observed number of
alleles (Salvia: r=0.540, t=2.22, 0.01<P<0.025;
Scabiosa: r= 0.819, t=4.51, 0.0005 <P< 0.001), but
not between the population size and gene diversity
(Salvia: r=0.309, t=1.12, 0.1<P<0.15; Scabiosa:
r=0.490, t=1.78, 0.05<P<0.075). The lack of
correlation between the population size and He in both
species was mainly due to the smallest population
showing a relatively high value and the largest popula-
tion showing a relatively low value.
To establish the extent of genetic differentiation
Scab ass
0
a0S0a0C00a0U-
0-45
0-30
0-IS
(a
IN.
NU
r0-713
10 10 100 000 10000 100000
1-45
(-30
0-I5
N
U
r=0-819
10 000 000 0000 00000
0-2C c)
0-15 II
NUU
0-10
•.
0-05 r0 490
Fig. 2 Weighted regression of proportion of polymorphic loci (a), mean observed number of alleles (b) and gene diversity
(c) on population size (log scale) for both Salvia and Scabiosa. r is the correlation coefficient.
186 R. VAN TREUREN ETAL.
Table 5 Analysis of gene diversity (Nei, 1987) in populations of Salvia and Scabiosa, together with the Chi-square value of G1
for the deviation from zero. The coefficient of gene differentiation (GST ) is the proportion of the total gene diversity (HT) that
can be attributed to the average gene diversity between populations (HT —Ha). Deviation of GST from 0 (no differentiation) was
tested by using the Chi-square test of heterogeneity of gene frequencies (Workman & Niswander, 1970)
Salvia Scabiosa
Locus HT HGST x2 Locus HT H5 GST x2
Allpopulations Sordh
Me-i
lcd-i
Pgd-i
Pgd-2
Perox
Got-i
Got-2
Pgm-i
Pgm-2
Tpi-i
Tpi-2
Gpi-i
0.034
0.077
0.000
0.094
0.214
0.562
0.198
0.128
0.115
0.190
0.140
0.015
0.000
0.030
0.061
0.000
0.072
0.197
0.436
0.167
0.118
0.101
0.165
0.129
0.014
0.000
0.122
0.203
—0.237
0.081
0.224
0.155
0.080
0.120
0.130
0.073
0.076
—
58.6**
202.9**
—755**
131.1**
4349**
294.4**
100.6**
944**
209.2**
124.0**
41.1**
—
Pgd-1
Pgd-3
Got-i
Pgm-1
Pgm-2
Acn-i
Acn-2
Tpi-1
Tpi-2
Gpi-1
Gpi-2
Gpi-3
—
0.237
0.022
0.271
0.228
0.000
0.008
0.095
0.257
0.044
0.130
0.262
0.000
—
0.206
0.021
0.213
0.178
0.000
0.007
0.083
0.231
0.041
0.102
0.199
0.000
—
0.131
0.055
0.212
0.220
—0.035
0.122
0.103
0.078
0.216
0.238
——
190.9**
34.8**
170.4**
252.0**
—38.4*
92.5**
122.8**
549**
260.6**
417.5**
——
Populations (all loci)
All 0.136 0.115 0.156 0.129 0.107 0.175
Small 0.128 0.105 0.181 0.131 0.100 0.236
Large 0.144 0.127 0.115 0.124 0.112 0.101
*001 <P<0.025.
P< 0.0005.
among populations, an analysis of gene diversity was
performed (Table 5). Significant differentiation was
found for alllociof both species. For all loci combined,
GST was 0.156 and 0.175 for Salvia and Scabiosa,
respectively. A subsequent analysis of gene diversity hi
the group of small populations and in the group of
large populations showed that the coefficient of gene
differentiation was substantially higher in the group of
small populations (Salvia: G5T=O.lSl and 0.115,
respectively; Scabiosa: GST = 0.236 and 0.101, respec-
tively).
Discussion
The basic assumption underlying our research project
was the hypothesis that, as a consequence of genetic
drift, inbreeding and restricted gene flow, small and
isolated populations show decreased levels of genetic
variation. The smaller number of variable loci and the
smaller number of alleles found in the small popula-
tions are in agreement with this prediction. Similar
results have been reported by Hamrick et at. (1979),
Levin etal. (1979), Schmidtke & Engel (1980), Moran
& Hopper (1983) and Karron (1987). No significant
correlation was found between population size and
gene diversity. However, 'rare' alleles reach high
frequencies (possibly due to genetic drift) only in small
populations. This effect will inflate He in small popula-
tions and consequently weaken the correlations
between He and the population size. Therefore, gene
diversity appears not to be a useful comparative
measure of genetic variation in small populations.
Moreover, many other population characteristics, such
as population structure (neighbourhood size, relative
plant density, etc.), effective population size and breed-
ing system might affect not only He but also the other
measures of genetic variation. Varvio-Aho (1981) for
example showed that gene diversity in the Finnish
watertrider was not correlated with population size
but clearly with effective population size. The impact of
these other population characteristics is currently
being investigated.
If genetic drift predominantly affects allelic fre-
quencies in populations, and levels of gene flow
between populations are low, population genetic
theory predicts genetic differentiation between popula-
tions. The results of the analysis of gene diversity agree
with this prediction. Loveless & Hamrick (1984)
analysed the available data that describes genetic
differentiation from a large number of studies and
GENETIC DIFFERENTIATION IN RELATION TO POPULATION SIZE 187
computed the mean GST values for a number of
variables. They found that GST was 0.118, 0.109 and
0.077 for predominantly outcrossing species (n =76),
dioecious species (n =3) and long-lived perennials
(n =48), respectively. The mean GST of 43 predomi-
nantly outcrossing, long-lived perennials was 0.068.
Compared to these values, Salvia (GST= 0.156) and
Scabiosa (GST =0.175) show substantial genetic differ-
entiation, probably resulting from a significant amount
of genetic drift in the small populations. This explana-
tion is supported by the finding that small populations
are more differentiated from each other than are large
populations. Together with the observation that
average gene diversity did not differ substantially
between the group of small and large populations
(Table 5), our results are similar to those of Brakefield
(1989). Rich et a!. (1979) also found a significant
increase in the variance of allelic frequencies among
populations due to genetic drift and showed that this
increase was inversely proportional to population size.
This agrees with our observation that the rare alleles
are found in high frequency only in small populations,
resulting in larger variances of allelic frequencies and
subsequently larger GST values in the group of small
populations.
If allelic frequencies in populations are predomi-
nantly affected by genetic drift and gene flow between
populations is restricted, it is also to be expected that
genetic differentiation occurs even within relatively
short distances. No significant correlations are found
between geographic and genetic distances (Salvia:
r= —0.022, t= —0.206, P<0.4; Scabiosa: r=0.167,
t=1.357, 0.075<P<0.1), which suggests that gene
flow is indeed restricted. The genetic structure of both
species resembles an island model of population struc-
ture, as found for Desmodium nudi:florum (Schaal &
Smith, 1980) and Sarracenia purpurea (Schwaegerle &
Schaal, 1979), where populations are geographically
isolated from each other with the chance of gene flow
between populations being greatly reduced.
Estimates of the average level of gene flow between
natural populations can be derived from the GST values
(Slatkin & Barton, 1989). GST values of 0.156 (Salvia)
and 0.175 (Scabiosa) are equivalent to Nm= 1.166 and
Nm =0.990 respectively, which means about only one
migrant every generation. It has been suggested that the
exchange of a single individual per generation among
small endangered (sub)populations is sufficient to have
them behave almost as one panniictic population (e.g.
Franklin, 1980; Frankel & Soulé, 1981; Allendorf,
1983; and Frankel, 0.11., 1983). This general guideline
for the management of small populations has been
deduced from the equilibrium theory of Wright's
infinite island model (Wright, 1931). However, popula-
tions are generally not in equilibrium and the number
of subpopulations is often small. Therefore, Varvio et
a!. (1986) studied the dynamics of genetic differentia-
tion by using the finite island model and showed that
the values of H, HT and GST in transient populatioils
depend on the pattern of population subdivision and
that it may take time for them to approximate the equi-
librium values. Furthermore, the problem is compli-
cated, among others, by fluctuating population sizes,
subdivision and extinction of subpopulations. They
therefore concluded that a single guideline, e.g. the 'one
migrant per generation' rule, is not theoretically well
justified.
In practice it is difficult to separate the role of selec-
tive and non-selective forces in genetic differentiation
(Varvio-Aho, 1983). A way to examine the problem is
to investigate whether the gene frequency variation is
homogeneous over loci. If so, genetic differentiation
is most likely to be the result of random processes
because they affect all loci simultaneously and to the
same extent (Lewontin & Krakauer, 1973; Schaal,
1975; Varvio-Aho, 1983). FST values for individual
alleles range from 0.031 to 0.243 (Salvia) and from
0.018 to 0.450 (Scabiosa). The ratio observed/
expected variance in FST which is Chi-square/d.f.
distributed (Lewontin & Krakauer, 1973) is 2.264
(0.0005 <P< 0.00 1) and 3.332 (P< 0.0005) for Salvia
and Scabiosa respectively, indicating that the differen-
tiation of gene frequencies is clearly non-random. It
seems unlikely, therefore, that the genetic constitution
of both species can be entirely accounted for by
random processes.
The amount of allozyme variation is clearly corre-
lated with population size, the small populations being
less variable. The genetic structure of Salvia and
Scabiosa in The Netherlands can most satisfactorily be
explained by an island model of population structure,
with restricted gene flow between populations. This
may imply that: (i) small populations are also less
variable with respect to favourable alleles and/or fixed
for deleterious ones, as a result of genetic drift and
inbreeding, and/or (ii) small populations have reduced
evolutionary potential but are well adapted to their
current environment, as a result of selective forces.
Experiments are planned to reveal whether: (i) plants in
small populations show decreased fitness due to
inbreeding depression, and/or (ii) plants in small
populations experience different environmental condi-
tions to which they have become adapted. The out-
come of these experiments will be used to evaluate the
effectiveness of measures proposed to restore the level
of genetic variation. Hybridization of populations, for
example, will increase genetic variability and fitness
when populations are suffering from inbreeding
188 R. VAN TREUREN ETAL.
depression but will result in outbreeding depression
(Templeton, 1986) when populations have been
adapted to differential local conditions.
Acknowledgements
We would like to thank an anonymous reviewer for
constructive comments on the manuscript and A. C.
Boerema, J. Haeck and K. Reinink for support in
carrying out the experiments. This research project is
partly subsidized by the Ministry of Agriculture,
Nature Management and Fisheries.
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