Soil microbial activity and biomass in the primary succession of
a dry heath forest
Sami Aikio
a,*, Henry VaÈre
b, 1, Rauni StroÈmmer
a, 2a
Department of Biology, P.O. Box 3000, 90014, University of Oulu, Oulu, Finland b
Botanical Museum, P.O. Box 3000, 90014, University of Oulu, Oulu, Finland Accepted 2 February 2000
Abstract
Changes in vegetation, soil organic matter content, soil nutrient concentration, microbial activity and microbial biomass were studied in Scots pine (Pinus sylvestris) forests on the post-glacial land uplift island of Hailuoto in Finland, along altitudinal transects representing about 1000 years of primary succession. The characteristics of microbial communities in the humus layer were compared both within altitude classes and within TWINSPAN (two-way indicator species analysis) clusters of ®eld layer vegetation. Non-metric multidimensional scaling (NMDS) was employed to reveal gradients in the data. During succession, the vegetation changed from dominance by bryophytes and deciduous dwarf shrubs to evergreen dwarf shrubs and lichens. The thickness of the humus layer and the amount of organic matter in the soil decreased along the succession, which in turn reduced microbial biomass, microbial activity and soil nutrients when calculated on an areal basis. The nutrient concentration of the soil OM (organic matter) showed no successional trend on a concentration basis but the C-to-N ratio of organic matter increased with increasing soil age and lichen coverage. Thus, the nutrient availability decreased during succession but this could not be demonstrated by calculating results against unit weight of organic matter. Soil basal respiration and microbial biomass increased during the succession when calculated per unit weight of organic matter. The successional decrease in site productivity appeared to be due to leaching of nutrients from the sandy mineral soil and thinning of the humus layer. Plants and soil microbes became increasingly N limited during the course of the succession, suggesting the increased importance of mycorrhizal symbiosis for plant performance and increased energy costs among soil microbes in nutrient uptake.7 2000 Elsevier Science Ltd. All rights reserved.
Keywords:Primary succession; Soil respiration; Scots pine; Nutrient leaching
1. Introduction
Age is a useful explanatory variable for many veg-etation patterns, and a lot of research has been carried out in constructing a mechanistic view of the processes
behind successional pathways (Connell and Slatyer, 1977; Tilman, 1982, 1985, 1988; Glenn-Lewin and van der Maarel, 1992). However, there has been little research into the changes in soil microbial activity and biomass during the primary succession (Insam and Haselwandter, 1989; Wardle and Ghani, 1995; Ohto-nen et al, 1999), and few theoretical principles have therefore been developed in this area. Soil fungi and bacteria are the major organisms responsible for ent cycling and for controlling the amounts of nutri-ents available to plants. Plants in turn add energy to the soil subsystem in the form of litter and root exu-dates, and act as symbiotic partners for mycorrhizal fungi. Therefore, microbial succession should be
stu-Soil Biology & Biochemistry 32 (2000) 1091±1100
0038-0717/00/$ - see front matter72000 Elsevier Science Ltd. All rights reserved. PII: S 0 0 3 8 - 0 7 1 7 ( 0 0 ) 0 0 0 1 9 - 5
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* Corresponding author. Tel.: +358-8-553-1530; fax:+358-8-553-1061.
E-mail address:sami.aikio@oulu.® (S. Aikio).
1Present address: Botanical Museum, P.O. Box. 7, 00014 Univer-sity of Helsinki, Helsinki, Finland.
2
died in the context of the vegetation succession and not merely as a function of soil age.
Plants exploit nutrients from their area of occu-pation and therefore nutrient availability and other soil properties should be measured on volume or area basis, in order to be relevant for explaining vegetation patterns. Soil microbes are mostly decomposers and are therefore dependent on the nutrient concentrations of soil organic matter (OM). Microbial processes should therefore be explained in terms of soil nutrient concentrations relative to the unit mass of OM present (VaÈre et al., 1996b; Ohtonen et al., 1997, 1999). How-ever, when soil properties are discussed in the context of ecosystem development, interpretations on areal basis are most appropriate.
Net primary production increases in the early stages of the primary succession, but often starts to decrease in the middle or later stages when the ratio of photo-synthetic to heterotrophic phytomass decreases and the leaching of soil nutrients causes increased nutrient limitation (Odum, 1969; Tilman, 1988; Peet, 1992). The detritus of later successional coniferous forests resists decomposition due to its high concentration of recalcitrant compounds and low concentration of N. Our hypotheses are that soil microbial activity and biomass, when expressed on areal basis, are directly proportional to measures of system productivity, whereas the microbial properties per unit mass of OM are directly proportional to measures of the decompo-sability of OM. The productivity of the system is assumed to be proportional to the concentration of nutrients per unit area of habitat. The decomposability of soil OM is measured as the nutrient concentration and the C-to-N ratio of OM.
We have tested these hypotheses by using data on vegetation, soil microbial activity, microbial biomass and soil nutrient concentrations during primary succes-sion of Scots pine forests in a land uplift area. The im-portance of organic matter decomposition, nutrient leaching and mycorrhizal symbiosis are discussed in terms of ecosystem development.
2. Materials and methods
Soil samples and vegetation data were collected from the island of Hailuoto (65802'N, 24835'E, about 230 km2 in area) in the Gulf of Bothnia between Finland and Sweden which belongs geobota-nically to the intermediate part of the oceanic-conti-nental sector of the middle-boreal vegetation zone (Ahti et al., 1968; Tuhkanen, 1984).The annual mean temperature is 1.98C and precipitation is 465 mm/year (Institute of Meteorology, 1991). Hailuoto began to emerge from the sea 1700±1800 years ago as a conse-quence of post-glacial land uplift and this uplift
con-tinues at the annual rate of 8.6±9.0 mm in this area (Alestalo, 1979). This makes the age of a site pro-portional to its altitude above sea level. On sandy shores, ¯uvial and aeolian processes have formed belts of dunes running parallel to the shoreline. These dunes have been dated dendrochronologically from trees bur-ied in the sand, indicating that the 5 and 10 m con-tours correspond to where the shoreline was present about 400 and 1000 years ago, respectively (Alestalo, 1971, 1979). The island becomes dominated by Scots pine (Pinus sylvestris L.) on soils of age about 300 years, and the oldest soils on Hailuoto have been forested for about 1000 years.
Three transects (labelled A, B and C) perpendicu-lar to the shore line were established in Scots pine forests, one of them situated in the south-western part of the island and the other two in the north-ern part. The altitudes 2.5, 4, 5, 10 and 15 m a.s.l. (labelled 1±5) on each transect were located in the ®eld according to a map of scale 1:20,000 and cho-sen as sites for closer examination. Five 100 m2 quadrats (labelled a±e) on the tops of dunes and located 5 m apart were established perpendicular to the transect at each site, giving 75 quadrats in all. Each 100 m2 quadrat was given a code in which the ®rst capital letter indicates the transect, the following numeral the altitude and the last small case letter the quadrat, e.g. B4c is the quadrat c in the 10 m altitude class on transect B. The vegetation cover was esti-mated on a percentage scale as an average of 10 sys-tematically selected 1 m2 squares in each quadrat. The nomenclature and identi®cation of species follows HaÈmet-Ahti et al. (1998) for vascular plants, Koponen (1994) for bryophytes and Vitikainen et al. (1997) for lichens.
Soil water and OM content were determined as above, but the soils were not moistened.
Microbial analyses were performed on the 1995 samples in two replicates per quadrat using the Respi-cond II respirometer apparatus of Nordgren (1988) with a soil quantity corresponding to 1 g OM (d.w. bases). Basal respiration (Bas) was analysed for 40 h of stable respiration rate after an initial respiration pulse following the melting of the samples. A substrate of 200 mg glucose, 103.7 mg (NH4)2SO4and 10.1 mg
KH2PO4 was mixed into the samples in order to
obtain substrate-induced respiration (SIR; Anderson and Domsch, 1978, as modi®ed by Nordgren et al., 1988). SIR was transformed to microbial biomass car-bon (Cmic) by the equation: Cmic (mg C g soilÿ1) =
22.24SIR (mg CO2±C g soilÿ1hÿ1) + 0.0037
(modi-®ed from Anderson and Domsch, 1978).
The total N concentrations of the soil samples were determined with micro-Kjeldahl method with three replicates per quadrat (Kubin, 1978). Soluble P was determined colorimetrically from CaCl2-solution (25
ml soil, 50 ml 10 mM CaCl2) according to the method
by John (1970). The same CaCl2-solution was also
used for pH-measurements. Electrical conductivity was measured from a 1:2 soil:water extraction. The NH4+
concentrations in the soil samples were determined by the indophenol blue method of Page et al. (1982) with three replicates. Exchangeable cations (Fe, K, Ca, Mg) were determined in three replicates from the am-monium acetate extraction (25 ml soil, 125 ml 1 -M NH4OAc, pH 4.65) with an atomic absorption
spectro-photometer (AAS), according to Halonen et al. (1983). The vegetation data were classi®ed by means of a two-way indicator species analysis (TWINSPAN, Hill, 1979) to detect the convergence between vegetational and altitudinal change. This analysis forms clusters of vegetationally similar quadrats and detects one or more species that are particularly good diagnostic divi-ders between clusters. The resulting clusters were com-pared with the altitudinal change. TWINSPAN classi®cation was performed with the following pseu-dospecies cut-o levels: <0.5% = 1, 0.5±1.0% = 2, 1±2% = 3, 2±4%=4, 4±8% = 5, 8±16% = 6, 16± 32% = 7, 32±64% = 8, 64% = 9. Each 100 m2 quadrat is an observation unit in this analysis (N = 75).
The vegetation data were ordinated by non-metric multidimensional scaling (NMDS; Kruskal and Wish, 1978; Kenkel and OrloÂci, 1986; Kenkel and Booth, 1992) using the DECODA software (Minchin, 1988). A principal components analysis (PCA) was performed with PC-ORD (McCune and Meord, 1995) on the largely autocorrelated soil nutrients to reduce the amount of environmental variables in the ordination diagram. The three principal components (PCA1±3) with the greatest eigenvalues cumulatively explain the
highest percentage of variation in the nutrient concen-trations of the humus layer and were used in NMDS as environmental variables together with microbial variables, total coverage of lichens and bryophytes and the altitude of the site on the transect.
The vegetation coverage values are averages for the ®ve 100 m2 quadrats at each site. Site C1, which formed the TWINSPAN cluster VI (Table 1), was vegetationally marked outlier in the data and was excluded from the analysis (resulting in N = 70) in order to enable the ordination to distinguish gradients in the remaining data. The analysis was performed for a two-dimensional solution. The vegetation data were subjected to Bray±Curtis transformation, involving standardization of both row and column means. This transformation has been found to give good corre-spondence between the ordination con®guration and the real gradient in computer simulations (Kenkel and OrloÂci, 1986; Faith et al., 1987). The environmental data were used without transformation. The signi®-cance of the correlation between species/site points and environmental variables was assessed by a Monte Carlo simulation method with 1000 permutations of data matrices.
Plant species that are close to each other in the NMDS con®guration grow at similar sites and have ecological similarities, while sites that are close to each other in the con®guration have similar vegetation. The values for environmental variables increase in the direction of vectors, with the vectors that point in the same direction correlating positively with each other and those pointing in opposite directions correlating negatively. Long vectors have signi®cant explanatory power with respect to the ordination con®guration. The order of species and site points in relation to a vector is the order of their perpendicular projections on that vector.
The assumptions normally required for parametric tests were not generally met in our data, as shown through the use of the Shapiro±Wilk W-test. Microbial parameters, nutrient concentrations and other vari-ables were therefore compared within altitude classes and vegetation clusters of the TWINSPAN analysis with the non-parametric Kruskal±Wallis test using the SPSS statistical package (Jandel., San Rafael, CA). We assumed a constant 58% C concentration in soil or-ganic matter (580 mg C gÿ1 OM; cf. Paul and Clark,
1996) and divided that with the total-N per OM con-centration to obtain an indirect estimate of C-to-N ratio. This inverse transformation does not aect the Kruskal±Wallis statistics which yields the same par-ameter values as does the total-N per OM. To avoid repetition, altitude groups and TWINSPAN-clusters were compared for C-to-N ratios using Spearman's rank correlation coecient (rS). Strengths of
relation-ships between the altitudes of the sites and the
TWINSPAN classi®cation of the vegetation. Each quadrat is labelled with a three-letter code composed of the transect (A, B and C), position at the transect (1±5 representing altitude classes 2.5±15 m a.s.l.) and the quadrat itself (a±e). The percentage cover values were transformed to 1±9 scale as follows: <0.5%=1, 0.5±1.0%=2, 1±2%=3, 2±4%=4, 4±8%=5, 8±16%=6, 16± 32%=7, 32±64%=8, >64%=9. TWINSPAN clusters are referred to by the Roman numerals I±VI. The emphasized coverage class values show the indicator species in the TWINSPAN cluster they are associated with. The ®rst TWINSPAN division separated clusters I±III from clusters IV±VI with the eigenvaluel=0.420. The second division separated clusters I±II from cluster III (l=0.169) and clusters IV and V from cluster VI (l=0.303). At the third level clusters I and II were separated (l=0.097), and likewise clusters IV and V (l=0.157)
Transect AAAAABB CAAAAAAABAABBBBBBBCCCCCAC CCCCCBCCCBBB BABBBBAAAAAABAB BBBAABCCCCC CCCCC
Position 1132322 4111233222311111222333323 222243444333 354445444445454 55555555555 11111
Quadrat: deadcad bcabbdeccebabcdebeeacdeab abdcaecdeabc debcecbcdeaadba abdcdeabecd aebcd
TWINSPAN-cluster: I II III IV V VI
Polytrichum commune 121---- 1---1--- --- --- ---
--1--Ptilium crista-castrensis 5636565 -1321211--6443614---23 -44--- --- --- ---Aulacomnium palustre 1--- --- --- --- --- ---Cornus suecica -4--- --- --- --- --- ---Dicranum bergeri --1---- --- --- --- ---
---Lycopodium annotinum 111-1-1 ---1---1--1-1-- --- --- --- ---Sorbus aucuparia -2--- ---1---1 --- --- ---
---Betula pubescens --- --1---1--- --- --- ---
---Linnaea borealis 3232233 -231231332133322231332114 111---11-- --- ---
---Luzula pilosa 1--- ---1---1--- --- --- ---
---Salix lapponum --- 2--- --- --- ---
---Trientalis europaea 111-112 -2111--13111111111-111111 ---1-1--- --- --- ---Maianthemum bifolium 11-1122 ---241211---21--111-- --- 1--- ---
---Hylocomium splendens 5537352 3686755674487574567667666 2-534-255466 1---1--- ---
-1---Ledum palustre ---31-1 --1-1325---1-1--- ---2--3- 2--- --- ---Vaccinium myrtillus 7877646 6676667453561445542454555 332123244351 1--1---131--211 -1---1--- 11-11 Vaccinium uliginosum 4-4-1-- 3433313-2-11----1---2- 111---1- --- ---
---Juniperus communis 1--- -4-213---1111-11-1-1111-1 111---1- --- ---
-1---Peltigera aphtosa --- ---1-- ----1--- --- ---
---Deschampsia ¯exuosa 1111111 -1211-111111111111-111111 1111--111--- --- --- 11111
Dicranum fuscescens 55311-- 243111222-1-1111--3221133 332354332555 311-21111111112 -1111111111 43322 Dicranum polysetum 6654155 4543643644354533543245544 125365767555 322454352441433 44411221141 34143 Empetrum niggrum 412112- 63251243-1214421214665534 113453355464 -23233354-13454 113--2-1-44 11111 Pleurozium schreberi 8888899 9989885989888999898888899 998989898999 957676777485879 66513242144 77155 Vaccinium vitis-idaea 7767676 6777766766677767676666677 666567666666 666666666666666 55656635112 41322 Cladina arbuscula --- -111--- 2-12511-1313 1121---2121111- 12213224221 56777 Pohlia nutans --- -2--- --- ---1---- --- ---11
Polytrichum piliferum --- ---11 --- --- --- --111
Cladina rangiferina ---1--1 1---11-11-1-1---2-11- 33545-314444 155557666654444 55645556545 25453 Cladonia cornuta --- ---1---1-- -1-1---1---- ----1-1-1--1--- -11--1-11-1 -1111 Melampyrum pratense -1--- --- --- ----1--- ---
---Pinus sylvestris 1--1--1 1-1--1-1---1--- --111-1--- 1-111111111--11 11111111111 11211 Calluna vulgaris --- ---1--- 111--- -32213--1--2141 43-43322154 -31-3 Cladina stellaris --- --- ---145 477777777777676 88887887888 -1---Arctostaphylos uva-usi --- --- --- --- -1----31321
---1-Cladonia clorophaea --- --- --- --- ---1-11 ----1
Cladonia uncialis --- --- -2--- ---1- --11-111-11 -2-11 Cladonia gracilis --- ---1- ---1---1 ---11--- -111--11111 11111 Cladonia coccifera --- --- --- ----1--- ---1--- -1-11 Cladonia deformis --- ---1- ---1--- ----1--- ---1--1-- -1111
Cetraria ericetorum --- --- -1--- ---1- ---1-- 55455
Cladonia cervicornis --- --- --- --- --- ---11
Cladonia crispata --- --- --- --- --- -1111
Cladonia furfuracea --- --- --- --- ---
---1-Ptilidiumsp. --- --- --- --- ---
1311-Stereocaulonsp. --- --- --- --- --- --1-1 Cetraria islandica --- ---1--- 11114--1-111 ---1111- 11--1--- 11111
Dicranum scoparium --- 1---1---1-11312 133-2--13--- -1----21--21111 1-1111--- -2113
Polytrichum juniperinum --- ---1--- ---41--- --- ---1-11
--11-S.
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1091±11
SPAN clusters I±V was tested with Spearman's rank correlation coecient.
3. Results
The TWINSPAN analysis primarly divided the veg-etation data into bryophyte±dwarf shrub and lichen-rich clusters (Table 1). The bryophyte±dwarf shrub cluster was further divided into a more herb-rich clus-ter and a clusclus-ter with some lichens (clusclus-ter III). The herb-rich cluster was then divided into clusters I and II, the former having more herbs than the latter. The lichen-dominated cluster of the ®rst division was further divided into the ®ve quadrats from site C1 (cluster VI) and a cluster with reindeer lichens (Cladina
spp.) dominating the ground layer in the vegetation. ThisCladina-cluster included all sites at altitudes of 10 and 15 m a.s.l. and one at 5 m a.s.l. The remainder of the lichen-dominated cluster was further divided into a cluster containing quadrats which had Pleurozium schreberi cover (cluster IV) and one in which C. stel-lariswas more abundant (cluster V). The TWINSPAN clusters I±V (cluster VI was omitted as explained in
the methods) were positively correlated with the order of altitude of the sites (rS = 0.828, N = 70, P <
0.0001), suggesting a relation between vegetation and altitude.
The environmental variables for the humus and min-eral soil layers are compared within altitude classes and within TWINSPAN clusters in Tables 2±5. Table 2 compares the nutrient and microbial characteristics of the humus layer across altitude classes. The thickness of the humus layer decreased from about 9 to 3 cm and the amount of soil organic matter decreased from about 9 kg mÿ2
to 2.5±4 kg mÿ2
with increasing alti-tude. Total nutrients in the humus layer, measured per unit area, decreased with increasing altitude, and thus with successional age. Some nutrients (Mg, Ca, K) showed dierences when expressed per unit weight of OM, but only Ca showed consistent decreases with altitude. The C-to-N ratio increased with increasing altitude class (rS = 0.305, N = 70, P = 0.010). The
decreasing amount of soil nutrients with altitude is summarized by the increasing values on the ®rst and second principal components of soil nutrient concen-trations. The third principal component did not show any signi®cant dierences between altitude classes.
Table 2
Comparisons between altitude classes in terms of microbial activity and biomass measurements, soil nutrient concentrations and other site vari-ables for the humus layer. Values are means2standard error of the mean. The statistical signi®cances of the dierences between the altitude classes are assessed with the Kruskal±Wallis test. Basal respiration (Bas), microbial biomass (Cmic) and nutrient concentrations are calculated per unit weight of organic matter (OM) and per unit area (m2). PCA 1±3 are the ®rst three principal components of soil nutrient concentrations
Altitude 2.5 4 5 10 15 Kruskal±Wallis
N= 10 15 15 15 15 X2 P
Humus layer, cm 9.23020.56 8.4620.70 9.2920.65 5.8520.43 3:0120:21 43.83 < 0.0001
OM, kg mÿ2 9.620.8 8.521.0 9.021.1 4.020.4 2.620.2 45.12 < 0.0001
Total lichens, % 120.1 1.020.4 1.520.7 19.823.7 43.122.6 50.35 < 0.0001
Total bryophytes, % 88.622.7 82.622.3 72.025.4 42.027.8 7.021.5 45.32 < 0.0001
Bas,mg CO2±C gÿ1OM hÿ1 30.521.8 31.421.9 35.021.7 42.921.9 41.022.1 23.42 < 0.000 Bas/mÿ2, mg CO
2±C mÿ2hÿ1 290224 256229 294225 167215 10729 39.37 < 0.0001
Cmic,mg C gÿ1OM 5.3820.85 7.7521.22 8.8621.30 8.6621.00 8.5120.80 5.47 0.2425
Cmicmÿ2, g C mÿ2 49.827.1 52.329.0 66.428.6 35.325.4 21.822.3 26.62 < 0.0001
pH 2.5720.02 2.5620.02 2.5620.02 2.6020.01 2.7320.05 16.47 0.0024
Total-N, mg OM 15.420.5 20.824.4 15.522.1 19.424.8 12.323.7 6.98 0.1367
Total-N, g mÿ2
149215 198244 130217 67214 34211 28.05 < 0.0001
NH4 +
,mg gÿ1
OM 1424 2124 2025 2525 1925 3.36 0.4988
NH4 +
, mg mÿ2
150260 160230 140230 110230 50210 16.14 0.0028
P, mg gÿ1
OM 4.9120.35 4.7020.53 5.6520.36 7.8321.73 3.5521.19 8.54 0.0738
P g mÿ2 47.024.7 44.626.7 49.625.9 28.825.4 10.023.4 26.86 < 0.0001
Mg,mg gÿ1OM 340230 260210 290220 290210 230210 4.14 0.0069
Mg, g mÿ2 3.3620.58 2.1820.27 2.7920.49 1.1720.13 0.6020.04 44.04 < 0.0001
Ca,mg gÿ1OM 160210 110210 120210 90210 60210 25.90 < 0.0001
Ca, g mÿ2 1.5120.17 1.0320.20 1.1720.22 0.3920.06 0.1720.02 41.20 < 0.0001
K,mg gÿ1OM 360240 240230 170220 290250 300250 13.59 0.0087
K, g mÿ2 3.4220.34 2.0820.36 1.7520.39 1.0320.17 0.7620.12 25.37 < 0.0001
Fe,mg gÿ1OM 490220 500250 590250 7802160 4402110 6.48 0.1659
Fe, g mÿ2 4.7020.37 4.6820.72 5.1420.61 2.8320.47 1.2120.31 27.80 < 0.0001
PCA 1 ÿ2.2720.54 ÿ0.9220.69 ÿ1.0420.59 0.8520.31 2.6120.20 35.91 < 0.0001
PCA 2 ÿ2.1120.37 ÿ0.3920.40 1.0420.19 0.6920.74 0.0820.51 17.99 0.0012
PCA 3 0.1820.37 0.3820.21 ÿ0.5420.50 0.1220.74 ÿ0.0820.52 2.58 0.6297
Total lichen cover increased with altitude, and the bryophyte cover decreased. Basal respiration decreased when calculated on an areal basis, but increased when calculated on a per unit OM basis. The microbial bio-mass carbon on an areal basis decreased in tandem with basal respiration, but no dierences were found for Cmic when determined on a per unit OM basis. In general, the dierences seem to be greatest in the tran-sition from altitude 5 m a.s.l. to altitude 10 m a.s.l.
Table 3 presents a comparison of the TWINSPAN clusters with respect to the measurements made in the humus layer. The thickness of the humus layer and amount of organic matter decreased from the bryo-phyte dominated quadrats (cluster I) to the lichen dominated quadrats (cluster V), and basal respiration and total nutrients per unit area also decreased. The concentrations of Mg and Ca in soil OM decreased from cluster I to cluster V while K varied but without any clear regularity. The C-to-N ratio increased from cluster I to cluster V (rS = 0.262, N = 70, P =
0.028). The ®rst principal component of soil nutrient concentrations increased from cluster I to cluster V, in-dicating decreasing nutrient concentrations; however
the second and third principal components do not dif-fer signi®cantly between the clusters. The cover of bryophytes is approximately the same in clusters I±III, but much lower in clusters IV and V. The cover of lichens increased from cluster I to V and basal respir-ation per unit OM decreased from cluster I to IV.
Nutrient concentrations in the mineral soil are pre-sented in Table 4 for comparison between the altitude classes and in Table 5 for comparison between the TWINSPAN clusters. OM did not signi®cantly dier between altitudes, while the dierence between the TWINSPAN clusters appeared to be caused by the low OM content of clusters IV and V. The concen-trations of Mg and NH4+ per unit area decreased
along the altitude gradient. The NH4+ concentration
on OM basis decreased with increasing altitude but did not dier between the TWINSPAN clusters, whereas the concentration of NH4+ per unit area decreased
from cluster I to V. The concentrations of other nutri-ents did not seem to have any clear pattern. Ca did not vary between altitudes, but its concentration is much lower in TWINSPAN cluster IV than in the other clusters. K had its lowest concentrations in the
Table 3
Comparisons between TWINSPAN clusters I±V in terms of microbial activity and biomass measurements, soil nutrient concentrations and other site parameters for the humus layer. Values are means2standard error of the mean. The statistical signi®cances of the dierences between the TWINSPAN clusters are assessed with the Kruskal±Wallis test. Basal respiration (Bas), microbial biomass (Cmic) and nutrient concentrations are calculated per unit weight of organic matter (OM) and per unit area (m2). PCA1±3 are the ®rst three principal components of soil nutrient con-centrations
TWINSPAN I II III IV V Kruskal±Wallis
N= 7 25 12 15 11 l2 P
Humus layer, cm 10.420.9 9.320.4 7.120.6 4.720.3 2.820.2 50.54 < 0.0001
OM, kg mÿ2 11.321.3 9.320.7 5.520.5 3.520.4 2.520.2 49.64 < 0.0001
Total lichens, % 0.0220.01 0.1320.03 4.020.9 27.522.7 47.022.6 59.89 < 0.0001
Total bryophytes, % 74.525.1 80.323.5 80.722.7 24.925.9 5.221.3 43.70 < 0.0001
Bas,mg CO2±C gÿ1OM hÿ1 27.921.5 32.021.2 36.922.1 46.321.2 39.022.5 34.78 < 0.0001 Bas, mÿ2,mg CO
2±C mÿ2hÿ1 309229 288220 203221 159218 9627 40.28 < 0.0001
Cmic, mg C gÿ1OM 3.8620.83 7.4220.92 10.7020.73 7.3420.97 9.3420.81 14.27 0.0065
Cmic,mÿ 2
, g C mÿ2
44.125.7 59.126.7 57.525.5 26.325.6 23.022.5 31.96 < 0.0001
pH 2.5420.02 2.5720.01 2.5720.02 2.6120.01 2.7720.06 15.32 0.0041
Total-N, mg gÿ1
OM 22.025.1 16.222.3 13.022.9 21.025.0 12.024.4 6.62 0.1573
Total-N, g mÿ2
233250 154223 82219 72218 34213 27.90 < 0.0001
NH4 +
,mgÿ1
OM 2527 2124 1824 1723 2226 1.43 0.8392
NH4+, mg mÿ2 280280 160220 100230 60210 50210 24.57 0.0001
P, mg gÿ1OM 5.3020.29 5.2420.28 5.2820.28 7.0221.86 3.4521.36 5.20 0.2675
P, g mÿ2 59.727.0 49.024.0 30.225.5 23.626.0 9.523.8 31.06 < 0.0001
Mg,mg gÿ1OM 35025 300210 250220 270210 230210 12.30 0.0152
Mg, g mÿ2 4.2420.94 2.7220.23 1.3920.16 0.9320.11 0.5620.04 50.82 < 0.0001
Ca,mg gÿ1OM 140210 140210 80210 80210 60210 34.20 < 0.0001
Ca, g mÿ2 1.6220.26 1.3420.15 0.4520.08 0.2920.04 0.1620.03 49.81 < 0.0001
K,mg gÿ1OM 310230 260230 130210 370250 260250 20.22 0.0005
K, g mÿ2 3.4320.41 2.4720.29 0.6720.06 1.1820.17 0.6220.13 33.26 < 0.0001
Femg gÿ1OM 550230 510220 560280 7602170 4402130 3.84 0.4288
Fe g mÿ2 6.1320.67 4.8620.44 3.2320.54 2.5720.58 1.2020.37 28.14 < 0.0001
PCA 1 ÿ3.4220.81 ÿ1.5620.36 1.0420.41 1.3820.32 2.7320.23 45.17 < 0.0001
PCA 2 ÿ0.7520.77 ÿ0.2920.38 0.8620.38 ÿ0.2420.76 0.5220.49 4.66 0.3241
15 m altitude class and in TWINSPAN clusters III and V.
The NMDS ordination of the vegetation (Fig. 1) was strongly in¯uenced by altitude, total cover of lichens and bryophytes and the amount of OM per unit area. The variation in the thickness of the humus layer and consequently in the amount of OM per unit area override most of the variation introduced by the concentration of nutrients in OM. The same applies to basal respiration, which increased towards the lichen-dominated sites when calculated per unit OM but towards the bryophyte-dominated sites when calcu-lated on an areal basis. NMDS placed the bryophyte and herb-dominated nutrient-rich sites at lower alti-tudes to the right in the ordination and the lichen-dominated sites at higher altitudes to the left. The ®rst principal component of nutrient concentrations (PCA1) increased towards lichen dominated quadrats. PCA 2 increased with increasing Ca in the mineral soil and PCA 3 was related to K concentrations of OM in both the humus layer and the mineral soil.
Concentrations of the nutrients had a strong
nega-tive correlation with the ®rst principal component (Table 6). The correlation was stronger on areal basis than on a per unit weight of OM basis. PCA 2, on the other hand, has more closely correlated with nutrient concentrations per unit weight of OM than with measurements expressed on an areal basis. Total-N and soluble P had a high positive correlation with PCA 3 whereas NH4+ and Mg had a negative
corre-lation.
4. Discussion
The measurements of microbial variables and soil nutrient concentrations, when expressed on an areal basis, decreased with increasing altitude of the site and vegetation shift from domination by bryophytes and deciduous dwarf shrubs to domination by evergreen dwarf shrubs and lichens. This supports our hypothesis that both vegetation composition and microbial prop-erties (expressed as an areal basis) depend on the avail-ability of nutrients on an areal basis. The decrease is
Table 4
Comparisons between the ®ve altitude classes in terms of organic matter and nutrient concentrations in the mineral soil. Values are means2stan-dard error of the mean. The statistical signi®cances of the dierences between the classes are assessed with the Kruskal±Wallis test. Nutrient con-centrations are calculated per unit weight of organic matter (OM) and per unit area (m2)
Altitude 2.5 4 5 10 15 Kruskal±Wallis
N= 10 15 15 15 15 X2 P
OM, kg mÿ2 1.120.1 1.220.1 1.720.2 1.320.2 1.120.1 7.85 0.0970
Mg,mg gÿ1OM 270220 260240 160220 230230 190210 14.13 0.0069
Mg, mg mÿ2 290220 260220 250240 240230 210220 10.80 0.0289
Ca,mg gÿ1OM 90210 110220 180250 180260 120250 8.14 0.0865
Ca,mg mÿ2 100220 150230 3802130 4202180 2002120 7.93 0.0944
K, mg gÿ1OM 3.9320.55 2.3520.44 1.0520.14 2.5720.65 1.9420.39 19.67 0.0006
K, g mÿ2 4.1220.46 2.7220.45 1.8520.41 2.0820.38 1.9820.38 14.02 0.0072
NH4+,mg gÿ1OM 6626 6227 3328 3725 3525 22.68 0.0001
NH4+, g mÿ2 7025 6424 4826 41929 3625 25.88 < 0.0001
Table 5
Comparisons between the TWINSPAN clusters I±V in terms of organic matter and nutrient concentrations in the mineral soil. Values are means 2standard errors of the mean. The signi®cances of the dierences between the clusters are assessed with the Kruskal±Wallis test. Nutrient con-centrations are calculated per unit weight of organic matter (OM) and per unit area
TWINSPAN I II III IV V Kruskal±Wallis
N= 7 25 12 15 11 X2 P
OM, kg mÿ2 1.620.3 1.520.1 1.620.3 0.820.1 1.220.1 23.84 0.0001
Mg,mg gÿ1OM 240210 200220 220240 250220 200220 5.12 0.2754
Mg, mg mÿ2 310240 260220 290250 200210 220220 9.47 0.0505
Ca,mg gÿ1OM 160240 170240 190260 50210 150270 21.44 0.0003
Ca,mg mÿ2 3202150 300290 440220 40210 2602160 25.60 0.0000
K, mg gÿ1OM 2.6920.90 2.4020.37 1.0220.16 3.3920.57 1.4420.33 17.75 0.0014
K, g mÿ2 3.4620.67 2.9120.35 1.4720.39 2.6620.43 1.4620.29 15.72 0.0034
NH4 +
,mg gÿ1OM 56214 4725 48212 4424 3226 4.55 0.3370
NH4 +
, mg mÿ2
71209 6024 57212 3524 3225 24.01 0.0001
primary due to the reduced amount of OM and the increased leaching of nutrients during succession. In general, the amounts of OM and nutrients in soil increase in the early phases of primary succession but decrease in the later stages, when a high proportion of nutrients have been leached from the soil (Crocker and Major, 1955; Odum, 1969; Tilman, 1988; Peet, 1992). The observed change in vegetation suggests that the quality of the detritus decreases during succession and becomes more recalcitrant to decomposition. However, when microbial activity and biomass were expressed per unit mass of OM, the highest basal respiration was found in the lichen-dominated sites at high altitudes (as also noted by Ohtonen and VaÈre, 1998). This does not support our hypotheses that microbial activity and biomass decrease with the decreasing nutrient concen-tration of OM.
There are several possible reasons as to why an increase in basal respiration occurs as lichen domi-nated vegetation develops when the results are expressed on a per unit OM basis. Soil OM had a low concentration of N at all our study sites and the alti-tude classes and vegetation clusters of the sites did not dier signi®cantly with respect to the nutrient content of OM. Calculations of C-to-N ratios, which re¯ect the decomposability of OM (Kaye and Hart, 1997), showed increased ratios with increasing altitude and lichen dominance. Increasing C-to-N ratios have been found to be associated with high amounts of recalci-trant compounds (Northup et al., 1995). Under nutri-ent-de®cient conditions in pine forests, organic N (the main N pool present) is bound in recalcitrant com-pounds which are inaccessible for those plants which do not have ericoid and ectomycorrhizal fungi (Northup et al., 1995, NaÈsholm et al., 1998).
Assimila-tion of compounds like amino acids and dissolved or-ganic matter has a high energy requirement (Wareing and Patrick, 1975), which increases respiration. When the C-to-N ratio of the detritus is high, the decompo-sers probably have no need to maximize carbon ®x-ation in their biomass, and a greater proportion of the carbon can be used to supply energy for metabolic processes. This may explain the high basal respiration of our samples from lichen-rich sites, which we suggests leads to an increased C loss rate and to a decreased rate of accumulation of OM and thereby a thinner humus layer. Basal respiration measures the amount of carbon that is decomposed but not retained in the microbial biomass, and the high basal respir-ation in the soils of lichen-dominated forests may be due to a preferential allocation of carbon to catabolic processes rather than to structures or storage. Most plant detritus has a C-to-N ratio higher than the criti-cal value for microbes, suggesting N limitation among decomposers.Plants and microbes are therefore poten-tial competitors for N (Kaye and Hart, 1997).
Plants growing in nutrient de®cient habitats may produce photosynthetically ®xed carbon in excess of their physiological needs, and this carbon may be allo-cated to mycorrhizal fungi (Smith and Read, 1997). This source of carbon would increase the performance of mycorrhizal fungi relative to saprophytic fungi and may explain the increased basal respiration per unit OM towards the nutrient de®cient late successional stages. The ratio of mycorrhizal sporocarp to sapro-phytic fungal sporocarp yields is higher in dry, nutri-ent-poor soils than in moist, nutrient-rich ones (VaÈre et al., 1996a) and a similar trend may exist in below-ground hyphal biomass also. When soil nutrients decrease during succession, the ratio of available car-bon to available nutrients appear to increase for both plants and mycorrhizal fungi.
Leaching of nutrients is greatest shortly after forest ®res, which are common in Scots pine forests (Esseen et al., 1997). Some buried pieces of charcoal were found at our study sites, indicating forest ®res, although these have not been dated. Leaching of nutri-ents causes herbs and other nutrient-demanding plants to decrease in abundance, and this favours less nutri-ent demanding late successional lichens and evergreen dwarf shrubs. Wardle and Ghani (1995) showed an increase in soil nutrient concentrations over the ®rst 12,000 years of a primary succession caused by the retreat of the Franz Josef Glacier in New Zealand, after which nutrient availability decreases. In our data, nutrients in the humus layer decreased from the ear-liest sites sampled, indicating that the leaching of nutrients is important even within a few decades fol-lowing emergence of land from the sea. On ®ne-tex-tured and nutrient-rich soils such as those studied by Wardle and Ghani, it takes much longer before the
ac-Table 6
cumulation of nutrients into the biomass or loss of nutrients by leaching causes impoverishment of the soil and ultimately the composition of the vegetation. A sandy soil with low pH and low water holding ca-pacity, as was the case in the present study, has a lower nutrient retention capacity than do clay-rich or silt-rich soils.
Acknowledgements
We wish to thank Johanna Heikkinen for assistance in the ®eld and Tuulikki Pakonen for help with the nutrient analyses. Marko HyvaÈrinen and Pasi Rautio gave valuable comments on statistical methods.
Com-ments and criticism made by Juha Tuomi, David War-dle, Anna Mari Markkola, Esa HaÈrmaÈ and the anonymous referees are also much appreciated. The study was ®nancially supported by the Graduate School in Evolutionary Ecology.
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