Plant and Soil

, Volume 377, Issue 1–2, pp 169–177 | Cite as

Soil microbial activity in relation to dissolved organic matter properties under different tree species

  • Oili Kiikkilä
  • Sanna Kanerva
  • Veikko Kitunen
  • Aino Smolander
Regular Article


Background and aims

The total concentration of dissolved organic carbon (DOC) has often been observed to correlate positively with soil microbial respiration. The aim was to explain the correlation with the properties of dissolved organic matter (DOM).


A dataset from previously published papers was gathered together and subjected to multivariate analyses. Samples were collected from five tree species experiments in Finland. The degradability of DOM was assessed by measuring bacterial and fungal growth in DOM. The chemical properties of DOM were assessed by XAD resin fractionation and molecular weight. Soil microbial activity was assessed as C and N mineralization and microbial biomass.


Both low and high molecular weight compounds, as well as hydrophilic neutral compounds, seemed to be relatively easily degradable. In contrast to our presupposition, easily degradable DOM seemed to be less abundant in soil where variables describing microbial activity were higher. Birch soil with higher microbial biomass N seemed to contain less easily degradable DOM than spruce soil.


We suggest that DOM collected and characterized at a certain point reflects more the accumulation of refractory compounds following high microbial activity than the easily degradable compounds that microbes would be using when measured.


DOC Properties of DOM XAD Ultrafiltration Soil Litter Microbial activity 


Dissolved organic matter (DOM) in soil is produced during litter and soil organic matter (SOM) decomposition and solubilization. In addition, DOM in root exudates has an important role in soil because of its remarkable quantity and possible priming effect on organic matter decomposition (Neff and Asner 2001; Kuzyakov 2010). Soil microbial activity could be expected to exist in relation to the quantity and properties of DOM, because the dissolved form of elements has, in general, been regarded as a prerequisite for microbial uptake. Indeed, it has been observed several times that the total concentration of dissolved organic carbon (DOC) derived from soil correlate positively with variables describing soil microbial activity (e.g. Michel and Matzner 1999; Sjöberg et al. 2003; Zhao et al. 2008; Smolander and Kitunen 2011; Peterson et al. 2013). The existence of the correlation, as well as its explanation is still, however, under debate and seems to depend on site characteristics such as redox conditions (Zhao et al. 2008; Wang et al. 2013; Hanke et al. 2013). Although it has been assumed that DOM represents a labile part of SOM and that total DOC concentration and especially its easily degradable part resembles soil microbial activity, it has been suggested that a great part of DOM in soil represents a relatively stable by-product of microbial activity (Neff and Asner 2001; Hagedorn et al. 2002; Kalbitz et al. 2003; Wickland et al. 2007; Sanderman et al. 2008; Zhao et al. 2008; Wang et al. 2013).

The correlation between soil microbial activity and the concentration of DOC might be explained by the properties of DOM. The complex chemical structure and the proportion of aromatic compounds in DOM have been used to describe the refractory nature of DOM. The complexity and aromaticity of DOM have been suggested to decrease soil CO2 production (Zhao et al. 2008; Wieder et al. 2008; Bu et al. 2010) whereas the high turnover of low molecular weight (LMW) compounds has been suggested to increase soil CO2 production (reviewed by van Hees et al. 2005). However, large datasets combining soil microbial activity and DOM properties are lacking.

Tree species experiments offer an unique opportunity to study the correlation between soil microbial activity and DOC concentration, because tree species are known to affect soil microbial activity. Microbial activity related to C and N cycling has often been suggested to be higher in soil under deciduous silver birch (Betula pendula Roth.) than coniferous Norway spruce (Picea abies (L.) Karst.) as reviewed by Smolander and Kitunen (2011). They also observed positive correlations between DOC concentration extracted from soil and the rate of C and net N mineralization and amount of C and N in microbial biomass, which were used to assess soil microbial activity. In order to explain the correlation we have gathered together a large dataset by combining our previously published datasets of variables describing microbial activity and the properties of DOC and DON with multivariate analysis. Samples had been taken from five tree species experiments of varying site characteristics in Finland.

First, we relate the degradability of DOM to the chemical fractions, according to molecular weight and adsorption properties (XAD resin fractionation), of DOC and DON in order to discover the easily degradable fractions. Several papers have reported that when hydrophilic or LMW compounds are abundant, the degradability of DOM is high and when hydrophobic compounds are abundant, the degradability of DOM is lower (Marschner and Kalbitz 2003; Qualls 2005; Kiikkilä et al. 2013). The hydrophobic acid fraction contains mainly altered lignin degradation products of relatively high molecular weight while the hydrophilic neutral fraction contains breakdown products of carbohydrates strongly related to soil microbial activity (Guggenberger et al. 1994). DOM degradability has often been measured as the loss of DOC during incubation, the result of which is sensitive to the flocculation of DOM, and small differences in the incubation time and conditions (McDowell et al. 2006). We have, in addition, assessed the degradability of DOM by measuring relative bacterial or fungal growth in DOM, and try to increase the comparability of the results across different studies and sources of DOM. Second, we relate the fractions of soil derived DOM to variables that describe microbial activity in soil.

The aim was to see 1) whether bacterial growth in solution could be used as a measure of the degradability of DOM, 2) whether a relationship exists between soil microbial activity and the properties of DOM and can it explain the previously observed correlation between DOC concentration and soil microbial activity variables, and 3) whether DOM properties separate soil under birch from that of spruce and offer any explanation for the previously observed higher soil microbial activity under birch than under spruce. We hypothesize that easily degradable fractions are more abundant in soil under birch with higher soil microbial activity than in soil under spruce.


Datasets from our previous articles, where samples had been taken from litter (L), fermentation (F), humus (H) or combined F and H layers or from laboratory experiment on litter decomposition were combined. All samples had been collected from silver birch (Betula pendula Roth.), Norway spruce (Picea abies (L.) Karst.) or Scots pine (Pinus sylvestris L.) stands. Five tree species experiments on different site types in different parts of Finland from South-East to close to Arctic Circle were used (Table 1). The sample sites were situated in Kivalo (Smolander and Kitunen 2002; Kanerva and Smolander 2007; Kiikkilä et al. 2006), Eno (Smolander et al. 2005; Kiikkilä et al. 2011), Taivalkoski, Lieksa and Punkaharju (Smolander and Kitunen 2011). All soils were podzols, the site fertility varied from relatively low to high and the age of tree stands varied between 20 and 72 years. The site characteristics have been described in detail by Smolander and Kitunen (2011). In addition to soil samples decomposing litter was sampled three times during decomposition in laboratory incubation: 1) in the early stages, 2) after the mass loss reached 20–30 % and 3) when the mass loss reached 30–40 %.
Table 1

Characteristics of the sample sites


Latitude (N)

Longitude (E)

Forest site typea

Age of the stand, years

Soil C/N ratiob































aAccording to Cajander (1949): HMT Pleurozium shreberi-Vaccinium myrtillus, VT-CT Vaccinium vitis-ideae-Calluna vulgaris, OMT Oxalis acetocella-Maianthemum bifolium, MT Vaccinium myrtillus. Order of increasing fertility CT < VT < HMT = MT < OMT

bMean C/N ratio of the birch/spruce/pine stands

Methods have been described in our previous papers listed above in detail. Shortly, soil solution had been collected either with water extraction or centrifugation-drainage technique from fresh samples. DOM had been derived by filtering the solution through 0.45 μm membrane and the concentration of DOC and DON had been measured. The degradability of DOM had been assessed by measuring the relative bacterial or fungal growth in DOM with 3H-thymidine incorporation or 14C-acetate- in-ergosterol technique, introduced to soil studies by Bååth et al. (2001) and Bååth (2001). The degradability of DOM was measured in three papers of Kiikkilä et al. (2006; 2011; 2013). From the same samples also the loss of DOC during short-term (15–20 days) incubations had been measured. The composition of DOM had been characterized in each of our studies by determining DOC and DON in different fractions according to their adsorption properties (XAD-8 resin) (Guggenberger et al. 1994). The technique divides DOC and DON proportionally to hydrophobic and hydrophilic acid, neutral and base fractions. DOM had been also characterized according to molecular weight by ultrafiltration, which divides DOC and DON proportionally to >100 kDa (high molecular weight, HMW), 10−100 kDa, 1−10 kDa and <1 kDa (low molecular weight, LMW) fractions. Soil microbial activity had been described by the rate of C mineralization (CO2 production) and net N mineralization in soil and amounts of C and N in soil microbial biomass (fumigation-extraction) (Smolander and Kitunen 2002, 2011; Smolander et al. 2005; Kanerva and Smolander 2007).

Pearson correlation coefficients were calculated between different measures of the degradability of DOM (from separate datasets and the combined dataset) in order to assess which of the measures are comparable over different studies. Two canonical correlation analyses (CCA), a technique for analysing the relationship between two set of variables, were performed (SAS 9.3). CCA finds a linear combination of variables from each set, called a canonical variable, such that the correlation between the two canonical variables is maximized. Scatter plot diagrams with samples and the most important variables (as vectors) constructing the canonical variables are used to present the result. CCA was first used in order to assess the relation of the chemical fractions of DOM to the degradability of DOM where the measurements for the bacterial and fungal growth and the amount of each chemical fraction of DOC and DON were calculated per amount of DOC in solution. CCA of bacterial growth alone and fungal growth alone against chemical fractions were chosen for the presentation. The second CCA was used in order to assess the relation of the chemical fractions of DOM to the variables describing soil microbial activity. Variables describing soil microbial activity were calculated per soil organic matter. DOC and DON were calculated as the proportional distribution (as %) in order to make DOM derived by centrifugation and water extraction comparable. The combination of soil microbial variables and microbial biomass N alone against chemical fractions were chosen for the presentation.


Degradability of DOM

The loss of DOC in solution during a short-term incubation correlated positively with the bacterial growth in solution in separate datasets. The correlation coefficients were as follows: r = 0.90, n = 27 (Kiikkilä et al. 2006); r = 0.94, n = 14 (Kiikkilä et al. 2011); r = 0.56, n = 27 (Kiikkilä et al. 2013). When the datasets were combined, a very low correlation coefficient (r = 0.3) was observed, indicating no relation. Neither the canonical correlation analysis (CCA) between the loss of DOC and the chemical fractions of DOM was successful. Fungal growth correlated with neither the loss of DOC nor bacterial growth.

CCA was used to find the DOM fractions that were most degradable. In CCA the bacterial growth in DOM solution, used to assess the degradability of DOM, correlated strongly with the combination of DOM fractions (r = 0.88, n = 100) (Fig. 1a). CCA sample score plot diagram between standardized variables, bacterial growth and the canonical variable (Chem = a combination of chemical fractions) was interpreted to indicate that, in general, DOM derived from senescent needles and leaves and litter layer (situating on the right upper part of the diagram, darker symbols) supported the highest bacterial growth. Instead, DOM solution that had been incubated in laboratory supported the lowest bacterial growth (left lower part, small empty symbols). Thus, samples can be separated by the decomposition degree of organic matter (SOM and DOM) but not by tree species.
Fig. 1

Canonical correlation analysis (CCA) of a bacterial growth and b fungal growth versus the concentrations DOC and DON in various fractions according to adsorption properties and molecular weight of DOM originating from humus, fermentation and litter layer and senescent litter of birch, spruce and pine forests. Sample score plots of the first new normalized canonical variables (Bacterial growth or Fungal growth against Chem) are presented. Vectors along x-axis refer to the variable loadings indicating the importance of variables in constructing Chem. The darkness of the symbol refers to the decomposition stage of the source material. Black symbols refer to the litter layer (L), grey to the fermentation (F), empty to the humus (H), and small empty symbols to DOM incubated in laboratory for about 2 weeks. Squares refer to the litter decomposition experiment (Kiikkilä et al. 2013) where 1st, 2nd and 3rd refer to the increasing decomposition stages of litter (1st = in the early stages, 2nd = after the mass loss reached 20–30 % and 3rd = when the mass loss reached 30–40 %). Triangles refer to samples collected in Eno (Kiikkilä et al. 2011) and circles in Kivalo (Kiikkilä et al. 2006). C and N refer to DOC and DON in different fractions. >100, 10–100, 1–10 and <1 refer to molecular weight fractions (kDa). >100 = high molecular weight fraction (HMW), <1 = low molecular weight fraction (LMW), phiA = hydrophilic acid, phiB = hydrophilic bases, phiN = hydrophilic neutrals, phoA = hydrophobic acids, W phoA = weak hydrophobic acids

Variable loadings of CCA describe the most important variables that construct the canonical variable, i.e. variables that are responsible for the separation of the samples. Loadings are presented as vectors in the figures. Positive vectors along Chem (Fig. 1a) indicated that the concentration of DOC in hydrophilic neutral, HMW (>100 kDa) and LMW (<1 kDa) fraction as well as DON in weak hydrophobic acid fraction were higher when bacterial growth was higher. DON in hydrophilic acid and DOC in 1–10 kDa fraction correlated negatively with bacterial growth according to CCA.

Fungal growth and Chem correlated positively according to CCA (r = 0.84, n = 100) (Fig. 1b). The vectors indicated that the concentration of DOC in the HMW fraction was higher when fungal growth was higher. Several fractions of DOC correlated negatively with fungal growth. CCA sample plot diagram separated neither the degradation stages of DOM or SOM nor the tree species.

Soil microbial activity

A combination of soil microbial variables (Biological activity) correlated strongly with Chem in CCA (r = −0.83, n = 66) (Fig. 2a). The vectors indicate that C mineralization and microbial biomass N and C constructed the canonical variable Biological activity. The negative vectors on Chem indicated that the proportion of DON in 10–100 kDa and HMW as well as DOC in hydrophilic neutral fraction were higher when Biological activity was higher. The positive vectors indicate that the proportion of both DOC and DON in the LMW fraction as well as DOC in weak hydrophobic acid fraction was higher when Biological activity was lower.
Fig. 2

CCA of a variables describing soil microbial activity and b soil microbial biomass N (Nmic) versus proportions of DOC and DON in various fractions according to adsorption properties and molecular weight of DOM originating from humus, fermentation and litter layer under birch, spruce and pine. Sample score plots of the first new normalized canonical variables (Biological activity or Nmic against Chem) are presented. Vectors along axes refer to the loadings of the most important variables in constructing canonical variables. Datasets from papers published previously have been used: Taivalkoski, Lieksa and Punkaharju (Smolander and Kitunen 2011); Eno (Smolander et al. 2005); Kivalo H (Smolander and Kitunen 2002); Kivalo H, F and L (Kanerva and Smolander 2007; Kiikkilä et al. 2011). See abbreviations of the fractions in Fig. 1

Tree species were separated when microbial biomass N (Nmic) was chosen alone to CCA (r = −0.68, n = 66) (Fig. 2b). The vectors indicate that when Nmic was higher the proportion of DON in 10–100 kDa, HMW and hydrophobic acid fraction were higher. DOC and DON in LMW fraction as well as DON in hydrophilic neutral and base fraction were higher when Nmic was lower.


Degradability of DOM

Measuring the loss of DOC in solution during a short-term incubation seemed to be highly dependent on the small differences in the incubation time and conditions and the used inoculum. Instead, the relative bacterial growth in solution, using ultrapure water + soil as a control, seemed to be comparable across different studies and was therefore used here to assess the degradability of DOM.

The compounds supporting highest bacterial growth and thus, with highest degradability seemed to belong to hydrophilic neutral, HMW or LMW fractions. They are regarded here as relatively easily degradable fractions. This easily degradable DOM seemed to decrease fairly consistently during the degradation of organic matter as observed previously (Cleveland et al. 2004; Don and Kalbitz 2005). Easily degradable DOM decreased also during the degradation of DOM in laboratory incubation. LMW or hydrophilic neutral compounds have been regarded mostly easily degradable whereas the HMW fraction has often been regarded relatively refractory and connected to lignin derived compounds (Guggenberger et al. 1994; Marschner and Kalbitz 2003; Qualls 2005). Here it was interpreted to contain also easily degradable compounds. The HMW fraction was in general higher in litter than in humus samples. Thus, in our samples the easily degradable part of the HMW fraction seems to be connected to the litter samples i.e. to the freshness of the source material. This has been suggested earlier concerning surface water samples (Amon and Benner 1996) and is not contradictory to previous observations of lignin derived DOM mentioned above. In contrast, recently Malik et al. (2013) showed that recent plant carbon was less abundant in HMW compounds in DOM derived from soil and microbial biomass. Thus, the picture is not clear.

Leaching of relatively refractory compounds have been suggested to increase at the later stages of litter decomposition (Cleveland et al. 2004; Kalbitz et al. 2006; Kiikkilä et al. 2012). Our analysis showed no general indication of the possible increase in hydrophobic acids during organic matter decomposition. Hydrophobic acid compounds have usually been reported relatively refractory (Marschner and Kalbitz 2003; Qualls 2005; Kiikkilä et al. 2011) but they did not correlate with the degradability of DOM when DOM originating from litter and humus were combined. This can be explained by the high proportion (>60 %) of hydrophobic compounds also in the most degradable litter DOM. The black-and-white division of chemical fractions between easily degradable and refractory may often be too simplistic. None of the fractions according to molecular weight or adsorption properties contain either easily degradable or refractory compounds alone; rather, the exact composition of a fraction depends largely on the origin and decomposition stage of DOM.

The analysis may indicate some differences between fungi and bacteria in utilizing DOM. The degradation stage of DOM seemed to control bacterial growth but not fungal growth (Fig. 1). Fungal growth correlated positively only with the abundance of HMW compounds meaning that HMW compounds supported fungal growth. Several fractions, like the LMW fraction, had, however, negative loadings. This indicates that they correlated negatively with the fungal growth. The negative loadings are difficult to interpret here and fungal growth measured in solution phase may include artifacts and deserves further research. The contribution and dominance of fungi to DOM degradation may be a lot stronger in natural systems than in DOM degradation assays.

Soil microbial activity

The interpretation of the canonical correlation between variables describing microbial activity and DOM fractions was not straightforward. Easily degradable compounds became either more (hydrophilic neutrals) or less (LMW) abundant when variables describing soil microbial activity increased. The high loading for hydrophilic neutrals was interpreted to result from the litter layer samples where the microbial activity variables were highest and where also hydrophilic neutral compounds were relatively abundant. Litter DOM is known to be rich in hydrophilic neutral compounds compared to humus (Uselman et al. 2012; Kiikkilä et al. 2011). The relation between hydrophilic fraction and microbial activity variables seemed not to be strong in the humus samples alone. Therefore the high abundance of hydrophilic neutrals could not explain high microbial activity in the humus layer.

In contrast to our hypothesis, variables describing soil microbial activity or biomass seemed to be negatively related to the degradability of DOM. This was deduced from both canonical correlation analyses (Fig. 2a, b). In analysis with Nmic, the interpretation seemed to be obvious. When Nmic was higher the compounds regarded often easily degradable, i.e. LMW, hydrophilic neutrals or hydrophilic bases, were lower. In contrast, compounds regarded often refractory, i.e. HMW and hydrophobic acid, were higher when Nmic was higher. It is therefore suggested that in organic forest soil with a relatively high microbial activity, and thus, active SOM decomposition, high amounts of DOM are produced but easily degradable compounds are degraded. At the same time, refractory compounds accumulate in the solution. The relative enrichment of refractory compounds during DOM degradation has been suggested previously (Wickland et al. 2007; Kalbitz et al. 2003).

The earlier often observed correlation between soil microbial activity and total DOC concentration in soil probably reflects the accumulation of refractory compounds after high microbial activity. It does not tell about high amount of easily degradable compounds that microbes would be using at the point of measurement. We support the view of Bengtson and Bengtsson (2007) that soil respiration can be explained rather by the turnover of DOC than the concentration of DOC. The turnover of DOC is, however, difficult to assess from the measurements at a certain point, because the turnover is a dynamic process. It is also known that the most easily degradable compounds degrade during the processing of DOM in the laboratory (Rousk and Jones 2010). When DOM has been derived from live foliage or from dried and ground samples using extraction combined with suppression of microbial growth, DOM seems to have a relatively high degradability as well as high amount of easily degradable compounds (Cleveland et al. 2004; Bu et al. 2010; Kiikkilä et al. 2011; Uselman et al. 2012). These techniques may describe better the easily degradable DOM that potentially could release during the decomposition of organic matter, but not the total turnover of DOM.


DOM properties seem to correlate with variables describing soil microbial activity and thus, SOM decomposition, as assumed. However, opposite to general assumption, the correlation was interpreted as indicating the accumulation of refractory compounds after easily degradable compounds have been degraded due to high soil microbial activity. In our soils, signs of higher microbial activities under birch than under spruce had been reported, but, in contrast to our hypotheses, birch soil appeared to have less easily degradable DOM than spruce soil. It has been shown previously that DOM collected from lysimeters is mostly old and stable. We suggest that also DOM that we collect by water extraction or centrifugation-drainage technique is more a leftover product than the active part of SOM decomposition.

Measuring the total concentration of DOC, the amount of DOC that potentially could release or even the chemical properties or degradability of DOM at a certain moment does not tell us about the dynamic processes of DOM. In our soils, easily degradable DOM did not reflect microbial activity when measured at the certain moment. However, we suggest that the total flux of easily degradable DOM is higher under birch than under spruce (Kiikkilä et al. 2012). Few efforts to quantitatively assess the fluxes of various DOM fractions from the forest floor (Qualls et al. 1991) or the importance of refractory DOC to C storage in mineral soil (Kalbitz and Kaiser 2008; Klotzbücher et al. 2012) have been published. A more comprehensive view, by modeling the dynamic processes of DOM quantitatively, taking into account DOM properties, would increase our understanding of the origin and fate of DOM in soil and water ecosystems.



We thank A. Siika for the figures and M. Waller for checking the English. The research was supported by the Academy of Finland.


  1. Amon RMW, Benner R (1996) Bacterial utilization of dissolved organic matter. Limnol Oceanogr 41:41–51CrossRefGoogle Scholar
  2. Bååth E (2001) Estimation of fungal growth rates in soil using 14C-acetate incorporation into ergosterol. Soil Biol Biochem 33:2011–2018CrossRefGoogle Scholar
  3. Bååth E, Pettersson M, Söderberg KH (2001) Adaptation of a rapid and economical microcentrifugation method to measure thymidine and leucine incorporation by soil bacteria. Soil Biol Biochem 33:1571–1574CrossRefGoogle Scholar
  4. Bengtson P, Bengtsson G (2007) Rapid turnover of DOC in temperate forest accounts for increased CO2 production at elevated temperatures. Ecol Lett 10:783–790PubMedCrossRefGoogle Scholar
  5. Bu X, Ding J, Wang L, Yu X, Huang W, Ruan H (2010) Biodegradation and chemical characteristics of hot-water extractable organic matter from soils under four different vegetation types in the Wuyi Mountains, southeastern China. Eur J Soil Biol 47:102–107CrossRefGoogle Scholar
  6. Cajander AK (1949) Forest types and their significance. Acta For Fenn 56:1–71Google Scholar
  7. Cleveland CC, Neff JC, Townsend AR, Hood E (2004) Composition, dynamics, and fate of leached dissolved organic matter in terrestrial ecosystems: results from a decomposition experiment. Ecosystems 7:275–285CrossRefGoogle Scholar
  8. Don A, Kalbitz K (2005) Amount and degradability of dissolved organic carbon from foliar litter at different decomposition stages. Soil Biol Biochem 37:2171–2179CrossRefGoogle Scholar
  9. Guggenberger G, Zech W, Schulten HR (1994) Formation and mobilization pathways of dissolved organic matter: evidence from chemical structural studies of organic matter fractions in acid forest floor solutions. Org Geochem 21:51–66CrossRefGoogle Scholar
  10. Hagedorn F, Blaser P, Siegwolf R (2002) Elevated atmospheric CO2 and increased N deposition effects on dissolved organic carbon–clues from δ13C signature. Soil Biol Biochem 34:355–366CrossRefGoogle Scholar
  11. Hanke A, Cerli C, Muhr J, Borken W, Kalbitz K (2013) Redox control on carbon mineralization and dissolved organic matter along a chronosequence of paddy soils. Eur J Soil Sci 64:476–487CrossRefGoogle Scholar
  12. Kalbitz K, Kaiser K (2008) Contribution of dissolved organic matter to carbon storage in forest mineral soils. J Plant Nutr Soil Sci 171:52–60CrossRefGoogle Scholar
  13. Kalbitz K, Schwesig D, Schmerwitz J, Kaiser K, Haumaier L, Glaser B, Ellerbrock R, Leinweber P (2003) Changes in properties of soil-derived dissolved organic matter induced by biodegradation. Soil Biol Biochem 35:1129–1142CrossRefGoogle Scholar
  14. Kalbitz K, Kaiser K, Bargholz J, Dardenne P (2006) Lignin degradation controls the production of dissolved organic matter in decomposing foliar litter. Eur J Soil Sci 57:504–516CrossRefGoogle Scholar
  15. Kanerva S, Smolander A (2007) Microbial activities in forest floor layers under silver birch, Norway spruce and Scots pine. Soil Biol Biochem 39:149–1467CrossRefGoogle Scholar
  16. Kiikkilä O, Kitunen V, Smolander A (2006) Dissolved organic matter from surface organic horizons under birch and conifers: degradation in relation to chemical characteristics. Soil Biol Biochem 38:737–746CrossRefGoogle Scholar
  17. Kiikkilä O, Kitunen V, Smolander A (2011) Properties of dissolved organic matter derived from silver birch and Norway spruce stands: degradability combined with chemical characteristics. Soil Biol Biochem 43:421–430CrossRefGoogle Scholar
  18. Kiikkilä O, Kitunen V, Spetz P, Smolander A (2012) Characterization of dissolved organic matter in decomposing Norway spruce and silver birch litter. Eur J Soil Sci 63:476–486CrossRefGoogle Scholar
  19. Kiikkilä O, Smolander V, Kitunen V (2013) Degradability, molecular weight and adsorption properties of dissolved organic carbon and nitrogen leached from different types of decomposing litter. Plant Soil 373:787–798Google Scholar
  20. Klotzbücher T, Kaiser K, Stepper C, van Loon E, Gerstberger P, Kalbitz K (2012) Long-term litter input manipulation effects on production and properties of dissolved organic matter in the forest floor of a Norway spruce stand. Plant Soil 355:407–416CrossRefGoogle Scholar
  21. Kuzyakov Y (2010) Priming effects: interactions between living and dead organic matter. Soil Biol Biochem 42:1363–1371CrossRefGoogle Scholar
  22. Malik A, Blagodatskaya E, Gleixner G (2013) Soil microbial carbon turnover decreases with increasing molecular size. Soil Biol Biochem 62:115–118Google Scholar
  23. Marschner B, Kalbitz K (2003) Controls of bioavailability and biodegradability of dissolved organic matter in soils. Geoderma 113:211–235CrossRefGoogle Scholar
  24. McDowell WH, Zsolnay A, Aitkenhead-Peterson JA, Gregorich EG, Jones DL, Jödemann D, Kalbitz K, Marschner B, Schwesig D (2006) A comparison of methods to determine the biodegradable dissolved organic carbon from different terrestrial sources. Soil Biol Biochem 38:1933–1942CrossRefGoogle Scholar
  25. Michel K, Matzner E (1999) Release of dissolved organic carbon and nitrogen from forest floors in relation to solid phase properties, respiration and N-mineralization. J Plant Nutr Soil Sci 162:645–652CrossRefGoogle Scholar
  26. Neff JC, Asner GP (2001) Dissolved organic carbon in terrestrial ecosystems: synthesis and a model. Ecosystems 4:29–48CrossRefGoogle Scholar
  27. Peterson ME, Curtin D, Thomas S, Clough TJ, Meenken ED (2013) Denitrfication in vadoze zone material amended with dissolved organic matter from topsoil and subsoil. Soil Biol Biochem 61:96–104CrossRefGoogle Scholar
  28. Qualls RG (2005) Biodegradability of fractions of dissolved organic carbon leached from decomposing leaf litter. Environ Sci Technol 39:1616–1622PubMedCrossRefGoogle Scholar
  29. Qualls RG, Haines BL, Swank WT (1991) Fluxes of dissolved organic nutrients and humic substances in a deciduous forest. Ecology 72:254–266CrossRefGoogle Scholar
  30. Rousk J, Jones DL (2010) Loss of low molecular weight dissolved organic carbon (DOC) and nitrogen (DON) in H2O and 0.5 M K2SO4 soil extracts. Soil Biol Biochem 42:2331–2335CrossRefGoogle Scholar
  31. Sanderman J, Baldock JA, Amundson R (2008) Dissolved organic carbon chemistry and dynamics in contrasting forest and grassland soils. Biogeochemistry 89:181–198CrossRefGoogle Scholar
  32. Sjöberg G, Bergkvist B, Berggren D, Nilsson SI (2003) Long-term N addition effects on the C mineralization and DOC production in mor humus under spruce. Soil Biol Biochem 35:1305–1315CrossRefGoogle Scholar
  33. Smolander A, Kitunen V (2002) Soil microbial activities and characteristics of dissolved organic C and N in relation to tree species. Soil Biol Biochem 4:651–660CrossRefGoogle Scholar
  34. Smolander A, Kitunen V (2011) Comparison of tree species effects on microbial C and N transformations and dissolved organic matter properties in the organic layer of boreal forests. Appl Soil Ecol 49:224–233CrossRefGoogle Scholar
  35. Smolander A, Loponen J, Suominen K, Kitunen V (2005) Organic matter characteristics and C and N transformations in the humus layer under two tree species, Betula pendula and Picea abies. Soil Biol Biochem 37:1309–1318CrossRefGoogle Scholar
  36. Uselman SM, Qualls RG, Lilienfein J (2012) Quality of soluble organic C, N, and P produced by different types and species of litter: Root litter versus leaf litter. Soil Biol Biochem 54:57–67CrossRefGoogle Scholar
  37. van Hees PAW, Jones DL, Finlay R, Godbold DL, Lundström US (2005) The carbon we do not see-the impact of low molecular weight compounds on carbon dynamics and respiration in forest soils: a review. Soil Biol Biochem 37:1–13CrossRefGoogle Scholar
  38. Wang X, Cammeraat LH, Wang Z, Zhou J, Govers G, Kalbitz K (2013) Stability of organic matter in soils of the Belgian Loess Belt upon erosion and deposition. Eur J Soil Sci 64:219–228CrossRefGoogle Scholar
  39. Wickland KP, Neff J, Aiken GR (2007) Dissolved organic carbon in Alaskan boreal forest: sources, chemical characteristics, and biodegradability. Ecosystems 10:1323–1340CrossRefGoogle Scholar
  40. Wieder WR, Cleveland C, Townsend AR (2008) Tropical tree species composition affects the oxidation of dissolved organic matter from litter. Biogeochemistry 88:127–138CrossRefGoogle Scholar
  41. Zhao M, Zhou J, Kalbitz K (2008) Carbon mineralization and properties of water extractable carbon in soils of the south Loess Plateau in China. Eur J Soil Biol 44:158–165CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Oili Kiikkilä
    • 1
  • Sanna Kanerva
    • 1
    • 2
  • Veikko Kitunen
    • 1
  • Aino Smolander
    • 1
  1. 1.Finnish Forest Research InstituteVantaaFinland
  2. 2.Department of Food and Environmental SciencesUniversity of HelsinkiHelsinkiFinland

Personalised recommendations