Biodivers Conserv (2013) 22:1301–1316 DOI 10.1007/s10531-013-0471-y ORIGINAL PAPER
Vital survivors: low genetic variation but high germination in glacial relict populations of the typical rock plant Draba aizoides Frank Vogler • Christoph Reisch
Received: 17 August 2012 / Accepted: 14 March 2013 / Published online: 11 April 2013 Ó Springer Science+Business Media Dordrecht 2013
Abstract Glacial relict populations are isolated remnants of arctic-alpine species resulting from shifts of the distribution range during glaciations. Recently, the conservation value of relict populations has been emphasized, since they are adapted to stressful ecological conditions, which may be important for future distribution range shifts due to climate change. However, glacial relict populations have strongly been affected by historical fragmentation processes. Limited genetic variation and reduced reproduction can, therefore, be postulated for glacial relict populations. In our study we tested these assumptions. We investigated central European populations of the typical rock plant Draba aizoides from the Alps (considered as a core distribution area) and from the Swabian Alb, the Southern and Northern Franconian Jura (where its populations are considered glacial relict populations). We analysed genetic variation using molecular markers AFLPs and studied the reproduction of the populations in germination experiments. Glacial relict populations were genetically less variable and strongly differentiated, but they exhibited higher germination than populations from the Alps. From our results it can be concluded that glacial relict populations may have limited genetic variation, but they do not necessarily exhibit a limited reproductive capacity. Glacial relict populations are, therefore, vital survivors of the Pleistocene, which deserve full conservation attention, especially against the background of future climate change. Keywords
Draba aizoides Glacial relict AFLP Reproduction Population size
Introduction The present day distribution of plant species has been shaped tremendously by environmental changes in preceding eras. Especially the climatic oscillations within the quaternary Electronic supplementary material The online version of this article (doi:10.1007/s10531-013-0471-y) contains supplementary material, which is available to authorized users. F. Vogler C. Reisch (&) Institute of Botany, University of Regensburg, 93040 Regensburg, Germany e-mail:
[email protected]
123
1302
Biodivers Conserv (2013) 22:1301–1316
paved the way for today’s plant distribution (Webb and Bartlein 1992; Willis and Whittaker 2000). Rapid fluctuations of the environmental conditions shifted the borders of the colonized areas (Hewitt 1996) and caused the actually fragmented and disjunct distribution areas of many plant species (Hulte´n and Fries 1986). Alpine plant species survived glaciations in several refugia along the borders of the Alps (Scho¨nswetter et al. 2005; Tribsch 2004; Tribsch and Scho¨nswetter 2003). However, survival in the prealpine region cannot fully be excluded. Clear evidence exists for Minuartia biflora (Scho¨nswetter et al. 2006), but several other species were also supposed to have survived in central Europe (Bauert et al. 1998; Holderegger et al. 2002; Reisch 2008; Reisch et al. 2003; Scho¨nswetter et al. 2004). Arctic-alpine species immigrated postglacially from their refugia into the Alps and to Scandinavia. Simultaneously, forest species immigrated from south eastern and south western refugia to central Europe and the lower regions of the Alps displacing alpine species in these regions. However, on some naturally ‘forest-free islands’, such as cliffs, populations of less competitive alpine species survived postglacial reforestation. They exhibit a highly fragmented, disjunct distribution, with isolated populations mostly at the edge of the distribution range (Hampe and Jump 2011). Being remnants of a formerly different or more widespread distribution, these populations are considered as glacial relict populations (Crawford 1989; Wilmanns 2005). The fragmentation processes occurring during glaciations have, in all likelihood, affected the characteristics of glacial relict populations. First, geographic isolation of glacial relict populations due to climatic oscillations may have changed the structure of genetic variation. In postglacial colonized parts of the distribution area, low levels of genetic variation within and between populations have been observed due to founder events and long-distance dispersal (Comes and Kadereit 1998; Hewitt 1996, 1999, 2000). In contrast, glacial relict populations often exhibit low levels of variation within populations but high levels of variation between populations due to consecutive bottlenecks and long-term isolation (Hensen et al. 2010; Reisch et al. 2002, 2003). Second, limited size and decreased genetic variation could have affected reproductive traits. Recent studies demonstrated a clear positive relationship between genetic variation and reproductive success such as seed set or seedling survival (Fischer and Matthies 1998; Kolb 2005; Leimu et al. 2006). Long-term isolation and decreased genetic variation could, therefore, have resulted in reduced reproductive capacity of glacial relict populations. Recently, the conservation value of relict populations has been emphasized (Habel et al. 2010a; Hampe and Petit 2005), mainly due to their evolutionary significance: relict populations have existed successfully under stressful ecological conditions for long periods of time (Ronikier et al. 2012). Furthermore, they are exposed to strong directional selection processes and therefore specifically adapted to their environment, which is mostly located at the edge of the distribution range. For this reason, relict species may be relevant to challenge future climatic changes (Habel et al. 2010b). Studies dealing explicitly with glacial relict populations are, however, rare. While the genetic variation of glacial relict populations has been analysed at least in few studies (Hensen et al. 2010; Reisch et al. 2002, 2003; Bauert et al. 2007; Sˇmidova´ et al. 2011; Rusterholz et al. 2012), actually no data are specifically available about the reproduction of glacial relict populations. In our study we tried to bridge this gap. Therefore, we selected the yellow whitlow grass (Draba aizoides), a typical rock species which is mainly distributed in the Alps but also occurs in central Europe with isolated glacial relict populations. In a comparative approach we studied the impact of pleistocene glaciations on genetic variation and seed germination capacity of these relict populations.
123
Biodivers Conserv (2013) 22:1301–1316
1303
Methods Species description Draba aizoides is a perennial evergreen chamaephyte that grows in dense cushions in crevices and on ledges of calcareous cliffs (Do¨rr and Lippert 2001; Kay and Harrison 1970). Flowering takes place from March to August (Seybold 2006). Pollination is mainly entomophilous but selfing is possible (Kay and Harrison 1970; Sebald et al. 1998). Seed production is abundant (Wilmanns and Rupp 1966), but vegetative propagation by detached rosettes is also possible (Sebald et al. 1998). D. aizoides is mainly distributed throughout the Alps, the Pyrenees and the Carpathians (Hegi 1986; Kay and Harrison 1970; Seybold 2006). However, in Germany the species also occurs in the mountain regions of the Northern and Southern Franconian Jura and the Swabian Alb (Haeupler and Scho¨nfelder 1988). These populations are considered as glacial relict populations (Sebald et al. 1998; Widmer and Baltisberger 1999). In south eastern central Europe the species is endangered (Scheuerer and Ahlmer 2003), and the populations are affected by rock climbing (Vogler and Reisch 2011). Study design and sampled populations Covering the distribution range of D. aizoides in Germany, for this study we selected populations on five cliffs from the Alps (AL) and, with increasing distance to the Alps, on each five cliffs from the Swabian Alb (SA), the Southern Jumbo (SJ) and the Northern Franconian Jura (NJ) (Table 1; Fig. 1). The selected cliffs were single outcrops, which were more or less completely inhabited by D. aizoides. The spatial distance to the next adjacent population was minimum 500 m. Individuals from each cliff were, therefore, considered as one population and population size was determined at each locality by estimating cliff size, which differed clearly among the four regions (Table 2). The largest populations occurred in the NJ (2,362 ± 840 m2), followed by those from the SA (1,817 ± 650 m2) and the Southern Franconian Jura (399 ± 130 m2). The smallest populations have been found in the Alps (318 ± 70 m2). Genetic variation was assessed through genome-wide genotyping with AFLPs, amplified fragment length polymorphisms (Vos et al. 1995). For this study, young leaf rosettes were collected randomly from ten individuals, covering the whole range of each population and dried over silica gel. Reproduction of glacial relict populations was analysed in germination experiments. For these experiments seed material was collected from June to August from at least 20 individuals per population and placed in paper bags. Seed material was air dried, cleaned and stored few weeks at 4 °C until the start of the germination experiment. Stratification was not necessary, since seeds germinated very well in preexperiments and exhibit no dormancy following literature (Kay and Harrison 1970). Molecular analyses DNA for AFLPs was extracted from dried leaf rosettes following the CTAB protocol from Rogers and Bendich (1994) in an adaptation by Reisch (2007). Solutions were diluted with water to 7.8 ng/lL and used for AFLPs, which were conducted in accordance with the protocol from Beckmann Coulter as described before (Bylebyl et al. 2008; Reisch 2008). DNA adapters were prepared by adding equal volumes of both single strands of EcoRI and
123
1304
Biodivers Conserv (2013) 22:1301–1316
Table 1 Code, names, and geographic location of the analysed populations in the four study regions Northern Franconian Jura (NJ), Southern Franconian Jura (SJ), Swabian Alb (SA) and Alps (AL) with their altitude (in m above sea level) and size (PS in m2) Code
Population
NJ01
Kreuz-Berg
Northern Franconian Jura
402
80
NJ02
Hohe Leite
Northern Franconian Jura
528
64
NJ03
Pfarrfelsen Du¨sselbacher Wand
Northern Franconian Jura
445
2,000
Northern Franconian Jura
456
3,600
Northern Franconian Jura
457
1,200
SJ01
Zanklstein Lo¨cherwand
Southern Franconian Jura
382
240
SJ02
Teufelsfelsen
Southern Franconian Jura
522
320
SJ03
Lintlberg
Southern Franconian Jura
366
350
SJ04
Schulerloch
Southern Franconian Jura
396
500
SJ05
Drabafels
Southern Franconian Jura
398
300
SA01
Swabian Alb
724
3,500
SA02
Stuhlfels ¨ schlesfels O
Swabian Alb
917
1,000
SA03
Schwarzlochfels
Swabian Alb
603
1,500
SA04
Wiesfels
Swabian Alb
766
1,200
SA05
Kreuzfels
Swabian Alb
606
3,200
AL01
Geißhorn
Alps
2,316
600
AL02
Alps
2,243
150
AL03
Kreuzeck Gru¨nten
Alps
1,674
400
AL04
Karkopf
Alps
1,404
400
AL05
Hochgern
Alps
1,660
250
NJ04 NJ05
Region
Altitude
PS
MseI adaptors (MWG Biotech) following a 5 min heating at 95 °C with a final 10 min step at 25 °C. DNA restriction and adapter ligation were performed in one step by adding a 3.6 lL mixture containing 2.5 U EcoRI (MBI Fermentas), 2.5 U MseI (MWG Biotech), 0.1 lM EcoRI and 1 lM MseI adapter pair, 0.5 U T4 Ligase with its corresponding buffer (MBI Fermentas), 0.05 M NaCl and 0.5 lg BSA (New England BioLabs) to 6.4 lL of genomic DNA in a concentration of 7.8 ng/lL. Following an incubation at 37 °C for 2 h with a final enzyme denaturation step at 70 °C for 15 min, the restriction-ligation products were diluted tenfold with 19 TE buffer for DNA (20 mM Tris–HCl, pH 8.0; 0.1 mM EDTA, pH 8.0). For preselective DNA amplification, 1 lL diluted DNA restriction-ligation product, preselective EcoRI and MseI primers (MWG Biotech) were added to an AFLP core mix (PeqLab, Germany) containing 19 buffer S, 0.2 mM dNTPs and 1.25 U taq-polymerase. In a 5 lL reaction volume PCR was performed on at 94 °C for 2 min then 30 cycles of 20 s denaturation at 94 °C, 30 s annealing at 56 °C and 2 min elongation at 72 °C and a final 2 min 72 °C and 30 min 60 °C step for complete extension ending with a final cool down to 4 °C. After PCR, products were diluted 20-fold with 19 TE buffer for DNA. Three primer combinations were chosen for a subsequent selective PCR reaction after a wider-scale screening (M-CAC/D2-E-AGC, M-CTT/D3-E-AAG, M-CAC/D4-E-ACT, Beckman Coulter). Therefore, PCR was carried out in a total reaction volume of 5 lL containing an AFLP Core Mix (19 buffer S, 0.2 mM dNTP’s, 1.25 U taq-polymerase,
123
Biodivers Conserv (2013) 22:1301–1316
1305
NJ01,02 NJ03 NJ05 NJ04 SJ01-04
SA04
SA05
SA02
SJ05
SA03
SA01 AL04
AL05
AL03 AL02 AL01
Fig. 1 Geographic position of the sampled populations in the four study regions: Northern Franconian Jura (NJ), Southern Franconian Jura (SJ), Swabian Alb (SA) and Alps (AL). Squares indicate the analysed population
Peqlab, Germany), 0.05 lM selective EcoRI (Proligo, France), 0.25 lM MseI (MWG Biotech) primers and 0.75 lL diluted preselecive amplification product. For detection, EcoRI primers labelled with different fluorescent dyes were used. PCR parameters used
123
1306
Biodivers Conserv (2013) 22:1301–1316
Table 2 Molecular variance within and among populations from the four study regions calculated in different analyses of molecular variance (AMOVA) Level of variation
df
SS
MS
%
18.08
UPT
NJ–SJ–SA–AL Among regions
3
778.08
259.36
Among populations
16
1330.03
83.13
38.16
Within populations
165
1516.54
9.19
43.76
0.562***
NJ Among populations
4
303.24
75.81
48.44
Within populations
45
328.20
7.29
51.56
0.484***
SJ Among populations
4
272.71
68.18
44.63
Within populations
43
335.69
7.81
55.37
0.446***
SA Among populations
4
332.45
83.11
46.18
Within populations
37
376.86
10.19
53.82
0.462***
AL Among populations
4
421.63
105.41
46.72
Within populations
40
475.76
11.86
53.38
0.467***
SS indicates the sum of squares, MS the mean squares, % the proportion of genetic variability. Levels of significance are based on 999 iteration steps and are indicated by three * (p \ 0.001). Regions: Northern Franconian Jura (NJ), Southern Franconian Jura (SJ), Swabian Alb (SA) and Alps (AL)
were 2 min at 94 °C, 10 cycles 20 s denaturation at 95 °C, annealing 30 s at 66 °C and 2 min elongation at 72 °C, where annealing temperature was reduced every subsequent step by 1 °C, additional 25 cycles of 20 s denaturation at 94 °C, 30 s annealing at 56 °C and 2 min elongation at 72 °C completed by a following 30 min step at 60 °C and a cool down to 4 °C. Selective PCR products were diluted fivefold (D2) and tenfold (D4) with 19 TE buffer for DNA. D3 products were used without a further dilution. After pooling 5 lL of each selective PCR product of a given sample and adding them to a mixture of 2 lL sodium acetate (3 M, pH 5.2), 2 lL Na2EDTA (100 mM, pH 8) and 1 lL glycogen (Roche), DNA was precipitated in a 1.5 mL tube by adding 60 lL of 96 % ethanol (-20 °C) and an immediate shaking. DNA was pelleted by 20 min centrifugation at 14,0009g at 4 °C, the supernatant was poured off and the pellet was washed once by adding 200 lL 76 % ethanol (-20 °C) and centrifugation at the latter conditions and was subsequently vacuum dried in a concentrator. After redissolving the pelleted DNA in a mixture of 24.8 lL sample loading solution (SLS, Beckman Coulter) and 0.2 lL CEQ size standard 400 (Beckman Coulter), selective PCR products were separated by capillary gel electrophoresis on an automated sequencer (CEQ 8000, Beckmann Coulter). Results were examined using the CEQ 8000 software (Beckman Coulter) and analyzed using the software Bionumerics 6.6 (Applied Maths, Kortrijk, Belgium). From the computed gels only those fragments were taken into account for further analyses that showed
123
Biodivers Conserv (2013) 22:1301–1316
1307
intense and articulate bands. Samples yielding no clear banding pattern or obviously representing PCR artefacts were first repeated. However, due to weak and ambiguous banding patterns, 15 specimens were finally excluded from the analyses. Reproducibility of molecular analyses was investigated by means of estimating the genotyping error rate (Bonin et al. 2004). We replicated 10 % of all analysed samples (18 individuals) using the same DNA extracts and replicated the whole AFLP procedure separately. We scored fragments and calculated the percentage of fragments where differences between original and replicate occurred. Following this procedure we determined a genotyping error rate of 2.3 %. Germination Germination was studied in experiments at three standard temperature treatments (06/14, 14 and 14/22 °C) with a 14 h light period in germination chambers (RUMED, Rubarth Apparate GmbH, Germany) representative for the temperature regimes in the natural habitat (Baskin et al. 2006). For the experiment each 15 seeds were placed in Petri dishes with a double layer of filter paper (Sartorius-Stedim 3hw) moistened with distilled water. Each germination treatment was analysed using 8 replicates per population. The experiments ran over a period of 5 weeks and Petri dishes were controlled twice a week. When the radicle was at least 1 mm long seeds were considered as germinated and removed from the Petri dishes. We used a Tetrazolium test (Lakon 1942) to check viability of seeds, but observed no significant differences between seeds from the different regions. Statistical analysis With the AFLP fragment data, a binary matrix was created. Using this matrix, a hierarchical AMOVA based on pairwise Euclidian distances between samples was performed applying GenAlEx 6.3 (Peakall and Smouse 2006) to analyse the genetic relationships within and between populations. A Mantel test was used to analyse whether genetic and geographic distances between populations were correlated (Mantel 1967). Additionally, a Bayesian cluster analysis using 10,000 markov chain monte carlo (MCMC) simulations was calculated with 20 iterations per K = 2–21 and a burning period of 10,000 with the software Structure 2.2 (Pritchard et al. 2000). From the values of the groups K thus obtained and the average of the log likelihood at each step of the MCMC subtracted with half their variance LnP(D), DK was computed as the slope of the absolute value for the second order rate of the likelihood function LnP(D) divided by the standard deviation sd of LnP(D): K = (m|LnP(D)00 |)/(sd[LnP(D)]) (Evanno et al. 2005). Genetic variation within populations was determined applying the program PopGene 1.32 (Yeh et al. 1997) as percentage of polymorphic bands PB, Nei’s Gene Diversity H = 1 - R(pi)2 and shannon’s information index SI = R(pi)ln(pi), where pi represents the allele frequency. Data on genetic variation within populations and germination exhibited normal distribution and homoscedasticity of variances (after arcsine-square root transformation of germination percentages). Linear mixed models were computed using R software version 2.15.2 (R-Core-Team 2012) and were simplified via backward selection of the least significant variables until the final minimal adequate model contained significant terms (p value \ 0.05). Improved models were verified by computing ANOVAs (Crawley 2007). Models were calculated using (a) germination percentages or (b) genetic variation indices as depending and altitude, population size, region (NJ, SJ, SA, AL) and (a) genetic variability indices or (b) germination percentages as explaining variable.
123
1308
Biodivers Conserv (2013) 22:1301–1316
Correlation analyses of germination and time point of seed collection as well as seed viability were based on Spearman’s rank correlation coefficient and were conducted with PASW Statistics version 17 (SPSS, Illinois).
Results Genetic variation AFLP genotyping of 185 individuals yielded 214 clear and distinct fragments (D2 and D3: 75, D4: 64) of which 90.19 % were polymorphic. In the Bayesian cluster analysis the dataset was clearly structured into three distinct groups (DK = 22.08). An evaluation of the cluster data unravelled these groups to be arranged in 70 % of the iteration cases in a group of individuals from the Northern and in a group of individuals from the Southern Franconian Jura and in a third group comprising individuals from the Swabian Alb and the Alps (Fig. 2). In 30 % of the iteration cases, a group of individuals from the Northern Franconian Jura was opposed to a group of individuals from the Southern Franconian Jura and the Swabian Alb and to a third group of individuals from the Alps. In a three level AMOVA, 43.76 % of the total variance was observed within populations, 38.16 between populations within regions and 18.08 % among the different regions with UPT of 0.56 (Table 2). Mean pairwise genetic distances UPT were highest between populations from the Northern Franconian Jura and populations from the Southern Franconian Jura and lowest between populations from the Swabian Alb and the Alps (data not
Fig. 2 Bar plot generated from the data of the Bayesian cluster analysis which based on 20 iterations and a burning period of 10,000. Distinct groups are the Northern Franconian Jura (bright grey), the Southern Franconian Jura (dark grey) and the Swabian Alb-Alps group (grey)
123
Biodivers Conserv (2013) 22:1301–1316
1309
shown). In separate analyses, genetic variation among populations within the study regions varied only marginally (UPT = 0.44–48). The Mantel test revealed a weak but significant correlation of genetic distances (UPT) and geographic distances (km) between populations (r = 0.263, p \ 0.005). Genetic variation measured as percentage of polymorphic bands (PB), Nei’s Gene Diversity (H) and shannon’s information index (SI) was largest in the alpine populations and declined with increasing distance to the Alps (Table 3). In simplified linear mixed models only the factor region was able to explain significant differences in genetic variability (Table 4). Differences were most significant between Jurassic and alpine populations. Notably, the highest genetic variation was obtained within the smallest alpine populations. Germination From a total of 7,200 seeds, 61.00 % germinated already within the first two weeks. Germination varied between 39.17 and 100.00 %. Independent from the treatment,
Table 3 Genetic variation measured as percentage of polymorphic bands (PB), Nei’s Gene Diversity (H) and Shannon’s Information Index (SI) as well as the results of the germination at the three studied treatments (06/14, 14/14, 14/22 °C; in %) of the analysed populations from the four study regions Northern Franconian Jura (NJ), Southern Franconian Jura (SJ), Swabian Alb (SA) and Alps (AL) Code
PB
H
SI
06/14 °C
14/14 °C
14/22 °C
NJ01
18.6
0.07
0.10
95.8
86.5
95.8
NJ02
18.2
0.06
0.09
98.3
99.1
98.3
NJ03
23.3
0.08
0.12
96.6
90.0
64.1
NJ04
22.9
0.08
0.12
94.1
93.3
93.3
NJ05
16.8
0.06
0.09
77.5
93.3
85.0
Mean
20.0 ± 1.32
0.07 ± 0.005
0.10 ± 0.007
92.46 ± 3.80
92.44 ± 2.09
87.30 ± 6.22
SJ01
20.5
0.07
0.11
92.5
95.0
71.4
SJ02
24.3
0.10
0.14
93.3
98.3
55.0
SJ03
14.9
0.05
0.07
79.1
66.6
67.5
SJ04
23.3
0.08
0.12
64.1
70.9
44.1
SJ05
15.4
0.05
0.08
100
97.5
96.6
Mean
19.7 ± 1.95
0.07 ± 0.009
0.10 ± 0.012
85.80 ± 6.40
85.66 ± 6.96
66.92 ± 8.84
SA01
30.3
0.11
0.16
95.0
95.8
79.1
SA02
24.3
0.08
0.12
61.6
55.0
40.0
SA03
24.3
0.09
0.13
78.3
89.1
63.3
SA04
20.0
0.08
0.11
60.0
67.5
46.6
SA05
19.6
0.08
0.11
86.6
94.1
82.5
Mean
23.7 ± 1.93
0.08 ± 0.007
0.13 ± 0.010
76.30 ± 6.86
80.30 ± 8.10
62.30 ± 8.47
AL01
33.6
0.10
0.16
75.8
78.3
47.5
AL02
26.6
0.09
0.13
50.0
65.0
42.5
AL03
25.7
0.09
0.13
60.0
79.1
47.5
AL04
32.7
0.12
0.18
66.6
86.6
89.1
AL05
28.5
0.10
0.15
39.1
65.8
49.1
Mean
29.4 ± 1.60
0.10 ± 0.006
0.15 ± 0.008
58.30 ± 6.39
74.96 ± 4.16
55.14 ± 8.56
Standard errors are given for mean values
123
1310
Biodivers Conserv (2013) 22:1301–1316
Table 4 Summary statistics of the linear mixed models for genetic variation measured as the percentage of polymorphic bands (PB), Nei’s Gene Diversity Index (H), and Shannon‘s Information Index (SI) Variable
Estimate
Std. error
t value
p value
\0.001***
PB Intercept
29.420
1.720
17.11
Region NJ
-9.460
2.432
-3.89
0.001**
Region SJ
-9.740
2.432
-4.00
0.001**
Region SA
-5.720
2.432
-2.35
0.032*
\0.001***
H Intercept
0.100
0.007
15.16
Region NJ
-0.030
0.009
-3.21
0.005**
Region SJ
-0.030
0.009
-3.22
0.005**
Region SA
-0.012
0.009
-1.29
0.217
SI Intercept
\0.001***
0.150
0.086
15.23
Region NJ
-0.046
0.122
-3.30
0.005**
Region SJ
-0.046
0.122
-3.30
0.005**
Region SA
-0.024
0.122
-1.72
0.104
ANOVA results for PB: R2: 0.566, F3,16 = 6.966, p = 0.0033**, for H: R2: 0.482, F3,16 = 4.966, p = 0.0127* and for SI: R2: 0.482, F3,16 = 4.962, p = 0.0127* *** p \ 0.001, ** p \ 0.01, * p \ 0.05
germination was highest in populations from the Northern Franconian Jura, followed by those from the Southern Franconian Jura and the Swabian Albs. The lowest germination was observed in populations from the Alps. Mean germination calculated over all treatments was 76.88 ± 5.03 % for populations from the Northern Franconian Jura, 59.63 ± 5.80 % for the Southern Franconian Jura, 52.44 ± 5.48 % for the Swabian Alb and 48.78 ± 4.98 % for the Alps (Table 3). In simplified linear mixed models based on the germination percentages, only the factor region was able to explain significant differences in germination rates (Table 5). These differences were significant in the lowest (06/14 °C) temperature regime treatment and just marginally not significant for the 14/22 °C treatment, and always prevailed between germination rates of populations from the Northern Franconian Jura and the Alps. Germination at all three treatments was not correlated with the time point of seed collection or with seed viability (Spearman’s rank correlation p [ 0.05).
Discussion Genetic variation AFLP analysis revealed substantial genetic variation both between populations within the four studied regions and between these regions. Such a pattern of strong genetic differentiation is typical for glacial relict populations and has been observed in previous studies
123
Biodivers Conserv (2013) 22:1301–1316
1311
Table 5 Summary statistics of the linear mixed models for germination the three studied treatments 06/14, 14 constant and 14/22 °C Treatment
Estimate
Std. error
t value
p value
Intercept
0.872
0.083
10.47
\0.001***
Region NJ
0.447
0.118
3.79
0.002**
Region SJ
0.368
0.118
3.12
0.007**
Region SA
0.212
0.118
1.80
0.091
Intercept
1.052
0.081
12.95
\0.001***
Region NJ
0.255
0.115
2.22
0.041*
Region SJ
0.178
0.115
1.55
0.141
Region SA
0.092
0.115
0.80
0.434
Intercept
0.848
0.098
8.68
\0.001***
Region NJ
0.395
0.138
2.86
0.011*
Region SJ
0.135
0.138
0.98
0.342
Region SA
0.070
0.138
0.51
0.620
06/14 °C
14/14 °C
14/22 °C
ANOVA results for 06/14 °C: R2: 0.512, F3,16 = 5.594, p = 0.0081**, for 14/14 °C: R2: 0.255, F3,16 = 1.830, p = 0.1824 and for 14/22 °C: R2: 0.368, F3,16 = 3.106, p = 0.0561 *** p \ 0.001, ** p \ 0.01, * p \ 0.05
for species such as Ranunculus pygmaeus, Saxifraga cernua or S. paniculata (Bauert et al. 1998; Reisch 2008; Reisch et al. 2003). Climatic warming since the end of the last glaciation has resulted in a fragmented distribution of these species, followed by subsequent isolation and genetic drift, which enhances genetic differentiation processes (Le Corre et al. 1997; Tremblay and Schoen 1999). The present day occurrence of D. aizoides can, therefore, be regarded as remainders of a more wide-spread distribution during the last glacial period (Wilmanns 2005; Wilmanns and Rupp 1966), and the related fragmentation process obviously increased isolation and genetic variation between relict populations. Glacial relict populations from the Swabian Alb were more similar to populations from the Alps, than the other relict populations, which may indicate that these two regions are linked by a common postglacial history. However, further phylogeographic analyses would be necessary to resolve this question finally. Comparing the four regions, genetic differentiation between populations from the Alps was not weaker than between relict populations from the Swabian and Franconian Alb. This may be due to the specific habitat of D. aizoides. Rocky outcrops are always strongly isolated habitats, which results in considerable genetic differentiation as observed for many other rock populating plant species such as Erinus alpinus or Eritrichum nanum (Stehlik et al. 2002a, b). Genetic variation within populations continuously decreased with distance to the Alps and was lowest in the most distant relict populations from the Northern Franconian Jura. This observation supports the results of a previous study on D. aizoides, where also declining levels of nucleotide diversity have been found in relict populations from the Swiss Jura Mountains compared to populations from the Alps (Widmer and Baltisberger
123
1312
Biodivers Conserv (2013) 22:1301–1316
1999). Decreased levels of genetic variation within relict populations have also been reported for R. pygmaeus, Stipa capillata, S. cernua or S. paniculata (Bauert et al. 2007; Hensen et al. 2010; Reisch 2008; Reisch et al. 2003). Since genetic variation within populations of D. aizoides was not correlated generally with population size, although this relationship has been reported in many studies e.g. (Fischer and Matthies 1998; Galeuchet et al. 2005; Hensen et al. 2005; Reisch et al. 2003), differences can most likely be ascribed to historical events. Thus it can be assumed that glacial relict populations of D. aizoides suffered from reduced gene flow and bottlenecks, what consequently reduced genetic variation (Hewitt 2000). Germination Draba aizoides seeds germinated very well, which corresponds to the results of previous studies, where also high germination has been observed (Kay and Harrison 1970; Wilmanns and Rupp 1966). However, we observed clear differences in germination between seeds of populations from the different regions. At all treatments, seeds of populations from the Northern Franconian Jura germinated best, while worst germination was observed for seeds of populations from the Alps. This is in contrast to the widespread assumption that isolated populations, especially at the edge of a species range, exhibit a reduced fecundity (Jump and Woodward 2003; Pfeifer et al. 2009; Sagarin et al. 2006). However, in only few studies germination of seeds from small and isolated populations as a reproductive trait has been studied and if so, germination failed (Tsaliki and Diekmann 2009) or revealed no difference compared to other populations (Lammi et al. 1999). Different reasons may serve as explanation for the observed germination pattern. On the one hand, climatic differences between seeds of populations from different regions could have caused the observed variation in germination. Previous studies already revealed differences in germination due to variation in climatic conditions (Milberg and Andersson 1998; Shimono and Kudo 2005; Wagner and Simons 2008). Since climatic conditions on the Swabian Alb and in the Southern and Northern Franconian Jura are quite similar, specifically the decreased germination of seeds from alpine populations could be explained in this way. In previous studies it was already reported that germination of seeds from harsher environments at higher altitudes may be lowered (Schu¨tz and Milberg 1997). This may be due to the fact that adaptation to specific environmental conditions could have resulted in the development of ecotypes with varying germination ecology. Differences in germination were shown to persist even under similar environmental conditions in a common garden experiment (Wagner and Simons 2008). Another reason for this observation could, however, be that seeds from milder climates are less dormant than seeds from alpine conditions (Wagner and Simons 2008). The fact that after-ripening of D. aizoides seeds during winter (Hegi 1986) has been reported supports this assumption, which could then result in the observed decrease in germination rate of seeds from the Alps. On the other hand, it has been shown that population size may affect germination (Buza et al. 2000; Menges 1991), although this is not always the case (Oostermeijer et al. 1994). In this study, no general correlation of germination and population size was found, mainly due to the drastically increased germination of seeds from the Northern Franconian Jura and the small populations of the Southern Franconian Jura. The analysis of a larger number of populations and a more specific method to determine population size would perhaps reveal a significant relationship between both parameters. However, the smallest populations from the Alps showed the lowest germination and the largest populations from the Northern Franconian Jura exhibited the highest germination. The possible relationship
123
Biodivers Conserv (2013) 22:1301–1316
1313
between population size and germination should, therefore, not fully be excluded. The relationship between population size and fitness is well known (Leimu et al. 2006). Therefore, it is quite well conceivable, that larger glacial relict populations also exhibit a higher fitness, which manifests in higher germination rates. Conclusions with respect to conservation In contrast to previous assumptions, glacial relict populations are not necessarily small, genetically impoverished and exhibit a limited reproductive capacity. In our analysis glacial relict populations even proved to be larger and more reproductive than alpine populations, although genetic variation was decreased. Relict populations can be assumed, as many other isolated range margin populations, to occur under ecologically more stressful conditions (Hoffmann and Blows 1994). As a consequence, directional selection pressures are expected to promote, in association with genetic drift due to isolation, local adaptation and genetic divergence (van Rossum et al. 2003). Selection favors alleles that increase fitness under local conditions (Samis and Eckert 2007), which may be a reason for the observed strong reproduction in the glacial relict populations. This assumption is corroborated by the results of a study on Lychnis viscaria, where germination was also not decreased in isolated populations (Lammi et al. 1999). Previous authors already stated that the value of relict populations has remained largely unperceived by conservation biologists (Hampe and Petit 2005). From the results of our study it can be clearly concluded that these vital survivors indeed deserve specific attention in conservation. Acknowledgments The authors thank P. Gerstberger, J. Wagenknecht and the Verein zur Erforschung der Flora des Regnitzgebietes for their help with plant localities, M. Bernhardt- Roemermann for his support in statistical analysis and P. Poschlod for his generous support.
References Baskin CC, Thompson K, Baskin JM (2006) Mistakes in germination ecology and how to avoid them. Seed Sci Res 16:165–168 Bauert MR, Ka¨lin M, Baltisberger M, Edwards PJ (1998) No genetic variation within isolated relict populations of Saxifraga cernua in the Alps using RAPD markers. Mol Ecol 7:1519–1527 Bauert MR, Ka¨lin M, Edwards PJ, Baltisberger M (2007) Genetic structure and phylogeography of alpine relict populations of Ranunculus pygmaeus and Saxifraga cernua. Bot Helv 117:181–196 Bonin A, Belleman E, Eidesen PB, Pompanon F, Brochmann C, Taberlet P (2004) How to track and assess genotyping errors in population genetic studies. Mol Ecol 13:3261–3273 Buza L, Young A, Thrall P (2000) Genetic erosion, inbreeding and reduced fitness in fragmented populations of the endangered tetraploid pea Swainsonia recta. Biol Conserv 93:177–186 Bylebyl K, Poschlod P, Reisch C (2008) Genetic variation of Eryngium campestre (Apiaceae) in central Europe. Mol Ecol 17:3379–3388 Comes HP, Kadereit JW (1998) The effects of quaternary climatic changes on plant distribution and evolution. Trends Plant Sci 3:432–438 Crawford RMM (1989) Studies in plant survival. Blackwell Scientific Publications, Oxford Crawley MJ (2007) The R book. Wiley, Chichester Do¨rr E, Lippert W (2001) Flora des allga¨us. IHW, Eching Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure. Mol Ecol 14:2611–2620 Fischer M, Matthies D (1998) RAPD variation in relation to population size and plant fitness in the rare Gentianella germanica (Gentianaceae). Am J Bot 85:811–819
123
1314
Biodivers Conserv (2013) 22:1301–1316
Galeuchet DJ, Perret C, Fischer M (2005) Microsatellite variation and structure of 28 populations of the common wetland plant, Lychnis flos-cuculi in a fragmented landscape. Mol Ecol 14:991–1000 Habel JC, Assmann T, Schmitt T, Avise JC (2010a) Relict species: from past to future. In: Habel JC, Assmann T (eds) Relict species. Phylogeography and conservation biology. Springer, Heidelberg, Dordrecht, London, New York, pp 1–5 Habel JC, Schmitt T, Assmann T (2010b) Relict species research: some concluding remarks. In: Habel JC, Assmann T (eds) Relict species. Phylogeography and Conservation Biology, Springer, Heidelberg, Dordrecht, London, New York, pp 441–442 Haeupler H, Scho¨nfelder P (1988) Farn- und Blu¨tenpflanzen der Bundesprepublik Deutschland. Ulmer, Stuttgart Hampe A, Jump AS (2011) Climate relicts: past, present, future. Annu Rev Ecol Evol Syst 42:313–333 Hampe A, Petit RJ (2005) Conserving biodiversity under climate change: the rear edge matters. Ecol Lett 8:461–467 Hegi G (1986) llustrierte Flora von Mitteleuropa. Pteridophyta—Spermatophyta, vol 4(1). Blackwell, Berlin, pp 298–303 Hensen I, Oberprieler C, Wesche K (2005) Genetic structure, population size, and seed production of Pulsatilla vulgaris (Ranunculaceae) in Central Germany. Flora 200:3–14 Hensen I, Kilian C, Wagner V, Durka W, Pusch J, Wesche K (2010) Low genetic variability and strong differentiation among isolated populations of the rare steppe grass Stipa capillata in Central Europe. Plant Biol 12:526–536 Hewitt GM (1996) Some genetic consequences of ice ages, and their role in divergence and speciation. Biol J Linn Soc 58:247–276 Hewitt GM (1999) Post-glacial re-colonization of European Biota. Biol J Linn Soc 68:87–112 Hewitt GM (2000) The genetic legacy of the quaternary ice ages. Nature 405:907–913 Hoffmann AA, Blows MW (1994) Species borders: ecological and evolutionary perspectives. Trend Ecol Evol 9:223–227 Holderegger R, Stehlik I, Abbott RJ (2002) Molecular analysis of the pleistocene history of Saxifraga oppositifolia in the Alps. Mol Ecol 11:1409–1418 Hulte´n E, Fries M (1986) Atlas of the north European vascular plants. Koeltz Scientific Books, Ko¨nigstein Jump AS, Woodward FI (2003) Seed production and population density decline approaching the range edge of cirsium species. New Phytol 160:349–358 Kay QQN, Harrison J (1970) Draba aizoides biological flora of the british isles no. 94.1. J Ecol 58(3):877–888 Kolb A (2005) Reduced reproductive success and offspring survival in fragmented populations of the forest herb Phyteuma spicatum. J Ecol 93:1226–1237 Lakon G (1942) Topographischer Nachweis der Keimfa¨higkeit der Getreidefru¨chte durch Tetrazoliumsalze. Ber Dtsch bot Ges 60:299–305 Lammi A, Siikama¨ki P, Mustaja¨rvi K (1999) Genetic diversity, population size, and fitness in central and peripheral populations of a rare plant Lychnis viscaria. Conserv Biol 13(5):1069–1078 Le Corre V, Dumoulin-Lapegue S, Kremer A (1997) Genetic variation at allozyme and RAPD loci in sessile oak Quercus petraea Liebl.: the role of history and geography. Mol Ecol 6:519–529 Leimu R, Mutikainen P, Koricheva J, Fischer M (2006) How general are positive relationships between plant population size, fitness and genetic variation. J Ecol 94:942–952 Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27:209–220 Menges ES (1991) Seed germination percentage increases with population size in a fragmented prairie species. Conserv Biol 5:158–164 Milberg P, Andersson L (1998) Does cold stratification level out differences in seed germinability between populations? Plant Ecol 134:225–234 Oostermeijer JGB, van Eijk MW, Den Nijs JCM (1994) Offspring fitness in relation to population size and genetic variation in the rare perennial plant Gentiana pneumonanthe (Gentianaceae). Oecologia 97:289–296 Peakall R, Smouse PE (2006) GENALEX 6: genetic analyses in excel. Population genetic software for teaching and reseach. Mol Ecol Notes 6:288–295 Pfeifer M, Schatz B, Pico´ FX, Passalacqua NG, Fay MF, Carey PD, Jeltsch F (2009) Phylogeography and genetic structure of the orchid Himanthoglossum hircinum Spreng. across its European central-marginal gradient. J Biogeogr 36:2353–2365 Pritchard JK, Stephens M, Donelly P (2000) Inferring of population structure using multilocus genotype data. Genetics 155:945–959
123
Biodivers Conserv (2013) 22:1301–1316
1315
R-Core-Team R (2012) A language and environment for statistical computing. R-Foundation for Statistical Computing, Vienna Reisch C (2007) Genetic structure of Saxifraga tridactylites (Saxifragaceae) from natural and man-made habitats. Conserv Genet 8:893–902 Reisch C (2008) Glacial history of Saxifraga paniculata (Saxifragaceae)—molecular biogeography of a disjunct arctic-alpine species in Europe and North America. Biol J Linn Soc 93:385–398 Reisch C, Poschlod P, Wingender R (2002) Genetic variation of sesleria albicans Kit ex Schultes (Poaceae): lack of evidence for glacial relict endemism in central Europe. Plant Biol 4:1–9 Reisch C, Poschlod P, Wingender R (2003) Genetic variation of Saxifraga paniculata (Saxifragaceae): molecular evidence for glacial relict endemism in central Europe. Biol J Linn Soc 80:11–21 Rogers SO, Bendich AJ (1994) Extraction of total cellular DNA from plants, algae and fungi. In: Gelvin SB, Schilperoort RA (eds) Plant molecular biology manual, 2nd edn. Kluwer Academic Press, Dordrecht, pp 1–8 Ronikier M, Schneeweis GM, Scho¨nswetter P (2012) The extreme disjunction between Beringia and Europe in Ranunculus glacialis (Ranunculaceae) does not coincide with the deepest genetic split—a story of the importance of temperate mountain ranges in arctic-alpine phylogeography. Mol Ecol 21:5561–5578 Rusterholz HP, Aydin D, Baur B (2012) Population structure and genetic diversity of relict populations of Alyssum montanum on limestone cliffs in the Northern Swiss Jura mountains. Alpine Botany 122:109–117 Sagarin RD, Gaines SD, Gaylord B (2006) Moving beyond assumptions to understand abundance distributions across the ranges of species. Trend Ecol Evol 21:524–530 Samis KE, Eckert CG (2007) Testing the abundant center model using range-wide demographic surveys of two coastal dune plants. Ecology 88:1747–1758 Scheuerer M, Ahlmer W (2003) Rote Liste Gefa¨sspflanzen Bayerns mit regionalisierter Florenliste. Schriftenreihe des Bayerischen Landesamtes fu¨r Umweltschutz 165:1–372 Scho¨nswetter P, Tribsch A, Niklfeld H (2004) AFLP reveals no genetic divergence of the Eastern Alpine endemic Oxytropis campestris ssp. tiroliensis (Fabaceae) from widespread subsp. campestris. Plant Syst Evol 244:245–255 Scho¨nswetter P, Stehlik I, Holderegger R, Tribsch A (2005) Molecular evidence for glacial refugia of mountain plants in the European Alps. Mol Ecol 14:3547–3555 Scho¨nswetter P, Popp M, Brochmann C (2006) Rare arctic-alpine plants of the European Alps have different immigration histories: the snow bed species Minuartia biflora and Ranunculus pygmaeus. Mol Ecol 15:709–720 Schu¨tz W, Milberg P (1997) Seed dormancy in carex canescens: regional differences and ecological consequences. Oikos 78:420–428 Sebald O, Seybold S, Philippi G, Wo¨rz A (1998) Farn- und Blu¨tenpflanzen Baden-Wu¨rttembergs, vol 7. Ulmer, Stuttgart Seybold S (2006) Schmeil-Fitschen: Flora von Deutschland, 93rd edn. Quelle & Meyer, Wiebelsheim Shimono Y, Kudo G (2005) Comparisons of germination traits of alpine plants between fellfield and snowbed habitats. Evol Ecol Res 20:189–197 Sˇmidova´ A, Mu¨nzbergova´ Z, Placˇkova I (2011) Genentic diversity of a relict plant species, Ligularia sibirica Cass. (Asteraceae). Flora 206:151–157 Stehlik I, Blattner FR, Holderegger R, Bachmann K (2002a) Nunatak survival of the high Alpine plant Eritrichum nanum Gaudin in the central Alps during the ice ages. Mol Ecol 11:2027–2036 Stehlik I, Schneller J, Bachmann K (2002b) Immigration and in situ glacial survival of the low-alpine Erinus alpinus (Scrophulariaceae). Biol J Linn Soc 77:87–103 Tremblay NO, Schoen J (1999) Molecular phylogeography of Dryas integrifolia: glacial refugia and postglacial recolonization. Mol Ecol 8:1187–1198 Tribsch A (2004) Areas of endemism of vascular plants in the Eastern Alps in relation to pleistocene glaciation. J Biogeogr 31:747–760 Tribsch A, Scho¨nswetter P (2003) Patterns of endemism and comparative phylogeography confirm palaeoenvironmental evidence for pleistocene refugia in the eastern Alps. Taxon 52:477–497 Tsaliki M, Diekmann M (2009) Fitness and survival in fragmented populations of Narthecium ossifragum at the species’ range margin. Acta Oecol 35:415–421 van Rossum F, Vekemans X, Gratia E, Meerts P (2003) A comparative study of allozyme variation of peripheral and central populations of Silene nutans (Caryophyllaceae) from Western Europe: implications for conservation. Plant Syst Evol 242:49–61 Vogler F, Reisch C (2011) Genetic variation on the rocks—the impact of climbing on the population ecology of a typical cliff plant. J Appl Ecol 48:899–905
123
1316
Biodivers Conserv (2013) 22:1301–1316
Vos P, Hogers R, Bleeker M, Reijnans M, van de Lee T, Hornes M, Frijtjers A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA fingerprinting. Nucl Acids Res 23:4407–4414 Wagner I, Simons AW (2008) Intraspecific divergence in seed germination traits between high- and lowlatitude populations of the arctic-alpine annual Koenigia islandica. Arct Antarc Alp Res 40:233–239 Webb T, Bartlein PJ (1992) Global changes during the last 3 million years: climatic controls and biotic response. Annu Rev Ecol Syst 23:141–173 Widmer A, Baltisberger M (1999) Extensive intraspecific chloroplast DNA (cpDNA) variation in the alpine Draba aizoides (Brassicaceae): haplotype relationships and population structure. Mol Ecol 8:1405–1415 Willis KJ, Whittaker RJ (2000) The refugial debate. Science 287(5457):1406–1407 ¨ berlegungen zur Wilmanns O (2005) Ka¨ltezeitliche Reliktpflanzen der schwa¨bischen Alb: aktualistische U pra¨historischen Landschaft. Hoppea 66:447–468 Wilmanns O, Rupp S (1966) Welche faktoren bestimmen die verbreitung alpiner felsspaltenpflanzen auf der schwa¨bischen Alb? Vero¨ffentlichungen der Landesstelle fu¨r Naturschutz und Landschaftspflege Baden-Wu¨rttemberg 34:62–85 Yeh FC, Yang RC, Boyles TBJ, Ye ZH, Mao JX (1997) POPGENE, the user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, Alberta
123