Plant and Soil 242: 171–182, 2002.© 2002 Kluwer Academic Publishers. Printed in the Netherlands.

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Tree species mediated soil chemical changes in a Siberian artificialafforestation experimentTree species and soil chemistry

Oleg V. Menyailo1,4, Bruce A. Hungate2 & Wolfgang Zech3

1Institute of Forest SB RAS, Krasnoyarsk 660036, Russia. 2 Department of Biological Sciences and Merriam PowellCenter for Environmental Research, Northern Arizona University, AZ 86001, USA. 3Institute of Soil Science andSoil Geography, University of Bayreuth, Bayreuth 95447, Germany. 4Corresponding author∗

Key words: artificial afforestation, forest ecosystems, grassland conversion, soil acidity, soil solution, tree specieseffect

Abstract

Natural and human-induced changes in the composition of boreal forests will likely alter soil properties, butpredicting these effects requires a better understanding of how individual forest species alter soils. We show that 30years of experimental afforestation in Siberia caused species-specific changes in soil chemical properties, includingpH, DOC, DON, Na+, NH4

+, total C, C/N, Mn2+, and SO42−. Some of these properties — pH, total C, C/N, DOC,

DON, Na+ — also differed by soil depth, but we found no strong evidence for species-dependent effects on verticaldifferentiation of soil properties (i.e., no species × depth interaction). A number of soil properties — NO3

−, N,Al3+, Ca2+, Fe3+, K+, Mg2+ and Cl− — responded to neither species nor depth. The six studied species may beclustered into three groups based on their effects on the soil properties. Scots pine and spruce had the lowest pH,highest C/N ratio and intermediate C content in soil. The other two coniferous species, Arolla pine and larch, hadthe highest soil C contents, highest pH values, and intermediate C/N ratios. Finally, the two deciduous hardwoodspecies, aspen and birch, had the lowest C/N ratio, intermediate pH values, and lowest C content. These tree-mediated soil chemical changes are important for their likely effects on soil microbiological activities, including Cand N mineralization and the production and consumption of greenhouse gases.

Introduction

The influence of tree species on soil chemical proper-ties is a critical question in soil science and biogeo-chemistry, especially given increasing artificial affor-estation in Europe, North America and Russia as a wayto reduce net CO2 emissions. Additionally, the speciescomposition of boreal forests will likely change in re-sponse to climate and atmospheric change. Pastor andPost (1988) suggested that changes in temperature andprecipitation resulting from increasing atmosphericCO2 concentrations will cause a northward migrationof the hardwood-conifer forest border in North Amer-ica. Such migration of hardwood forests will likelytake also place in Russian Siberia. Thus, a betterunderstanding of the effects of different species on

∗ E-mail: menyailo@hotmail.com

soil properties is needed to predict how such human-induced and natural changes in species compositionwill alter ecosystem processes. However, there are nopublished data on the direct effects of Siberian treespecies on soil chemical properties.

The effects of tree species on soil chemistry havebeen studied in temperate and boreal forests of North-ern America and Europe (Finzi et al., 1998b; Muysand Lust, 1992; Priha and Smolander, 1997), yet suchresponses may not represent well how species altersoil properties in Siberian forests. First, Larix sibirica(larch) and Pinus sylvestris (Scots pine) are dominantspecies in Siberian forests; Larix sibirica is absent inNorth American and European boreal forests, whilePinus sylvestris is a dominant species in Europeanboreal forests. Second, as species effects may inter-act with nutrient availability and acid deposition, thelow rate of N deposition in Siberia (less than 2 kg

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ha−1 year−1) may lead to qualitatively different spe-cies effects in Siberia compared to Europe and NorthAmerica. Thus, the responses of soil chemical vari-ables to different tree species in Siberia may differfrom those reported in literature for European andAmerican forests.

One of the potential problems in examining plant-induced soil changes is the confounding effects of sitevariability and land-use history. For a study to assesshow plants influence soil, more precise estimates canbe made if experiments are established on an initiallyhomogeneous substrate (Binkley, 1994). If soils areinitially uniform, then any differences in soil variablesthat arise over time among experimental treatments(between species) can be fully attributed to specieseffects (Wedin and Tilman, 1990). Experiments to testthe effects of individual tree species on soil propertiesare difficult to set up compared to those for agriculturalor herbaceous plants, and require long-term mainten-ance in order to be able to observe species effectson soil properties. Thus, there are few artificial af-forestation experiments around the world (Priha andSmolander, 1997) and little data on the effects of forestspecies on soil properties. Here, we report results fromthe only artificial afforestation experiment in RussianSiberia, investigating the effects of single tree specieson soil chemical properties after 30 years of standdevelopment.

The primary aim of our work was to discern theeffects of the six most commonly dominant tree spe-cies in Siberian forests on soil chemical variables,including total carbon and nitrogen, dissolved organiccarbon and nitrogen (DOC and DON), acidity, and themajor ions in soil solution. Second, we wanted to dis-cern the effect of soil depth on these properties, andthe interaction between depth and species. A third goalwas to elucidate the effect of grassland conversion toforestry.

Materials and methods

Research sites

The research plots are located 50 km Northwest fromKrasnoyarsk and were established by the laboratory ofsoil science of the Institute of Forest, Siberian Branchof the Russian Academy of Sciences. The upper 0–50 cm of soil of a 1.5-ha area were removed, mech-anically homogenized to minimize vertical and spatialheterogeneity of chemical, physical and biological

properties prior to planting, and subsequently returnedto the site prior to experimental planting. In 1971–1972, 2–3-year-old seedlings of spruce (Picea abies),birch (Betula pendula), Scots pine (Pinus sylvestris),aspen (Populus tremula), larch (Larix sibirica) andArolla pine (Pinus cembra) were sown into individualplots, each occupying 2400 m2 (Figure 1). An area of9600 m2 was left for grassland as a control, and thesoil under grass was not mechanically homogenized.The region is characterized by continental climaticconditions: average rainfall is 500 mm year−1, aver-age summer temperature is 20 ◦C, depth to permafrostis 70–170 cm, and soil temperature at 20 cm depthin winter is −4 to −14 ◦C and 10 to 12 ◦C in sum-mer. The soil is the gray forest type according toRussian Soil Classification System and Greyzem ac-cording to FAO (1990). In August 1999, each plot wassub-divided into three parts: A, B and C. From eachsub-plot, two trees were randomly chosen and foursoil samples were taken at 50 cm apart of the stem ofeach tree. In grassland, three sub-plots (each of 2 m2)were chosen along the forest plantation; at each sub-plot six soil samples were taken at each depth. Soilsamples were taken at three depth (0–10, 10–20 and20–30 cm) and soils from one depth and one sub-plotwere mixed. Thus, one species resulted in nine soilsamples, three sub-plots versus three soil depths. Thetotal number of soil samples was 63: six species plusgrassland by three subplots by three depths. Becauseeach species occupies only a single plot, subsampleswithin these plots are not independent, and the designof this experiment thus suffers from pseudoreplication(sensu Hurlbert, 1984). Nevertheless, because suchlong-term artificial afforestation experiments are rare,we felt that use of inferential statistics in this experi-ment would provide useful estimates of the effects ofsingle tree species on soil properties.

Study of soil chemical properties

All samples were analyzed for pH in water solu-tion (1:2.5). The major ions in water solution (1:5)— Na+, K+, Ca2+, Mg2+, Mn2+, Fe3+, and Al3+— were measured by atomic absorption spectrometry(AAS 4100, Perkin-Elmer), NH4

+, NO3−, Cl− and

SO42− by a flow injection analyzer (Lachat), and DOC

as CO2 by infrared detection after persulfate oxid-ation. Total dissolved nitrogen was also determinedin the water extract using a Total Nitrogen Analyzer(TN-05, Mitsubishi Kasei Corp.). Dissolved organicnitrogen (DON) was determined as the difference

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Figure 1. Schema of the Siberian artificial afforestation experiment, organized by laboratory of soil science of the Institute of Forest SB RASin 1971–1972.

between total dissolved N and inorganic N. Total C, Nand C/N were determined by Dumas combustion andgas chromatography (Heraeus elemental analyzer).All chemical characteristics (except pH, C and N)were determined in the central analytical laboratoryof BITÖK (Bayreuth Institute of Terrestrial Ecosys-tem Research). Total C, N and pH were analyzed atthe Department of Soil Science of the University ofBayreuth.

Statistical data analysis

All variables were tested for normality of distribu-tion and were log-transformed when necessary. Theeffects of tree species and soil depth were determinedby two-way analysis of variance (ANOVA) with threereplicates. First, the main effects of species and soildepth were determined for forest plots only (withoutgrassland, n=54). When significant main effects weredetected, post hoc comparisons with the Tukey’s hon-est significant difference (HSD) test were performed todiscern which species and at what depths differenceswere significant. To determine the effect of grasslandconversion to forests, one-way ANOVA was com-puted with species as a main factor including grassland(n=63) without regard to soil depth. We considered ef-fects significant at P<0.05. Interrelationships amongsoil properties were studied with Spearman rank ordercorrelations. After that, principal components werecomputed in order to cluster all variables studied andto discern common factors affecting groups of vari-ables. Scores of Varimax rotated principal componentswere compared using two-way ANOVA to test forspecies and depth effects. All statistics were carriedout with the statistical package STATISTICA (5.0 forWindows, StatSoft, 1997).

Results

Soil pH was affected by tree species (P<0.001) andby soil depth (P<0.001) with no interaction betweenthe two factors (Figure 2a). The pH in the upperlayer (0–10 cm) was lower than that in the 10–20(P=0.007) and 20–30-cm (P<0.001) layers, and thedifference between the deeper layers was not signific-ant (P>0.050). The decline of acidity with soil depthprovides evidence that forest litter and possibly sur-face roots contribute mostly to the observed variationin pH among species. The highest pH values wereunder Arolla pine and larch (6.02 and 6.06, respect-ively, for 0–10 cm), significantly higher than otherspecies. The two deciduous species (aspen and birch)had lower pH values (5.82 and 5.80, respectively, for0–10 cm), similar to those under Scots pine. The low-est pH was found under spruce (5.55, for 0–10 cm),significantly lower than that observed under any otherspecies (P<0.001). Compared to grassland soil, soilpH is lower under spruce (P<0.001) and higher underArolla pine (P=0.022).

Total soil C concentration (Figure 2b) was affectedby tree species (P=0.040). The highest C contentswere under larch and Arolla pine (4.8 and 4.1% forthe 0–10 cm depth), and C content under larch wassignificantly higher than that beneath birch (2.65%)and Scots pine (2.86%), where the lowest C concen-tration was found. No effect of grassland conversionon total soil C concentration was found. The effect ofsoil depth on total soil C concentration was marginallysignificant (P=0.055), and there was no interactionbetween species and depth. For all species, soil Cconcentrations tended to decline with depth.

Soil C/N ratio (Figure 2c) was strongly affectedby tree species (P<0.001). The highest soil C/N ra-tios were found under spruce and Scots pine (17.5

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Figure 2. Soil pH (a), total C contents (b) and C-to-N ratios of soil samples under six tree species and grassland (n=3).

and 16.3, respectively). The soil C/N ratio beneathspruce was significantly higher than that observed un-der all other species (P<0.050), and the soil C/N ratiounder Scots pine was significantly higher than thatobserved under birch (P=0.040). The soil C/N ratiounder larch was significantly higher than that underaspen and birch (P=0.030 and P=0.004, respectively),but the difference was not large. The lowest soil C/Nratio (near 13–14) was found under the deciduous spe-cies, aspen and birch. The main effect of soil depthwas marginally significant (P=0.058), and mean val-ues of soil C/N tended to decrease with soil depth.

Larch (P<0.001) and spruce (P=0.015) increased soilC/N ratio compared to grassland. Total C and N con-centrations were closely correlated (r=0.81, P<0.001,n=54). The relationship between soil N concentrationand C/N ratio was not significant, whereas C concen-tration was correlated strongly with C/N ratio (r=0.52,P<0.001, n=54), indicating that soil C/N ratio wasmostly determined by variation in total C.

NH4+ concentration (Figure 3a) was affected

by tree species only (P<0.001), primarily due tothe markedly higher (3–4-fold) NH4

+ concentrationfound in soils under Arolla pine compared to all other

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Table 1. Soil chemical properties studied at three soil depths in grassland and under the six tree species in Siberian artificial afforestationexperiment. Here soil parameters are given, which were affected neither by species nor by soil depth. All values are in mg/kg. Mean values andstandard error in parenthesis

Depth (cm) Spruce Scots pine Arolla pine Larch Aspen Birch Grass

NO3− 0–10 1.14 (0.7) 0.63 (0.6) 4.47 (2.3) 6.81 (1.7) 3.25 (2.7) 4.05 (2.3) 4.25 (1.8)

10–20 1.10 (0.6) 5.09 (2.7) 3.25 (0.5) 3.19 (0.9) 3.54 (1.4) 5.13 (2.4) 2.12 (0.3)

20–30 0.93 (0.5) 1.20 (0.6) 4.20 (0.5) 3.54 (3.0) 4.73 (1.8) 7.20 (4.2) 0.54 (0.5)

N 0–10 0.18 (0.0) 0.18 (0.0) 0.27 (0.1) 0.31 (0.1) 0.22 (0.0) 0.18 (0.0) 0.31 (0.1)

10–20 0.17 (0.0) 0.17 (0.0) 0.20 (0.0) 0.22 (0.0) 0.20 (0.0) 0.19 (0.0) 0.18 (0.0)

20–30 0.21 (0.1) 0.15 (0.0) 0.20 (0.0) 0.20 (0.0) 0.20 (0.0) 0.17 (0.0) 0.12 (0.0)

Al3+ 0–10 252.8 (27.8) 259.6 (21.4) 140.3 (28.1) 168.3 (37.3) 208.0 (34.7) 199.6 (27.9) 177.6 (32.7)

10–20 181.1 (65.8) 155.6 (30.2) 161.6 (35.0) 138.1 (25.9) 218.0 (39.0) 199.0 (66.5) 52.58 (8.2)

20–30 263.5 (45.6) 240.8 (69.6) 138.1 (26.6) 145.0 (10.3) 297.1 (89.6) 208.5 (60.7) 396.5 (177.2)

Ca2+ 0–10 65.03 (20.5) 53.55 (3.4) 48.68 (4.5) 49.67 (4.8) 47.05 (1.8) 46.20 (0.3) 62.63 (21.3)

10–20 46.00 (5.0) 36.08 (2.9) 43.38 (3.1) 41.90 (1.1) 46.70 (4.5) 44.23 (5.6) 39.78 (9.9)

20–30 64.40 (18.2) 43.73 (5.3) 42.48 (4.7) 44.03 (1.1) 82.23 (34.5) 54.73 (3.7) 56.65 (16.8)

Fe3+ 0–10 150.8 (14.6) 153.8 (13.5) 84.0 (17.6) 105.33 (22.7) 127.6 (21.7) 125.1 (16.7) 109.5 (19.8)

10–20 109.0 (40.1) 95.8 (20.0) 95.1 (21.4) 87.00 (16.3) 136.3 (21.9) 125.3 (41.7) 33.40 (5.5)

20–30 158.5 (29.6) 148.3 (46.0) 84.1 (14.7) 92.83 (7.2) 184.1 (53.1) 131.3 (37.4) 249.3 (107.8)

K+ 0–10 45.28 (7.4) 73.80 (35.9) 24.52 (4.2) 26.22 (4.9) 31.90 (3.9) 30.27 (3.7) 35.58 (5.6)

10–20 22.97 (7.9) 21.47 (4.4) 21.48 (3.1) 24.40 (7.0) 30.10 (4.4) 29.17 (8.5) 17.52 (3.9)

20–30 33.58 (4.7) 30.78 (7.9) 18.72 (3.6) 19.57 (1.5) 38.83 (10.1) 27.98 (7.6) 54.23 (19.1)

Mg2+ 0–10 36.70 (4.0) 36.18 (3.4) 24.53 (3.6) 28.40 (5.0) 33.10 (4.5) 30.45 (3.5) 30.85 (5.8)

10–20 26.22 (7.5) 23.75 (4.3) 23.95 (3.3) 23.32 (3.5) 33.65 (4.4) 30.97 (8.6) 11.20 (1.1)

20–30 36.67 (4.8) 34.58 (8.6) 22.73 (3.6) 23.72 (1.3) 43.55 (11.1) 31.68 (8.6) 54.63 (22.2)

Cl− 0–10 6.93 (0.2) 30.98 (23.8) 8.32 (0.1) 9.78 (2.6) 7.18 (1.1) 6.58 (0.6) 6.47 (0.5)

10–20 5.87 (0.1) 9.35 (1.2) 8.67 (0.9) 8.35 (1.0) 6.93 (1.4) 5.83 (0.7) 6.20 (0.1)

20–30 5.33 (0.4) 7.73 (0.6) 7.47 (0.8) 7.28 (0.2) 6.78 (0.9) 5.80 (0.6) 5.50 (0.5)

tree species and grassland (P<0.001). Larch tended tohave higher NH4

+ concentrations compared to spruceand Scots pine, though these differences were not sig-nificant (P=0.250) Surprisingly, NO3

− and total Nwere affected neither by tree species nor by soil depthand the interaction species versus depth was not sig-nificant (Table 1). However, birch had higher NO3

−content than grassland (P=0.034).

Tree species and soil depth significantly affecteddissolved organic carbon (DOC) concentration (forboth P<0.001) (Figure 3b). Overall, DOC concentra-tion decreased with soil depth, with the uppermost soillayer diverging significantly from the deeper two lay-ers. The highest values of DOC concentrations wereunder larch and aspen: they both significantly differedfrom Scots pine (P=0.006 and P=0.001, respectively)and birch (P=0.027 and P=0.002, respectively). DOCunder aspen was also significantly higher than that ob-served under Arolla pine (P=0.030), and DOC underspruce was significantly higher than that under Scots

pine (P=0.001). The lowest concentrations of DOCwere found beneath birch; the values differed signific-antly from those under spruce, aspen and larch (for allP<0.030). DOC concentration was lower in grasslandthan under Arolla pine (P=0.016), spruce, larch andaspen (for all, P<0.001).

Dissolved organic nitrogen (DON) was affected byboth tree species (P=0.046) and soil depth (P<0.001)(Figure 3c). DON, similar to DOC, decreased withsoil depth under all species. As for pH and DOC,DON concentration was significantly higher in theupper soil layer (0–10 cm) from that in the 10–20-and 20–30-cm soil layers with no significant differ-ence between these deeper two layers. DON contentwas lowest under Scots pine, significantly lower thanthat observed under spruce (P=0.030), Arolla pine(P=0.025) and aspen (P=0.009). The two decidu-ous species also differed significantly in DON, withlower values observed under birch than under aspen(P=0.020). DOC and DON were closely interrelated

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Figure 3. NH4+ (a), DOC (b) and DON (c) contents in soil samples under six tree species and grassland (n=3).

(r=0.72, P<0.001, n=54). DON was correlated to totalN (r=0.55, P<0.001) and total C (r=0.54, P<0.001).The relationships between DOC and total C and Nwere weaker, but still significant (r=0.36 and 0.46,respectively, for both P=0.015). Soil C/N ratio wascorrelated to DOC (r=0.39, P=0.003) but not to DON.In contrast to DOC, grassland conversion to forestshad no effect on soil DON concentration.

Neither tree species nor soil depth affected theconcentrations of water soluble Al3+, Ca2+, Fe3+,K+, mg2+ and Cl− (Table 1). There were also no

interactions between species and depth for these para-meters. It seems that tree species do not affect con-centration of these elements after 30 years of growth.Possibly, more time (than 30 years) is needed to causesignificant changes in concentration of these elementsin soil solution among different tree species or throughsoil profile. Another possible explanation of the lackof the effect is that we measured only soluble an-ions and cations in water solution, capturing thus onlya small part of the total soil concentrations of theseelements.

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Figure 4. Mn2+ (a), Na+ (b) and SO42− (c) contents in soil samples under six tree species and grassland (n=3).

The concentration of Mn2+ was affected by treespecies (P=0.003). The lowest Mn2+ content was un-der Scots pine, Arolla pine and larch; the values weresignificantly higher beneath spruce (P<0.010) and as-pen (P<0.020). Birch had significantly higher Mn2+contents than Arolla pine (P=0.040). The effect of soildepth as well as grassland conversion on Mn2+ contentwas not significant (Figure 4).

Both factors (species and depth) influenced Na+concentration (P=0.004 and P<0.001, respectively).Overall, Na+ concentration increased with depth,

though the upper-horizon (0–10 cm) did not signi-ficantly differ from the middle horizon (10–20 cm)(P=0.060) due to an unexpected increase of Na+content in 0–10 cm under Scots pine. The differ-ence between 10–20 and 20–30 cm was significant(P<0.001). The highest concentrations of Na+ wereunder Scots pine, significantly higher than under allother species (P<0.002).

SO42− concentration was also affected by tree spe-

cies (P<0.001), primarily due to a 2–3-fold increase inSO4

2− concentration in all soil horizons under spruce

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Table 2. Principal components loadings after Varimax rotation.Chemical parameters are grouped according to the maximumfittings (loading coefficient >0.60) to principal components

PC1 PC2 PC3 PC4 PC5

Total variability

explained by PC (%): 32.00 19.40 10.90 10.00 5.90

Al 0.97 −0.13 0.02 0.08 −0.04

Ca 0.75 0.22 −0.07 0.04 0.00

Fe 0.97 −0.14 0.04 0.07 −0.05

Mg 0.98 −0.05 0.05 0.06 −0.01

Mn 0.94 0.02 −0.18 −0.01 0.06

N 0.01 0.95 0.04 −0.02 0.13

C 0.00 0.95 −0.14 −0.04 0.13

C-to-N ratio −0.03 0.18 −0.76 −0.11 0.05

SO42− −0.04 0.05 −0.72 0.15 −0.09

pH −0.23 0.50 0.62 0.02 0.12

K 0.60 0.03 −0.09 0.73 −0.01

Cl −0.11 0.06 −0.04 0.92 0.06

Na 0.13 −0.25 0.03 0.61 −0.50

NH4+ −0.23 0.03 0.22 0.04 0.74

DON 0.47 0.46 −0.10 −0.01 0.61

DOC 0.47 0.29 −0.36 −0.13 0.59

NO3− −0.12 0.29 0.41 −0.33 −0.06

compared to all other tree species (for all P<0.003)and grassland (P<0.001).

We used principal components analysis (PCA) todescribe overall patterns of interrelationships amongindividual soil properties and to extract commonfactors responsible for total variation. PCA explained78% of the total variation of all soil properties ex-amined with five principal components (Table 2). Thefirst principal component (PC1) explained 30.8% ofthe variance, and had strong loadings for Al3+, Ca2+,Fe3+, Mg2+ and Mn2+. Thus, PC1 captured the vari-ance associated with soil cation exchange capacity.Most of the cations (except Mn2+) were, however, notaffected by tree species or soil depth. The second prin-cipal component (PC2) explained 19.8% of the totalvariation, and was primarily associated with variancein total C and N content. Thus, PC2 tended to explainthe amount of total organic matter. The third principalcomponent (PC3) accounted for 11% of the total vari-ance and was associated with C/N, SO4

2− and to a

Table 3. Effects of species and depth and their interactions onfive principal components received from the principal compon-ents analysis

PC1 PC2 PC3 PC4 PC5

Species 0.040 <0.001 <0.001 NS <0.010

Depth 0.049 <0.001 <0.001 NS NS

Depth × NS NS NS NS NS

species

lesser extent with pH. PC3 might be thus interpretedas soil acidity and organic matter quality (C/N). Thefourth principal component (PC4) explained 9.5% ofthe total variance and was associated with Cl−, K+and Na+. These elements are highly soluble and notheld strongly on clay exchange sites, or otherwise ad-sorbed or fixed (Waring and Running, 1998). Theseforms are among those most likely to be leached fromforest ecosystems, even in undisturbed conditions.PC4 thus indicated soluble element concentrations.PC5 explained 7.5% of the total variance and wasassociated with NH4

+ and DON.The effects of tree species and soil depth on prin-

cipal components were tested with ANOVA (Table 3).Species significantly affected all principal compon-ents except PC4 (Figure 5a). Soil depth significantlyaffected PC1, PC2 and PC3 (Figure 5b). No signi-ficant interactions between depth and species werefound. PC1 clearly distinguished spruce and aspenon the one hand from larch and Arolla pine on theother, with Scots pine, birch, and grassland inter-mediate (Figure 5a), a grouping that is consistentwith observed species effects on Mn2+ (see above).PC2 separated larch and Arolla pine from spruce(P<0.010), Scots pine (P<0.001), birch (P<0.050)and grass (P<0.010); aspen also differed from Scotspine (P=0.004), reflecting differences among thesespecies in total soil C and N. Figure 5b shows dif-ference of the soil depth distribution along the twoprincipal components: PC1 separated 10–20 cm fromthe other two, while PC2 separated the upper-mostlayer (0–10 cm) from the underlying two, reflect-ing the higher accumulation of organic matter at thesurface.

Discussion

Because all of the tree species studied were the sameage, the Siberian artificial afforestation experiment

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Figure 5. Principal components 1 and 2, summarizing the dataof relative contribution of each species and grassland (a) and soildepths (b) included in factor analysis.

provided a useful design for elucidating cause-and-effect relationships between boreal tree species andsoil chemistry. Moreover, mixing the initial soil to50 cm depth made it possible to test for species-dependent effects on vertical differentiation of chem-ical variables through the soil profile. However, theSiberian artificial afforestation experiment includespseudoreplication (Figure 1), a problem in many large-scale experiments in ecology (Hurlbert, 1984). Theinterpretation of the results should thus be basedon the assumption that on the field chosen for ex-periment there are no other factors influencing soilproperties stronger than species. The results provideevidence that 30 years of development of forest standsplanted with Siberian tree species caused species-specific changes in soil chemical properties. Whilesome variables were affected both by species and soildepth (pH, C, C/N, DOC, DON, Na+); others wereinfluenced by species only (NH4

+, Mn2+, SO42−).

Some measured variables were affected neither by

species nor by depth as main factors (NO3−, N, Al3+,

Ca2+, Fe3+, K+, Mg2+ and Cl−). No soil variableswere affected by soil depth as a main factor only, sug-gesting an overall stronger influence of species thanof soil depth during 30 years of soil development. Ofcourse, this may be true only for our research plots,where studied horizons were homogenized (mixed)before trees were sown, and the duration of our exper-iment was likely insufficient to cause as clear verticaldifferentiation through soil profile as in natural forestsoils. In natural forest ecosystems, the effects of soildepth are likely more pronounced than were observedin our experiment.

Tree species caused small (0.5) but significantdifference in soil pH. We found that two conifer-ous species (Arolla pine and larch) increased soil pHvalues compared to the deciduous species birch andaspen. It was suspected that the types of vegetationgrowing on a soil should have a marked influenceon soil acidity because of the inherent differencesin base content of their litter (Pritchett and Fisher,1987). However, it was not clear whether acidity ofsoil causes differences in species composition or spe-cies modify soil pH. Soils supporting conifers tend tobe more acid than those supporting hardwood species,partly because conifer leaves and litter have a lowerbase content (Ritchett and Fisher, 1987). There are,however, some exceptions. In the western USA, forexample, one of the most abundant coniferous speciesof woodland ecosystems, one-seeded juniper (Juni-perus monosperma), increases soil pH by 2–2.5 unitscompared to the deciduous species aspen (Populustremuloides) (Menyailo and Hungate, unpublished).As shown here for boreal Siberian species, the ef-fect of different conifers on soil pH can be positiveas well as negative compared to deciduous species.Relatively high pH under larch and Arolla pine is con-sistent with the highest microbial activities measuredunder these species including net N mineralization, netnitrification and denitrification potential (Menyailo etal., 2002). The density of stands was high and noherbaceous plants were grown possibly due to lightlimitation. The herbaceous plants thus cannot explainhigher soil pH under larch and Arolla pine than underhardwood species.

Larch had the highest capacity to accumulate soilC. The capacity of larch to preserve soil C is al-most two times higher than that of birch and Scotspine. One of the possible reasons is that larch is theonly coniferous species (among studied) with annuallitter fall, contributing to a high annual deposition

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of C to the forest floor compared to other conifers.Furthermore, the high litter C/N ratio compared tobirch and aspen (Vorob’ev, 1983) likely decreases lit-ter decomposition rate (Melillo et al., 1982; Prescott,1995; Prescott et al., 1993; Stump and Binkley, 1993),further enhancing soil C accumulation.

Tree species caused no significant differences intotal N content but did alter soil C/N ratios. As cor-relation analysis has shown, the differences in C/Nratios between species were associated primarily withvariation in soil C concentrations, and not N concen-trations. The C/N ratio is one predictor of soil organicmatter quality (Howard et al., 1998), influencing therates of decomposition, CO2 emission, N mineraliz-ation and denitrification (Menyailo and Huwe, 1999;Merilä and Ochtonen, 1997), and this parameter wasstrongly affected by species and depth.

DOC and DON declined with soil depth but signi-ficantly only under deciduous species, indicating thatforest litter and not root exudates are likely to be themain source of dissolved organic matter. This is con-sistent with the results of Smith (1976) who found thatsoluble organic matter exuded by roots comprised onlyabout 0.09% of net primary productivity, and that mostsoluble organic matter is likely derived from litter.Other studies have found that root exudates are verylabile substances with decay constants on the order of50 × 10−3 day−1 (Reid and Goss, 1983). Uselmanet al. (2000) found that most of the exudates of treeseedlings of Robinia Pseudoacacia were rapidly de-composed with a rate constant of 500 × 10−3 day−1. Itis thus reasonable that the production of root exudatesis much smaller in quantity than production of litter(Qualls, 2000).

Arolla pine increased the concentration of NH4+ in

all soil horizons by 3-fold compared to the other spe-cies examined. There are many factors affecting NH4

+concentration in soil solution. First, biological pro-cesses may affect NH4

+: microbial N mineralization,nitrification, immobilization and root uptake. We stud-ied net N mineralization and net nitrification in thesesoils (Menyailo et al., 2002), and found no evidencethat either high N mineralization or low nitrificationcould be responsible for such increases in NH4

+ con-centration. Second, minerals may bind NH4

+, and thisis affected by soil pH. However, the parent materialand minerals are the same under all species and the pHis almost the same as under larch. Chemical bindingof NH4

+ could thus not explain an increase in NH4+

concentration under Arolla pine. Possibly, differencesin the preferences of species, in particular Arolla pine,

to take up either NO3− or NH4

+ might explain thiseffect; however, no data are available on nutritionalpreference of Arolla pine compared to larch and/orother species.

No effect of tree species on total N either NO3−

content was found. The concentration of NO3− was

smaller in all soils than that of NH4+. Overall, con-

centrations of different N species in our soils followedthe same order reported for most temperate and borealforests: DON > NH4

+ > NO3−(Currie et al., 1996;

Northrup et al., 1995). The lack of a species effecton NO3

− may be explained by its low concentrationand, consequently, low variation. Finzi et al. (1998a)studied the effect of tree species on total soil N in or-ganic (forest floor) and mineral horizons. They foundthe highest N content in the 0–7.5 cm layer (mineralsoil) and the lowest in forest floor under all species.N content in mineral soil was lower under beech, redoak, and hemlock, compared to red maple, white ash,and sugar maple. However, large differences amongspecies in the size of the forest floor N pool were offsetby the differences in the N pool size of the mineral soilhorizons, leading to relatively few differences amongspecies in total soil N (Finzi et al., 1998a).

We also found that tree species affected Mn2+.Almost under all coniferous species (except spruce),Mn2+ content was lower than under deciduous spe-cies. Mn2+ was closely correlated with other anionsand cations as seen in factor analysis (Table 2), sug-gesting that factors affecting these other ions wereaffecting Mn2+ concentration as well.

Na+ and SO42− were affected by tree species and

Na+ was also influenced by soil depth. Sulfate wascorrelated to pH (as seen in factor analysis) and wasalso correlated to Na+; the relationship between pHand Na+ was, however, weak. Nevertheless, it is pos-sible to consider all these variables to be interrelated;the highest content was under species with lowest pH(Scots pine and spruce). But Na+ content increasedwith soil depth. Probably, differences in litter chem-istry among species could explain an increase in Na+content under Scots pine.

Priha and Smolander (1997) studied microbialactivities in relation to soil chemical properties in ar-tificially afforested plots in Finland. In spite of cleardifferences in the ground vegetation and in the mi-crobiological characteristics of the litter samples, noeffect of tree species on soil pH or soil C/N ratios wasobserved in organic or mineral soils after 23–24 yearsof tree growth. In contrast, Mikola (1985) studied 30-to 50-year-old spruce and birch forests growing on ori-

181

ginally similar sites and found higher pH and lowerC/N ratio in the birch plots than in the spruce plotsin surface soil (0–1.5 cm). This is consistent with ourresults. Possibly, the originally lower pH values in theplots in the Finland study (4.5–4.9, Priha and Smolan-der, 1997) made the effects of spruce, aspen and birchon soil pH difficult to detect. Our soils were originallyless acidic (6.0–6.1) and were exposed for a some-what longer period to the experimental treatments,both possibly favoring the development of species ef-fects on soil pH. One other possible reason is thatFinland’s artificial afforestation experiment does notinclude Arolla pine and larch, which we found to differmarkedly from birch and spruce in soil pH and totalsoil C.

The conversion of grassland to forestry causedchanges in some variables, including pH, NH4

+, C/N,DOC and SO4

2−. Spruce decreased soil pH (P<0.001)and increased C/N ratio and SO4

2− compared to grass-land. NH4

+ content was higher under Arolla pinethan in grassland. Spruce, larch and aspen speciesincreased DOC by 30–50% compared to grassland.Although the soil under grassland was not mixed dur-ing the experimental set up, no variable was affectedby soil depth in the grassland, indicating little hori-zontal differentiation of soil chemical properties in thisecosystem type. We found no significant change insoil C or N after conversion of grassland to forests. Inthe literature, rates of soil C change under aggradingforest range from small losses under cool temperate-zone pine-dominated ecosystems undergoing naturalsuccession (Pregitzer and Palik, 1996) to an increaseof 300 g C m−2 year−1 in a subtropical wet forestplantation (Brown and Lugo, 1990). In our experi-ment, the mechanical homogenization in the plots laterplanted with the six tree species very likely stimulatedsoil microbial activity and associated declines in soilC concentration (Odell et al., 1984). The grassland‘control’, however, was not homogenized, makingit difficult to compare the grassland treatment withthe effect of afforestation treatments with confidence.Despite of the lack of effect of conversion on C andN, tree species increased dissolved organic carbon.This may indicate that soluble organic matter derivedfrom forest litter is more recalcitrant than under grass-land. Almost all microbiological activities were higherunder grassland than under forests, possibly, due todifferences in quality of DOC (Menyailo et al., 2001).

To summarize, we observed significant changes insoil C content, C/N ratio and pH in response to 30years of stand development under particular forest spe-

cies. The six studied species may be clustered intothree groups based on their main effect on soil proper-ties. Scots pine and spruce had the lowest pH, highestC/N ratio and intermediate C content in soil. The othertwo conifers, Arolla pine and larch, had the highestability to accumulate and store soil C, the highest pH,and intermediate soil C/N ratios. Finally, the two de-ciduous hardwood species, aspen and birch, had thelowest C/N ratios, intermediate pHs, and lowest Ccontent. These tree-species mediated changes in soilchemical properties will likely affect important eco-system processes, such as C and N mineralization, andthe production and consumption of greenhouse gases.

Acknowledgements

This work was supported by the German ResearchFoundation (DFG No. 436 RUS 17/89/99 (S)) andby a Fellowship from the Fulbright Program (USA)awarded to OVM. We would like to thank the Cent-ral Analytic Laboratory of the Bayreuth Institute forTerrestrial Ecosystems(BITÖK) for their help with thesoil chemical analysis (BMBF No. 0339476C).

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