Genetic make-up and diversity of regenerated Betula maximowicziana Regel. sapling populations in scarified patches as revealed by microsatellite analysis

Forest Ecology and Management 203 (2004) 273–282 www.elsevier.com/locate/foreco

Genetic make-up and diversity of regenerated Betula maximowicziana Regel. sapling populations in scarified patches as revealed by microsatellite analysis Susumu Gotoa,1,*, Yoshiaki Tsudab,2, Kyoko Nagafujic,3, Kentaro Uchiyamab,2, Yasuo Takahashia,1, Takeshi Tanged,4, Yuji Ideb,2 a

University Forest in Hokkaido, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yamabe, Furano, Hokkaido 079-1561, Japan b Laboratory of Forest Ecosystem Studies, Department of Ecosystem Studies, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan c Laboratory of Plant Biotechnology, Department of Global Agricultural Sciences, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan d Research Division of University Forest, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan Received 21 November 2003; received in revised form 25 May 2004; accepted 21 July 2004

Abstract In June 2002, the genetic make-up and diversity of regenerated populations of Betula maximowicziana Regel. saplings in two scarified patches were investigated by microsatellite analysis. The scarified patches, SP-1 (0.63 ha) and SP-2 (0.20 ha), were established in 1988 around single seed-trees of B. maximowicziana in the Tokyo University Forest in Hokkaido, located in central of Hokkaido district in Japan. Comparing genotypic data of the adult population around the two patches with the sapling populations, the genetic contribution of the seed-trees to SP-1 and SP-2 was evaluated by three methods of parentage analysis: simple exclusion, categorical allocation and fractional allocation. Although the scarified patches were established close to the seed-trees, the genetic contributions of the seed-trees to SP-1 and SP-2 were surprisingly low: 4.25% and 2.35%, respectively, according to simple exclusion, 2.08% and 0.00% according to categorical allocation and 2.39% and 1.95% according to

* Corresponding author. Tel.: +81 167 42 2111; fax: +81 167 42 2689. E-mail address: [email protected] (S. Goto). 1 Tel.: +81 167 42 2111; fax: +81 167 42 2689. 2 Tel.: +81 3 5841 5490; fax: +81 3 5841 5494. 3 Tel.: +81 3 5841 7515; fax: +81 3 5841 5304. 4 Tel.: +81 3 5841 8640; fax: +81 3 5841 5494. 0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.07.053

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fractional allocation. The areas covered by SP-1 and SP-2 were small compared to that of the adult population, but their genetic diversity was similar to that of the adult population: the expected heterozygosity (HE) of SP-1, SP-2 and the adult population was 0.365, 0.341 and 0.371, respectively. The genetic differentiation between pairs of populations was low; pairwise FST values ranged from 0.003 to 0.016. Genetic diversity may be maintained in the regenerated sapling populations in scarified patches by temporal gene flow from the old to the new populations, and by extensive spatial gene flow, promoted by the species’ small winged seeds and long-distance pollen flow. # 2004 Elsevier B.V. All rights reserved. Keywords: Betula maximowicziana; Genetic diversity; Genetic make-up; Microsatellite; Parentage analysis; Scarification

1. Introduction Betula maximowicziana Regel. is a common tree species in the cool-temperate zone in northern Japan (Ohwi, 1965). This hardwood tree species is favored as a source of premium-quality wood materials for furniture. It has typical regeneration characteristics of pioneer trees, including the production of highvolumes of small, anemochoric seeds with high dispersal ability (Yanagisawa, 1961), and rapid growth rates in open sites (Watanabe, 1988). B. maximowicziana has often been found to establish even-aged stands, following the occurrence of large-scale disturbance with intense disruption of the soil surface (Osumi and Sakurai, 1997) caused by natural events such as forest fires (Tsuda et al., 2002) and human activities such as site preparation and planting of conifer stands (Hasegawa and Taira, 2000). In sub-boreal forests in Hokkaido, northern Japan, most stands have been managed by selective logging (Nagaike et al., 1999). B. maximowicziana has been one of the main target species for wood production by selective logging in this area. In Tokyo University’s Forest in Hokkaido, a natural forest management regime (the silvicultural management system, SMS), based on selective logging and natural regeneration, has been adopted, due to its proposed suitability as a sustainable management model for the sub-boreal forests of Hokkaido (Watanabe and Sasaki, 1994). One of the most important factors preventing regeneration in such stands is the dense cover of dwarf bamboo (Sasa senaensis and S. kurilensis) frequently found on the forest floor. Most tree seedlings, including those of B. maximowicziana, will not regenerate naturally in such environments (Watanabe and Sasaki, 1994). Therefore, a scarification method has been applied in which ground cover

and topsoil, including dwarf bamboo rooting systems, are removed by a bulldozer to expose the subsoil and thus promote the regeneration of tree species (Fujiwara et al., 1984). This treatment is effective for the regeneration of Abies, Picea and Betula species (Takahashi et al., 1981, 1984, 2002). In 1988, two patches in the 33rd compartment of the University Forest were clear-cut and harvested around each single seed-tree of B. maximowicziana, and then scarified to promote regeneration of the offspring of these seed-trees. However, the genetic make-up and diversity of sapling populations regenerated in such scarified patches are unknown. Preservation of genetic variability is crucial for adaptation and survival of tree species, because tree species experience the heterogeneous environmental pressures over space and time (Mu¨ ller-Starck, 1995). If very few adults contribute to sapling populations, the genetic diversity of them will be low. Therefore, we should evaluate the genetic make-up and genetic diversity of these populations. In this study, we analyzed the genetic make-up and diversity of these sapling populations using microsatellite marker analysis.

2. Materials and methods 2.1. Study site The study site was located in the 33rd compartment of the Tokyo University Forest in Hokkaido, which is located in the Furano city administrative district, Japan (43.2898 N, 142.478 E). Key climatic parameters for the arboretum garden in this University Forest (230 m elevation) are as follows: annual mean temperature, 6.8 8C; mean annual precipitation,

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Fig. 1. Location of scarified patches and sampled adult trees, including seed-trees. This study site was located in the 33rd compartment of Tokyo University’s Forest in Hokkaido. Black circles (ST-1 and ST-2) represent seed-trees of each scarified patch. SP-1 and SP-2 are scarified patches established in 1988. Saplings occurred in two scarified patches. Unfilled circles mark the location of adult trees around scarified patches.

1230 mm; mean snow cover, 100 cm. The elevation of this study site is about 420 m, and the vegetation consists of mixed conifer-hardwood forests that are typical of the cool-temperate zone. In the summer of 1988, two patches (SP-1, 0.63 ha; SP-2, 0.20 ha) were harvested by clear-cutting, then scarified around seedtrees ST-1 and ST-2, respectively (Fig. 1). These seedtrees were registered as being phenotypically superior by visual inspection (Yamamoto et al., 1989). The heights of ST-1 and ST-2 were 26.2 and 26.8 m, and their diameters at breast height (DBH) were 58.0 and 61.2 cm, respectively. 2.2. Field investigation Within each scarified patch, we randomly established three quadrates (4 m
4 m), respectively. The distances from ST-1 to each quadrate were 30.3, 31.0, and 34.0 m, in an average of 31.8 m. Those of ST-2 were 17.8, 18.1, and 27.8 m, in an average of 21.2 m.

We measured the DBH and height of all B. maximowicziana saplings within the quadrates in June 2002, and subsequently collected fresh leaves or pieces of inner bark from them as sample tissues for DNA analysis. To elucidate the age of the sapling populations, we felled 30 saplings around the quadrates (10 saplings around each quadrate) and collected discs of stems at 5 cm height above the ground. We then counted the annual rings of each disc to estimate the age of each sapling. To estimate the genetic contribution of the seed-trees to the sapling populations, and to evaluate the genetic diversity of the adult B. maximowicziana population, we examined 54 adults (DBH >30 cm) in an area of about 20 ha around SP-1 and SP-2. Locations of all the adults were mapped (Fig. 1), and fresh leaves and/or inner bark of each adult tree were collected as sample tissues for DNA analysis. These adults were used as candidate parents in parentage analysis of the sapling populations.

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2.3. DNA extraction and microsatellite genotyping Total DNA was extracted from sample tissues of each sapling and adult tree using a DNeasy Plant Mini Kit (Qiagen Co. Ltd.). Microsatellite loci were amplified using seven primer pairs developed for B. maximowicziana (Ogyu et al., 2003), and four for B. platyphilla var. japonica (Wu et al., 2002). Genotypes were scored according to PCR product length at each locus using a Prism 3100 Genetic Analyzer (ABI) and GeneScan analysis software (ABI).

2.4. Genetic contributions of seed-trees to sapling populations The genetic contribution of the seed-trees to sapling populations was estimated by comparing genotypic data for the adult population with data obtained for SP-1 and SP-2. Parentage analysis of SP1 and SP-2 was conducted by three methods: simple exclusion, categorical allocation and fractional allocation. First, we applied the simple exclusion method. This method uses incompatibility between parents and offspring to reject particular parent–offspring hypotheses. Ideally, all but one parent pair will be excluded as candidate parents for each offspring. However, few studies (Dow and Ashley, 1996; Isagi et al., 2000) have achieved this ideal. In this study, we assigned the same value to all non-excluded parents, after parentage analysis at 11 microsatellite loci. If diagnostic adult was excluded from candidate parents, its genetic contribution is 0. If diagnostic adult was comprised in non-excluded candidate parents, its genetic contribution was calculated as 1/n, n; the number of nonexcluded adults. Second, we applied the categorical allocation method. This method assigns the entire offspring to a particular adult, using likelihood-based approaches to select the most likely parent from a pool of nonexcluded parents. For this, we used a computer program, CERVUS 2.0 (Marshall et al., 1998), to calculate a logarithm of likelihood ratio (LOD score), then assigned offspring to the parent with the highest LOD score. The genetic contribution of a particular adult was then given by the proportion of saplings assigned to it as diagnostic parent.

Third, we applied the fractional allocation method. Devlin et al. (1988) proposed this method for paternity analysis of progeny for which one parent is known, but we used it here for parentage analysis of saplings for which both parents are unknown. In this method, some fraction between 0 and 1 was assigned to each nonexcluded parent. The proportion of an offspring allocated to a particular candidate parent is proportional to its likelihood (LOD score) of parenting the offspring compared to all other non-excluded candidate parents. The genetic contribution of a particular adult was then given by the proportion of its sum of its LOD scores as a diagnostic adult to the total. 2.5. Genetic diversity of the adult population, SP-1 and SP-2 To evaluate within-population genetic diversity, the number of detected alleles (A), the observed (HO) and expected (HE) heterozygosity, and inbreeding coefficient (FIS) were calculated according to Nei (1978). The allelic richness (R) suggested by Petit et al. (1998) was also calculated using the computer program FSTAT ver. 2.9.3 (Goudet, 1995). Levels of significance where FIS 6¼ 0 were also determined after 1000 permutations by this program (Goudet, 1995). 2.6. Genetic differentiation between pairs of populations To evaluate genetic differentiation between pairs of populations, pairwise FST values, as proposed by Weir and Cockerham (1984), were calculated using the computer program FSTAT ver. 2.9.3 (Goudet, 1995). The number of migrants (Nm) between pairs of populations was also calculated, according to Wright (1931, 1951).

3. Results 3.1. DBH, height, and age of sapling populations The total number of saplings regenerated in the three 48 m2 quadrates was 56 in SP-1 and 74 in SP-2 (Table 1). The average calculated tree density was 11,667 trees/ha in SP-1 and 15,416 trees/ha in SP-2, while the average DBH for SP-1 and SP-2 was 15.0

S. Goto et al. / Forest Ecology and Management 203 (2004) 273–282 Table 1 DBH, height, and age of the sapling populations in the scarified patches Patch n

DBH (mm)

Height (cm)

Mean  S.D. Mean  S.D. SP-1 SP-2

56 15.0  10.5 74 24.0  12.4

Agea n

281.6  139.0 30 448.0  172.8 30

Mean  S.D. 10.9  1.3 11.6  1.2

a

Ages were estimated by counting annual rings after felling 30 saplings.

and 24.0 mm, respectively, and the average height of the saplings was 281.6 and 448.0 cm. DBH and height were significantly different between patches according to t-tests (DBH; t = 4.379, P < 0.0001, height; t = 5.902, P < 0.0001). The saplings in SP-1 and SP-2 were 10.9 and 11.6 years old on average, respectively. Age was not significantly different between patches according to t-tests (t = 2.00, P > 0.05). 3.2. Genetic contribution of seed-trees to sapling populations According to the simple exclusion method, 42.9% and 45.2% of the saplings in SP-1 and SP-2 had incompatible alleles at one or more loci with their respective seed-tree. Therefore, they did not appear to be offspring of seed-trees. The genetic contribution of the seed-trees to sapling populations, estimated by the three methods, was surprisingly low. The genetic contribution of ST-1 to SP-1 was 4.25%, 2.08% and 2.39% according to the simple exclusion, categorical allocation and fractional allocation analyses, respectively (Fig. 2a), while the corresponding figures for the genetic contribution of ST-2 to SP-2 were 2.35%, 0.00% and 1.95% (Fig. 2b). 3.3. Genetic diversity of the adult population, SP-1 and SP-2 Statistics related to within-population genetic diversity are given in Table 2. For each population, the mean number of detected alleles (A) and the mean allelic richness (R) ranged from 2.727 to 3.000 and from 2.727 to 2.956, respectively. The observed heterozygosity (HO) at each locus ranged from 0.000 to 0.593 in the adult population, from 0.020 to 0.673 in SP-1, and from 0.000 to 0.645 in SP-2. The expected heterozygosity (HE) at each locus ranged from 0.000

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to 0.611 in the adult population, from 0.020 to 0.685 in SP-1, and from 0.000 to 0.637 in SP-2. These parameters of genetic diversity were very similar between adult and sapling populations. Hardy-Weinberg equilibrium could not be rejected, except for SP-1 at locus Bm 630 and SP-2 at locus Bp 12. Over the 11 loci examined, the expected heterozygosity (HE) was slightly lower than the observed heterozygosity (HO), causing the mean inbreeding coefficient (FIS) to be negative, but not statistically significantly so, in all of the populations. 3.4. Genetic differentiation between pairs of populations Over the 11 tested loci, pairwise FST values ranged from 0.0028 between SP-1 and SP-2 to 0.0158 between the adult population and SP-1 (Table 3), suggesting that levels of genetic differentiation were low. Nm values, which describe the level of gene flow between pairs of populations, ranged from 15.6 to 89.0 (Table 3), suggesting that gene flow is extensive.

4. Discussion Scarification with soil disturbance can improve seedbed receptivity and light conditions by exposing more of the surface (Pre´ vost, 1997), thus promoting the regeneration of Betula species (Osumi and Sakurai, 1997; Pre´ vost, 1997; Takahashi et al., 2002). In both scarified patches examined in this study, sufficient numbers of saplings regenerated to form dense stands. In primary forests in Hokkaido, most B. maximowicziana seedlings establish in mounds created through the ground being pushed up when trees are uprooted (Goto, S., personal observation). In selectively logged stands, there is less coarse woody debris than in primary forests (Nakagawa et al., 2001), and uprooting is also rare. Consequently, due to the reduction in abundance of appropriate sites for B. maximowicziana seedlings, very few saplings are usually observed in selective logging stands. To remedy this deficiency, scarification should provide an effective means for promoting the regeneration of B. maximowicziana in Hokkaido. However the age of sapling populations was similar in SP-1 and SP-2, the height and DBH of them were

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significantly different between patches. Takahashi et al. (1984) reported that the height of seedlings regenerated after 5 years from the scarification was significantly different among the scarified patches established in 1979. Soil nutrient conditions after the scarification were not uniform. We think that soil condition difference may affect the growth rate of sapling populations in SP-1 and SP-2. We analyzed parentage by three methods: simple exclusion, categorical allocation and fractional allocation. The results from parentage analyses must be carefully considered in terms of the strength and weakness of the analytical method used (Jones and Ardren, 2003). The overall trends derived using the three methods regarding the genetic contributions of each adult were similar, but there were discrepancies

between the results of the simple exclusion and categorical allocation analyses for a few adults. For example, the genetic contributions of adults 419 and 420 to SP-1 were estimated to be 2.57% and 2.05% by simple exclusion, respectively, compared to 2.08% and 12.5% according to categorical allocation (Fig. 2a). Simple exclusion is most powerful when highly polymorphic genetic markers are available (Dow and Ashley, 1996; Isagi et al., 2000). The cited authors used highly polymorphic markers with 10–20 alleles per locus, but the number of detected alleles in this study was only 3.00 on average. Few candidate parents were excluded in this study, so the variance in genetic contribution for each adult may have been underestimated. On the other hand, evaluating genetic contributions by categorical allocation tends to give

Fig. 2. (a) Genetic contribution of each adult tree to SP-1, estimated by simple exclusion, categorical allocation and fractional allocation methods. ST-1 and ST-2 represent seed-trees of SP-1 and SP-2, respectively. Nos. 409–460 refer to adult trees around the scarified patches. Black and gray bars represent the genetic contributions of the seed-trees and the other adult trees to sapling populations, respectively. (b) The genetic contribution of each adult tree to SP-2, as estimated by simple exclusion, categorical allocation and fractional allocation methods. ST-1 and ST-2 represent seed-trees of SP-1 and SP-2, respectively. Nos. 409–460 refer to adult trees around scarified patches. Black and gray bars represent the genetic contributions of seed-trees and other adult trees, respectively to sapling populations.

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Fig. 2. (Continued ).

Table 2 Number of detected alleles (A), allelic richness (R), observed (HO) and expected heterozygosity (HE), and inbreeding coefficient (FIS) at 11 loci for the adult population and the SP-1 and SP-2 sapling populations Locus

Adult population

SP-1

SP-2

A

R

HO

HE

FISa

A

R

HO

HE

FISa

A

R

HO

HE

FISa

Bm 093 Bm 097 Bm 529 Bm 544 Bm 607 Bm 630 Bm 671 Bp 01 Bp 11 Bp 12 Bp 15

3 4 2 4 4 5 3 1 2 2 3

2.992 4.000 2.000 4.000 3.815 4.807 2.907 1.000 2.000 2.000 2.992

0.148 0.481 0.296 0.593 0.426 0.389 0.593 0.000 0.537 0.426 0.333

0.172 0.611 0.302 0.577 0.403 0.360 0.437 0.000 0.461 0.375 0.343

0.136 0.212 0.017 0.027 0.057 0.080 0.356 0.000 0.164 0.136 0.027

3 4 2 4 3 4 2 2 2 2 2

3.000 4.000 2.000 4.000 3.000 4.000 2.000 2.000 2.000 2.000 2.000

0.143 0.673 0.224 0.388 0.286 0.653 0.449 0.020 0.510 0.571 0.265

0.133 0.685 0.199 0.487 0.375 0.477 0.408 0.020 0.447 0.453 0.286

0.073 0.017 0.129 0.204 0.237 0.368* 0.099 0.031 0.142 0.261 0.073

2 4 2 4 2 5 5 1 2 2 3

2.000 4.000 2.000 3.998 2.000 4.789 4.538 1.000 2.000 2.000 2.790

0.177 0.532 0.194 0.548 0.145 0.500 0.613 0.000 0.581 0.645 0.145

0.162 0.637 0.175 0.550 0.135 0.435 0.498 0.000 0.495 0.448 0.190

0.094 0.165 0.105 0.003 0.073 0.149 0.231 0.000 0.172 0.440* 0.234

Mean

3.000

2.956

0.384

0.367

0.039

2.727

2.727

0.380

0.361

0.020

2.909

2.829

0.371

0.339

0.042

The markers Bm 093, 097, 529, 544, 607, 630 and 671 were developed by Ogyu et al. (2003), while Bp 01, 11, 12 and 15 were developed by Wu et al. (2002). a Levels of significance when FIS 6¼ 0 were determined after 1000 permutations by the computer program FSTAT ver. 2.9.3 (Goudet, 1995); *P < 0.05; all other values, not significant.

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Table 3 Pairwise FST values are given below the diagonal, and Nm values are given above the diagonal

Adult population SP-1 SP-2

Adult population

SP-1

SP-2

– 0.0028 0.0158

89.0 – 0.0117

15.6 21.1 –

overestimates for parents with many homozygous loci, and underestimates for parents with many heterozygous loci (Devlin et al., 1988). Trees 419 and 420 were homozygous at three and seven of the 11 loci examined, respectively. Thus, the findings related to these trees are consistent with the conclusions of Devlin et al. Fractional allocation should provide more exact estimates of genetic contribution (Jones and Ardren, 2003), but it may also underestimate variance in genetic contribution. In cases like this study, where there are many candidate parents and highly polymorphic genetic markers are not available, we think that the genetic contribution of the diagnostic adults should be evaluated by all three methods. However, the genetic contributions of ST-1 to SP-1 and ST-2 to SP-2 were less than 5%, according to all three methods. Therefore, we conclude that the seed-trees did not contribute greatly to sapling populations regenerated in scarified patches, genetically. Since the scarified patches were established so close to the seed-trees, we anticipated that most of the saplings would be their offspring. From this perspective, the genetic contributions of the seedtrees to the scarified patches were surprisingly low. These findings may be due to extensive, windmediated spatial gene flow through seed and pollen. The small, winged seeds of B. maximowicziana enable dispersal across wide areas (Yanagisawa, 1961), and we have detected seed-rain at distances greater than 100 m from isolated trees in B. maximowicziana using seed traps (Ogyu et al., unpublished data). Pollen flow over several hundred meters has been observed in wind-pollinated tree species (Dow and Ashley, 1996, 1998; Streiff et al., 1999), and has also been detected in B. maximowicziana (Tsuda et al., in preparation). However, wind-dispersal of seed and pollen often follows

leptokurtic functions (Streiff et al., 1999; Heuertz et al., 2003). Thus, even though B. maximowicziana has small, winged seeds, most of them should be dispersed in the vicinity of mother trees (Ogyu et al., unpublished data). If most of seeds dispersed in such a fashion, half-sib families were clustered in the vicinity of mother trees. Seeds and seedlings that escape attacks by densitydependent fungi and herbivores, which are often frequent in the vicinity of their parents, tend to have disproportionate success compared with those dispersed further distances (Janzen, 1970; Clark and Clark, 1984; Tomita et al., 2002). Relatively strong genetic structures are found in seeds or seedlings, but these structures tend to disappear as the plants grow, due to demographic thinning of seedling patches (Hamrick et al., 1993; Ueno et al., 2002). Since the sapling populations studied here were over 10 years old, the genetic contribution of the seed-trees may have declined during their development from the seedling to the sapling stage. We have just established a test plantation to clarify these thinning effects due to sib-competition in early stages of B. maximowicziana seedling development. In the early stages of seedling development, B. maximowicziana is subject to high mortality rates due to drought and cold stresses (Osumi and Sakurai, 2002). If wide areas were scarified, drought and cold may severely affect the performance of B. maximowicziana seedlings. In this study, the genetic diversity of an adult population across an area of about 20 ha was maintained in sapling populations that regenerated in narrow scarified patches. This finding is useful for deciding scarified patch areas. Genetic diversity was maintained by spatial gene flow; the ability of the species’ seed and pollen to disperse over substantial distances enables many adult trees to contribute genetically to sapling populations (Fig. 2). Nm values between adult and sapling populations, which are useful indicators of the extent of gene flow, were 89.0 between the adult population and SP-1, and 15.5 between the adult population and SP-2 (Table 3), indicating that extensive gene flow occurs from old to new populations. The genetic diversity of sapling populations regenerated in scarified patches may be also maintained by temporal gene flow from the old to new populations.

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Acknowledgements We are grateful to the staff of the Tokyo University Forest in Hokkaido for the help they provided during this investigation. We are also grateful to Dr. H. Yoshimaru, Dr. Y. Isagi, T. Sato, Dr. Y. Suyama, and M. Kimura for helpful comments. This study was supported in part by a Grant-in-Aid for Science Research (No. 15380100) from the Ministry of Education, Science and Culture, Japan.

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