Eight pairs of climbed and pristine cliffs were selected in the Northern Franconian Jura (NJ, five pairs) and on the Swabian Alb (SA, three pairs) to study the impact of climbing on the population structure and genetic variation of D. aizoides (Table 1). We first chose pristine cliffs, representative of the distribution of D. aizoides in these regions. These were paired with climbed cliffs which were located close to the pristine cliffs, easily accessible, used for climbing for at least 50 years and having more than five climbing routes and being, if possible, of similar size and orientation. Cliffs were classified as climbed if they were mentioned in rock climbing literature or if climbing was evident. Cliffs within any pair did not differ greatly in distance, aspect or elevation above sea level (mean differences ± 1 SE: distance: 15·89 ± 7·78 km, aspect: 50·50 ± 16·02, elevation: 40·38 ± 18·92 m). The number of climbing routes varied between 7 and 117, depending on the size of the cliff. Population structure of D. aizoides was analysed on all cliffs using vertical transects.
Table 1. Climbed (C) and pristine (P) cliffs from the Northern Franconian Jura (NJ) and the Swabian Alb (SA) included in this study, with geographical position, altitude, cliff face area, climbing intensity (CI, number of climbing routes per 100 m2) and the size of the Draba aizoides populations
|Code||Population||La. (N)||Lo. (E)||Altitude (m)||Cliff area (m2)||CI||Population size|
|NJ01||Nankendorfer Block (C)||49°52′59″||11°20′21″||376||1500||0·47||489|
|NJ03||Röthelfels (C)||49°44′51″||11°14′41″||513||8750||1·34||11 181|
|NJ04||Hohe Leite (P)||49°48′27″||11°23′59″||528||64||0·00||140|
|NJ05||Pfarrfelsen Egloffstein (C)||49°42′21″||11°15′44″||445||2000||0·95||811|
|NJ07||Düsselbacher Wand (C)||49°32′51″||11°28′58″||456||3600||0·58||1547|
|NJ08||Eschenbacher Geißkirche (P)||49°32′03″||11°28′47″||513||1125||0·00||3422|
|SA02||Cliff below Rossfels (P)||48°30′17″||09°19′23″||770||140||0·00||249|
|SA05||Untere Peilerwand (C)||48°23′43″||09°46′55″||542||750||2·40||382|
Population Structure Analysis
Vertical transects were spanned over the cliffs and ranged 5 m downwards from the cliff plateau, through the whole face and 5 m deep into the cliff talus (Fig. 1). For safety reasons, the ability to fix the rope for rappelling downwards (e.g. a tree or a bolt) was a prerequisite for the position of the transect. Furthermore, we selected transect positions lacking extreme ledges (to avoid distortions of the transect) and having an orientation comparable to that of the pristine cliffs. Vertical transects had a constant width of 4 m and a varying length because of different heights of the cliff faces. Transects were divided in a 1-m2 grid, and during rappelling downwards, the exact position of each cushion of D. aizoides within the transect was noted, the number of rosettes per cushion was counted, and the length and width of each cushion as well as the diameter of the smallest and largest rosette within each cushion were measured. Subsequently, cushion frequency (CF, number of cushions within a transect/transect surface in square metre), rosette frequency, coverage and cushion surface (CS, length times width of each cushion) were determined. Statistical analyses revealed strong correlation between these parameters. For this reason, only data on the most significant parameters CF and CS are presented.
Figure 1. Structure of the vertical transect. With a constant width of 4 m, transects ranged downwards from 5 m deep in the plateau over the whole cliff face into the talus with a depth of 5 m. Transects were subdivided into eight sections, whereas sections 1 and 2 lay in the plateau, 3–6 in the face and 7 and 8 in the talus.
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The transect records were divided into the cliff parts ‘plateau’, ‘face’ and ‘talus’ and further subdivided into eight transect sections. To yield these eight sections, the cliff plateau and talus were subdivided into two planes of the same size by dividing the transect line after 2·5 m. Having begun ranging downwards from the plateau, sections 1 and 2 (plateau) and 7 and 8 (talus) all had a length of 2·5 m each. The sections 3–6 were subsequently determined by subdividing the cliff face height into four equal distances. For the subdivided transects, the percentage surface covered by the species was calculated as the surface covered divided by the surface of the transect section of each cliff. Because of heterogeneity in the field, the absolute length of these sections differed between cliff pairs. To remove these inequalities, variables were recalculated on a unit area (m−2) basis and these data were used in subsequent analyses.
Before sampling plant material for molecular analyses, the extent of the total rock area of each cliff and the rocky area covered by D. aizoides was determined by measuring width and height of the respective cliff parts. Using this information, we calculated the total size of the population for each cliff by multiplication of the CF with the size of the cliff area covered by the species. Climbing intensity was calculated as climbing route density per 100 m2 by dividing the total rock area by the number of climbing routes (obtained from the Deutsche Alpenverein, DAV).
Twenty young, green, rosettes were collected from each of the five pairs of climbed and pristine cliffs in the Northern Franconian Jura. For sampling, each cliff was divided into an upper cliff half and a lower cliff half such that the upper cliff half was defined as the whole plateau and 2 m of the topmost cliff face and the lower cliff half as 2 m of the lowermost face and the whole talus, providing two subpopulations per cliff. In each subpopulation, 10 samples (200 samples in total) were collected at approximately the same distances on the total width of the rock area. To avoid sampling from the same individual, a minimum distance of at least 2 m between rosettes was used.
Plant material was dried on silica gel and total cellular DNA was extracted following the CTAB protocol from Rogers & Bendich (1994) in an adaptation by Reisch (2007). Concentrations of the DNA extracts were measured photometrically. Solutions were diluted with water to 7·8 ng μL−1 and used for the analysis of amplified fragment length polymorphisms (AFLPs), which were conducted in accordance with the protocol from Beckmann Coulter (Brea, USA) as described previously (Bylebyl, Poschlod & Reisch 2008; Reisch 2008). DNA adapters were prepared by adding equal volumes of both single strands of EcoRI and MseI adaptors (MWG Biotech, Ebersberg, Germany) 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-μL mixture containing 2·5 U EcoRI (MBI Fermentas, St. Leon-Rot, Germany), 2·5 U MseI (MWG Biotech), 0·1 μM EcoRI and 1 μM MseI adapter pair, 0·5 U T4 Ligase with its corresponding buffer (MBI Fermentas), 0·05 M NaCl and 0·5 μg BSA (New England BioLabs, Ipswich, USA) to 6·4 μL of genomic DNA in a concentration of 7·8 ng μL−1. 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 10-fold with 1× TE buffer for DNA (20 mM Tris–HCl, pH 8·0; 0·1 mM EDTA, pH 8·0).
For preselective DNA amplification, 1 μL diluted DNA restriction-ligation product, preselective EcoRI and MseI primers (MWG Biotech) were added to an AFLP Core Mix (PeqLab, Erlangen, Germany) containing 1× Buffer S, 0·2 mM dNTP’s and 1·25 U Taq-Polymerase. In a 5-μL reaction volume, polymerase chain reaction (PCR) was performed on an automated thermocycler 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 1× TE buffer for DNA.
Three primer combinations were chosen for a subsequent selective PCR. Therefore, PCR was carried out in a total reaction volume of 5 μL containing an AFLP Core Mix (1× Buffer S, 0·2 mM dNTP’s, 1·25 U Taq-Polymerase; PeqLab), 0·05 μM selective EcoRI (Proligo, Paris, France), 0·25 μM MseI (MWG Biotech) primers and 0·75 μL diluted preselective amplification product. For detection, EcoRI primers labelled with different fluorescent dyes (M-CAC/D2-E-AGC, M-CTT/D3-E-AAG, M-CAC/D4-E-ACT; Beckmann Coulter) were used. PCR parameters used were 2 min at 94 °C, 10 cycles of 20-s denaturation at 95 °C, 30-s annealing at 66 °C and 2-min elongation at 72 °C, after which 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 and a following 30-min step at 60 °C for complete elongation and a cool down to 4 °C. Selective PCR products were diluted fivefold (D2) and 10-fold (D4) with 1× TE buffer for DNA. D3 products were used without a further dilution.
After pooling 5 μL of each selective PCR product of a given sample and adding them to a mixture of 2 μL sodium acetate (3 M, pH 5·2), 2 μL Na2EDTA (100 mM, pH 8) and 1 μL glycogen (Roche, Manheim, Germany), DNA was precipitated in a 1·5-mL tube by adding 60 μL of 96% ethanol (4 °C) and an immediate shaking. DNA was pelleted by 20-min centrifugation at 14 000 g at 4 °C, the supernatant was poured off, and the pellet was washed once by adding 200 μL of 76% ethanol (4 °C) and centrifuged at the latter conditions and was subsequently vacuum-dried in a concentrator.
After redissolving the pelleted DNA in a mixture of 24·8 μL Sample Loading Solution (SLS; Beckmann Coulter) and 0·2 μL CEQ Size Standard 400 (Beckmann 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 (Beckmann Coulter) and analysed 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 intense and articulate bands. Samples yielding no clear banding pattern or obviously representing PCR artefacts were repeated or finally excluded from further analyses. Reproducibility of molecular analyses was investigated with 10% of all analysed samples by means of estimating the genotyping error rate (Bonin et al. 2004), which was 2·3%.
In the case of normal distribution and variance homogeneity, population structure was analysed using dependent t-tests; otherwise paired Wilcoxon and U-tests were conducted. Correlation analyses of geographical characteristics and population structure parameters were based on Spearman’s rank correlation coefficient. All statistical analyses were conducted with pasw Statistics 17 (IBM, Munich, Germany) for Windows.
From the AFLP bands, a binary (0/1) matrix was created wherein the presence of a fragment of a given length was counted as 1 and the absence as 0. As one individual was omitted from the study, the final matrix and all further calculations comprised 199 samples. Employing the software PopGene 1.32 (Yeh et al. 1997) genetic variation within populations was computed as the percentage of polymorphic bands (PB), as Nei’s Gene Diversity H (H = 1 − Σ (pi)2) and as Shannon’s Information Index SI (SI = Σ (pi) ln (pi); pi = allele frequency). Wilcoxon tests were used to compare genetic variation within populations because the data were not normally distributed (KS test P < 0·200). Correlation between genetic variation within populations and population size was tested using Spearman’s rank correlation coefficient. Both analyses were conducted with pasw Statistics 17 (SPSS) for Windows. The apportionment of genetic variation within and between populations and subpopulations was assessed by hierarchical amova with the software GenAlEx 6.3 (Peakall & Smouse 2001).