Carbon sequestration in a chronosequence ofScots pine stands in a reclaimed opencast oilshale mine

Helen Karu, Robert Szava-Kovats, Margus Pensa, and Olevi Kull

Abstract: Ecosystems that develop on mine spoil can serve as significant sinks for CO2. The aim of this study was to esti-mate the rate of carbon accumulation and its distribution along forest ecosystem partitions in young Scots pine (Pinus syl-vestris L.) plantations in the Narva oil shale opencast, Estonia. The tree layer was measured in 2004 in 13 standsafforested with 2-year-old seedlings during 1968 to 1994. Three stands (afforested in 1990, 1983, and 1968) were selectedfor detailed analysis of the carbon sequestration. Soil profiles were sampled in these stands in 2005. Radiocarbon analysiscombined with a simple model of litter production was used to differentiate between plant-derived recent carbon and car-bon stemming from fragments of oil shale. Total carbon accumulated since afforestation in vegetation, forest floor, and Ahorizon was 7.8 t�ha–1 in the stand established in 1990, 34.5 t�ha–1 in that established in 1983, and 133.4 t�ha–1 in that es-tablished in 1968. Most of the sequestered carbon was allocated to tree stems; their portion increasing with age from 28%to 51%. The portion of recent soil organic carbon increased from 5% to 23%, which shows that soils contribute signifi-cantly to carbon accumulation during early forest succession on degraded land.

Resume : Les ecosystemes qui se developpent sur les deblais miniers peuvent servir de puits importants de CO2. Le butde cette etude consistait a estimer le taux d’accumulation du carbone et sa distribution le long de segments d’ecosystemeforestier dans de jeunes plantations de pin sylvestre (Pinus sylvestris L.) etablies dans la mine a ciel ouvert de shale bitu-mineux de Narva, en Estonie. La strate arborescente a ete mesuree en 2004 dans 13 peuplements plantes avec des semisages de deux ans de 1968 a 1994. Trois peuplements (plantes en 1990, 1983 et 1968) ont ete selectionnes pour une analysedetaillee de la sequestration du carbone. Les profiles de sol ont ete echantillonnes en 2005 dans ces peuplements. L’an-alyse de l’isotope radioactif du carbone (14C) combinee a un modele simple de production de litiere a ete utilisee pour dif-ferentier le carbone recent derive de la vegetation du carbone provenant de fragments de shale bitumineux. La quantitetotale de carbone accumule depuis le reboisement dans la vegetation, la couverture morte et l’horizon A atteignait 7,8t�ha–1 dans le peuplement etabli en 1990, 34,5 t�ha–1 dans celui etabli en 1983 et 133,4 t�ha–1 dans celui etabli en 1968. Lamajeure partie du carbone sequestre avait ete allouee a la tige des arbres dans une proportion qui a augmente de 28 % a51 % avec l’age. La portion de carbone organique recent dans le sol a augmente de 5 % a 23 %, ce qui indique que lessols contribuent de facon significative a l’accumulation du carbone durant les premiers stades de succession forestiere surles terrains degrades.

[Traduit par la Redaction]

IntroductionOpencast mining disturbs the preexisting carbon balance

of ecosystems over large areas. Mining activities raze the in-itial vegetation and cause large-scale disturbances of soil, re-sulting in carbon losses. In fact, the carbon content of minespoils is usually very low (Shrestha and Lal 2006); there-fore, soils developing on mine spoils can act as important

sinks for CO2 through accumulation of biomass and soil or-ganic carbon (SOC) (Ussiri and Lal 2005). However, thecarbon budget of ecosystems emerging on former miningareas is poorly understood (Shrestha and Lal 2006). Adeeper understanding could lead to ecosystem restorationpractices that maximize carbon accumulation.

Plantations established on spoils are useful sites to studyfactors affecting carbon sequestration in forests, as the his-tory of the stands is typically well documented and speciescomposition is usually homogeneous across a wide area.Thus, differences in the carbon content among stands of dif-ferent age are a good proxy for carbon accumulation. How-ever, in many instances, mine soils contain a substantialamount of fossil carbon, which obfuscates estimation of car-bon sequestration. Measurement of radiocarbon activity hasbeen used to differentiate between plant-derived recent car-bon and fossil carbon (Rumpel et al. 1999, 2003;Morgenroth et al. 2004; Fettweis et al. 2005), although nodefinitive methodology has been developed. The lack of anaccepted method for quantifying fossil carbon decreases thereliability of measured rates of SOC accumulation (Ussiri

Received 8 December 2008. Accepted 12 May 2009. Publishedon the NRC Research Press Web site at cjfr.nrc.ca on 8 August2009.

H. Karu.1 Institute of Ecology and Earth Sciences, University ofTartu, Lai 40, 51005 Tartu, Estonia; NE Estonian Department,Institute of Ecology, University of Tallinn, Pargi 15, 41537Johvi, Estonia.R. Szava-Kovats and O. Kull. Institute of Ecology and EarthSciences, University of Tartu, Lai 40, 51005 Tartu, Estonia.M. Pensa. NE Estonian Department, Institute of Ecology,University of Tallinn, Pargi 15, 41537 Johvi, Estonia.

1Corresponding author (e-mail: helen.karu@ut.ee).

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Can. J. For. Res. 39: 1507–1517 (2009) doi:10.1139/X09-069 Published by NRC Research Press

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and Lal 2005) and complicates the comparison of results ob-tained in different studies.

In large-scale assessments of forest carbon stocks, tree bi-omass is often calculated based on forest inventory data,which account for only merchantable stem wood and leaveother tree biomass components either omitted or estimatedfrom constant ratios (e.g., Intergovernmental Panel on Cli-mate Change 2003). Such estimates may be biased, sincestem biomass contributes significantly less to total biomassin young forests than in mature forests (Peichl and Arain2006). It has been suggested that changes in allocation andbiomass distribution with age can be responsible, at leastpartly, for the observed decline in tree production after can-opy closure (Kira and Shidei 1967; Magnani et al. 2000;Ryan et al. 2004). Carbon allocation may also affect thesoil carbon cycle, since decomposition rates differ for plantorgans (Gower et al. 1997). Therefore, knowledge ofchanges in biomass distribution during stand development isnecessary to model carbon dynamics and assess carbonstocks.

Estonia is home to the world’s largest commercially ex-ploited oil shale deposits, and opencast oil shale mining hasdegraded about 130 km2 of land. Since the spoil of opencastoil shale mining is extremely coarse and depleted in nu-trients and organic matter, afforestation is considered themost suitable reclamation option for these areas (Vaus1970). Earlier studies have described the pedogenesis andSOC accumulation on oil shale mine spoil (Reintam andKaar 1999, 2002; Reintam et al. 2002; Reintam 2004), butthere are no estimates of total carbon stocks of reclaimedforest ecosystems. Since Scots pine (Pinus sylvestris L.)stands dominate the afforested areas, we chose this speciesto investigate carbon dynamics in developing forest ecosys-tems. Specifically, the aims of this study were (i) to estimatethe rate of carbon accumulation in young Scots pine planta-tions growing on severely degraded land (mine spoil), (ii) todetermine the distribution of sequestered carbon along forestecosystem partitions, and (iii) to develop a simple and ro-bust method for finding the recent carbon contribution to to-tal SOC.

Materials and methods

Study sitesThe study was carried out in the Narva opencast oil shale

mine, in north-east Estonia (59815’–59817’N, 27840’–27846’E). The mean annual temperature in the region is4.8 8C and precipitation 639 mm. The Estonian oil shale(kukersite) basin was formed in the Middle Ordovicium and

is covered by Ordovician and Devonian carbonaceous rocksand Quaternary deposits. A description of mining practicesin the Narva mine is given in detail in Pensa et al. (2004).

Afforestation of mine spoil started in 1959, and by 2008,11 000 ha of degraded land had been recultivated. Reclama-tion is carried out in two stages: firstly, the spoil heaps arelevelled, and secondly, tree seedlings are planted after acouple of years. The spoil is alkaline and highly skeletal,containing 40%–75% limestone (Reintam 2004). The or-ganic carbon content in fine earth fraction varies between1.4% and 2% but may attain 4%–5% (Reintam 2004). Plantsgrowing on spoil may occasionally suffer from drought, butthe moisture regime in the top layers of levelled spoil is tol-erable for most of the tree species (Raid 1972). Mostly Scotspine has been used for reclamation, and pine plantationscover 86% of the afforested land (Ostonen et al. 2006).Other more frequently planted tree species include silverbirch (Betula pendula Roth), Norway spruce (Picea abies(L.) Karst.), larch (Larix sibirica Ledeb. and Larix deciduaMill.), and black alder (Alnus glutinosa (L.) Gaertn.)(Ostonen et al. 2006). Productive forests with moder-typeforest floor and Calcaric Regosols and Calcaric Arenosolsdevelop on mine spoil within 20–30 years after afforestation(Reintam and Kaar 2002; Reintam et al. 2002; Reintam2004). Total concentrations of major soil nutrients (nitrogen,phosphorus, potassium) and soil pHKCl under different-agedpine stands in the Narva mine are given in Table 1.

The studied stands were afforested with 2-year-old Scotspine seedlings in 1968–1994 (Table 2; Fig. 1). Willows(Salix spp.), silver birch, and common aspen (Populus trem-ula L.) co-exist in the tree layer along with the planted Scotspine. The understorey consists of willows, silver birch, Nor-way spruce, grey alder (Alnus incana (L.) Moench), com-mon aspen, and raspberry (Rubus idaeus L.). Groundvegetation is dominated by Tussilago farfara L., Calama-grostis epigeios (L.) Roth, Calamagrostis arundinacea (L.)Roth; co-dominants are Epilobium angustifolium L., De-schampsia caespitosa (L.) P. Beauv., Taraxacum officinaleF.H. Wigg. (coll.), Fragaria vesca L., and Medicago lupu-lina L.

In July 2004, we established a 100 m2 circular plot ineach stand and recorded the diameters at breast height(DBH) of all trees with DBH >1 cm. Stem numbers andbasal areas at breast height per hectare were computed sepa-rately for each species. The average height of the stand wasmeasured with a Haglof electronic clinometer (0.5 m preci-sion). Three stands (Nos. 1–3 in Table 2) were selected fordetailed analysis of carbon stocks. The relationship betweenbasal area and stand age of the selected stands was close to

Table 1. Characteristics of soil chemistry at a depth of 0–15 cm underdifferent-aged pine stands in the Narva mine.

Stand age pHKCl

Nitrogen(%)

Phosphorus(mg�g–1)

Potassium(mg�g–1)

Pioneer stage 8.0±0.2 0.03±0.01 69.0±31.8 132.0±75.510 7.8±0.3 0.07±0.03 42.8±19.1 134.9±78.520 7.6±0.4 0.09±0.7 32.3±11.9 95.0±63.130 7.3±0.3 0.15±0.08 16.1±7.4 63.7±39.6

Note: Values are the mean ± standard deviation. Data are from Pensa et al.(2008).

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Table 2. Structural characteristics of the stands in 2004.

Stand No.*Year ofafforestation

Meanheight (m) Species

Density(stems�ha–1)

Mean DBH(cm){

Basal area(m2�ha–1)

1 1990 4 Pinus sylvestris 2300 4.1 (1.4) 3.43Salix spp. 200 2.0 (1.4) 0.08

2 1983 7.5 P. sylvestris 3200 7.0 (3.3) 14.993 1968 14 P. sylvestris 3100 12.5 (3.3) 40.904 1994 2 P. sylvestris 1600 2.1 (1.7) 0.895 1991 4 P. sylvestris 4200 3.9 (2.4) 6.86

Salix spp. 700 2.6 (0.5) 0.386 1990 4 P. sylvestris 4000 2.6 (2.1) 3.44

Salix spp. 600 2.3 (0.8) 0.287 1989 2 P. sylvestris 3600 1.1 (1.5) 0.92

Salix sp. 100 1.0 (0) 0.01Populus tremula 100 2.0 (0) 0.03

8 1987 7 P. sylvestris 2300 10.0 (2.9) 19.39Salix spp. 1700 6.5 (2.4) 6.30P. tremula 100 4.0 (0) 0.13

9 1983 9 P. sylvestris 2600 10.1 (3.0) 22.4910 1982 12 P. sylvestris 3100 11.0 (2.6) 30.87

Salix spp. 200 8.5 (0.7) 1.1411 1981 4 P. sylvestris 4500 3.3 (1.6) 4.8212 1978 15.5 P. sylvestris 1200 14.5 (5.1) 22.05

Salix spp. 800 14.1 (3.5) 13.22Betula pendula 100 14.0 (0) 1.54

13 1976 11 P. sylvestris 2400 10.9 (3.6) 24.65B. pendula 200 10.0 (0) 1.57

*Stands 1–3 were selected for detailed analysis of carbon stocks.{Numbers in parentheses are standard deviations.

Fig. 1. Location of the Narva opencast (indicated with a star in inset) and studied stands in the quarry. Numbers refer to stand No. (seeTable 2), stands 1–3 were selected for detailed study. White areas denote forest; roads and buildings are marked with dark gray, and bodiesof water with light gray. Hatching denotes swampy areas and cross hatching mine spoil.

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the average of all sampled plantations, so we assumed theywere representative for the area.

Biomass carbon stocks

Tree layerTo estimate the biomass of Scots pines, nine trees (three

in each detailed-study stand) were felled for destructivesampling in summer 2004 (Table 3). Model tree selectionwas based on stem diameter frequency distribution of alltrees in the plot but was random within the diameter class.Allometric equations to calculate dry mass of different treecompartments were derived using sample tree data. Thesemodels were then applied to all trees.

After the trees were felled, the height of the model treesand wet mass of stems were determined on site. Three diskswere cut from each stem to convert wet mass to dry mass.Disks were taken from the tree base, at 1.3 m and at thebase of the living crown (just below the lowest greenbranch), transported to the laboratory, and weighed. In theyoungest stand (No. 3 in Table 2), only two disks per stemwere cut, since the living crown started from the base of thestem. Disks were cut into small pieces and oven-dried at70 8C for 48 h. To calculate dry mass for the entire stem,we used the mean dry-matter percentages of the sampleddisks.

The crown was divided into sections with equal length.Branches in each section were separated into living anddead and weighed on site. Typical living branches fromeach section were selected for further analysis and trans-ported to the laboratory in plastic bags. Needles and coneswere removed from these branches, all fractions wereweighed. Dry mass was determined after oven-drying at75 8C for 48–72 h. Based on biomass distributions amongneedles, branch wood (with bark), and cones in samplebranches, and on dry-matter contents for these fractions, to-tal dry masses of needles, branches, and cones were calcu-lated for each crown section. The wet mass of deadbranches was converted to dry mass by using similar sub-samples to determine dry mass ratios.

Belowground biomass was estimated only for average sizeclass model trees (Nos. 1, 4, and 7 in Table 3). Stumps andcoarse roots (>2 mm) were carefully excavated, cleaned, andweighed. The dry mass of the belowground component wasobtained by multiplying its total wet mass by the dry masspercentage of a subsample.

Allometric equations were developed to estimate tree bio-mass for each stand. In the detailed-study stands, only modeltrees from the same site were used to derive relationshipsamong the dry mass of aboveground compartments andstem diameter.

½1� Wi ¼ a� DBHb

where Wi is the dry mass of compartment i (stem, foliage,live and dead branches), and a and b are model parameters.This model is most often used to calculate tree biomass,since it enables accurate estimation with low data require-ments (Ter-Mikaelian and Kozukhin 1997). An equation forcone biomass was not developed because of too few data.

To calculate aboveground tree biomass for other stands(Nos. 4–11 in Table 2), we used the equation

½2� Wi ¼ a� DBHb � Hc

where H is tree height and c is an additional parameter. Thisrelationship was based on all the model trees. Height wastaken as an independent variable in addition to DBH be-cause all stands exhibited different densities, and it hasbeen shown that density can affect height to diameter ratios(Makela and Vanninen 1998). Since heights of all the treeswere not measured, the average stand height was used incalculations.

For belowground biomass (Wb), the linear relationshipwith stem mass (Ws) gave the best fit (as in Vanninen et al.1996).

½3� Wb ¼ a�Ws þ b

Values for parameters a, b, and c were determined bynonlinear (eqs. 1 and 2) and linear (eq. 3) regression (Statis-tica 6.0, StatSoft, Inc.). Choice of the equation applied wasbased on the coefficient of determination (R2) and standarderror of estimate.

Stem biomass for other tree species was estimated usingOzolins’s equation for calculating stem volume and wooddensities (Lemming 2000; De Vries et al. 2003). Ground-area-based estimates for different tree biomass compart-ments were obtained by dividing summed dry masses of alltrees in a given plot by the plot area. The carbon content ofall biomass fractions was considered to be 50%. This is ingood agreement with generally accepted methodology to es-timate changes in forest carbon stocks (IntergovernmentalPanel on Climate Change 2003).

UnderstoreyAboveground understorey biomass was estimated only for

the three detailed-study stands. Understorey was divided intoshrub and herb layers. Wet mass of the shrub layer, whichincluded shrubs, tree saplings (height < 1.3 m), andR. idaeus, was determined in two randomly selected 2 m �2 m quadrats. Subsamples of different tissues were collectedand dried at 65 8C for 48 h to calculate dry masses. Herblayer biomass was measured in five 0.4 m � 0.5 m quadrats,which were randomly situated in each plot. The exact posi-tion of quadrats was selected so that they were at least 1 maway from any tree stem. Within quadrats, herbaceousplants were cut at ground level, dried for 48 h at 60 8C, andweighed. The dry mass shrub and herb layer was convertedto carbon by multiplying by 0.5.

Organic carbon stocks in soil

Sampling and sample pretreatmentThree soil profiles were sampled in each detailed-study

stand in July 2005. For forest floor, 0.4 m � 0.5 m frameswere used. In two older stands, the forest floor was sepa-rated into ground litter (Oi) and fermentation (Oe) horizons.Mineral soil was divided into A and C horizons and sampledunderneath the removed forest floor. These horizons, how-ever, are not used in their traditional meaning in soil sci-ence, but rather refer to mine spoil with (A horizon) andwithout (C horizon) visible organic content. Since the soilswere very stony, the soils were excavated. The volume ofthe resultant pits was determined by refilling with measured

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volumes of sand. The thickness of the A horizon was meas-ured from each pit, and the C horizon was sampled to adepth of 10 cm below the A horizon.

Collected samples were air-dried and weighed. Mineralsoil was sieved through a 2 mm sieve. Visible plant materialthat passed through the 2 mm sieve was removed by hand.Particles larger than 2 mm were weighed separately, andtheir volume was determined by water displacement. Thesamples from each horizon were composited into a singlesample per plot and ground before analyses.

Radiocarbon datingLaboratory analyses were carried out in summer 2006 in

the AMS C14-Labor of the University Erlagen-Nurnberg,Germany (http://www.14c.uni-erlangen.de/). Samples werepretreated to remove carbonates and dried. The carbon con-tent of the pretreated sample material was determined bymass spectrometry after the sample material was oxidizedin an elemental analyzer. 14C activity was obtained by meas-uring the ratios of the different carbon isotopes, 14C, 13C,and 12C, by accelerator mass spectrometry.

Calculation of soil carbon stocksThermonuclear bomb testing in the 1950s and early 1960s

caused a substantial increase in atmospheric 14C content, itspeak levels reaching over 180 percent modern carbon (pMC)compared with 100 pMC, the hypothetical level in 1950.Since the banning of atmospheric nuclear tests in 1963, 14Cactivity has declined to less than 110 pMC. Plants take upthis ‘‘bomb’’ 14C from the atmosphere and deposit it intothe soil upon death. Annual litterfall has been found to bestrongly correlated with stand basal area and stem volume(Starr et al. 2005; Matala et al. 2008), parameters that indi-rectly describe the stand biomass. Assuming that litter inputinto the soil is proportional to tree biomass, the proportionof litter formed in year j from the total litter production dur-ing stand growth (litter%j) is

½4� litter%j ¼ Wj=Xn�1

j¼k

Wj

where Wj is tree biomass in year j, k denotes the year of re-clamation, and n is the year of soil sampling. Values for Wjwere derived from a power regression model that relatedchanges in stand biomass to stand age (Fig. 2).

Litter added to the soil in any given year was assumed tohave the same 14C content as the atmosphere for that year;therefore, the 14C activity of recent soil organic matter(pMCrecent) was calculated as follows:

½5� pMCrecent ¼Xn�1

j¼k

ðlitter%j � pMCatmjÞ

where pMCatmj represents atmospheric 14C activity in yearj. pMCatmj values were obtained from Levin and Kromer(2004); summer means (May–August) were used. Total soilorganic carbon (TOC) was then divided into recentlyformed (Crecent) and oil-shale-derived carbon (Cgeogenic; 14Cactivity = 0 pMC) using the following equations (Rumpelet al. 2003; Morgenroth et al. 2004):

Tab

le3.

Mod

eltr

eech

arac

teri

stic

san

dbi

omas

ses

ofdi

ffer

ent

com

part

men

ts.

Tre

eN

o.St

and

No.

Stan

dag

e(y

ears

)D

BH

(cm

)H

eigh

t(m

)St

em(k

g)N

eedl

es(k

g)L

ivin

gbr

anch

es(k

g)D

ead

bran

ches

(kg)

Con

es(g

)A

bove

grou

ndto

tal

(kg)

Bel

owgr

ound

part

(kg)

11

144

3.3

1.9

1.6

1.6

0.01

05.

10.

92

114

33.

21.

11.

31.

00.

004

03.

43

114

64.

22.

92.

42.

30.

10.

047.

84

221

88.

210

.91.

82.

52.

00.

0317

.32.

15

221

138.

926

.17.

48.

53.

20.

545

.76

221

35.

21.

50.

30.

40.

50

2.7

73

3613

14.3

43.7

3.3

5.6

2.5

055

.27.

58

336

812

.319

.20.

81.

81.

90.

003

23.7

93

3619

15.9

90.2

5.63

16.5

25.5

0.01

137.

9

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½6� Crecent% ¼ pMCTOC=pMCrecent

and

½7� Cgeogenic% ¼ 1� pMCTOC=pMCrecent

Carbon stocks (t C�ha–1) in the organic (Oi and Oe) hori-zons were calculated by multiplying their dry mass by thepercentage of organic carbon (total, recent, or geogenic).Carbon pools in the mineral soil were determined from car-bon contents, horizon depth, and bulk density of fine earth(<2 mm). Because of the low number of samples, we deter-mined ‘‘field variability’’ based on the pooled variance ofthe relative variation for each horizon type and for eachstand, i.e., single measures of variability were calculatedbased on the variation of each stand in terms of their respec-tive mean.

Results

Tree biomassAboveground biomass of Scots pine model trees in the

14-year-old stand was almost equally divided among stems,needles, and branches (Table 3); their average proportionswere 36%, 34%, and 30%, respectively. Older trees had ahigher share of their aboveground biomass in stems (59% inthe 21-year-old stand and 75% in the 36-year-old stand) andless in crown fractions. On average, needles made up 12%and living branches 16% of the total aboveground biomassof the model trees cut in stand 2. In the third stand, needlesmade up 5% and living branches 10%. The average propor-tion of dead branches from aboveground biomass of themodel trees was less than 1% in stand 1, 13% in stand 2,and 10% in stand 3. Differences in biomass and its distribu-tion among the model trees were larger in older stands. Theproportion of belowground biomass with respect to the totaltree biomass was 15%, 11%, and 12% from the youngest tooldest trees.

Using regression equations based on model trees and drymass carbon content (50%), total carbon stock in tree bio-

mass was calculated for all the studied stands. It variedfrom 2.5 t C�ha–1 in the youngest stand, afforested 10 yearsbefore vegetation sampling, up to 101.6 t�ha–1 in the 36-year-old stand (Fig. 2). The rate of carbon accumulation inbiomass increased during this period of stand development.

Carbon stocks in detailed-study stands

VegetationTotal vegetation carbon stock was 7.4 t C�ha–1 in the

youngest detailed-study stand, 29.5 t C�ha–1 in the 21-year-old stand, and 102.1 t C�ha–1 in the 36-year-old stand, affor-ested in 1968 (Table 4). Most of the carbon in vegetationwas in pine biomass: 91.4%, 98.0%, and 99.5%, in theyoungest to oldest stands. The portion of shrub and herblayer was largest in the youngest stand (6.9% and 1.5%)and decreased during stand development. In the oldest stand,shrubs and herbs formed less than 1% of the total vegetationcarbon pool. Stem biomass contained the largest percentageof the total tree biomass, increasing with stand age from32% to 67%.

SoilThe calculated 14C activities of recent SOC were 107.9,

108.7, and 110.8 pMC for the first, second, and third de-tailed-study stand, respectively. Samples taken from the for-est floor horizons had practically the same activities, so thecarbon contained was essentially entirely of recent origin(Table 5). With depth, the share of recent carbon decreased.SOC in C horizon originated mostly from oil shale but alsocontained considerable amounts of recent carbon (16%–39%of TOC, 0.4%–1.4% of soil fine fraction).

The forest floor was undifferentiated in the youngeststand (afforested in 1990) and contained 0.1 t C�ha–1 (Fig.3a). The mass of the organic layers (Oi + Oe) increased ex-ponentially with time, as carbon sequestration in the forestfloor was 4.6 t C�ha–1 in stand 2 and 12.3 t C�ha–1 in stand3. The A horizon was very thin in the two youngest sites(varying from 0 to 0.5 cm); and therefore, the amount of re-cent carbon was also small (0.2 and 0.4 t C�ha–1, respec-tively) (Fig. 3b). In the third stand, the average thickness ofthe A horizon was over 8 cm, and the accumulated carbonstock was 19.0 t C�ha–1, exceeding the corresponding valuefor the forest floor. Sites exhibited great differences in totaland geogenic organic carbon contained in the upper 10 cm

Fig. 2. Carbon accumulation in tree biomass. Numbers refer to thestand number (see Table 2). Solid line is the power regressionmodel (y = 0.0033x2.96, R2 = 0.68); dashed line is the logistic re-gression fit for comparison.

Table 4. Carbon stocks of vegetation in detailed-study stands.

Carbon stock (t C�ha–1)

Fraction Stand 1 Stand 2 Stand 3Stems 2.15 15.68 68.21Needles 1.96 3.32 4.44Living branches 1.71 4.0 9.30Dead branches 0.04 2.66 8.07Stumps and coarse

roots0.90 3.28 11.63

Total pine biomass 6.76 28.93 101.64Willows 0.02 — —Shrub layer

(mean±SD)0.51±0.61 0.58±0.65 0.45±0.55

Herb layer (mean±SD) 0.11±0.06 0.01±0.01 0.04±0.02

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layer of the C horizon (Fig. 3c). The recent carbon stored inthe C horizon was almost equal in the 14- and 21-year-oldstands: 6.0 and 5.5 t C�ha–1, respectively. At the oldest site,the recent carbon stock in the C horizon was 13.4 t C�ha–1.Compared with other soil horizons, the rate of carbon accu-mulation was greatest in the A horizon.

SynthesisTotal recent carbon storage in vegetation and topsoil (O

and A horizons) was 7.8 t�ha–1 in the stand afforested in1990 (i.e., 14 years prior to vegetation and 15 years beforesoil sampling), 34.5 t C�ha–1 in the stand reclaimed in 1983(21 years old at the time of biomass sampling), and133.4 t�ha–1 in the 36-year-old stand. Tree stems contributedmost to the carbon sequestration — their share increasedwith age from 28% to 51% (Fig. 4). Recent SOC formed5% of the total ecosystem carbon stock in the youngest,15% in the second, and 23% in the oldest detailed-studystand.

DiscussionSeveral methods have been used to study the carbon bal-

ance of ecosystems developing on reclaimed mine spoils(Shrestha and Lal 2006). We used the chronosequence ap-proach, which is based on the assumption that sampledstands of different age represent the developmental stagesof a forest. The use of chronosequences is considered themost feasible option to study long-term changes in forestsover the short term (e.g., Wang et al. 2003). However, thismethod is not a panacea, since other factors also vary amongsites (Yanai et al. 2003). In the Narva opencast the substrateis very heterogenic (Vaus 1970; Kuznetsova and Mandre2006). We overcame this problem by selecting many (13)sample plots with small age gaps for biomass assessment;thus, the sampling plots reflected the average productivityof pine plantations in this area. Three stands where carbonpools were studied in detail were situated in close proximity,and the relationship between basal area and stand age ofthese stands was near to the average of all sampled planta-tions.

Despite seemingly adverse growing conditions, tree bio-masses of young Scots pine plantations in the Narva open-cast were comparable to or higher than that of several other

Scots pine stands of the same age, growing in similar cli-mate but on undisturbed soils (Malkonen 1974; Ilvesniemiand Liu 2001; Helmisaari et al. 2002; Kolari et al. 2004).This is in accordance with the conclusion reached byKuznetsova and Mandre (2006) that concentrations of majornutrients in the soil of the Narva opencast are sufficient forpine growth.

Our tree biomass measurements were incomplete, sincewe did not measure the biomass of fine roots (<2 mm), butother studies on Scots pine have shown that most of the be-lowground biomass rests in stumps and coarse roots, and theshare of fine roots from the total tree biomass in 10- to 50-year-old stands varies from <1% to 15% (Vanninen et al.1996; Ilvesniemi and Liu 2001; Helmisaari et al. 2002;Xiao and Ceulemans 2004) and decreases with age(Vanninen et al. 1996; Helmisaari et al. 2002). Measuredvalues of fine root biomasses in young Scots pine forestsrange from 1.5 to 4 t�ha–1 (Makkonen and Helmisaari 1998;Oleksyn et al. 1999; Vanninen and Makela 1999; Helmisaariet al. 2002).

Stem biomass exhibited the largest portion of the totaltree biomass. Its contribution increased with age, but21 years after stand establishment, stem biomass still ac-counted for only 54% of total tree biomass. This demon-strates that ignoring other biomass pools in forest carbonstock estimations may underestimate the tree biomass inyoung stands by as much as 50%.

Since soils in restored oil shale opencasts also containfragments of carbon-containing oil shale, the measurementsof soil TOC overestimate real carbon sequestration. To solvethis problem, we used radiocarbon analysis to obtain thecontribution of plant-derived recent carbon in TOC, consid-ering that the 14C content of the soil depends on the amountof recent carbon and the time period it entered soil, whichdetermines its 14C activity (pMCrecent). Our approach wassimilar to the one developed by Rumpel et al. (2003) whocalculated pMCrecent in mine soils by combining a model forthe turnover of soil organic matter with the record of atmos-pheric 14C activity. They found that modelled SOC dynam-ics had rather little impact on the pMCrecent values. Thissupports our simplified assumption that age distribution ofrecent SOC depends only on the litter production over time,which in turn is related to changes in stand biomass. This

Table 5. 14C activity (pMC), total organic carbon content (TOC), and contribution of recent and geogenic carbon in TOC ascalculated by eqs. 6 and 7, respectively.

Year ofafforestation Horizon

Thickness(cm)

Coarse fraction(vol %) pMC (error)

TOC*(%)

Recent carbon(% of TOC)

Geogenic carbon(% of TOC)

1990 O 108.29 (0.47) 40.6 100.0 0.0A 0.2 13.6 72.88 (0.45) 1.8 67.5 32.5C 10 30.7 17.40 (0.28) 2.3 16.1 83.9

1983 O1 108.01 (0.48) 54.6 99.4 0.6O2 109.57 (0.52) 48.5 100.0 0.0A 0.3 7.0 68.42 (0.38) 2.4 62.9 37.1C 10 6.9 42.88 (0.34) 1.0 39.4 60.6

1968 O1 110.59 (0.48) 55.4 99.8 0.2O2 109.49 (0.51) 48.8 98.8 1.2A 8.3 20.4 37.06 (0.29) 8.8 33.4 66.6C 10 17.6 23.43 (0.27) 6.6 21.1 78.9

*TOC of fine soil fraction <2 mm.

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simplification was also supported by the fact that calculatedradiocarbon activities for recent carbon were the same asthat measured for forest floor horizons that contain onlyplant-derived carbon.

Although the power regression model that was used forcalculating tree biomass and litterfall has the advantage ofdetermining residuals based on relative deviation, it predictsunrealistically a never-ending increase in biomass with age.A logistic fit, in contrast, attains a maximum biomass withincreasing age, but bases its fit on absolute deviations. Thelogistic regression model (Fig. 2) resulted in a slightlygreater 14C activity of recent carbon than the power regres-

sion model, e.g., about 2% for the oldest stand, most ofwhich is attributable to the first decade of regrowth. How-ever, the logistic model predicted only a 75-fold net increasein total biomass, suggesting the model is likely overestimat-ing biomass in the earlier years. Although the logistic modelis likely more realistic for older aged stands, the lack ofcontrast in atmospheric radiocarbon activity results in a neg-ligible effect on the estimate of pMCrecent. Because atmos-pheric 14C was greatest when the tree biomass (andtherefore litterfall) was low, the choice of model had littleinfluence on the 14C activity estimates.

As our results demonstrate, soils in the Narva mine con-tain considerable amounts of recent carbon beneath the Ahorizon also. Considering that overburden is placed selec-tively into heaps in the Narva opencast, this recent carbonmay originate (at least partly) from peat and soil from pre-mining ecosystems. Since it was not possible to differentiatecarbon that had accumulated after afforestation from the car-bon from the previous ecosystem, we omitted the recent car-bon in the C horizon from estimations of total soil andecosystem carbon sequestration. Therefore, the rate of car-bon accumulation in our stands is probably underestimated.Furthermore, the number of stands is too small to draw con-clusions for a wider area, but our work can provide insightinto the role of soils in total stand carbon sequestration fol-lowing afforestation.

The rate of soil development depends on the parent sub-strate. Reintam (2004) has suggested that high contents ofcoarse fractions and fragments of oil shale in mine spoil in-hibit humus accumulation. Our second detailed-study stand,which was reclaimed in 1983, exhibited the lowest geogeniccarbon content in the C horizon. The percentage of >2 mmfractions in that stand was also low. However, the A horizonthat had developed in about 20 years in stand 2 was verythin (up to 0.5 cm). Reintam et al. (2002) measured 5 cmthick A horizons under 18- and 20-year-old pine standsgrowing in the Narva opencast. Perhaps slow soil develop-ment in the second detailed-study stand can be attributed topoor ground vegetation, which is extremely important forhumus formation (Reintam et al. 2002). Additional researchis needed to determine the factors affecting the rate of car-bon sequestration in highly heterogenic soils created byopencast oil shale mining.

The average annual increase in carbon in the oldest de-tailed-study stand was 0.33 t�ha–1�year–1 in the forest floorand 0.51 t�ha–1�year–1 in the A horizon. These values arewithin the range of rates obtained by Reintam et al. (2002),who studied soil formation under Scots pine stands planted inthe Narva oil shale opencast 29–34 years ago. They estimatedcarbon sequestration up to 1.74 t�ha–1�year–1 for the combinedforest floor and humus horizon and 2.38 t�ha–1�year–1 for thewhole soil profile (including AC horizon); the amount of re-cent carbon in mineral soil was found by subtracting the con-tent of organic carbon in spoil from the %TOC in upper soilhorizons (A and AC). This entailed the assumption that minespoil initially contains only geogenic carbon. However, ifsome of the organic carbon in spoil originates from preminingsoil, this method underestimates the real SOC accretion.Comparable rates of SOC accumulation were also observedunder alder plantations on reclaimed coal mine heaps in theCzech Republic (Sourkova et al. 2005). Compared with our

Fig. 3. Storage of recent, geogenic, and total organic carbon in thesoil profiles at the investigated stands. Geogenic carbon was absentin the forest floor horizon of the youngest stand. Error bars showrelative precision based on field variation (see Materials and meth-ods section for details).

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results, the rate of soil carbon sequestration was higher in alignite mine in Germany afforested with Scots pine, to which50 t�ha–1 new carbon was already added to the soil in less than40 years (Rumpel et al. 1999; Fettweis et al. 2005). In Ohio(USA), the estimated rate of SOC accumulation in afforestedcoal mine was as high as 2.3 t�ha–1�year–1 for the 0–15 cm soildepth during the first 20 years after reclamation (Akala andLal 2001). However, the climate in Ohio is warmer and mois-ter than in Estonia; therefore, biomass as well as litter produc-tion and decomposition are probably higher there than at oursites.

There are few publications providing concurrent estimatesof change in biomass and soil carbon stocks following affor-estation in degraded land. In plantations in Europe andNorth America established on former agricultural lands,about 70%–100% of the added carbon is allocated to tree bi-omass (Richter et al. 1999; Hooker and Compton 2003;Thuille and Schulze 2006; Ouimet et al. 2007; Vesterdal etal. 2007), in accordance with our results. Mineral soils onformer arable lands and especially grasslands may even losecarbon after afforestation (Guo and Gifford 2002; Paul et al.2002; Thuille and Schulze 2006). Since mine spoils typi-cally contain little organic carbon, SOC sequestration poten-tial should be substantial until a new steady state betweenlitter input and decomposition is reached. In our 36-year-oldScots pine plantation growing on a reclaimed oil shale open-cast, the recent carbon stock of the A horizon comprised14% and forest floor 9% of the ecosystem total carbonpool. This shows that soils contribute significantly to carbonaccumulation during early forest succession on degradedland. The relative contributions of forest floor and mineral

soil to total soil carbon sequestration vary greatly amongdifferent sites and depend on climate, soil type, tree species,former agricultural land use, and sampling methodology(Vesterdal et al. 2007). Stand age might also be an impor-tant factor, as we found that the average rate of SOC accre-tion was higher in the forest floor than in the mineral soiltwo decades after afforestation in stand 2, whereas recentcarbon storage in the A horizon already exceeded the forestfloor carbon stock in the 36-year-old stand. Similar patternswere also observed by Rumpel et al. (1999) under pinestands in the Lusatian lignite mining district in Germany.On the other hand, other studies conducted in the same min-ing district and under the same species exhibit contrastingresults. Rumpel et al. (2003) estimated that the O horizonscontained 70% of the total SOC pool in the 32-year-oldScots pine stand (in which the mineral soil was sampled toa depth of 5 cm), and Fettweis et al. (2005) found evenhigher forest floor contribution for a stand established37 years ago — 87% of the accumulated SOC was parti-tioned in the forest floor and only 13% in the topsoil (0–10cm). The factors affecting carbon distribution in soils de-serve more attention to identify management practices in-creasing carbon allocation to mineral soil, which isconsidered a more permanent carbon pool than forest floor(Jandl et al. 2007).

Conclusions

Combining the measurement of radiocarbon activity indifferent soil horizons with a simple model of litter produc-tion was a successful approach to differentiate SOC into

Fig. 4. Carbon stocks of different vegetation pools, forest floor, and A horizon, expressed as percent of total carbon. Ecosystem total carbonsequestration is expressed as t�ha–1, values in parentheses show soil (forest floor + A horizon) recent carbon stocks. Tree crowns, dead andliving branches and needles; stems, pine stems and willows; understorey, herb and shrub layer.

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plant-derived and geogenic carbon pools. In the model, litterproduction was related to the stand biomass, but becausestand basal area is usually strongly correlated with tree bio-mass and is easy to measure, we recommend using this pa-rameter instead when biomass data are not available.

Plantations of Scots pine show remarkably good growthon calcareous and stony oil shale mining spoil, having thepotential to accumulate over 130 t C�ha–1 less than 40 yearsafter establishment. According to our results, soils contributea significant part to total stand carbon sequestration, but be-cause of the high variability of the parent substrate, there arestill large uncertainties concerning the average rate of SOCaccumulation in reclaimed oil shale opencasts.

AcknowledgementsThe authors thank Aarne Luud, Riina Vaht, Elga Rull,

Ene Rull, Olaf Raim, Pille Mand, Eve Eensalu, and IngmarTulva for their help during field sampling. We also thankthe employees of the RMK East-Viru County Forest Dis-trict for providing the forestry data for our stands, and theEstonian Oil Shale Ltd. for permission to conduct researchin the Narva opencast. Two anonymous reviewers and asso-ciated editor made valuable comments that helped to im-prove the manuscript. The study was funded by theEstonian Science Foundation (grant 5764), and the EstonianMinistry of Education and Research (projects 0282119s02and 0182732s06).

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