Journal of
Plant Ecology
VOLUME 3, NUMBER 1,
PAGES 41–48
MARCH 2010
doi: 10.1093/jpe/rtp017
Advanced Access published
on 7 September 2009
available online at
www.jpe.oxfordjournals.org
On the relationship between plant
species diversity and genetic
diversity of Plantago lanceolata
(Plantaginaceae) within and
between grassland communities
Nidal Odat1,2, Frank H. Hellwig3, Gottfried Jetschke1 and
Markus Fischer4,*
1
Institute of Ecology, Friedrich-Schiller-University, Dornburger Straße 159, 07743 Jena, Germany
Department of Biology, Al-Hussein Bin Talal University, PO Box 20, Ma’an, Jordan
3
Institute of Systematic Botany, Friedrich-Schiller-University, Philosophenweg 16, D-07743 Jena, Germany
4
Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern, Switzerland
*Correspondence address. Institute of Plant Sciences, University of Bern, Altenbergrain 21, CH-3013 Bern,
Switzerland. Tel: +41-31-631-4943; Fax: +41-31-631- 4942; E-mail: [email protected]
2
Abstract
Aims and Methods
The relationship between genetic diversity and species diversity and
the underlying mechanisms are of both fundamental and applied interest. We used amplified fragment length polymorphism (AFLP) and
vegetation records to investigate the association between genetic diversity of Plantago lanceolata and plant species diversity using 15
grassland communities in central Germany. We used correlation
and partial correlation analyses to examine whether relationships
between genetic and species diversity were direct or mediated by
environmental differences between habitats.
Important Findings
Both within- and between-population genetic diversity of P. lanceolata were significantly positively correlated with plant species diver-
INTRODUCTION
Species diversity of a community and genetic diversity of a species may covary positively within and between sites due to the
possible effects of drift, selection and species turnover (e.g.
Antonovics 1971; Gugerli et al. 2008; Odat et al. 2004; Vellend
2004, 2005). Within sites, local habitat characteristics may affect the niche width (Van Valen 1965), which, in turn, may
similarly affect both the population size of a species and the
species diversity of a community and thus lead to a positive
relationship between genetic and species diversity (Mitton
1997; Nevo 2001; Prentice et al. 1995), because larger popula-
sity within and between sites. Simple and partial correlations
revealed that the positive correlations indirectly resulted from the
effects of abiotic habitat characteristics on plant species diversity
and, via abundance, on genetic diversity of P. lanceolata. Thus, they
did not reflect a direct causal relationship between plant species
diversity and genetic diversity of P. lanceolata, as would have been
expected based on the hypothesis of a positive relationship between
plant species diversity and niche diversity.
Keywords: AFLP d beta
diversity d biodiversity d conservation d ecological
niche d genetic diversity d species richness
Received: 19 August 2009 Accepted: 19 August 2009
tions normally are more genetically diverse (Frankham 1996;
Leimu et al. 2006). For example, in habitats of high productivity we might expect, based on a simple prediction of the more
individuals hypothesis (Srivastava and Lawton 1998), an increase in species number accompanied by an increase in the
total abundance of a species, which, in turn, may lead to higher
genetic diversity within a species. However, the relationship
maybelessstraightforwardbecause,forinstance,atmoreproductive sites a decrease in species richness may occur (Rosenzweig
and Abramsky 1993), which may decrease genetic diversity
by decreasing niche diversity. Moreover, higher species richness
may cause a lower average relative abundance per species
Ó The Author 2009. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
All rights reserved. For permissions, please email: [email protected]
42
and may thus even reduce the population size and genetic
variation of most species (Roscher et al. 2008; Valone and
Hoffman 2003).
Between sites, random processes may result in a change in
the number of genetic variants in populations and in the species composition of communities (Hubbell 2001) and thus lead
to a positive relationship of between-site genetic diversity and
diversity in plant species composition, i.e. beta diversity. Alternatively, species turnover and selection, i.e. variation in selection due to habitat characteristics between sites, may also affect
genetic diversity and species composition (Legendre 2008) and
thus lead to a positive relationship of genetic diversity and species beta diversity between sites (Vellend 2005). Moreover,
variation in habitat conditions across sites such as differences
in elevation, soil characteristics and other biotic factors may
affect species composition via changes of patterns of local extinction and colonization (Borrvall et al. 2000) and at the same
time may generate significant barriers to gene flow, e.g. via
effects of phenology, and thus lead to increased genetic differentiation between local populations of a species (Linhart and
Grant 1996; Lugon-Moulin et al. 1999).
Here, we hypothesize that the association between grassland
plant species diversity and genetic diversity of a species may be
positive both within and between sites. Moreover, we propose
that such a relationship rather is indirect and mediated by environmental variation between sites rather than direct and causal.
We investigated the relationship between the genetic diversity of Plantago lanceolata and plant species diversity within and
between 15 grasslands in central Germany. We suggest that
studying such relationships is useful for fundamental biodiversity research and for conservation biology. For example, it is
important to know whether conservation efforts implemented
to positively affect one level of diversity, such as species diversity, are likely to also positively affect other levels, such as genetic diversity of a species, or whether conservation conflicts
may occur.
The grassland communities in our study sites vary in plant
species composition and species richness, probably as a result
of the intensity of management and the history of land use in
the past (Ellenberg 1996). Plantago lanceolata is a long-lived
outcrossed perennial, which is common enough to be found
at all study sites but not so abundant that it would be expected
to occur in large populations at all sites. From its life history, we
expect some genetic differentiation between populations and
most of its genetic variation to reside within populations
(Kuiper and Bos 1992; Nybom 2004). We estimated genetic
diversity using amplified fragment length polymorphism
(AFLP; Mueller and Wolfenbarger 1999; Vos et al. 1995).
Specifically, we aim to address the following questions: (i) Is
genetic diversity of P. lanceolata correlated with grassland plant
species diversity within and among sites? (ii) Are genetic diversity of P. lanceolata and species diversity correlated with environmental variables? and (iii) If so, does this suggest that the
relationship between genetic and species diversity is due to indirect mediation via environmental variation
Journal of Plant Ecology
MATERIALS AND METHODS
Study species, study sites and plant material
Plantago lanceolata L. (Plantaginaceae) is a rosette perennial
herb that commonly inhabits base-rich meadows and waysides. Its distribution covers most of Europe and north-western
Asia (Rothmaler 1996). Plantago lanceolata is self-incompatible,
wind pollinated and flowers from May through early September
(Grime et al. 1988).
Our 15 study populations of P. lanceolata were randomly selected among 20 montane hay meadows in a plateau-like
mountain range of the Thuringer Schiefergebirge/Frankenwald in central Germany. The meadows are all situated between 500 and 840 m above sea level. All meadows had
been managed at low intensity for at least 10 years prior to
our sampling with one or two cuts per year (in June/July
and in September), without any fertilization and without
any livestock grazing. The sites had been chosen for a larger
project in order to represent a gradient in plant species diversity from ;10 species per square meter in the species-poor
meadows to ;40 species in the most diverse mountain hay
meadows (Stein et al. 2008). Pairwise geographical distances
between our study populations ranged from 1 to 28 km.
At each of the 15 study sites with P. lanceolata populations,
we recorded the presence and relative abundances of all higher
plant species in an area of 6 3 6 m2 composed of four separate
quadrats of 3 3 3 m2. In some of our study sites, the abundance
of P. lanceolata was so low that it was absent from recording
plots. In these cases, we scored the abundance of P. lanceolata
as zero, although it was of course present at the site (see
Table 1).
At each site, we randomly sampled two to four leaves of 8–
10 (in three populations, 5–6; in one population, 27) flowering
P. lanceolata plants that were at least 5 m apart. The sampled
leaves of all 142 plants were immediately placed in drying silica
gel for transportation to the DNA extraction lab in Jena.
AFLP diversity
Template genomic DNA from individual plants was prepared as
described in detail by Krüger et al. (2002). The AFLP procedure
was performed according to Vos et al. (1995) using the AFLPÒ
Core Reagent Kit (Invitrogen Life Technologies, Karlsruhe,
Germany), with a few modifications as outlined in Odat et al.
(2004). After a survey of 40 plants from five populations with
26 primer pairs, we used four selective primer pairs (EcoRIAAC/MseI-CCT, EcoRI-AAG/MseI-CCG, EcoRI-AGG/MseICAA and EcoRI-AAG/MseI-CGA; MWG Biotech AG, Ebersberg, Germany) to screen all 142 plants.
Statistical analysis
Genetic diversity of Plantago lanceolata within and
between populations
We established the presence–absence (1/0) matrix of AFLP
bands for each of the 142 plants with the help of RFLPscanä
version 2.1 (Scanalytics Inc., Fairfax, VA, USA). We estimated
Odat et al.
|
Species diversity and genetic diversity
43
Table 1: plant community diversity, abundance and gene diversity of Plantago lanceolata and means of the Ellenberg’s indicator values for
nutrients and soil reaction for the 15 studied grassland sites (see Materials and Methods)
Site
Plant species
number
Plant species
evenness
Abundance of
P. lanceolata
Gene diversity of
P. lanceolata
Nutrients
Soil
reaction
1
26
0.238
0.00
0.191
2
24
0.215
0.00
0.190
9
6.265
5.880
8
6.406
3
33
0.234
9.50
6.566
0.221
9
6.348
4
31
0.205
5.418
0.00
0.156
5
6.869
6.449
5
21
6
38
0.195
0.00
0.188
6
7.139
6.091
0.292
13.00
0.221
9
3.946
7
4.343
33
0.397
11.25
0.208
9
4.251
4.829
8
38
0.249
14.25
0.230
10
4.498
4.910
9
36
0.228
2.25
0.312
27
3.642
4.143
10
37
0.269
17.50
0.256
10
5.165
4.736
11
36
0.260
11.75
0.214
9
4.912
4.459
12
24
0.220
0.00
0.235
9
6.176
5.393
13
33
0.210
0.00
0.207
8
5.971
4.876
14
31
0.240
21.25
0.245
6
3.859
4.439
15
28
0.227
5.50
0.218
8
3.566
4.289
n
Species number and evenness of higher plants were obtained from records of plant species presence and abundance in four randomly selected 3- 3
3-m2 plots per site. Gene diversity was estimated using AFLP.
within-population genetic diversity of P. lanceolata as gene diversity HE after Nei (1973) with the software POPGENE (Yeh
et al. 1997). We tested whether the unequal sample size of our
populations (see Table 1) influenced the estimate of withinpopulation genetic diversity by conducting a multiple random
reduction approach (Leberg 2002). To this end, we re-examined
the AFLP gene diversity after reducing the original sample size
of each population to match the smallest sample size (i.e.
five individuals) in our data set. This procedure was repeated
100 times and an average of genetic diversity calculated. This
turned out to be very closely and highly significantly related
to the estimate based on all samples (Spearman’s r = 0.935,
P < 105).
To estimate genetic differentiation between populations of
P. lanceolata, we calculated pairwise genetic distances, UST (an
analog of FST), with analysis of molecular variance (AMOVA;
Excoffier et al. 1992).
Plant community diversity within and between sites
We quantified species diversity at each site as species richness
and species evenness. We estimated evenness (Evar), which is
based on the variance in species abundance and is independent
of species richness, according to Smith and Wilson (1996) as
follows:
s
s
.
Evar = 1 ð2=pÞarctan + lnðXj Þ + lnðXk Þ=S 2 S
j=1
k=1
where S is the number of species in a community and Xk the
abundance of the kth species. With the software PC-ORD, we
calculated a Bray–Curtis coefficient used as a distance measure
in a pairwise 15 3 15 matrix of grassland communities based
on the difference in relative abundances of all species across
sites (Faith et al. 1987).
Ecological conditions at sites and differences between sites
To characterize ecological conditions at each of our study site, we
used the occurrence and abundance of different plant species to
calculate the means of Ellenberg’s indicator values for levels of
light, temperature, continentality (rather continental versus
rather oceanic climate), moisture, soil reaction (indicating pH
preference and tolerance) and productivity (Ellenberg et al.
1992; Ozinga et al. 2005). In central Europe, this system of indicator values has been shown to be an accurate method for inferring the prevailing environmental conditions at a site (e.g.
Diekmann 2003; Schaffers and Sýkora 2000). These values score
each species for specific environmental variables and indicate
the conditions under which each species is usually found in
the field. To describe ecological differences between pairs of sites,
we calculated a 15 3 15 Euclidian distance matrix based on the
six-dimensional space spanned by the Ellenberg coordinates.
Relationship between population genetic diversity of
Plantago lanceolata and local plant community diversity
We tested whether population genetic diversity of P. lanceolata
within populations was related to local plant community diversity (species richness and species evenness) within sites.
We also tested whether gene diversity was related to the abundance of P. lanceolata and to any of Ellenberg’s indicator values
at each studied site (Table 1). To see whether the relationship
between genetic diversity and plant community diversity is
44
Journal of Plant Ecology
likely to be direct, i.e. independent of the influence of
Ellenberg’s values or the abundance of Plantago, we used partial
correlations to test how the observed relationship between AFLP
genetic diversity and species diversity changed after correcting
for these potential determinants of AFLP genetic diversity.
To test for a relationship between genetic diversity of P. lanceolata among populations and plant community diversity
among sites, we did a Mantel (1967) test with the software
ZT (Bonnet and Van de Peer 2002). First, we tested the relationship among the 15 3 15 matrix of pairwise genetic distances (UST) between P. lanceolata populations and the 15 3 15
matrix of pairwise distances in plant community composition
(Bray–Curtis coefficient) with a simple Mantel test. To investigate whether this relationship could have been influenced by
geographical distances and or ecological differences between
sites, we tested for correlations of both pairwise genetic and
community distances with geographic distances and with ecological distances using simple Mantel tests. Finally, to study the
relationship between genetic and plant community distances
independent of the possible confounding effects of geographic
and or ecological distances, we performed partial Mantel tests
(Manly 1997).
RESULTS
Genetic diversity of Plantago lanceolata within and
between populations
The four selective primer pairs enabled us to score 259 AFLP
loci, of which 59.79% were polymorphic. Gene diversity HE
within the studied populations of P. lanceolata ranged from
0.156 to 0.312 (Table 1). When we partitioned total AFLP ge-
netic variation of Plantago with AMOVA, we found that most
genetic diversity resides within populations (90.30%).
AMOVA also showed that the genetic diversity across all populations, i.e. genetic differentiation, was statistically highly significant (9.70% of variance resided between populations,
global UST = 0.097, P < 0.0001). The pairwise genetic distances
UST between populations of P. lanceolata ranged from 0.004 to
0.208. Of the 105 pairwise genetic distances between populations, 101 were statistically significant (Table 2).
Relationship between population genetic diversity
of Plantago lanceolata and local plant community
diversity within sites
Within-population gene diversity HE of P. lanceolata was significantly positively correlated with plant species number (n = 15,
Spearman’s r = 0.516, P = 0.049; Fig. 1a) and marginally, positively, significantly correlated with species evenness at a site
(n = 15, Spearman’s r = 0.486, P = 0.066). Additionally, the
number of AFLP polymorphic loci was higher with higher species number (Spearman’s r = 0.541, P = 0.037) and species
evenness at a site (Spearman’s r = 0.504, P = 0.055). HE
was significantly higher at sites with lower Ellenberg reaction
values, lower Ellenberg nutrient values and higher abundance
of P. lanceolata, and these three measures were highly significantly correlated with each other (Table 3).
In partial correlations, where we corrected for variation in
Ellenberg’s reaction values, Ellenberg’s nutrient values, or the
abundance of P. lanceolata, the relationship between AFLP genetic diversity and species diversity was weak and nonsignificant (Table 4). Moreover, when we held the species
number constant, only the correlation between genetic
Table 2: pairwise distances in genetic diversity of Plantago lanceolata (UST, measured with AFLP, below diagonal) and in plant community
composition (measured as Bray–Curtis coefficient, above diagonal) between the 15 studied grassland sites
Population
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
1
—
0.181
0.701
0.607
0.589
0.872
0.886
0.824
0.952
0.754
0.763
0.739
0.564
0.916
0.946
2
0.140
—
0.711
0.573
0.614
0.884
0.893
0.824
0.958
0.758
0.769
0.759
0.573
0.922
0.955
3
0.054
0.092
—
0.700
0.706
0.817
0.796
0.711
0.849
0.501
0.675
0.710
0.631
0.809
0.817
4
0.084
0.158
0.100
—
0.627
0.752
0.857
0.784
0.935
0.764
0.793
0.784
0.719
0.883
0.933
5
0.116
0.155
0.114
0.087
—
0.875
0.933
0.868
0.963
0.792
0.786
0.741
0.685
0.946
0.971
6
0.135
0.199
0.144
0.167
0.136
—
0.409
0.402
0.569
0.615
0.567
0.772
0.707
0.413
0.476
7
0.110
0.186
0.108
0.146
0.132
0.034
—
0.282
0.437
0.595
0.614
0.811
0.646
0.387
0.368
8
0.131
0.208
0.147
0.156
0.126
0.069
0.032
—
0.491
0.530
0.502
0.705
0.581
0.332
0.386
9
0.084
0.118
0.075
0.096
0.082
0.064
0.050
0.053
—
0.600
0.586
0.891
0.744
0.414
0.289
10
0.133
0.151
0.099
0.157
0.127
0.099
0.098
0.115
0.017
—
0.380
0.626
0.550
0.445
0.635
11
0.150
0.169
0.112
0.170
0.159
0.110
0.120
0.135
0.029
0.004
—
0.551
0.674
0.403
0.575
12
0.131
0.175
0.124
0.155
0.130
0.097
0.099
0.084
0.051
0.059
0.098
—
0.560
0.788
0.856
13
0.134
0.208
0.148
0.149
0.133
0.110
0.132
0.102
0.062
0.097
0.113
0.063
—
0.684
0.736
14
0.134
0.146
0.124
0.144
0.103
0.086
0.113
0.094
0.037
0.030
0.060
0.021
0.048
—
0.321
15
0.153
0.193
0.138
0.175
0.156
0.092
0.125
0.132
0.059
0.066
0.084
0.032
0.066
0.039
—
Values in bold indicate the probability that a random genetic distance UST is significantly larger than the observed distance and are based on 999
iterations.
Odat et al.
|
Species diversity and genetic diversity
45
community composition (simple Mantel’s rM = 0.433, P =
0.0009; Fig. 1b).
Both genetic (simple Mantel’s rM = 0.641, P = 0.0001) and
plant community distances (simple Mantel’s rM = 0.438, P =
0.0029) between sites were significantly positively correlated
with the matrix of pairwise geographical distances between
sites. Moreover, matrices of both genetic (simple Mantel’s
rM = 0.470, P = 0.0019) and community distances (simple
Mantel’s rM = 0.846, P = 0.0009) between sites were significantly positively correlated with the matrix of pairwise ecological distances between sites. When we controlled for the effect
of geographic distances using a partial Mantel’s test, the positive relationship between the matrices of pairwise genetic distances UST and plant community distances was maintained
(partial Mantel’s rM = 0.220, P = 0.031). However, when we
controlled for the effect of ecological distance, the positive relationship between the matrices of pairwise genetic distances
UST and plant community distances was weak and nonsignificant (partial Mantel’s rM = 0.074, P = 0.304).
DISCUSSION
Relationship between population genetic diversity
of Plantago lanceolata and local plant community
diversity
Figure 1: relationshipsbetweenplantcommunitydiversityandAFLPgeneticdiversityofPlantago lanceolata within and between 15 grassland sites.
(a) Correlation between plant species richness and gene diversity (HE) of
P. lanceolata within 15 grassland sites (Spearman’s r = 0.516, P = 0.049).
(b) Correlation between pairwise distances in plant community composition (Bray–Curtis coefficient) and pairwise genetic differentiation UST
(Mantel rM = 0.433, P = 0.0009) between study sites. For details on measures of diversity and distances, see Materials and Methods.
diversity and reaction value was significant (Table 4). Overall,
these results suggest that the correlation between genetic diversity and species number was indirect and mediated by ecological differences between habitats.
Relationship between genetic diversity of Plantago
lanceolata and plant community diversity between
sites
The matrix of pairwise genetic distances UST between P. lanceolata populations was significantly positively correlated with the
matrix of pairwise distances (Bray–Curtis coefficient) of plant
The high proportion (90.30 %) of the AFLP genetic variation in
P. lanceolata we found within rather than between populations
corresponded well with the outcrossing mating system of this
common and widespread wind-pollinated perennial plant species (Hamrick and Godt 1990; Loveless and Hamrick 1984;
Nybom 2004; Richter et al. 1994).
Within-site AFLP genetic diversity of P. lanceolata was positively correlated with local plant species diversity (species
number and species evenness) (see Fig. 1a and Results). In
a previous study, we did not detect such a relationship between species diversity and within-population genetic diversity of Ranunculus acris (Odat et al. 2004), although positive
relationships have been reported for some other plants
(Vellend 2004; Vellend and Geber 2005). At first sight, the positive correlation between the population genetic diversity of
P. lanceolata and the local species diversity seems to indicate
a direct relationship in accordance with the niche variation hypothesis, which predicts that higher habitat variability brings
with it more variable niche space and in turn higher genetic
diversity (e.g. Hedrick et al. 1976; Mitton 1997; Nevo 2001).
However, based on the more individuals hypothesis, both species diversity and total abundance of a species are expected to
increase at more productive habitats (Srivastava and Lawton
1998). Because the abundance of P. lanceolata at a site covaried
positively with the increase in species number, the observed
relationship between species diversity and genetic diversity
appears to be indirect rather than direct. This was confirmed
when we tested whether species diversity was influenced by
habitat quality and whether habitat quality was likely to affect
population genetic diversity. Species number turned out to be
46
Journal of Plant Ecology
Table 3: Spearman’s simple rank correlations between gene diversity of Plantago lanceolata, species diversity (number and evenness),
abundance of P. lanceolata and site means of six ecological indicator values (Ellenberg 1992, see Materials and Methods) for the 15 study sites
in central Germany
Light
Temperature
Continentality
Moisture
Reaction
Nutrients
Gene diversity of P. lanceolata
0.300 (0.277)
0.483 (0.068)
0.298 (0.280)
0.166 (0.554)
0.683 (0.005)
0.651 (0.009)
Plant species number
0.460 (0.084)
0.290 (0.295)
0.036 (0.899)
0.239 (0.391)
0.556 (0.031)
0.509 (0.053)
Plant species evenness
0.286 (0.302)
0.418 (0.121)
0.204 (0.467)
0.107 (0.704)
0.521 (0.046)
0.564 (0.028)
Abundance of P. lanceolata
0.431 (0.125)
0.559 (0.030)
0.140 (0.618)
0.275 (0.322)
0605 (0.017)
0.620 (0.014)
The values are correlation coefficients; P values are given in parentheses.
Table 4: Spearman’s partial correlations between gene diversity
of Plantago lanceolata and species richness at a site when controlling
for the effect of abundance, mean Ellenberg’s reaction value and
nutrient value (see Materials and Methods), and between genetic
diversity and abundance, and reaction value when controlling for
the effect of species richness at a site
rs
P
Gene diversity 3 species
richness (abundance)
0.118
0.689
Gene diversity 3 species
richness (reaction value)
0.224
0.441
Gene diversity 3 species
richness (nutrient value)
0.282
0.328
Gene diversity 3 abundance
(species richness)
0.459
0.098
Gene diversity 3 reaction
value (species richness)
0.556
0.039
Gene diversity 3 nutrient
value (species richness)
0.526
0.053
higher at more nutrient-poor (less productive) and less acidic
sites (Table 3), as is commonly observed in grasslands (Ellenberg 1996; Petit et al. 2004). Moreover, the abundance of P.
lanceolata was also higher at such sites, in line with its habitat
requirements (Hegi 1982). When we controlled for the effects
of abiotic habitat characteristics and the abundance of P. lanceolata at the study sites using partial correlations, the positive
relationship between species number and genetic diversity disappeared (see Results), supporting our hypothesis that this relationship had been indirect and mediated by differences in
habitat quality. This corresponds well with the findings of
He et al. (2008) on Banksia attenuata on sand dunes in Australia.
In our study, the abundance of P. lanceolata was higher at
sites with higher local plant species diversity. However, only
few species may increase their abundance at sites with higher
species diversity because higher species number automatically reduces mean abundance per species (e.g. Roscher
et al. 2008; Valone and Hoffman 2003). Therefore, in other
species, negative relationships between species diversity
and genetic diversity of a species may be expected. Indeed,
a study on animals (Karlin et al. 1984) and one recent experimental plant study (Silvertown et al. 2009) suggest such negative relationships.
Relationship between genetic diversity of Plantago
lanceolata and plant community diversity between
sites
Between sites, pairwise genetic distances between Plantago populations were positively correlated with pairwise differences in
species composition (see Fig. 1b). Moreover, both distance
measures were also positively correlated with geographic distances between sites and with ecological distances between
sites. Partial Mantel tests showed that the positive relationship
between genetic distance and community distance was best
explained by pairwise ecological differences between sites. A
similar pattern of association between variation in plant diversity between sites and genetic distance between local populations had been found in Ranunculus acris (Odat et al. 2004).
Because AFLP markers are considered to be selectively neutral, it appears difficult to assert which factor is responsible for
such a pattern. Possibly, some of the AFLP markers assayed in
this study may have been linked to other nearby loci that are
under the influence of selection. Alternatively, and in our
opinion more likely, ecological variation between sites may
have acted as a partial barrier against successful gene flow between local populations, thus shaping the genetic differentiation between local populations of a species (Cooper 2000;
Linhart and Grant 1996; Lugon-Moulin et al. 1999) and affecting the pattern of local extinctions and colonization by seed
dispersal, which may, in turn, have shaped community differences between sites in similar ways (e.g. Borrvall et al. 2000).
This hypothesis merits being tested with quantitative genetic
methods in the future (Storfer 1996).
CONCLUSIONS
We conclude that positive relationships between species diversity and genetic diversity can exist both within and between
sites, although they do not necessarily indicate a direct causal
relationship. From a conservation viewpoint, these positive
relationships appear encouraging because they do not suggest
a conflict between the promotion of high species diversity and
high genetic diversity between species. Possibly, however, as in
our study, the positive relationship between within-population
genetic diversity and species richness was mediated by a positive
relationship of the abundance of P. lanceolata with gene
Odat et al.
|
Species diversity and genetic diversity
diversity, it may constitute the exception rather than the rule
because normally average abundance per species decreases
with increasing species richness.
In our study, the relationships between genetic diversity and
species diversity were influenced by environmental variation,
and thus, they provide no evidence that higher species diversity
led to higher niche diversity, which, in turn, could have increased genetic diversity. To study the causal relationship between species diversity and genetic diversity independent of
environmental variation, we suggest experiments with controlled manipulations of species diversity in otherwise common
environments (e.g. Diemer et al. 1997; Roscher et al. 2004,
2008) using both molecular and quantitative genetic methods.
FUNDING
German Federal Ministry of Education and Research
(01LC0013).
47
Faith DP, Minchin PR, Belbin L (1987) Compositional dissimilarity as
a robust measure of ecological distance. Vegetatio 69:57–68.
Frankham R (1996) Relationship of genetic variation to population size
in wildlife. Conserv Biol 10:15008.
Grime JP, Hodgson JG, Hunt R (1988) Comparative Ecology. A Functional
Approach to Common British Species. London, UK: Unwin Hyman.
Gugerli F, Englisch T, Niklfeld H, et al. (2008) Relationships among levels of biodiversity and the relevance of intraspecific diversity in conservation—a project synopsis. Persp Plant Ecol Evol Syst 10:259–81.
Hamrick JL, Godt MJ (1990) Allozyme diversity in plant species. In:
Brown AHD, Clegg MT, Kahler AL, Weir BS (eds). Plant Population
Genetics, Breeding and Germplasm Resources. Sunderland, MA:
Sinauer, 43–63.
He TH, Lamont BB, Krauss SL, et al. (2008) Covariation between intraspecific genetic diversity and species diversity within a plant
functional group. J Ecol 96:956–61.
Hedrick PW, Ginevan ME, Ewing EP (1976) Genetic polymorphism in
heterogenous environments. Ann Rev Ecol Syst 7:1–32.
Hegi G (1982) Illustrierte Flora von Mittel Europa. München und Hamburg, Germany: Parey.
ACKNOWLEDGEMENTS
Hubbell SP (2001) The Unified Neutral Theory of Biodiversity and Biogeography. Princeton, NJ: Princeton University Press.
We thank W.W. Weisser and the other collaborators of the interdisciplinary biodiversity project DIVA for providing stimulating research
surroundings; B. Bubner and J. Eckstein for technical assistance;
C. Wagner, A. Badani and M. Hasan for help and discussion of AFLP
gel patterns; W. Friedt for the great hospitality in his laboratories in
Giessen; C. Augspurger for discussion on Ellenberg’s indicator values;
S. Gebauer-Jung for the resampling program; and C. McInerney,
J. Perner and M. Clauss for commenting on the manuscript. The comments of three anonymous reviewers on an earlier version greatly
helped to improve the manuscript.
Karlin AA, Guttman SI, Rathbun SL (1984) Spatial autocorrelation
analysis of heterozygosity and geographic distribution in populations
of Desmognathus fuscus (Amphibia: Plethodontidae). Copeia 2:341–57.
Krüger AM, Hellwig FH, Oberprieler C (2002) Genetic diversity in natural and anthropogenic inland populations of salt-tolerant plants:
random amplified polymorphic DNA analyses of Aster tripolium L.
(Compositae) and Salicornia ramosissima Woods (Chenopodiaceae).
Mol Ecol 11:1647–55.
Kuiper PJC, Bos M (1992) Plantago: A Multidisciplinary Study. Ecological Studies, Vol. 89. Berlin, Germany: Springer, .
REFERENCES
Leberg PL (2002) Estimating allelic richness: effects of sample size and
bottlenecks. Mol Ecol 11:2445–9.
Antonovics J (1971) The effects of a heterogeneous environment on
the genetics of natural populations. Am Sci 59:593–9.
Legendre P (2008) Studying beta diversity: ecological variation partitioning by multiple regression and canonical analysis. J Plant Ecol
1:3–8.
Bonnet E, Van de Peer Y (2002) ZT: a software tool for simple and partial Mantel tests. J Stat Softw 7:1–12.
Borrvall C, Ebenman B, Thomas Jonsson TJ (2000) Biodiversity lessens
the risk cascading extinction in the model food webs. Ecol Lett 3:131–6.
Cooper ML (2000) Random amplified polymorphic DNA analysis of
southern brown bandicoot (Isoodon obesulus) populations in Western Australia reveals genetic differentiation related to environmental variables. Mol Ecol 9:469–79.
Diekmann M (2003) Species indicator values as an important tool in
applied plant ecology—a review. Basic Appl Ecol 4:493–506.
Diemer M, Joshi J, Körner C, et al. (1997) An experimental protocol to
assess the effects of plant diversity on ecosystem functioning utilized
in a European research work. Bull Geobot Inst ETH 63:95–107.
Leimu R, Mutikainen P, Koricheva J, et al. (2006) How general are positive relationships between plant population size, fitness, and genetic variation? J Ecol 94:942–52.
Linhart YB, Grant MC (1996) Evolutionary significance of local genetic
differentiation in plants. Ann Rev Ecol Syst 27:237–77.
Loveless MD, Hamrick JL (1984) Ecological determinations of genetic
structure in plant populations. Ann Rev Ecol Syst 15:65–95.
Lugon-Moulin N, Brünner H, Balloux F, et al. (1999) Do riverine barriers, history or introgression shape the genetic structuring of a common shrew (Sorex araneus) population? Heredity 83:155–61.
Manly BFI (1997) Randomization, Bootstrap and Monte Carlo Methods in
Biology. London, UK: Chapman & Hall.
Ellenberg H (1996) Vegetation Mitteleuropa mit den Alpen in ökologischer,
dynamischer und historischer Sicht. Stuttgart, Germany: Ulmer.
Mantel N (1967) The detection of disease clustering and generalized
regression approach. Cancer Res 27:209–20.
Ellenberg H, Weber HE, Düll R, et al. (1992) Zeigerwerte von Pflanzen in
Mitteleuropa Scripta Geobotanica XVIII. Göttingen, Germany: Erich
Goltze.
Mitton JB (1997) Selection in Natural Populations. Oxford, UK: Oxford
University Press.
Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among haplotypes: application
to human mitochondrial DNA restriction data. Genetics 131:479–91.
Mueller UG, Wolfenbarger LL (1999) AFLP genotyping and fingerprinting. Trends Ecol Evol 14:389–94.
Nei M (1973) Analysis of gene diversity in subdivided populations. Proc
Natl Acad Sci U S A 70:3321–3.
48
Nevo E (2001) Evolution of genome-phenome diversity under environmental stress. Proc Natl Acad Sci U S A 98:6233–40.
Nybom H (2004) Comparison of different nuclear DNA markers for
estimating intraspecific genetic diversity in plants. Mol Ecol
13:1143–55.
Odat N, Jetschke G, Hellwig FH (2004) Genetic diversity of Ranunculus
acris L. (Ranunculaceae) in relation to species diversity and habitat
type in grassland communities. Mol Ecol 13:1251–7.
Journal of Plant Ecology
Schaffers AP, Sýkora KV (2000) Reliability of Ellenberg indicator values for moisture, nitrogen and soil reaction: a comparison with field
measurements. J Veg Sci 11:225–44.
Silvertown J, Biss PM, Freeland J (2009) Community genetics: resource addition has opposing effects on genetic and species diversity
in a 150-year experiment. Ecol Lett 12:165–70.
Smith B, Wilson JB (1996) A consumer’s guide to evenness indices.
Oikos 76:70–82.
Ozinga WA, Schaminée JHJ, Bekker RM, et al. (2005) Predictability of
plant species composition from environmental conditions is constrained by dispersal limitation. Oikos 108:555–61.
Srivastava DS, Lawton JH (1998) Why more productive sites have
more species: an experimental test of theory using tree-hole communities. Am Nat 152:510–29.
Petit S, Griffiths L, Smart SS, et al. (2004) Effects of area and isolation of
woodland patches on herbaceous plant species richness across Great
Britain. Landscape Ecol 19:463–71.
Stein C, Auge H, Fischer M, et al. (2008) Dispersal and seed limitation
affect diversity and productivity of montane grasslands. Oikos
117:1469–78.
Prentice HC, Lönn M, Lefkovitch LP, et al. (1995) Association between
allele frequencies of Festuca ovina and habitat variation in the alvar
grasslands on the Baltic island of Öland. J Ecol 83:391–402.
Storfer A (1996) Quantitative genetics: a promising approach for the
assessment of genetic variation in endangered species. Trends Ecol
Evol 11:343–8.
Richter TS, Soltis PS, Soltis DE (1994) Genetic variation within and
among populations of the narrow endemic. Delphinium viridescens
(Ranunculaceae). Am J Bot 81:1070–6.
Valone TJ, Hoffman CD (2003) Population stability is higher in more
diverse annual plant communities. Ecol Lett 6:90–5.
Roscher C, Schumacher J, Baade J, et al. (2004) The role of biodiversity
for element cycling and trophic interactions: an experimental approach in a grassland community. Basic Appl Ecol 5:107–21.
Roscher C, Schumacher J, Weisser WW, et al. (2008) Genetic identity
affects performance of species in grasslands of different plant diversity: an experiment with Lolium perenne cultivars. Ann Bot
102:113–25.
Rosenzweig ML, Abramsky Z (1993) How are diversity and productivity related? In: Ricklefs RE, Schluter D (eds). Species Diversity in Ecological Communities. Chicago, IL: University of Chicago Press, 52–65.
Rothmaler W (1996) Exkursionsflora von Deutschland: Band 2. Gefäßpflanzen.
Jena, Germany: Gustav Fischer.
Van Valen L (1965) Morphological variation and width of ecological
niche. Am Nat 99:377–90.
Vellend M (2004) Parallel effects of land-use history on species diversity and genetic diversity of forest herbs. Ecology 85:3043–55.
Vellend M (2005) Species diversity and genetic diversity: parallel processes and correlated patterns. Am Nat 166:199–215.
Vellend M, Geber MA (2005) Connections between species diversity
and genetic diversity. Ecol Lett 8:767–81.
Vos P, Hogers R, Bleeker M, et al. (1995) AFLP: a new technique for
DNA fingerprinting. Nucleic Acids Res 23:4407–41.
Yeh FC, Yang RC, Boyle T (1997) POPGENE Version 1.32: Software for
Population Genetic Analysis. Edmonton, Canada: University of
Alberta.