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1. Introduction

Afforestation is considered to be the best practice for ecosystem restoration on former opencast oil shale mining areas in Estonia because harsh soil conditions are rarely suitable for other land uses [1]. The increasing annual inputs of leaf and root litter, as well as permanent ground vegetation forming on skeletal quarry spoil could significantly increase soil organic matter pools and develop into the productive ecosystem during the first two to three decades after afforestation [2-5]. Since the 1960s, more than 10 000 ha of former opencast mining areas have been afforested in north-eastern Estonia [1] where Scots pine (Pinus sylvestris L.) has been the dominant tree species (>90%)[1,6].

Afforestation of post-mining oil shale quarries in Estonia is carried out directly on levelled quarry spoil, which is characterised as a calcareous skeletal detritus with a poor water holding capacity, low organic material supply, and limited nutrient availability [4, 7, 8]. Covering the levelled quarry spoil with previously removed topsoil is expensive, and is generally aimed at restoring land for agricultural use [9]. However, the reestablishment of topsoil cover can enhance revegetation and ecosystem restoration during the early stages of stand development, compared to bare quarry spoil [10,11].

The main aim of degraded land restoration is to shorten the transitional time from overburden to self-functioning forest ecosystem [11]. Therefore, the choice of tree species for the afforestation of post-mining areas is an important factor that determines the duration of soil pedogenesis and successful forest ecosystem restoration [12, 13]. Monocultural pine stands are very prone to fire in dry quarry conditions, but fast-growing pioneer tree species like alders [5, 13] and birches [14-16] have several advantages over conifers in degraded land restoration. Deciduous trees have faster growth rates during early development [5, 17] and different fine root morphological adaptations [13, 15, 18]. The higher ameliorative potential of easily decomposable leaf litter [17, 19] could significantly influence soil biota abundance [20] and the faster accumulation of organic material [4].

Populus spp. have also successfully been used for post-mining areas restoration [21-23]. Poplars and their hybrids have been cultivated on a small scale on former quarry spoils in Estonia since the 1960s [14], and these attempts have shown that poplars can successfully be used if fast restoration is needed. For example, there are measurements from high productivity poplar stands on quarry spoil where the mean annual increment is more than 11 [m.sup.3] [ha.sup.-1] [yr.sup.-1], at the age of 25 [10]. Hybrid aspen (Populus tremula L. x P. tremuloides Michx.) has a potential for the restoration of post-mining areas, in terms of fast growth at a young age [10, 24, 25] and its ameliorative impact on former arable soils during the first half of the rotation period [26]. However, so far experience with hybrid aspen on post-mining oil shale areas includes only the early development of the stands [10].

Nutrient availability for trees and nutrient supply in the long term are important factors in terms of successful ecosystem restoration and soil development on nutrient-poor post-mining quarry soils [3, 8]. It should be kept in mind that spoil material has a very low water holding capacity [8], which could seriously limit the growth of and nutrient uptake by trees. Levelled quarry spoil creates nitrogen-limited conditions for trees [4, 8, 14], but several studies have shown that there is a clear positive impact of deciduous trees on soil nitrogen concentration in Estonian post-mining oil shale quarries [17, 19, 27]. The increase in nitrogen concentration is more clearly evident under [N.sub.2]-fixing black alder plantation [17], but the abundance of [N.sub.2]-fixing legume family species could also be an important source for nitrogen [28, 29].

The status of and changes in other important macronutrients are also essential in resource management and successful ecosystem restoration. For example, the available phosphorus (P) concentration is extremely low in quarry spoils [8, 14] and shows a clear decrease after post-mining quarry afforestation [17, 18]. The growth-controlling effects of P are evident during early development in post-mining soils [10, 21]. Generally, afforestation of former alkaline oil shale quarries under deciduous trees decreases soil acidity during the first decade [17], but sometimes the effect is more obvious after a longer period [18]. The status of and changes in soil micronutrients in post-mining quarries after afforestation have been studied more rarely [8, 23]. However, their importance to plant productivity and soil development cannot be neglected.

Successful restoration of deteriorated landscapes such as former mining areas includes also the recovery of floristic diversity. Restoration of the biodiversity that characterised the plant communities present in the period before mining is a time-consuming process. Even if the overall vegetation composition of reclaimed sites resembles that of the surrounding forest, a number of forest species may still be missing due to colonisation and recruitment problems [30, 31]. Studies of reclaimed Estonian oil shale and Czech coal mining sites have shown that different tree species have different impacts on the diversity and composition of understory [32-35].

So far, the impact of hybrid aspen plantations on the understory diversity on former mining areas has only briefly been studied in young stands [10], but the understory vegetation in older stands needs to be investigated as well. A study by Tullus et al. [36] of midterm-aged hybrid aspen plantations in former agricultural sites showed that hybrid aspen plantations host a rich understory flora where species with different ecological requirements are present, ranging from typical fallow species to shade-tolerant forest species. Studies of coal mine reclamation in the USA suggest that the species of herbaceous cover may be an important factor in forest establishment through both direct and indirect effects, and that the high diversity of ground cover may be beneficial for ecosystem development [37].

The main aim of this study is to assess the recovery of the forest ecosystem in 15-year-old (midterm) hybrid aspen plantations on a reclaimed oil shale quarry. The evaluation is based on repeated measurements of tree growth, understory vegetation (vascular plants and bryophytes), and the nutritional status of soil 5 and 15 years after afforestation. The study comprises mining sites subject to two different restoration methods: afforestation of bare quarry spoil (site group Al) and quarry spoil with restored topsoil (site group A2). Hybrid aspen plantations on former arable land with the prevailing soil type for the mining area (corresponding to the Hepatica forest site type) are used as a reference group (site group Bl). The specific aims of the study are: 1) to clarify the effect of different restoration methods on 10-year changes in tree layer and soil nutritional status (soil reaction ([pH.sub.KC1]), concentrations and stocks of macro-and micronutrients); 2) to determine tree-growth-limiting macro-and micronutrients at the midterm age; 3) to estimate how understory species affect mine soil properties, and to determine whether vegetation succession follows similar pathways in the two different quarry sites and whether plant communities on Al and A2 converge or diverge over time. The hypotheses were: 1) ecosystem recovery has been faster on A2; 2) development of trees and understory vegetation has improved soil nutritional status on Al; 3) plantations in former mining sites support similar understory species richness and diversity to plantations in former agricultural sites.

2. Materials and methods

2.1. Study area

The study was carried out in two hybrid aspen plantations in Aidu oil shale quarry in north-eastern Estonia (Table 1). Both plantations were established in 2000 with a mixed planting of 1-year-old micropropagated clones of Finnish origin (C05-99-8 to C05-99-34) [10]. According to the nearest weather station (Johvi), the mean annual temperature was 5.5 [+ or -] 0.16 [degrees]C and the mean annual precipitation was 751 [+ or -] 31 mm during the time period from 2000 to 2014 (Estonian Environment Agency).

One hybrid aspen plantation in Aidu was directly planted on levelled quarry spoil (59[degrees]19' N, 27[degrees]03' E) where four sample plots (Al) were established [10]. The quarry overburden is a mixture of calcareous disintegrated Ordovician limestone and Quaternary sediments [4]. The second hybrid aspen plantation was planted on quarry spoil covered with previously removed topsoil (59[degrees]20' N, 27[degrees]04' E) where three sample plots (A2) were established [10]. The removed topsoil was stored in piles during the mining process and placed back on top of levelled quarry spoil at a depth of 40 to 60 cm [10].

For comparison, three sample plots (B1) of hybrid aspen plantations on former agricultural lands in northern Estonia were used [10] (Table 1). The soils of B1 are calcareous, drought-sensitive, automorphic soils, corresponding to the Hepatica forest site type [38], which will probably be the site type formed during the pedogenesis of former quarry sites [4].

2.2. Tree growth measurement

Tree growth measurements in 15-year-old plantations on quarries were carried out on the same 12.5 m radius circular experimental plots that were subjected to measurements at the age of 5 [10]. The stem diameter at breast height over bark (DBH, cm) was recorded for every single tree with a millimetre-scale standard forest calliper. The height of every tree was measured with a telescopic measuring rod for trees smaller than 8 m. Trees over 8 m were measured with a Vertex IV (Haglof Sweden AB) with 0.1 m resolution.

Single tree volumes were calculated using Johnsson's equation [40]: V = 0.03186 x DB[H.sup.2] xH +0.43 xH +0.0551 x DB[H.sup.2] -0.4148 x DBH, (1) where V is single tree stem volume, [dm.sup.3]; DBH is stem diameter at breast height, cm; and H is tree height, m.

2.3. Soil analysis

The soil sampling in 15-year-old hybrid aspen plantations was carried out using the same methods as in an earlier survey [10]. Soil samples were taken systematically all over the sample plot and mixed together as a composite sample from both quarry sites. On levelled quarry detritus, the fine earth fractions between rock debris were collected. On levelled quarry spoil covered with previously removed soil, soil samples were taken from the 0-20 cm topsoil layer. Soil analysis for former arable land plantations was described by Lutter et al. [26] who used data about the 0-20 cm soil layer. The same was used in the current study.

For determination of soil [pH.sub.KC1], a 1 M KC1 suspension in the ratio of 10 g : 25 ml was used. The total nitrogen ([N.sub.tot]) was determined according to Kjeldahl (ISO 11261:1995) [41]. The available phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), copper (Cu) and manganese (Mn) were determined using the Mehlich method [42]. The available boron (B) was determined employing the hot-water extraction procedure [43].

Total nutrient stocks were calculated for the 0-20 cm soil layer by multiplying the nutrient concentration by the soil bulk density [44] and soil layer volume, from where the content of debris was subtracted [4]. All soil chemical analyses were carried out in the Laboratory of the Agricultural Research Centre in Saku ( (Table 2).

Data about [pH.sub.KC1], [N.sub.tot], P and K gathered during the earlier soil survey has been presented by Tullus et al. [10]. The rest of the data about 5-year-old quarry soils was collected within the framework of the same survey, but has not been previously published.

2.4. Floristic data

Floristic data were collected about permanent vegetation plots established at a young age (each 2 x 2 m in size, four in each study plot) [10]. For every vegetation plot a list of vascular plant and bryophyte species was compiled. The total percentage cover of the field and bryophyte layers and the percentage cover of individual species were estimated. In addition, a list of bryophyte species growing on the trunks of four trees situated near the vegetation plot corners was compiled. Data about bryophytes that could not be identified in field conditions were collected for further microscopic investigations. The nomenclature followed The Handbook of Estonian Vascular Plants [45] and Annotated checklist of Estonian bryophytes [46].

To characterise the understory species of hybrid aspen plantations, all vascular plants were classified by habitat preference based on The Handbook of Estonian Vascular Plants [45]. All bryophytes recorded in the plantations were classified as follows: short-lived species or perennial species, based on Dier[beta]en [47].

2.5. Statistical analyses

A pairwise Student's t-test was used to determine the significance of differences in soil nutrient concentrations and [pH.sub.KC1] between the first and second monitorings. One-way ANOVA, followed by the Tukey LSD test, was used to determine significant differences in soil nutrient stocks and [pH.sub.KC1] between the studied sites, to clarify the effects of growth characteristics (tree height and plantations basal area) and Fabaceae species cover on [N.sub.tot] concentration changes. Available P and Mn stocks were logtransformed in order to meet assumptions of the homoscedasticity and normal distribution of the residuals in the soil nutrient stocks comparison. The impact of soil [pH.sub.KC1] and nutrient stocks on tree height growth in midterm plantations were analysed using a non-linear regression model.

Species richness (S) and Simpson's diversity index (D') were estimated for vegetation plots with PC-ORD Version 6 [48] according to Equations (2) and (3):

S = n, (2)

[mathematical expression not reproducible] (3)

where n is the number of species present in the vegetation plot, and [p.sub.i] is the proportion of the sample belonging to the ith species. Variation in species composition was investigated with non-metric multidimensional scaling (NMDS) using the community ecology package Vegan in R [49]. NMDS was run with the "metaMDS" function and Bray-Curtis dissimilarities. Environmental variables were fitted onto the ordination using the function "envfit". To compare species composition between plantation types and assess the corresponding associations, Multiresponse Permutation Procedures (MRPP) and Indicator Species Analysis (ISA) were performed with PC-ORD 6. To correct the p-values for multiple comparisons in MRPP, the Bonferroni correction was applied. NMDS, MRPP and ISA were run with study-plot-level data, using the averaged vascular plants and ground-inhabiting bryophytes cover values for four vegetation plots.

A linear mixed model with R Statistics [50] function "lmer" in package lme4 (with sample plot as a random variable) was applied to clarify the plantation type effect on single tree growth characteristics and to clarify the plantation type effect on vegetation-plot-level estimates of vascular plant, bryophyte and Fabaceae species. The Tukey LSD test was applied if a statistically significant plantation type effect was observed to compare the group means.

Mean values are presented with standard error. The normality of the variables was tested with the Shapiro-Wilk test. Q-Q plots and residual distributions were used to assess the normality of model residuals. A level of significance of [alpha] = 0.05 was used to reject the null hypothesis after statistical tests.

3. Results and discussion

3.1. Tree growth

In 15-year-old hybrid aspen plantations, the mean tree height on bare levelled quarry spoil (A1) (5.4 [+ or -] 0.24 m) was significantly lower (p = 0.001) compared to reference (B1) sites on former agricultural land (13.6 [+ or -] 0.24 m). In contrast to preliminary observations at the age of 5 years [10], height growth on Al did not differ (p = 0.096) any more from that on quarry spoil with restored topsoil (A2) where the mean height was 10.0 [+ or -] 0.30 m (Fig. la). The significant difference between A1 and A2 persisted in the mean DBH (Fig. lb) and single tree stem volume (Fig. 1c). Hybrid aspen height growth on Al (5.4 m) exceeded that of same-aged Scots pine stands planted directly on quarry spoil (varying from 2.0 to 4.0 m) [1, 2, 19], and is similar to the results obtained in black alder and silver birch plantations (2.5 to 6 m) on stony quarry spoil of similar age class (10-12 years) [1, 14].

Compared to former arable land plantations (Bl = 100%), the relative tree height had dropped on both quarry sites (from 58 to 40% on Al and from 100 to 74% on A2) during the 10-year period (Fig. la). In addition to low nutrient pools on Al (Fig. 2), the inhibited growth on quarry sites, compared to former arable soils, may be probably explained by a limited soil water supply [51]. The soil water supply on quarry soils depends mainly on precipitation, as beneath topsoil there is skeletal material which lacks capillary groundwater support. The initially faster tree growth on A2 was because of a finer soil texture and better nutritional conditions compared to bare levelled spoil [10]. However, the layering of cover material with different textures creates interfaces that can influence the field capacity of soil moisture [52]. One possibility for improving the productivity of hybrid aspen plantations on drought sensitive quarry spoil is to select genotypes whose water use efficiency is higher in dry conditions, as suggested by Bungart and Huttl [22] for poplars on lignite mining areas in Germany.

The density of trees during the last 10-year period in the studied quarry sites has remained at a similar level, except on Al, where the mortality was 15% (Fig. 1d). Hybrid aspen tree density in the studied quarry sites (A1 = 698 and A2 = 353 trees per ha) is lower compared to other studies where tree density varies from around 1600 to 2300 trees per ha at the age of 30, for planted deciduous trees [17, 18]. Moreover, on A2 the density is already below 400 trees per ha, which is recommended for hybrid aspens at the maturity age of 25 years [25]. A low tree density could hamper soil development through low inputs of leaf and root litter. Moreover, dense light-demanding herbaceous ground vegetation could be promoted by a sparse tree layer and inhibit or delay the success of forest establishment by competing for soil resources with young trees [37].

3.2. Soil reaction and nutrients status

At the age of 15, the 0-20 cm topsoil reaction ([pH.sub.KC1]) and stocks of several macro- and micronutrients were significantly lower under hybrid aspen plantations on bare quarry spoil (A1) compared to quarry spoil with restored topsoil (A2) and former agricultural land (B1) (Fig. 2). However, over the 10-year period soil chemical characteristics in the studied sites showed only slight changes (Table 3). In nutrient-limited conditions plants start to invest the obtained resources into root expansions, and above-ground production will be retarded [53].

Soil reaction ([pH.sub.KC1]) had decreased according to a one-sided hypothesis (p = 0.030) by -0.32 units to 7.55 [+ or -] 0.09 on site group A1 (Table 3). In spite of its decrease on Al and non-change on A2 and B1, [pH.sub.KC1] was still significantly higher on Al than on A2 and B1 (Fig. 2a). A similar result was also found at the age of 15 [10]. Several studies report that deciduous trees are able to decrease soil reaction much faster in alkaline post-mining quarry sites when compared with conifers with easily decomposable plant litter and acid root exudates [17, 18]. After afforestation of quarry spoil (Al), the calcareous fragments of spoil material are expected to weather, with decarbonisation as a consequence. Superficial leaching is expected to occur, soil fine material content will increase, and Ca-bound nutrients will be released [54]. High soil reaction is hampering tree growth in the studied sites at the age of 15 (Fig. 3a). Similar effects have also been reported for silver birch plantations on quarry spoil during the first decade [17, 18] where pH stabilisation was observed after three decades [18]. The negative impact of high soil reaction was also observed in young hybrid aspen plantations on former arable land, although this effect disappeared at the midterm age [55] along with decreased [pH.sub.KC1] [26].

The stock of [N.sub.tot] on Al was significantly lower compared to A2 and B1 (Fig. 2b). A low stock of [N.sub.tot] also showed a growth-controlling effect on Al (Fig. 3b), as seen at the young age [10]. However, during the period from young to midterm age, a marginally significant increase in [N.sub.tot] concentration (+127%) had occurred on Al. The change of [N.sub.tot] concentration on Al had a significant positive relationship with the cover of [N.sub.2]-fixing Fabaceae family species and tree growth characteristics (Table 4). The positive impact of tree growth on the [N.sub.tot] concentration increase means that higher amounts of litter inputs positively influence soil development. A positive relationship between stand age and increasing amounts of plant litter in terms of [N.sub.tot] increase has also been observed for silver birch in less than a decade following afforestation [17, 18] and over a longer period of time for Scots pine [19]. [N.sub.2]-fixing alders can cause [N.sub.tot] increase in less than a decade following planting [17], and high concentrations could remain even after several decades [33]. The results presented here demonstrate that the presence of [N.sub.2]-fixing Fabaceae species in understory vegetation also plays an important role in soil development by increasing soil nitrogen storage (Table 4). For example, the rates of symbiotic [N.sub.2]-fixing legumes vary with plant species, growing season and soil fertility, but are commonly between 100 and 300 kg*[ha.sup.-1]*[yr.sup.-1] [28]. The presence of legume species in the studied sites was spontaneous, but the sowing of legume species could be an effective approach to improving soil nitrogen status on N-deficient post-mining areas, being also environmentally friendlier than fertilisation [29, 37]. On the other hand, a vigorous herbaceous cover could inhibit the natural regeneration of trees, or cause high mortality and a growth-hampering effect on young tree seedlings [37].

The studied calcareous quarry spoil (Al) also has a very low available P supply compared to A2 and Bl (Fig. 2c). As soil reaction still remained higher than the optimum level (Fig. 2), the P stock remained unchanged compared to the young age on Al (Table 3). At the same time, studies with other tree species have reported a decrease of P on post-mining quarry spoils under Scots pine, silver birch and black alder in less than a decade following planting [17, 18]. The availability of P next to a low N supply was controlling tree growth in young hybrid aspen plantations on Al [10], and this influence continued at the midterm age (Fig. 3c). P is also reported as a growth-limiting factor in young black alder, silver birch and Scots pine plantations at the young age on quarry spoil in Estonia [38], but also on afforested post-mining areas, according to some studies [22, 56]. P fertilisation, along with N and K, is recommended on post-mining lignite poplar plantations after eight years [22]. Even though available K showed significant stock differences between two former quarry sites (Fig. 2), no influence of available K on tree growth was detected.

Regarding micronutrients, significantly lower available Cu, Mn and B stocks were observed on Al compared to A2 and B1 (Fig. 2g-i). B and Cu are considered to be the most deficient micronutrients in quarry spoil substrate to trees, according to an earlier study in Estonia [8]. During the 10-year period, available B concentration on A2 had significantly decreased, by -9% (p = 0.002), and on Bl, by -20% (p = 0.039). The decline of B in the A horizon was also observed in hybrid aspen plantations on former arable lands representing a wider range of soil types during the same age period [26]. The decline of available B was greater in plantations with faster tree growth [26], but B could easily be lost through the leaching after a pH drop [57]. B stocks on A2 and Bl were still high, and were not limiting tree growth (Fig. 3i), but low stocks of available B and Mn had a growth-controlling effect on Al (Fig. 3h-i). Generally, Mn deficiency occurs on highly calcareous soils: for example, the Mn concentration in tree leaves showed a strong negative relationship with soil pH [58]. An early study of white pine (Pinus strobus L.) growth on reclaimed strip mines showed that Mn was the second important nutrient, besides P, to explain growth variability [56].

The long-term storage of topsoil in stockpiles during the mining process could significantly and adversely alter the biological, physical and chemical properties of soil for plants [59]. At the same time, afforestation with hybrid aspen has not caused any further substantial changes in the chemical properties of restored topsoil. No differences in [pH.sub.KC1] and nutrient stocks between A2 and Bl were found 15 years after afforestation, indicating that the soil characteristics of site group A2 are similar to those of the dry Hepatica forest site type [38] forming on Bl after the afforestation of former calcareous arable lands. A sporadic humus layer, low fine material content and easily desiccating soil conditions suggest that the afforestation of Al has promoted the restoration of Rendzic soils [38, 39].

3.3. Floristic diversity and changes

Altogether 96 vascular plant species and 27 bryophyte species were found in the three plantation types, which is considerably more than the respective figures of 75 and 12 recorded at a young age. The overall species richness of vascular plants and bryophytes had increased in all plantation types, following a similar trend to that observed in midterm hybrid aspen plantations on former agricultural land [36]. While no bryophyte species were found on tree trunks or tree bases in young plantations, the bryoflora of midterm plantations contained epiphytic species as well. All vascular plant and bryophyte species recorded in the studied stands were common species.

MRPP tests revealed significant differences in the understory species composition between plantations on Al and A2 (p = 0.009) and between plantations on Al and Bl (p = 0.010), whereas the comparison of understory species composition between A2 and Bl revealed no differences (p = 0.117).

Compositional differences between plantation types were confirmed by NMDS ordination, as the plantation type significantly affected the position of study plots in the ordination space (Table 5, Fig. 4a). In addition, variation in species composition was significantly affected by the density and basal area of overstory trees, availability of N, P, Cu and B in the soil humus horizon, and by soil pH. The strong effect of soil conditions on understory has been observed in a number of studies analysing vegetation assemblages in post-mining sites [34, 60].

Despite the compositional differences, the species richness and diversity of vascular plants per vegetation plot were similar in all plantation types, whereas the cover of the field layer was significantly lower on Al (Table 6), similarly to the results obtained for young stands earlier [10]. In addition, all plantation types were dominated by species belonging to similar ecological groups, i.e. light-demanding grassland species. The results of indicator species analysis also showed that grassland species were characteristic of all plantation types; for example, Agrostis capillaris L., Erigeron acer L. and Leontodon autumnalis L. were typical of Al; Dactylis glomerata L., Festuca rubra L., Galium x pomeranicum Retz., Heracleum sibiricum L., Medicago falcata L., Veronica chamaedrys L. and Vicia cracca L., of A2; and Galium album Mill., of Bl (Fig. 4b).

These results are in accordance with those obtained by Mudrak et al. [34] who found that grassland species were the most common group of understory plants in 22- to 33-year-old plantations on spoil heaps in Czechia, explaining this by the availability of light and proximity to grasslands as seed sources. The same factors are probably responsible for the dominance of grassland species established in the current study. Typical forest understory species were only sparsely represented in the field layer, while their number was significantly higher in the stands located on former agricultural lands (Table 6). At the same time, the understory on Bl differed from that of quarry sites by a higher number of fallow species, due to the effect of the formerly agricultural land use, which agrees with the results of earlier studies that have demonstrated the long-term impact of former land use on understory species composition in plantations [61, 62]. The number of ground-dwelling bryophytes was the greatest and the coverage of the bryophyte layer the highest on Bl, followed by Al, where the abundance of short-lived bryophyte species was high. The dominance of short-lived species on Al was also illustrated by an indicator species analysis that pointed out Barbula convoluta Hedw, B. unguiculata Hedw., Ptychostomum imbricatulum (Mull.Hal) D.T.Holyoak & N.Pedersen and Ceratodon purpureus (Hedw.) Brid. as characteristic bryophyte species (Fig. 4b). These bryophytes are all pioneer species typical of early successional series, representing a colonist life strategy as they produce large quantities of small spores, and are able to disperse long distances.

One aim of the current study was to determine whether plant communities on Al and A2 converge or diverge over time. Concerning the vascular plants, no clear trends towards convergence or divergence could be observed as the comparison of vegetation characteristics between the two plantation types gave similar results at the time of both monitoring periods (based on the pair-wise Student's t-test, data not shown). Despite the spatial vicinity between plantations on Al and A2, only seven vascular plant species were common to both plantation types at the young age, whereas the total number of species recorded on Al and A2 was 54. In midterm plantations, nine vascular plant species were common to both plantation types out of the 61 recorded species. In the case of bryophytes, there was a tendency towards divergence as the species richness and diversity of ground-dwelling bryophytes were significantly higher on Al at the midterm age due to the higher number of short-lived bryophytes. On A2 the high coverage of the field layer (Table 6) probably inhibited the recruitment of short-lived bryophyte species, while on levelled quarry spoil their light spores could spread easily.

4. Conclusions

Repeated monitoring of the main forest ecosystem components (tree growth, soil properties and understory plant cover) was carried out to describe ecosystem recovery on a reclaimed oil shale quarry.

During the 10-year development from young to midterm age, the relative height growth of hybrid aspen on bare quarry spoil and on spoil covered by restored topsoil was slower than on former arable Cambisol. On levelled quarry spoil, [pH.sub.KC1] had decreased, [N.sub.tot] had increased and other macro- and micronutrients had remained unchanged. The marginal increase of [N.sub.tot] on quarry spoil was positively related to the cover of Fabaceae species and tree growth. Available B had decreased on quarry spoil covered with previously removed topsoil. In addition to dry conditions, tree growth on bare quarry spoil was limited by low stocks of [N.sub.tot], P, B and Mn.

The compositional differences that were observed at the young age in the understory vegetation of the quarry sites representing two different restoration methods persisted, and were evident in the midterm plantations as well. Generally, hybrid aspen plantations in former mining sites support the similar understory species richness to that in plantations in former agricultural sites and, regardless of plantation type, understory is dominated by light-demanding grassland species.

In conclusion, hybrid aspen is a prospective tree species for the restoration of post-mining landscapes. Generally, soil recovery and tree growth 15 years after restoration of quarry spoil with hybrid aspen are similar to those upon afforestation with other fast-growing deciduous trees such as black alder and silver birch, but faster than Scots pine. However, complete restoration of a forest ecosystem is a long-term process, which cannot be achieved in 15 years, therefore monitoring of these sites should be continued.


The study was supported by the institutional research funding IUT (grants IUT21-4 and IUT34-9) and the Estonian Ministry of Education and Research (Project P170053MIMK).


[1.] Kaar, E. Afforestation of flattened oil shale quarries. In: Mining and Rehabilitation in Estonia (Kaar, E., Kiviste, K., eds.). Estonian University of Life Sciences, Tartu, 2010, 129-154 (in Estonian with English summary).

[2.] Kara, H., Szava-Kovats, R., Pensa, M, Kull, O. Carbon sequestration in a chronosequence of Scots pine stands in a reclaimed opencast oil shale mine. Can. J. Forest Res., 2009, 39(8), 1507-1517.

[3.] Reintam, L., Kaar, E., Rooma, I. Development of soil organic matter under pine on quarry detritus of open-cast oil-shale mining. Forest Ecol. Manag., 2002, 171(1-2), 191-198.

[4.] Reintam, L. Rehabilited quarry detritus as parent material for current pedogenesis. Oil Shale, 2004, 21(3), 183-193.

[5.] Vares, A., Lohmus, K., Truu, M, Truu, J., Tullus, H., Kanal, A. Productivity of black alder (Alnus glutinosa (L.) Gaertn.) plantations on reclaimed oil-shale mining detritus and mineral soils in relation to rhizosphere conditions. Oil Shale, 2004, 21(1), 43-58.

[6.] Kaar, E. Coniferous trees on exhausted oil shale opencast mines. Forestry Studies, 2000, 36, 120-125.

[7.] Reintam, L. Changes in the texture and exchange properties of skeletal quarry detritus under forest during thirty years. Proc. Estonian Acad. Sci. Biol. Ecol., 2001,50(1), 5-13.

[8.] Vaus, M. Afforestation Potential of Estonian Oil Shale Quarry Soils. Valgus, Tallinn, 1970 (in Estonian).

[9.] Leedu, E. Agricultural reclamation of open cast oil shale mines. In: Mining and Rehabilitation in Estonia (Kaar, E., Kiviste, K., eds.). Estonian University of Life Sciences, Tartu, 2010, 219-254 (in Estonian with English summary).

[10.] Tullus, A., Soo, T., Tullus, H., Vares, A., Kanal, A., Roosaluste, E. Early growth and floristic diversity of hybrid aspen (Populus x wettsteinii Hamet-Ahti) plantations on a reclaimed opencast oil shale quarry in north-east Estonia. Oil Shale, 2008, 25(1), 57-74.

[11.] Macdonald, S. E., Landhausser, S. M, Skousen, J., Franklin, J., Frouz, J., Hall, S., Jacobs, D. F., Quideau, S. Forest restoration following surface mining disturbance: challenges and solutions. New Forest., 2015, 46(5-6), 703-732.

[12.] Vinduskova, O., Frouz, J. Soil carbon accumulation after open-cast coal and oil shale mining in Northern Hemisphere: A quantitative review. Environ. Earth Sci., 2013, 69(5), 1685-1698.

[13.] Kuznetsova, T., Lukjanova, A., Ots, K., Rosenvald, K., Ostonen, I., Lohmus, K. Biomass allocation, leaf and fine root morphological adaptations in young black alder (Alnus glutinosa (L.) Gaertn.), silver birch (Betula pendula Roth.) and Scots pine (Pinus sylvestris L.) plantations on reclaimed oil shale post-mining areas. Oil Shale, 2014, 31(3), 289-303.

[14.] Kaar, E., Raid, L. Some results about afforestation of flattened oil shale quarries. Forestry Studies, 1992, 25, 109-117 (in Estonian).

[15.] Ostonen, I., Lohmus, K., Alama, S., Truu, J., Kaar, E., Vares, A., Uri, V., Kur-vits, V. Morphological adaptations of fine roots in Scots pine (Pinus sylvestris L.), silver birch (Betula pendula Roth.) and black alder (Alnus glutinosa (L.) Gaertn.) stands in recultivated areas of oil shale mining and semicoke hills. Oil Shale, 2006, 23(2), 187-202.

[16.] Chodak, M, Niklihska, M. The effect of different tree species on the chemical and microbial properties of reclaimed mine soils. Biol. Fert. Soils, 2010, 46(6), 555-566.

[17.] Kuznetsova, T., Lukjanova, A., Mandre, M, Lohmus, K. Aboveground biomass and nutrient accumulation dynamics in young black alder, silver birch and Scots pine plantations on reclaimed oil shale mining areas in Estonia. Forest Ecol. Manag., 2011, 262(2), 56-64.

[18.] Rosenvald, K, Kuznetsova, T., Ostonen, I., Truu, M, Truu, J., Uri, V., Lohmus, K. Rhizosphere effect and fine-root morphological adaptations in a chronosequence of silver birch stands on reclaimed oil shale post-mining areas. Ecol. Eng., 2011, 37(7), 1027-1034.

[19.] Laarmann, D., Korjus, H, Sims, A., Kangur, A., Kiviste, A., Stanturf, J. A. Evaluation of afforestation development and natural colonization on a reclaimed mine site. Restor. Ecol., 2015, 23(3), 301-309.

[20.] Frouz, J., Keplin, B., Pizl, V., Tajovsky, K, Stary, J., Lukesova, A., Novakova, A., Balik, V., Hanel, L., Materna, J., Dtiker, C, Chalupsky, J., Rusek, J., Heinkele, T. Soil biota and upper soil layer development in two contrasting post-mining chronosequences. Ecol. Eng., 2001,17(2-3), 275-284.

[21.] Bungart, R., Huttl, R. F. Production of biomass for energy in post-mining landscapes and nutrient dynamics. Biomass Bioenerg., 2001, 20(3), 181-187.

[22.] Bungart, R., Huttl, R. F. Growth dynamics and biomass accumulation of 8-year-old hybrid poplar clones in a short-rotation plantation on a clayey-sandy mining substrate with respect to plant nutrition and water budget. Eur. J. For. Res., 2004,123(2), 105-115.

[23.] Casselman, C. N., Fox, T. R., Burger, J. A., Jones, A. T., Galbraith, J. M. Effects of silvicultural treatments on survival and growth of trees planted on reclaimed mine lands in the Appalachians. Forest Ecol. Manag., 2006, 223(1-3), 403-414.

[24.] Tullus, A., Tullus, H, Vares, A., Kanal, A. Early growth of hybrid aspen (Populus x wettsteinii Hamet-Ahti) plantations on former agricultural lands in Estonia. Forest Ecol. Manag., 2007, 245(1-3), 118-129.

[25.] Tullus, A., Rytter, L., Tullus, T., Weih, M., Tullus, H. Short-rotation forestry with hybrid aspen (Populus tremula L. x P. tremuloides Michx.) in Northern Europe. Scand. J. Forest Res., 2012, 27(1), 10-29.

[26.] Lutter, R., Tullus, A., Kanal, A., Tullus, T., Tullus, H. The impact of short-rotation hybrid aspen (Populus tremula L. x P. tremuloides Michx.) plantations on nutritional status of former arable soils. Forest Ecol. Manag., 2016, 362, 184-193.

[27.] Kuznetsova, T., Rosenvald, K., Ostonen, I., Helmisaari, H.-S., Mandre, M, Lohmus, K. Survival of black alder (Alnus glutinosa L.), silver birch (Betula pendula Roth.) and Scots pine (Pinus sylvestris L.) seedlings in a reclaimed oil shale mining area. Ecol. Eng., 2010, 36(4), 495-502.

[28.] Burns, R. C, Hardy, R. W. F. Nitrogen Fixation in Bacteria and Higher Plants. Springer-Verlag, New York, 1975.

[29.] Jefferies, R. A., Bradshaw, A. D., Putwain, P. D. Growth, nitrogen accumulation and nitrogen transfer by legume species established on mine spoils. J. Appl. Ecol., 1981, 18(3), 945-956.

[30.] Holl, K. D., Cairns, J. Jr. Vegetational community development on reclaimed coal surface mines in Virginia. B. Torrey Bot. Club, 1994, 121(4), 327-337.

[31.] Holl, K. D. Long-term vegetation recovery on reclaimed coal surface mines in the eastern USA. J. Appl. Ecol., 2002, 39, 960-970.

[32.] Pensa, M, Sellin, A., Luud, A., Valgma, I. An analysis of vegetation restoration on opencast oil shale mines in Estonia. Restor. Ecol., 2004,12(2), 200-206.

[33.] Pensa, M, Kara, H., Luud, A., Rull, E., Vaht, R. The effect of planted tree species on the development of herbaceous vegetation in a reclaimed opencast. Can. J. Forest Res., 2008, 38(10), 2674-2686.

[34.] Mudrak, O., Frouz, J., Velichova, V. Understory vegetation in reclaimed and unreclaimed post-mining forest stands. Ecol. Eng., 2010, 36(6), 783-790.

[35.] Vaht, R., Pensa, M, Sepp, M, Luud, A., Kara, H., Elvisto, T. Assessment of vegetation performance on semicoke dumps of Kohtla-Jarve oil shale industry, Estonia. Estonian J. Ecol., 2010, 59(1), 3-18.

[36.] Tullus, T., Tullus, A., Roosaluste, E., Lutter, R., Tullus, H. Vascular plant and bryophyte flora in mid-term hybrid aspen plantations on abandoned agricultural land. Can. J. Forest Res., 2015, 45(9), 1183-1191.

[37.] Franklin, J. A., Zipper, C. E., Burger, J. A., Skousen, J. G., Jacobs, D. F. Influence of herbaceous ground cover on forest restoration of eastern US coal surface mines. New Forest., 2012, 43(5-6), 905-924.

[38.] Lohmus, E. Ordination and classification of Estonian forests. Forestry Studies, 1974,11, 162-194 (in Estonian).

[39.] IUSS Working Group WRB. World Reference Base for Soil Resources 2014. International Soil Classification System for Naming Soils and Creating Legends for Soil Maps. World Soil Resources Reports No. 106, FAO, Rome, 2014.

[40.] Johnsson, H. Growth of young hybrid aspen and an attempt for future prognosis. Svenska Skogsvardsforeningens Tidskrift, 1953, 51, 73-96 (in Swedish).

[41.] ISO 11261:1995. Soil quality--Determination of total nitrogen--Modified Kjeldahl method. International Organization for Standardization, Geneva, Italy, 1995.

[42.] Mehlich, A. Mehlich 3 soil test extractant: A modification of the Mehlich 2 extractant. Commun. Soil Sci. Plan., 1984,15, 1409-1416.

[43.] Berger, K. C, Truog, E. Boron determination in soils and plants. Ind. Eng. Chem., Anal. Ed., 1939, 11, 540-545.

[44.] Kaar, E., Leedu, E., Kitse, E. Biological recultivation of the Estonian oil-shale fields. In: Problems of Soil Protection in Estonia (Reintam, L., ed.). Estonian Academy of Science, Tallinn, 1991, 108-121 (in Estonian).

[45.] Leht, M. Handbook of Estonian Vascular Plants. Estonian University of Life Sciences, Eesti Loodusfoto, Tartu, 2010 (in Estonian).

[46.] Vellak, K., Ingerpuu, N., Leis, M, Ehrlich, L. Annotated checklist of Estonian bryophytes. Folia Cryptog. Estonica, 2015, 52, 109-127.

[47.] Dier[beta]en, K. Distribution, Ecological Amplitude and Phytosociological Characterization of European Bryophytes. Bryophytorum Bibliotheca, 56, Berlin, Stuttgart, 2001.

[48.] McCune, B., Mefford, M. J. PC-ORD. Multivariate Analysis of Ecological Data. Version 6. MjM Software, Gleneden Beach, Oregon, U.S.A, 2011.

[49.] Oksanen, J., Blanchet, F. G., Kindt, R. M, Legendre, P., Minchin, P. R., O'Hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H. Vegan: Community Ecology Package. R Package Version 2.0-10, 2013, (

[50.] R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria, 2015, (

[51.] Tullus, A., Kanal, A., Soo, T., Tullus, H. The impact of available water content in previous agricultural soils on tree growth and nutritional status in young hybrid aspen plantations in Estonia. Plant Soil, 2010, 333(1-2), 129-145.

[52.] Zettl, J. D., Barbour, S. L., Huang, M, [S.sub.1], B. C, Leskiw, L. A. Influence of textural layering on field capacity of coarse soils. Can. J. Soil. Sci., 2011, 91(2), 133-147.

[53.] Putz, F. E., Canham, C. D. Mechanisms of arrested succession in shrublands: root and shoot competition between shrubs and tree seedlings. Forest Ecol. Manag., 1992, 49(3-4), 267-275.

[54.] Abakumov, E. V., Gagarina, E. I. Humus status of soils of overgrown quarries in Leningrad oblast. Eurasian Soil Sci., 2008, 41(3), 255-264.

[55.] Lutter, R., Tullus, A., Kanal, A., Tullus, T., Tullus, H. Above-ground growth and temporal plant-soil relations in midterm hybrid aspen (Populus tremula L. x P. tremuloides Michx.) plantations on former arable lands in hemiboreal Estonia. Scand. J. Forest Res., 2017, X, 1-12.

[56.] Andrews, J. A., Johnson, J. E., Torbert, J. L., Burger, J. A., Kelting, D. L. Minesoil and site properties associated with early height growth of eastern white pine. J. Environ. Qual., 1998, 27(1), 192-199.

[57.] Lehto, T., Ruuhola, T., Dell, B. Boron in forest trees and forest ecosystems. Forest Ecol. Manag., 2010, 260, 2053-2069.

[58.] Reimann, C, Arnoldussen, A., Boyd, R., Finne, T. E., Koller, F., Nord-gulen, [empty set]., Englmaier, P. Element contents in leaves of four plant species (birch, mountain ash, fern and spruce) along anthropogenic and geogenic concentration gradients. Sci. Total Environ., 2007, 377(2-3), 416-433.

[59.] Abdul-Kareem, A. W., McRae, S. G. The effects on topsoil of long-term storage in stockpiles. Plant Soil, 1984, 76(1-3), 357-363.

[60.] Prach, K., Rehounkova, K. Vegetation succession over broad geographical scales: which factors determine the patterns? Preslia, 2006, 78, 469-480.

[61.] Gachet, S., Leduc, A., Bergeron, Y., Nguyen-Xuan, T., Tremblay, F. Under-story vegetation of boreal tree plantations: Differences in relation to previous land use and natural forests. Forest Ecol. Manag., 2007, 242, 49-57.

[62.] Soo, T., Tullus, A., Tullus, H., Roosaluste, E. Floristic diversity responses in young hybrid aspen plantations to land-use history and site preparation treatments. Forest Ecol. Manag., 2009, 257(3), 858-867.


(a) Institute of Forestry and Rural Engineering, Estonian University of Life Sciences, Kreutzwaldi 5, 51014 Tartu, Estonia

(b) Department of Botany, Institute of Ecology and Earth Sciences, University of Tartu, Lai 40, 51005 Tartu, Estonia

(c) Department of Geography, Institute of Ecology and Earth Sciences, University of Tartu, Vanemuise 46, 51014 Tartu, Estonia

(*) Corresponding author: e-mail

Presented by V. Lahtvee

Received February 27, 2017
Table 1. General overview of the studied 15-year-old hybrid aspen
plantations on Aidu quarry and former arable soils

Plantation type        Planta-  Site   Plot          Soil type
                       tion     group                  [39]

Levelled quarry spoil  Aidu1    A1     A1-1  Calcaric Skeletic Regosol
Levelled quarry spoil  Aidu1    A1     A1-2  Calcaric Skeletic Regosol
Levelled quarry spoil  Aidu1    Al     A1-3  Calcaric Skeletic Regosol
Levelled quarry spoil  Aidu1    Al     A1-4  Calcaric Skeletic Regosol
Restored soil on       Aidu 2   A2     A2-1  Mixture of Calcaric
quarry debris                                Cambisol
Restored soil on       Aidu 2   A2     A2-2  Mixture of Calcaric
quarry debris                                Cambisol
Restored soil on       Aidu 2   A2     A2-3  Mixture of Calcaric
quarry debris                                Cambisol
Former agricultural    Soeru    B1     B1-1  Calcaric Skeletic Luvic
soil                                         Rendzic Phaeozem
Former agricultural    Soeru    B1     B1-2  Calcaric Rendzic Skeletic
soil                                         Leptosol
Former agricultural    Mikkeri  Bl     B1-3  Calcaric Endoleptic
soil                                         Cambisol

Plantation type            Density,              Basal
                       trees [ha.sup.-1]         area,

Levelled quarry spoil         774                 1.98
Levelled quarry spoil         652                 0.83
Levelled quarry spoil         611                 0.07
Levelled quarry spoil         754                 3.17
Restored soil on              448                 5.96
quarry debris
Restored soil on              326                 3.84
quarry debris
Restored soil on              285                 2.91
quarry debris
Former agricultural          1070                17.57
Former agricultural          1180                 9.97
Former agricultural           700                 3.65

Table 2. Chemical properties of soil of the studied sample plots in
15-year-old plantations

Plantation name  site group  Plot  [pH.sub.KC1]  [N.sub.tot],%

     Aidu1           Al      A1-1      7.4           0.11
     Aidu1           Al      A1-2      7.4           0.10
     Aidu1           Al      A1-3      7.8           0.06
     Aidu1           Al      A1-4      7.6           0.23
     Aidu2           A2      A2-1      7.0           0.25
     Aidu2           A2      A2-2      7.1           0.35
     Aidu2           A2      A2-3      7.3           0.28
     Soeru           B1      B1-1      7.3           0.25
     Soeru           B1      B1-2      7.1           0.19
    Mikkeri          Bl      B1-3      7.3           0.22

Plantation name  P,mg*[kg.sup.-1]  K,mg*[kg.sup.-1]  Ca,mg*[kg.sup.-1]

     Aidu1              13               123               7373
     Aidu1              5                 98               15520
     Aidu1              1                 37               38135
     Aidu1              4                468               29693
     Aidu2             126               232               4867
     Aidu2             189               104               6401
     Aidu2              39               110               6744
     Soeru             151               373               6506
     Soeru              48               163               3238
    Mikkeri             44               119               4125

Plantation name  Mg,mg*[kg.sup.-1]  Cu,mg*[kg.sup.-1]

     Aidu1              99                 3.3
     Aidu1              150                1.0
     Aidu1              211                0.3
     Aidu1             1050                0.7
     Aidu2              108                2.2
     Aidu2              89                 2.7
     Aidu2              162                2.1
     Soeru              220                2.8
     Soeru              160                1.3
    Mikkeri             246                1.2

Plantation name  Mn,mg*[kg.sup.-1]  B,mg*[kg.sup.-1]Plantation name

     Aidu1              38                0.33           Aidu1
     Aidu1              28                0.54           Aidu1
     Aidu1              22                0.27           Aidu1
     Aidu1              31                1.77           Aidu1
     Aidu2              229               1.58           Aidu2
     Aidu2              42                1.71           Aidu2
     Aidu2              41                1.77           Aidu2
     Soeru              55                2.13           Soeru
     Soeru              196               1.02           Soeru
    Mikkeri             180               1.00          Mikkeri

Plantation name  site group  Plot  [pH.sub.KC1]  [N.sub.tot],%

     Aidu1           Al      A1-1      7.4           0.11
     Aidu1           Al      A1-2      7.4           0.10
     Aidu1           Al      A1-3      7.8           0.06
     Aidu1           Al      A1-4      7.6           0.23
     Aidu2           A2      A2-1      7.0           0.25
     Aidu2           A2      A2-2      7.1           0.35
     Aidu2           A2      A2-3      7.3           0.28
     Soeru           B1      B1-1      7.3           0.25
     Soeru           B1      B1-2      7.1           0.19
    Mikkeri          Bl      B1-3      7.3           0.22

Plantation name  P,mg*[kg.sup.-1]  K,mg*[kg.sup.-1]  Ca,mg*[kg.sup.-1]

     Aidu1              13               123               7373
     Aidu1              5                 98               15520
     Aidu1              1                 37               38135
     Aidu1              4                468               29693
     Aidu2             126               232               4867
     Aidu2             189               104               6401
     Aidu2              39               110               6744
     Soeru             151               373               6506
     Soeru              48               163               3238
    Mikkeri             44               119               4125

Plantation name  Mg,mg*[kg.sup.-1]  Cu,mg*[kg.sup.-1]

     Aidu1              99                 3.3
     Aidu1              150                1.0
     Aidu1              211                0.3
     Aidu1             1050                0.7
     Aidu2              108                2.2
     Aidu2              89                 2.7
     Aidu2              162                2.1
     Soeru              220                2.8
     Soeru              160                1.3
    Mikkeri             246                1.2

Plantation name  Mn,mg*[kg.sup.-1]  B,mg*[kg.sup.-1]

     Aidu1              38                0.33
     Aidu1              28                0.54
     Aidu1              22                0.27
     Aidu1              31                1.77
     Aidu2              229               1.58
     Aidu2              42                1.71
     Aidu2              41                1.77
     Soeru              55                2.13
     Soeru              196               1.02
    Mikkeri             180               1.00

Table 3. Absolute and relative changes of soil [pH.sub.KC1] and
available nutrient concentrations in 5- to 15-year-old plantations
(levelled quarry spoil--site group A1; levelled quarry spoil with
restored topsoil--site group A2; former arable soil--site group B1)

Soil                           Al                             A2
                       Abs.    Rel.        One-     Abs.     Rel.
property              change   change,    tailed   change   change,
                                 %       p- value              %

[pH.sub.KC1]           -0.32   -114 (*)    0.030    -0.03     -10
P,mg*[kg.sup.-1]       -4       -39        0.177    10         9
K,mg*[kg.sup.-1]      103       130        0.134    62        72
Ca,mg*[kg.sup.-1]   -4042       -15        0.359   -16         0
Mg,mg*[kg.sup.-1]     131        53        0.298     2         2
Cu, mg*[kg.sup.-1]     -0.85    -39        0.144    +0.07      3
Mn, mg*[kg.sup.-1]     -3       -10        0.054    17        20
B,mg*[kg.sup.-1]       +0.198    37        0.232    -0.170    -9
[N.sub.tot], %         +0.070   127        0.058    +0.023     9

Soil                                     Bl
                     One-     Abs.      Rel.     One-
property            tailed   change    change,  tailed
                    p-value               %     p-value

[pH.sub.KC1]         0.211     +0.07     13      0.346
P,mg*[kg.sup.-1]     0.400      7         9      0.086
K,mg*[kg.sup.-1]     0.062    -37        -14     0.102
Ca,mg*[kg.sup.-1]    0.465   -644        -12     0.177
Mg,mg*[kg.sup.-1]    0.299     21        11      0.356
Cu, mg*[kg.sup.-1]   0.211     +0.12      7      0.270
Mn, mg*[kg.sup.-1]   0.148     24        20      0.168
B,mg*[kg.sup.-1]     0.002     -0.323    -19     0.039
[N.sub.tot], %       0.148     +0.004     2      0.409

(*) The relative change of H+ considers the logarithmic scale of pH.
The abbreviations used: Abs.--Absolute; Rel.--Relative.

Table 4. The regression slopes between soil total nitrogen
concentration changes and Fabaceae species cover and tree growth
characteristics (height and basal area) in the studied quarry sites

Factor                Site group  [delta][N.sub.tot] concentration, %

Cover of Fabaceae, %      A1               0.74 [+ or -]0.18
                          A2              -0.51 [+ or -]0.65
Height, m                 Al               0.90 [+ or -]0.19
                          A2               0.73 [+ or -] 0.22
Basal area,
[m.sup.2][ha.sup.-1]      Al               0.94 [+ or -]0.09
                          A2               0.73 [+ or -]0.21


Cover of Fabaceae, %   0.001
Height, m             <0.001
Basal area,
[m.sup.2][ha.sup.-1]  <0.001

Note: [delta][N.sup.tot]--total nitrogen concentration changes. All
variables were scaled in order to compare the magnitude of effects.

Table 5. Relationships between vascular plants and bryophyte species
composition (NMDS ordination, Fig. 4a) and environmental variables

Environmental factor  [r.sup.2]  p-value

Density of trees        0.75      0.003
Basal area              0.69      0.007
[N.sub.tot] stock       0.96      0.001
Available P stock       0.71      0.020
Available K stock       0.42      0.150
Available Ca stock      0.35      0.204
Available Mg stock      0.07      0.838
Available Cu stock      0.78      0.006
Available Mn stock      0.52      0.074
Available B stock       0.94      0.001
Soil [pH.sub.KC1]       0.59      0.032
Plantation type         0.88      0.001

(*) The [r.sup.2] values show the squared correlation coefficient for
the environmental factors fit onto the NMDS ordination; p- values are
based on random permutations of the data.

Table 6. Vegetation plot mean values ([+ or -] SE) of and plantation
type effect on the characteristics of vascular plant and bryophyte
species in midterm plantations

Vegetation characteristic                 Site group
                                  Al                    A2

S_vascular plants          13.9[+ or -] 1.2      16.9 [+ or -]1.4
D '_vascular plants         0.86 [+ or -]0.02     0.84 [+ or -]0.02
C_field layer              25.4 [+ or -] 6.5a    70.3 [+ or -] 7.5b
S_trees and shrubs          3.4 [+ or -] 0.5b     0.8 [+ or -] 0.6a
S_forest species            0.8 [+ or -] 0.2a     0.3 [+ or -] 0.2a
S_grassland species         6.6 [+ or -]1.1      11.8 [+ or -] 1.3
S_fallow species            2.9 [+ or -] 0.5a     4.1 [+ or -] 0.6a
S_bryophytes_ground         4.8 [+ or -] 0.7b     1.4 [+ or -] 0.8a
D '_bryophytes_ground       0.62 [+ or -] 0.07b   0.15 [+ or -] 0.08a
C_bryophyte layer          15.5 [+ or -] 8.1a     9.9 [+ or -] 9.3a
S_short-lived bryophytes    2.8 [+ or -] 0.3b     0.8 [+ or -] 0.4a
S_perennial bryophytes      2.0 [+ or -] 0.6ab    0.6 [+ or -] 0.6a
S_bryophytes_trunk          0.3[+ or -] 0.6a      3.5 [+ or -] 0.6b

Vegetation characteristic

S_vascular plants          18.7[+ or -] 1.4
D '_vascular plants         0.86 [+ or -]0.02
C_field layer              59.0 [+ or -] 7.5b
S_trees and shrubs          1.7[+ or -]0.6ab
S_forest species            1.5 [+ or -] 0.2b
S_grassland species         9.1 [+ or -]1.3
S_fallow species            6.2 [+ or -] 0.6b
S_bryophytes_ground         5.3 [+ or -] 0.8b
D '_bryophytes_ground       0.47 [+ or -] 0.08b
C_bryophyte layer          48.3 [+ or -] 9.3b
S_short-lived bryophytes    1.5 [+ or -] 0.4a
S_perennial bryophytes      3.8 [+ or -] 0.6b
S_bryophytes_trunk          2.3 [+ or -] 0.6b

Vegetation characteristic  Plantation type effect, p- value

S_vascular plants                         0.090
D '_vascular plants                       0.623
C_field layer                             0.006
S_trees and shrubs                        0.044
S_forest species                         <0.001
S_grassland species                       0.054
S_fallow species                          0.013
S_bryophytes_ground                       0.021
D '_bryophytes_ground                     0.009
C_bryophyte layer                         0.043
S_short-lived bryophytes                  0.015
S_perennial bryophytes                    0.026
S_bryophytes_trunk                        0.018

Note: Letters denote significant differences between site groups
according to the Tukey LSD test. The symbols used: S--species richness
(number of species per vegetation plot); D'--Simpson's diversity index
(values vary between 0 and 1); C = cover, %; SE--standard error.
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Author:Lutter, Reimo; Tullus, Tea; Tullus, Arvo; Kanal, Arno; Tullus, Hardi
Publication:Oil Shale
Article Type:Report
Geographic Code:4EXES
Date:Dec 1, 2017

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