Soil microbial activity and biomass in the primary succession of a dry heath forest

Soil Biology & Biochemistry 32 (2000) 1091±1100

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Soil microbial activity and biomass in the primary succession of a dry heath forest Sami Aikio a,*, Henry VaÈre b, 1, Rauni StroÈmmer a, 2 a

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 vegetation patterns, and a lot of research has been carried out in constructing a mechanistic view of the processes * Corresponding author. Tel.: +358-8-553-1530; fax:+358-8-5531061. E-mail address: sami.aikio@oulu.® (S. Aikio). 1 Present address: Botanical Museum, P.O. Box. 7, 00014 University of Helsinki, Helsinki, Finland. 2 Present address: Department of Ecological and Environmental Sciences, University of Helsinki, Niemenkatu 73, 15140 Lahti, Finland.

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; Ohtonen et al, 1999), and few theoretical principles have therefore been developed in this area. Soil fungi and bacteria are the major organisms responsible for nutrient cycling and for controlling the amounts of nutrients available to plants. Plants in turn add energy to the soil subsystem in the form of litter and root exudates, and act as symbiotic partners for mycorrhizal fungi. Therefore, microbial succession should be stu-

0038-0717/00/$ - see front matter 7 2000 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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S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

died in the context of the vegetation succession and not merely as a function of soil age. Plants exploit nutrients from their area of occupation 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). However, 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 photosynthetic 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 decomposability 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 succession of Scots pine forests in a land uplift area. The importance 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 geobotanically to the intermediate part of the oceanic-continental 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 consequence 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 proportional 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 buried in the sand, indicating that the 5 and 10 m contours 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) perpendicular 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 northern 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 chosen 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 estimated on a percentage scale as an average of 10 systematically 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 samples were taken twice, in August 1995 and August 1997. The 1995 samples, for microbial analysis, were taken from the humus layer with a soil corer of 3 cm in diameter to a depth of 3 cm at 20 cm intervals along the diagonal of each quadrat. The soil samples were pooled for each quadrat and sieved through a 5 mm mesh over an ice bath and stored frozen before analysis. Soil water and organic matter (OM) were determined gravimetrically after drying two subsamples at 1058C for 12 h and after combustion at 4758C for 4 h, respectively. For the microbial analyses, the soils were moistened immediately before analysis to a 250% water content of OM, which is reported to be the optimal amount for microbial respiration in forest soils (Nordgren et al., 1988). Samples C1d±e and C5a±d had water content higher than 250% of OM (max. 312%), and were not moistened. The 1997 samples, intended for nutrient analyses, were taken with soil corer of 6 cm diameter through the entire humus layer and the top 10 cm of the mineral soil. The material was homogenized by hand but not sieved.

S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

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 Respicond 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)2SO4 and 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 carbon (Cmic) by the equation: Cmic (mg C g soilÿ1) = 22.24  SIR (m g CO2±C g soilÿ1 hÿ1) + 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 NH+ 4 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 ammonium acetate extraction (25 ml soil, 125 ml 1 -M NH4OAc, pH 4.65) with an atomic absorption spectrophotometer (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 dividers between clusters. The resulting clusters were compared with the altitudinal change. TWINSPAN classi®cation was performed with the following pseudospecies 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 Me€ord, 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

1093

highest percentage of variation in the nutrient concentrations 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 correspondence 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 variables 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 organic matter (580 mg C gÿ1 OM; cf. Paul and Clark, 1996) and divided that with the total-N per OM concentration to obtain an indirect estimate of C-to-N ratio. This inverse transformation does not a€ect the Kruskal±Wallis statistics which yields the same parameter 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 coecient (rS). Strengths of relationships between the altitudes of the sites and the TWIN-

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Table 1 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 eigenvalue l=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)

1094 S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

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Table 2 Comparisons between altitude classes in terms of microbial activity and biomass measurements, soil nutrient concentrations and other site variables for the humus layer. Values are means 2 standard error of the mean. The statistical signi®cances of the di€erences 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

X

Humus layer, cm OM, kg mÿ2 Total lichens, % Total bryophytes, % Bas, mg CO2±C gÿ1OM hÿ1 Bas/mÿ2, mg CO2 ±C mÿ2hÿ1 Cmic, mg C gÿ1OM Cmic mÿ2, g C mÿ2 pH Total-N, mg OM Total-N, g mÿ2 ÿ1 NH+ 4 , mg g OM ÿ2 NH+ , mg m 4 ÿ1 P, mg g OM P g mÿ2 Mg,mg gÿ1 OM Mg, g mÿ2 Ca, mg gÿ1OM Ca, g mÿ2 K, mg gÿ1OM K, g mÿ2 Fe, mg gÿ1OM Fe, g mÿ2 PCA 1 PCA 2 PCA 3

9.23020.56 9.620.8 120.1 88.622.7 30.521.8 290224 5.3820.85 49.827.1 2.5720.02 15.420.5 149215 1424 150260 4.9120.35 47.024.7 340230 3.3620.58 160210 1.5120.17 360240 3.4220.34 490220 4.7020.37 ÿ2.2720.54 ÿ2.1120.37 0.1820.37

8.4620.70 8.521.0 1.020.4 82.622.3 31.421.9 256229 7.7521.22 52.329.0 2.5620.02 20.824.4 198244 2124 160230 4.7020.53 44.626.7 260210 2.1820.27 110210 1.0320.20 240230 2.0820.36 500250 4.6820.72 ÿ0.9220.69 ÿ0.3920.40 0.3820.21

9.2920.65 9.021.1 1.520.7 72.025.4 35.021.7 294225 8.8621.30 66.428.6 2.5620.02 15.522.1 130217 2025 140230 5.6520.36 49.625.9 290220 2.7920.49 120210 1.1720.22 170220 1.7520.39 590250 5.1420.61 ÿ1.0420.59 1.0420.19 ÿ0.5420.50

5.8520.43 4.020.4 19.823.7 42.027.8 42.921.9 167215 8.6621.00 35.325.4 2.6020.01 19.424.8 67214 2525 110230 7.8321.73 28.825.4 290210 1.1720.13 90210 0.3920.06 290250 1.0320.17 7802160 2.8320.47 0.8520.31 0.6920.74 0.1220.74

3:01 2 0:21 2.620.2 43.122.6 7.021.5 41.022.1 10729 8.5120.80 21.822.3 2.7320.05 12.323.7 34211 1925 50210 3.5521.19 10.023.4 230210 0.6020.04 60210 0.1720.02 300250 0.7620.12 4402110 1.2120.31 2.6120.20 0.0820.51 ÿ0.0820.52

43.83 45.12 50.35 45.32 23.42 39.37 5.47 26.62 16.47 6.98 28.05 3.36 16.14 8.54 26.86 4.14 44.04 25.90 41.20 13.59 25.37 6.48 27.80 35.91 17.99 2.58

SPAN clusters I±V was tested with Spearman's rank correlation coecient.

3. Results The TWINSPAN analysis primarly divided the vegetation data into bryophyte±dwarf shrub and lichenrich clusters (Table 1). The bryophyte±dwarf shrub cluster was further divided into a more herb-rich cluster and a cluster with some lichens (cluster 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. This Cladina-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. stellaris was more abundant (cluster V). The TWINSPAN clusters I±V (cluster VI was omitted as explained in

2

P < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.000 < 0.0001 0.2425 < 0.0001 0.0024 0.1367 < 0.0001 0.4988 0.0028 0.0738 < 0.0001 0.0069 < 0.0001 < 0.0001 < 0.0001 0.0087 < 0.0001 0.1659 < 0.0001 < 0.0001 0.0012 0.6297

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 mineral 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 altitude. 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 di€erences 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 concentrations. The third principal component did not show any signi®cant di€erences between altitude classes.

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S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

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 means 2 standard error of the mean. The statistical signi®cances of the di€erences 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 concentrations TWINSPAN

I

II

III

IV

V

Kruskal±Wallis

N=

7

25

12

15

11

l2

P

Humus layer, cm OM, kg mÿ2 Total lichens, % Total bryophytes, % Bas, mg CO2±C gÿ1OM hÿ1 Bas, mÿ2,mg CO2±C mÿ2 hÿ1 Cmic, mg C gÿ1 OM Cmic, mÿ2, g C mÿ2 pH Total-N, mg gÿ1 OM Total-N, g mÿ2 ÿ1 NH+ OM 4 , m g + NH4 , mg mÿ2 P, mg gÿ1 OM P, g mÿ2 Mg,mg gÿ1 OM Mg, g mÿ2 Ca, mg gÿ1OM Ca, g mÿ2 K, mg gÿ1 OM K, g mÿ2 Fe mg gÿ1OM Fe g mÿ2 PCA 1 PCA 2 PCA 3

10.420.9 11.321.3 0.0220.01 74.525.1 27.921.5 309229 3.8620.83 44.125.7 2.5420.02 22.025.1 233250 2527 280280 5.3020.29 59.727.0 35025 4.2420.94 140210 1.6220.26 310230 3.4320.41 550230 6.1320.67 ÿ3.4220.81 ÿ0.7520.77 ÿ0.4820.66

9.320.4 9.320.7 0.1320.03 80.323.5 32.021.2 288220 7.4220.92 59.126.7 2.5720.01 16.222.3 154223 2124 160220 5.2420.28 49.024.0 300210 2.7220.23 140210 1.3420.15 260230 2.4720.29 510220 4.8620.44 ÿ1.5620.36 ÿ0.2920.38 ÿ0.2920.32

7.120.6 5.520.5 4.020.9 80.722.7 36.922.1 203221 10.7020.73 57.525.5 2.5720.02 13.022.9 82219 1824 100230 5.2820.28 30.225.5 250220 1.3920.16 80210 0.4520.08 130210 0.6720.06 560280 3.2320.54 1.0420.41 0.8620.38 ÿ0.4920.63

4.720.3 3.520.4 27.522.7 24.925.9 46.321.2 159218 7.3420.97 26.325.6 2.6120.01 21.025.0 72218 1723 60210 7.0221.86 23.626.0 270210 0.9320.11 80210 0.2920.04 370250 1.1820.17 7602170 2.5720.58 1.3820.32 ÿ0.2420.76 1.3920.41

2.820.2 2.520.2 47.022.6 5.221.3 39.022.5 9627 9.3420.81 23.022.5 2.7720.06 12.024.4 34213 2226 50210 3.4521.36 9.523.8 230210 0.5620.04 60210 0.1620.03 260250 0.6220.13 4402130 1.2020.37 2.7320.23 0.5220.49 0.3220.68

50.54 49.64 59.89 43.70 34.78 40.28 14.27 31.96 15.32 6.62 27.90 1.43 24.57 5.20 31.06 12.30 50.82 34.20 49.81 20.22 33.26 3.84 28.14 45.17 4.66 9.00

< 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 0.0065 < 0.0001 0.0041 0.1573 < 0.0001 0.8392 0.0001 0.2675 < 0.0001 0.0152 < 0.0001 < 0.0001 < 0.0001 0.0005 < 0.0001 0.4288 < 0.0001 < 0.0001 0.3241 0.0612

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 biomass carbon on an areal basis decreased in tandem with basal respiration, but no di€erences were found for Cmic when determined on a per unit OM basis. In general, the di€erences seem to be greatest in the transition 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 bryophyte 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, indicating decreasing nutrient concentrations; however

the second and third principal components do not differ 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 respiration per unit OM decreased from cluster I to IV. Nutrient concentrations in the mineral soil are presented in Table 4 for comparison between the altitude classes and in Table 5 for comparison between the TWINSPAN clusters. OM did not signi®cantly di€er between altitudes, while the di€erence between the TWINSPAN clusters appeared to be caused by the low OM content of clusters IV and V. The concenper unit area decreased trations of Mg and NH+ 4 along the altitude gradient. The NH+ 4 concentration on OM basis decreased with increasing altitude but did not di€er between the TWINSPAN clusters, whereas per unit area decreased the concentration of NH+ 4 from cluster I to V. The concentrations of other nutrients 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

S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

1097

Table 4 Comparisons between the ®ve altitude classes in terms of organic matter and nutrient concentrations in the mineral soil. Values are means2standard error of the mean. The statistical signi®cances of the di€erences between the classes are assessed with the Kruskal±Wallis test. Nutrient concentrations 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

X

OM, kg mÿ2 Mg, mg gÿ1 OM Mg, mg mÿ2 Ca, mg gÿ1 OM Ca, mg mÿ2 K, mg gÿ1 OM K, g mÿ2 ÿ1 OM NH+ 4 , mg g ÿ2 + NH4 , g m

1.120.1 270220 290220 90210 100220 3.9320.55 4.1220.46 6626 7025

1.220.1 260240 260220 110220 150230 2.3520.44 2.7220.45 6227 6424

1.720.2 160220 250240 180250 3802130 1.0520.14 1.8520.41 3328 4826

1.320.2 230230 240230 180260 4202180 2.5720.65 2.0820.38 3725 41929

1.120.1 190210 210220 120250 2002120 1.9420.39 1.9820.38 3525 3625

7.85 14.13 10.80 8.14 7.93 19.67 14.02 22.68 25.88

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 lichendominated sites when calculated per unit OM but towards the bryophyte-dominated sites when calculated on an areal basis. NMDS placed the bryophyte and herb-dominated nutrient-rich sites at lower altitudes to the right in the ordination and the lichendominated 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-

2

P 0.0970 0.0069 0.0289 0.0865 0.0944 0.0006 0.0072 0.0001 < 0.0001

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 NH+ 4 and Mg had a negative correlation. 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 properties (expressed as an areal basis) depend on the availability of nutrients on an areal basis. The decrease is

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 di€erences between the clusters are assessed with the Kruskal±Wallis test. Nutrient concentrations 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 Mg, mg gÿ1 OM Mg, mg mÿ2 Ca, mg gÿ1 OM Ca, mg mÿ2 K, mg gÿ1 OM K, g mÿ2 ÿ1 NH+ OM 4 , mg g ÿ2 NH+ , mg m 4

1.620.3 240210 310240 160240 3202150 2.6920.90 3.4620.67 56214 71209

1.520.1 200220 260220 170240 300290 2.4020.37 2.9120.35 4725 6024

1.620.3 220240 290250 190260 440220 1.0220.16 1.4720.39 48212 57212

0.820.1 250220 200210 50210 40210 3.3920.57 2.6620.43 4424 3524

1.220.1 200220 220220 150270 2602160 1.4420.33 1.4620.29 3226 3225

23.84 5.12 9.47 21.44 25.60 17.75 15.72 4.55 24.01

0.0001 0.2754 0.0505 0.0003 0.0000 0.0014 0.0034 0.3370 0.0001

1098

S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

Table 6 Pearson's correlation coecients of nutrient concentrations in soil humus layer to the three principal components (PCA 1±3) that explain the greatest proportion of variance. Nutrient concentrations are given per unit weight of OM and on area basis. The statistical signi®cances of correlation coecients are P < 0.05 when |r| > 0.232, and P < 0.01 when |r| >0.302 (df = 69)

N OMÿ1 N mÿ2 NH4 OMÿ1 NH4 mÿ2 P OMÿ1 P mÿ2 Mg OMÿ1 Mg mÿ2 Ca OMÿ1 Ca mÿ2 K OMÿ1 K mÿ2

PCA 1

PCA 2

PCA 3

ÿ0.334 ÿ0.762 ÿ0.002 ÿ0.527 ÿ0.272 ÿ0.905 ÿ0.467 ÿ0.869 ÿ0.738 ÿ0.897 ÿ0.018 ÿ0.758

ÿ0.477 0.157 0.304 0.174 0.597 0.249 ÿ0.037 ÿ0.072 ÿ0.203 ÿ0.156 ÿ0.725 ÿ0.465

ÿ0.638 0.311 ÿ0.437 ÿ0.383 0.551 0.201 ÿ0.441 ÿ0.252 ÿ0.076 ÿ0.121 0.104 0.028

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 concentration of OM. There are several possible reasons as to why an increase in basal respiration occurs as lichen dominated 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 altitude classes and vegetation clusters of the sites did not di€er 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 recalcitrant compounds (Northup et al., 1995). Under nutrient-de®cient conditions in pine forests, organic N (the main N pool present) is bound in recalcitrant compounds 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 organic 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 decomposers probably have no need to maximize carbon ®xation 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 respiration 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 critical value for microbes, suggesting N limitation among decomposers.Plants and microbes are therefore potential 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 allocated 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 saprophytic fungal sporocarp yields is higher in dry, nutrient-poor soils than in moist, nutrient-rich ones (VaÈre et al., 1996a) and a similar trend may exist in belowground hyphal biomass also. When soil nutrients decrease during succession, the ratio of available carbon 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 nutrients causes herbs and other nutrient-demanding plants to decrease in abundance, and this favours less nutrient 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 earliest sites sampled, indicating that the leaching of nutrients is important even within a few decades following emergence of land from the sea. On ®ne-textured and nutrient-rich soils such as those studied by Wardle and Ghani, it takes much longer before the ac-

S. Aikio et al. / Soil Biology & Biochemistry 32 (2000) 1091±1100

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Fig. 1. NMDS ordination of the vegetation and soil data. Quadrats are marked with dots according to their TWINSPAN cluster: (I) ®lled square, (II) ®lled circle, (III) cross, (IV) open diamond and (V) open circle. Species names are abbreviated to four letters of the genus name and three letters of the species name. Full names are given in Table 1. The lines are vectors of environment and soil variables with the following abbreviations and signi®cances of correlations with the ordination structure: TWI = TWINSPAN cluster number (P < 0.001), ALT = altitude of the quadrat (P < 0.001), THICK = thickness of the humus layer (P = 0.002), OM/m2 = organic matter in humus layer mÿ2 (P < 0.001), OM/ m2 M = organic matter in the top 10 cm of mineral soil mÿ2 (P < 0.001), Bas/OM = basal respiration per unit weight of soil organic matter (OM) (P < 0.001), Bas/m2 = basal respiration mÿ2 (P < 0.001), Cmic/OM = microbial biomass carbon per unit OM (P = 0.261), Cmic/m2 = microbial biomass carbon mÿ2 (P < 0.001), Lich = total coverage of lichens (P < 0.001), Bryo = total coverage of bryophytes (P < 0.001), PCA1ÿ3 = principal components of soil nutrient concentration (PPCA1 < 0.001, PPCA2 = 0.205, PPCA3 = 0.012), accounting cumulatively for 27.3%, 46.4% and 62.8% of the variation in nutrient concentrations, respectively.

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 capacity, 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 Wardle, 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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