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Keywords:

  • genetic structure;
  • kinship coefficient;
  • Primula modesta;
  • safe site;
  • seed bank dynamics;
  • seedling establishment;
  • seed dispersal;
  • soil seed bank;
  • spatial autocorrelation;
  • spatiotemporal pattern

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • 1
    The spatial genetic structure of soil seed banks establishes the initial template for development of spatial genetic structure in above-ground plants, but is rarely evaluated.
  • 2
    We used kinship coefficients to analyse the fine-scale spatial genetic autocorrelation of plants and of seed banks from different soil depths for Primula modesta at a subalpine fen site on Mt Asama, central Japan.
  • 3
    The spatial genetic structure of surface seeds (0–1 cm depth) was significant, while deeper seeds (1–5 cm depth) had no significant genetic structure. We also detected a more pronounced spatial genetic association between the surface seeds and flowering genets than between the deeper seeds and flowering genets.
  • 4
    These results suggest that the surface seed bank accounts for a large proportion of the previous season's seed dispersal and therefore represents the transient seed bank, whereas the deeper (persistent) seed bank pools the reproductive output of multiple generations.
  • 5
    Directional analysis indicated that secondary dispersal by running water modifies the spatial genetic structure and extends dispersal distances. Over time, this may impact on the spatial pattern of soil seeds, possibly accounting for the absence of spatial genetic structure in deeper seeds.
  • 6
    Emerging seedlings and flowering ramets were strongly clustered together at distances up to 20 cm. Surviving seedlings were aggregated at short distances because of the patchy spatial distribution of safe sites for establishment, allowing development and strengthening of the marked fine-scale spatial genetic structure.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Genetic diversity can appear spatially structured at different scales, such as population, subpopulation or among neighbouring individuals. This spatial genetic structure is necessarily a product of interactions of past demographic history and life-history traits, such as mating system, seed and pollen dispersal and clonal growth under environmental influences (Ennos 2001). At a fine spatial scale, the most prevalent cause is likely to be the formation of local pedigree structures as a result of limited pollen and/or seed dispersal (Vekemans & Hardy 2004). In particular, seed dispersal directly links the end of the reproductive cycle of adult plants with the establishment of their offspring, and is widely accepted to have profound effects on spatial structures of plant populations (Nathan & Muller-Landau 2000).

Seed dispersal occurs not only in space but also over time. Most seeds do not germinate immediately after dispersal but, instead, remain dormant in the soil seed bank for several years, decades or perhaps even hundreds of years (Baker 1989; Tsuyuzaki & Goto 2001; Telewski & Zeevaart 2002). The spatial genetic structure of soil seed banks is the result of the reproductive activity of above-ground plants and establishes an initial template, but it has rarely been characterized. Despite their importance, the spatial dynamics of the relationship between seed banks and above-ground plant populations remain poorly understood.

In order to understand better how seed banks affect, and are affected by, above-ground plant spatial dynamics, we need to distinguish (Thompson & Grime 1979) between transient seed banks, composed of seeds that germinate or die before the second germination season following dispersal, and persistent seed bank, where seeds remain viable in the soil until at least the second germination season (Baskin & Baskin 1998). The availability of safe sites, i.e. favourable microsites for germination and/or establishment, is an additional major determinant of the spatial patterning of establishing seedlings (Harper 1977; Eriksson & Ehrlen 1992; Verheyen & Hermy 2001).

In species with limited seed dispersal, a transient seed bank may develop a fine-scale spatial genetic structure similar to that of the above-ground plant population. Although expected to be far more extensive in selfing species (Ennos 2001; Vekemans & Hardy 2004), spatial genetic structure has been detected in populations of preferentially outcrossing species. This is particularly apparent for maternally inherited markers (McCauley et al. 1996; Tarayre et al. 1997; Levy & Neal 1999; Caron et al. 2000), implying that seed dispersal is generally more limited than pollen transfer. On the other hand, a persistent seed bank may prevent the build-up and retention of significant genetic structure by pooling the reproductive output of many generations and averaging out the effects of each generation's dispersal pattern. In addition, a persistent seed bank is more likely than a transient one to have opportunities for secondary dispersal, such as by water flow or soil disturbance, which may weaken genetic structure.

We attempted to evaluate the spatial genetic structure of the transient and persistent components of soil seed banks and their relation to that of above-ground plants in a natural population of Primula modesta Bisset et Moore (Primulaceae). Although P. modesta is distylous, with both self and intramorph incompatibility (Wedderburn & Richards 1990), the limited dispersal of seeds, which are released from 10 to 20 cm height and have no special adaptations for dispersal, should create a spatial genetic structure within populations to some extent. Numerous seeds (1000–2700 seeds m−2, A. Shimono, unpublished data) are stored in the soil and stratified sampling from different soil depths may allow analysis of the spatial genetic structure of the soil seed components, because most seeds that are even partially buried in the soil form persistent seed banks owing to a strict light requirement for germination (Shimono & Washitani 2004).

We hypothesized that soil seed banks of P. modesta would exhibit fine-scale spatial genetic structure related to that of the above-ground plants and that the spatial association between seed banks and above-ground plants would be stronger in surface than in deeper soil layers, because the persistent seed bank is larger than the previous season's reproductive output. In addition, we investigated spatiotemporal patterns of seedling survival to evaluate the effect of safe site availability on the spatial structuring of above-ground plants and to identify the biological processes structuring the fine-scale spatial genetic structure of a population of P. modesta.

Materials and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

study species

Primula modesta is a small rosette herb that grows in a range of montane to alpine habitats in Japan. Like many other Primula species, P. modesta is distylous, with self and intramorph incompatibility (Wedderburn & Richards 1990). It produces one flowering stem 7–15 cm tall and an umbel with 3–20 flowers. In the subalpine zone of central Japan, bud burst occurs in early May, and the flowers bloom from late May to early July. The fruits (capsules) mature in late August to mid-September, and the seeds are dispersed on sunny days from a small apical opening that closes hygromechanically on rainy days. The seeds are minute (5–10 µg) and have no special adaptations for dispersal. Seed dispersal continues through autumn and winter.

The seeds require at least a month of moist chilling to be released from their primary dormancy, after which more than 90% of seeds are capable of germination at temperatures of 12–20 °C in the light (germination remains negligible in the dark; Shimono & Washitani 2004). More than 70% of buried seeds are still viable after burial for a year (A. Shimono, unpublished data), although the longevity of seeds in the seed bank and average time spent as a dormant seed are unknown.

study site

The study site was located on an oligotrophic fen in the subalpine zone (2100 m a.s.l.) of Mt Asama (36°24′12″ N, 138°31′34″ E, 2568 m a.s.l.) in Nagano Prefecture, central Japan. The site is flat to gently sloping. Juncus fauriensis Buchen., Carex doenitzii Böckeler and Drosera rotundifolia L. form a sparse vegetation cover, with a layer of Sphagnum spp. covering the ground. The total number of flowering ramets of P. modesta was approximately 5000, and their density was 20 m−2. The frequencies of the long- and short-styled morphs were roughly equal. Total ramet density, including non-flowering ramets, was approx. 400 m−2.

The climate of the study site can be deduced from the records available from the Karuizawa meteorological station, about 7 km to the east (36°20′3″ N, 138°32′9″ E, 999 m a.s.l.). Assuming a standard temperature decline of 0.55 °C for every 100-m increase in altitude, we estimated the annual mean air temperature (30-year average for 1971–2000) at the study site to be about 3 °C. The mean annual precipitation at the meteorological station was 1198 mm (30-year average for 1971–2000).

seed bank

To assess the spatial genetic structures of both the soil seeds and flowering plants, we set a 2.5 × 5.5 m quadrat, with the long side (y axis) parallel to the slope (Fig. 1). We divided the quadrat into 55 subquadrats (0.5 × 0.5 m) and collected 40 soil cores (5 cm diameter, 5 cm deep) at the intersections of the lattice in late April of 2003, just before spring germination began. We also collected the surface litter layer, if present, with each core and divided each soil core into depths of 0–1 cm (surface) and 1–5 cm (deeper). Primula modesta seeds have a strict light requirement (Shimono & Washitani 2004), which prevents the germination of even slightly buried seeds, because light is strongly attenuated by penetration through even thin layers of soil (Bliss & Smith 1985; Tester & Morris 1987). As samples collected at soil depths of 2–5 cm hold a relatively small fraction of the seed bank (approximately 8% of total soil seeds), 5 cm depth is sufficient for sampling all soil seeds. Each soil sample was bagged and brought to the laboratory, then spread into a thin layer (about 0.5 cm deep) over a 10 cm depth of vermiculite in trays. Emerging P. modesta seedlings were identified every 5 days during the following 5 months. The seedlings were transplanted into pots and grown for later genetic analysis. We defined the seed bank size as the mean density of germinable seeds in the 40 cores. Seed density per unit area was calculated by dividing the total seeds in the 40 cores by the area of the soil surface covered by the cores (40 × π × 2.5 cm × 2.5 cm). Flowering ramets in the quadrat were mapped in 2003.

image

Figure 1. Map of the distribution of flowering ramets (closed circles) and the number of seedlings (open circles) of Primula modesta that emerged from soil cores sampled at the intersections of the dashed lines.

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dna extraction and microsatellite genotyping

To determine the multilocus genotypes of the plants, we sampled one young leaf from every mapped flowering ramet in 2003 and from each of the seedlings that originated from the soil cores. Total DNA was extracted from leaves using a modified hexadecyltrimethyl ammonium bromide (CTAB) method (Murray & Thompson 1980). Leaves were stored at −30 °C until DNA extraction and ground to a fine powder. They were mixed with 750 µL of CTAB extraction buffer and incubated at 60 °C for 10 minutes. One volume of chloroform–octanol (24 : 1) was added and emulsified by shaking. The mixture was centrifuged at 15 000 r.p.m. for 10 minutes, and the aqueous phase was collected. DNA was then precipitated by adding two-thirds of a volume of isopropanol and washed once with 70% ethanol. The DNA was then vacuum-dried and resuspended in an appropriate volume (200–500 µL) of TE (Tris EDTA). For microsatellite amplification, 5–10 µg (1 µL) of the DNA was used in 10 µL of polymerase chain reaction (PCR) mixture. PCR was performed for 10 loci (PM175, PM179, PM324, PM668, PM769, PM770, PM772, PM801, PM850 and PM901) and genotypes analysed as described in detail by Shimono et al. (2004).

gene diversity

Genetic diversity parameters were estimated for each component (surface or deeper seed bank, flowering genet) by using FSTAT 2.9.3.2 software (Goudet 1995). Observed heterozygosity (HO), expected heterozygosity (HE), and allelic richness (A) were calculated. Deviation from Hardy–Weinberg equilibrium (HWE) within each component was tested with fixation index (F) (Weir & Cockerham 1984). The statistical significance of these values was determined on the basis of 20 000 randomizations of alleles among individuals within components.

Nei's (1973) gene diversity formula (GST) was used to evaluate the distribution of genetic diversity between the soil seed bank and above-ground populations.

fine-scale genetic structure

Fine-scale genetic structure was assessed by spatial autocorrelation analysis of genetic relatedness based on pairwise kinship coefficients (Loiselle et al. 1995), calculated as the frequency of allele sharing between two individuals relative to the average frequency of allele sharing based on the frequencies of the alleles in the sample population (the ‘reference population’). Fij, the average multiallelic and multilocus kinship coefficient between individuals i and j, is calculated as follows:

  • image

where pila and pjla are the frequencies of allele a at locus l in individuals i and j, respectively, pla is the frequency of allele a at locus l in the reference population, and n is the number of genes defined in the sample per locus. The second term adjusts for the bias attributable to finite sample size.

To analyse the relationship between pairwise physical distance and pairwise kinship coefficients, we calculated the Fij for seven distance classes: 0–30, 30–60, 60–90, 90–120, 120–150, 150–180 and > 180 cm. As soil seeds were sampled at 50-cm intervals in the quadrat, setting the distance classes at much lower intervals would not have helped elucidate details of the spatial structure. The coordinates of the soil seeds were assumed to be randomly distributed within the area of each soil core.

The Fij value was tested against the null hypothesis by randomization. The observed Fij for a given distance class was then compared with the randomized empirical distribution. The randomizations were conducted by randomly permuting multilocus genotypes, whilst keeping their locations in the stand constant. These permutations were generated 1000 times, and the Fij was calculated for each permutation. The overall significance of the trend shown in the correlograms was tested according to Bonferroni criteria.

The overall presence/absence of isolation by distance can be assessed by the slope (b) of a correlogram, i.e. by regressing pairwise Fij coefficients against the logarithm of the pairwise geographical distances (Vekemans & Hardy 2004). The significance of the linear regression slope was tested by Mantel tests (Manly 1997) with 1000 random permutations. Jackknife standard errors for b were obtained by jackknifing over loci.

In cases where isolation by distance was detected, we also evaluated its strength using Sp statistics, calculated as –b/(1−F(1)), where F(1) is the Fij for the first distance class. F(1) can be considered an approximation of the kinship between pairs of neighbours, provided the first distance class contains enough pairs of individuals to obtain a reasonably precise F(1) value (Vekemans & Hardy 2004).

Spatial autocorrelation analysis was also used to test whether the spatial structures of two components (surface seed bank vs. flowering genet, deeper seed bank vs. flowering genet, or surface seed bank vs. deeper seed bank) were dependent on each other, with i and j representing individuals from each of the two components.

In addition, to interpret the effect of secondary dispersal on the spatial association between the seed bank and a flowering genet, we classified pairs of individuals i (seed bank) and j (flowering genet) according to the angle (θ) between the X axis of the quadrat (perpendicular to the slope) and a vector from the flowering genet to the soil seed as: (i) right, −45° < θ < 45°; (ii) upward, 45° ≤ θ ≤ 135°; (iii) left, 135° < θ and θ < −135°; or (iv) downward, −135° ≤ θ ≤ −45°. It is likely that secondary dispersal occurs by rainfall running down the gentle slope (i.e seeds located downwards of a flowering plant could be in this category). In the directional analysis, the slope (b) of a correlogram was calculated in the 0–200 cm distance range that contained a roughly equal number of pairs in each direction. The number of pairs in the upward and downward directions increased with distance, while those in the right and left directions were saturated at distances of roughly 200–300 cm because the x axis (250 cm) is shorter than the y axis (550 cm).

spatiotemporal pattern of seedling survival

Seedling emergence was monitored in a 0.5 × 4.5 m subquadrat established within the main quadrat, because there were too many seedlings to monitor in the entire quadrat. In the subquadrat, the locations of newly emerged seedlings of P. modesta were mapped, and seedlings were marked with coloured toothpicks at 2- to 4-week intervals during the growing season from May to September in 2002. Seedling survival was monitored until May 2003. Flowering ramets had been mapped in 2001. Spatial relationships between seedlings (live + dead, live or dead) and flowering ramets in the previous year were analysed by examining neighbourhoods around individuals (Condit et al. 2000):

  • image

where dij is the distance of ith seedling (i = 1 …n1) and jth flowering ramet (j = 1 …n2), respectively; Ax is the annulus area between radius x and x+ Δx; Ix is an indicator function that equals 1 when xdij ≤ x + Δx and is 0 otherwise; and wij is a weighting factor correcting for edge effects. The weighting factor is the proportion of the circumference of the circle centred at i, passing through j, which is inside the plot. It is closely related to Ripley's K-function (Ripley 1977), but K(x) refers to neighbourhoods of ≤x from the focal individual, whereas D(x) refers to an annulus between x and x+ Δx.

D(x) was standardized by dividing by the mean density of given plants across the whole plot. This standardized index is called the relative neighbourhood density function (NDF) (Perry 2004), and simplifies display and interpretation of results as, for all values of t, the reference value under spatial randomness is 1. Thus NDF > 1 indicates spatial aggregation, and NDF < 1 indicates a pattern that is more regular than expected by random.

NDF was calculated at 1-cm intervals up to 25 cm by using SpPack (Perry 2004). Values of observed NDF were tested against the null hypothesis that distributions of dead seedlings were spatially independent of flowering ramets. The 95% confidence envelopes of NDF were estimated from 499 simulations of a random point process.

safe site for establishment

To evaluate the distribution of safe sites for recruitment, we monitored seedling emergence and survival in a series of 10 permanent quadrats (0.5 × 0.5 m) at 0.5-m intervals along a 10-m transect, taking considerable care not to cause any disturbance that might bias future censuses of surface plants. The locations of newly emerged seedlings of P. modesta were mapped, and seedlings were marked with coloured toothpicks at 2- to 4-week intervals during the growing season from May to September in 2001, 2002 and 2003. Seedling survival was monitored until May 2004.

We recorded ground surface conditions to characterize the heterogeneity of microenvironments within each quadrat. We subdivided each quadrat into four 0.25 × 0.25 m subplots and rated the ground surface conditions in each subplot as mossy hammock with sparse vegetation cover, mossy hammock with dense vegetation cover or hollow bare ground. To determine whether seedling survival differed among the microenvironments, we compared the survival curves of seedling cohorts that emerged in 2001, 2002 and 2003 until spring 2004 among categories, using the Kaplan–Meier procedure for survival analysis (Kaplan & Meier 1958). This procedure estimates survival functions from the survival durations of the seedlings, defined as the number of days between seedling emergence and death. We performed a Mantel–Cox test for homogeneity of survival across the sites.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

genetic diversity

Figure 1 maps the distribution of the flowering ramets and the number of seedlings that emerged from each soil core.

A total of 142 seedlings emerged from the soil samples, of which 123 were genotyped at the 10 microsatellite loci. The total seed density was estimated as approximately 1800 m−2. Most of the seeds (> 60%) were found within the surface layer (0–1 cm depth) (Table 1).

Table 1.  Number of individuals collected and analysed, allelic richness (A), observed heterozygosity (HO), expected heterozygosity (HE) and fixation index (F) for 10 microsatellite loci of seedlings raised from surface (0–1 cm) and deeper (1–5 cm) seed banks and of flowering genets of Primula modesta
ComponentsNo. individuals collectedNo. individuals analysedAHOHEF
Surface seeds 87 774.770.5570.579 0.038
Deeper seeds 55 464.300.5730.580 0.001
Flowering genets2381644.620.5730.571−0.004

A total of 238 ramets flowered in 2003, of which 213 were genotyped at the 10 microsatellite loci. Some plants, mostly occurring within 5 cm of each other, had identical multilocus genotypes. The probability that two individuals could have identical multilocus genotypes when both are produced by sexual reproduction (Parks & Werth 1993) is less than 3 × 10−6 and we can therefore be confident that identical genotypes were genets of the same clone. Genetic parameters were calculated for the 164 recognized genets (Table 1).

Fixation index values, which measure deviation from Hardy–Weinberg equilibrium, did not deviate from zero for any component. The GST values (variation among components) between seed banks and flowering genets were very small (GST = 0.001, surface seeds vs. flowering genets; GST = 0.000, deeper seeds vs. flowering genets).

fine-scale genetic structure

The pairwise kinship coefficient Fij decreased steadily with geographical distance in the flowering population (Fig. 2a). The slope (b) of the regression between Fij and logarithmic distances was significant (P < 0.0001), with a b-value (± SE) of −0.0184 ± 0.0033. The surface seed bank also showed significant (P < 0.05) spatial genetic structure (b = −0.0062 ± 0.0011) (Fig. 2b), while no significant spatial structure was detected in the deeper seed bank (b = −0.0012 ± 0.0009) (Fig. 2c).

image

Figure 2. Correlograms of Fij coefficients within (a) flowering genets, (b) surface seeds, and (c) deeper seeds. The solid line plots the observed data and dotted lines indicate the 95% confidence interval deduced from 1000 permutations of individual multilocus genotypes within each distance class. Asterisks indicate significance at the 5% probability level by Bonferroni criteria.

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There was significant spatial genetic association (P < 0.0001) between the flowering genets and both the surface seeds and the deeper seeds (b = −0.0132 ± 0.0026 and −0.0099 ± 0.0039, respectively) (Fig. 3a,b). However, the strength of the association differed, as shown by the Sp statistics (0.0137 and 0.0100 for the surface seeds vs. flowering genets and the deeper seeds vs. flowering genets, respectively), indicating that there was a more pronounced genetic association between the surface seeds and flowering genets than between the deeper seeds and flowering genets.

image

Figure 3. Correlograms of Fij coefficients between (a) surface seeds and flowering genets, (b) deeper seeds and flowering genets, and (c) surface and deeper seeds. Data presented as in Fig. 2.

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The spatial genetic association between the surface and deeper seeds was also significant (b = −0.0061 ± 0.0012, P < 0.0001) (Fig. 3c).

Where the soil seed lay to the right or left of the flowering genet, there were significant spatial genetic structures between the soil seeds and the flowering genets (Fig. 4a,c). The estimated regression slopes were −0.0251 ± 0.0069 (P < 0.001) and −0.0413 ± 0.0074 (P < 0.0001), respectively. Where the soil seed lay uphill of the flowering genet, there was weak but significant (P < 0.05) genetic structure between them (b = −0.0103 ± 0.0051) (Fig. 4b). In contrast, where the soil seed lay downhill of the flowering genet, there was no significant (P > 0.05) spatial genetic structure between them (b = −0.0064 ± 0.0038) (Fig. 4d).

image

Figure 4. Correlograms of Fij coefficients between flowering genets and seed bank (a) to the right, (b) upward, (c) to the left, and (d) downward. Data presented as in Fig. 2.

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spatiotemporal pattern of seedling survival

The total number of seedlings emerging in the entire 0.5 × 4.5 m subquadrat was 766 in 2002, of which 484 survived for 1 year. Emerging seedlings and flowering ramets were strongly clustered together at short distances up to 20 cm (Fig. 5a). Spatially non-random mortality occurred (Fig. 5c), and the surviving seedlings became more aggregated at shorter distances (up to 8 cm) (Fig. 5b).

image

Figure 5. Relative neighbourhood density function (NDF) showing spatial associations between (a) emerging seedlings and flowering ramets, (b) surviving seedlings and flowering ramets, and (c) dead seedlings and flowering ramets. The solid line plots the observed data and the two dotted lines indicate the 95% confidence interval for the pattern expected from an independent distribution of plant locations.

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safe sites for establishment

Mossy hammock with sparse vegetation cover occupied 45% of the area of the 10 0.5 × 0.5 m quadrats, mossy hammock with dense vegetation cover occupied 33%, and hollow bare ground occupied 22%. The numbers of seedlings that emerged in each category were: 654, 127 and 194 in 2001; 340, 89 and 99 in 2002; and 191, 43 and 30 in 2003. Survival probabilities were lowest in hollow bare ground in 2001 (3-year, χ2 = 43.8, P < 0.0001, d.f. = 2; Fig. 6a) and 2002 (2-year, χ2 = 11.1, P = 0.004, d.f. = 2 in 2002; Fig. 6b). There was no significant difference in 1-year survival among these categories in 2003 (χ2 = 3.2, P = 0.20, d.f. = 2; Fig. 6c). Seedling density was much lower in 2003 than in the other years.

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Figure 6. Survival curves for seedlings that emerged in (a) 2001, (b) 2002 and (c) 2003 to May 2004 in the seedling demographics plots. Cumulative values for all quadrats are shown.

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Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

genetic diversity in soil seed banks

Soil seed banks can disperse genes through time, and consequently may exhibit temporal genetic structure in the form of genetic differences between the seed bank and above-ground populations (Templeton & Levin 1979). In some species, strong differences in allelic frequencies between seed banks and adult populations (Tonsor et al. 1993; Cabin 1996) or significantly higher genetic diversity in the seed banks than in the corresponding adult populations (McCue & Holtsford 1998; Morris et al. 2002) have been detected. However, in other cases very little differentiation between the two stages has been reported (Mahy et al. 1999; Koch et al. 2003). In this study, seed banks from neither of the two depths examined differed substantially in genetic composition from the above-ground plants, according to the allelic frequency analyses, possibly because a flowering plant continues to influence the genetic structure of soil seeds throughout its life span. No direct estimates of longevity are available for P. modesta, but Tamm (1972) showed that the life span of the congeneric species P. veris could exceed 50 years. This indicates that the genetic consequences of seed banks may vary among species and/or populations depending on their demographic attributes, as suggested by Mahy et al. (1999).

As the species we analysed is strictly outcrossing, the seed banks and above-ground populations did not deviate from Hardy–Weinberg equilibrium (Table 1). However, FIS values were higher in the soil seeds than in the flowering genets, indicating a trend for the latter to have greater heterozygosity. Similar trends have been documented in various other outcrossing species such as Cecropia obtusifolia (Alvarez-Buylla et al. 1996), Plantago lanceolata (Tonsor et al. 1993) and Lesquerella fendleri (Cabin et al. 1998). A likely explanation for these observations is that heterozygotes tend to have higher fitness and survival rates than homozygotes, leading to adult populations with higher heterozygosity than the corresponding seed banks.

spatial genetic structure

The spatial association between seed banks and reproductive plants has been studied by comparing variations in density of seed rain or the seed bank with distance from reproductive plants (Dalling et al. 1998; Houle 1998; Witkowski & Garner 2000). However, the actual sources and temporal structures of seeds were not documented. Although recent advances in the analysis of molecular genetic markers have made it possible to characterize the pedigree of dispersed seeds in relation to the above-ground plants, few studies have examined the fine-scale spatial genetic structure of seed banks (Cabin 1996; Cabin et al. 1998). To our knowledge, this study is the first attempt to examine the spatial genetic association between seed banks sampled at different soil depths and above-ground plants, and to evaluate the effects of the temporal dispersal of seed banks on the fine-scale spatial genetic structure.

We tried to assign the parentage of the soil seeds using the maximum likelihood method with CERVUS (Marshall et al. 1998). However, total exclusion probabilities calculated from the exclusion probabilities of each locus were 0.9104 for the first parent and 0.9888 for the second parent and the probability of correctly excluding all unrelated adults within the quadrat was therefore low. In addition, most soil seeds were thought to have pollen parents outside the quadrat. No direct estimates of pollen dispersal are available for P. modesta, but a study on a congeneric species with a very similar entomophilous breeding system and heterostyly (Primula sieboldii) revealed pollen flow distances to be much greater than those of seed flow (Ishihama et al. 2003). As, in species with a long-lived seed bank, soil seeds might also not necessarily have parents within the current adult population, we abandoned parentage assignment.

Stratified sampling of the soil seed bank allows us to analyse temporal variations in the spatial structure of the seed bank. Minor soil disturbances probably homogenized the seed bank so that each soil layer contained seeds of different ages, consistent with the difference in the spatial genetic structures of the surface and deeper seed banks. The surface seeds showed significant spatial genetic structure (Fig. 2b), but not the deeper seeds (Fig. 2c). Furthermore, the spatial genetic association between the surface seeds and the flowering genets was stronger than the association between the deeper seeds and flowering genets (Fig. 3a,b), suggesting that the spatial structure of the surface seed bank reflects the previous season's seed dispersal pattern. Therefore, the surface seed bank is likely to account for a large proportion of the transient seed bank. Cabin (1996) and Cabin et al. (1998) also found significant spatial genetic structure in the surface seed bank (at a depth of 0–2 cm) of species with limited seed dispersal. These findings correspond with our results and suggest that the spatial structure of the surface seed bank and above-ground populations are mutually dependent.

On the other hand, we can suggest several possible reasons for the lack of spatial genetic structure in the deeper seeds. First, persistent seed banks would pool the reproductive outputs of multiple generations and average out the effects of each generation's dispersal pattern. Secondly, the persistent seed bank may have more opportunity for secondary dispersal, consistent with our finding that there was no spatial genetic structure in the downhill direction, in which secondary dispersal by water may occur, while considerable structure was detected in the right and left directions, in which such dispersal is virtually impossible (Fig. 4). It is likely that secondary dispersal by water flow elongates the seed shadow in the uphill-downhill direction. A possible reason for less relatedness between flowering genets and downhill seeds than flowering genets and uphill seeds is probably that the downhill seeds are transferred more distantly from parents than the uphill seeds. Moreover, the microtopographical nature (mossy hummock and hollow bare ground) of the site might have some influence on the secondary dispersal of the seeds as well as water flow. Including considerations of physical (e.g. hydrological or geological) processes in analyses of secondary seed dispersal (vertical and horizontal) may help to elucidate seed dynamics (Chambers et al. 1991; Hampe 2004).

The spatial genetic association between flowering genets and soil seeds might be obscured as soil depth increases because there are significant positive autocorrelations in the first distance class between surface seeds and flowering plants, and between surface seeds and deep seeds, but not between deep seeds and flowering plants (Fig. 3). However, it should be noted that the samples for the surface and deeper seeds in the first distance class were derived from the same soil cores. Therefore, Fij values of the soil seeds in the first distance class may tend to be overestimated because the true distance range they are based upon is, inevitably, the diameter of the soil cores (5 cm) rather than 0–30 cm.

spatiotemporal pattern of seedling survival

The transitions from seed to seedling and from seedling to juvenile are high-risk periods in the life cycle of many plants (Harper 1977; Silvertown & Charlesworth 2001). Spatial heterogeneity in microsites favourable for germination and/or establishment contributes to the generation and/or maintenance of the spatial genetic structure of a population (Sokal et al. 1989; Suzuki et al. 2003). Primula modesta is no exception: the mortality of seedlings was much higher than that of adults (A. Shimono, unpublished data from 3 years), mortality was spatially non-random (Fig. 5c) and there were significant differences in seedling mortality among ground surface conditions (Fig. 6), indicating that safe sites for seedling establishment are spatially heterogeneous.

Hollows collect water on rainy days and, although seeds can germinate, few can survive this disturbance of the soil surface. Mossy hummocks, where adults are clumped, are better for both seed germination and seedling establishment and seedlings therefore tend to establish successfully near flowering ramets. The patchy spatial distribution of these available safe sites is likely to contribute to the development of fine-scale spatial genetic structure in this population.

ecological processes affecting fine-scale spatial genetic structure

We can infer ecological processes underlying the spatial genetic structure of the seed bank in relation to the above-ground plants. Evidence for restricted seed dispersal comes from the significant autocorrelation between the surface seed banks and flowering genets at short distances, supported by the clustering of seedlings around flowering ramets. With the passage of time, seeds may be incorporated into deeper soil as plant litter and debris are accumulated: the seeds on the soil surface that germinate in spring are likely to have been dispersed in the previous season. Seedlings tend to be clumped near the flowering plants because of both the limited seed dispersal and the patchy distribution of safe sites for establishment. Such phenomena develop and strengthen the marked spatial structure at distances of up to 30 cm. However, this structure may be weakened by even minor soil disturbance, as suggested by the weak or absent spatial genetic association between the deeper seed bank (1–5 cm depth) and the adults.

Using stratified sampling to determine the spatial genetic association between an above-ground population and a seed bank may help reveal the spatiotemporal structure of the seed bank, because age-specific spatial patterns of seed banks are difficult to elucidate. Our study constitutes an important step towards the integration of spatiotemporal dynamics of soil seed bank and above-ground plants.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We thank the Chubu Regional Office for Nature Conservation, Toushin District Forest Office and Komoro City Office for allowing us to survey within the Joshinetsu Kogen National Park. We also thank Hiromi Obayashi, Keisuke Kanda, Fumio Nakayama and the staff of the Takamine Kogen Hotel for their warm encouragement throughout our field works. We thank the staff of the Laboratory of Conservation Ecology, The University of Tokyo, for their advice and assistance.

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  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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