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Effect of elevated CO2 on soil N dynamics in a temperate grassland soil
Soil Biology & Biochemistry 41 (2009) 1996–2001
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Effect of elevated CO2 on soil N dynamics in a temperate grassland soil Christoph Mu¨ller a, b, *, Tobias Ru¨tting c, M. Kaleem Abbasi b, d, Ronald J. Laughlin e, Claudia Kammann a, b, Tim J. Clough f, Robert R. Sherlock f, Jens Kattge g, Hans-Ju¨rgen Ja¨ger b, Catherine J. Watson e, R. James Stevens e a
School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland Department of Plant Ecology, Justus-Liebig University Giessen, Heinrich-Buff-Ring 26, 35392 Giessen, Germany c Department of Plant and Environmental Sciences, University of Gothenburg, Box 461, 405 30 Gothenburg, Sweden d Faculty of Agriculture, University of Azad Jammu & Kashmir, Rawalakot, Azad Jammu & Kashmir, Pakistan e Agriculture, Food and Environmental Science Division, Agri-Food and Biosciences Institute, Newforge Lane, Belfast BT9 5PX, Northern Ireland f Agriculture & Life Sciences Division, Lincoln University, PO Box 84, Canterbury, New Zealand g ¨ ll-Str. 10, 07745 Jena, Germany Max-Planck Institute for Biogeochemistry, Hans-Kno b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 December 2008 Received in revised form 29 June 2009 Accepted 2 July 2009 Available online 16 July 2009
The response of terrestrial ecosystems to elevated atmospheric CO2 is related to the availability of other nutrients and in particular to nitrogen (N). Here we present results on soil N transformation dynamics from a N-limited temperate grassland that had been under Free Air CO2 Enrichment (FACE) for six years. A 15N labelling laboratory study (i.e. in absence of plant N uptake) was carried out to identify the effect of elevated CO2 on gross soil N transformations. The simultaneous gross N transformation rates in the soil were analyzed with a 15N tracing model which considered mineralization of two soil organic matter (SOM) pools, included nitrification from NHþ 4 and from organic-N to NO3 and analysed the rate of þ dissimilatory NO 3 reduction to NH4 (DNRA). Results indicate that the mineralization of labile organic-N became more important under elevated CO2. At the same time the gross rate of NHþ 4 immobilization increased by 20%, while NHþ 4 oxidation to NO3 was reduced by 25% under elevated CO2. The NO3 dynamics under elevated CO2 were characterized by a 52% increase in NO immobilization and a 141% 3 increase in the DNRA rate, while NO 3 production via heterotrophic nitrification was reduced to almost þ zero. The increased turnover of the NH4 pool, combined with the increased DNRA rate provided an indication that the available N in the grassland soil may gradually shift towards NHþ 4 under elevated CO2. The advantage of such a shift is that NHþ 4 is less prone to N losses, which may increase the N retention and N use efficiency in the grassland ecosystem under elevated CO2. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: Elevated CO2 15 N tracing Model Progressive N limitation Gross N transformation Temperate grassland
1. Introduction Increasing levels of atmospheric CO2 potentially increase photosynthesis and plant growth. However, the long-term ecosystem response to elevated CO2 also depends on the availability of other nutrients, in particular nitrogen (N) (Hungate et al., 2003). Enhanced inputs of labile carbon (C) under elevated CO2 via root exudation and increased fine root turnover may increase the microbial N demand resulting in increased competition between plants and soil microorganisms for available N. This may lead to a progressive N limitation (PNL) in ecosystems (Luo et al., 2004).
* Corresponding author. School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland. Tel.: þ353 1 7167781; fax: þ353 1 7161102. E-mail address: [email protected] (C. Mu¨ller). 0038-0717/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2009.07.003
The PNL hypothesis is supported by Free Air Carbon dioxide Enrichment (FACE) studies that have considered the effects of various N treatments (Schneider et al., 2004). Progressive N limitation may be alleviated by an increased efficiency of N uptake (van Groenigen et al., 2006), by a tightening of the internal N cycle (Hu et al., 2006), or by an enhanced rate of mineralization of soil organic matter (SOM) to ammonium (NHþ 4 ). Ammonium is further oxidized to nitrate (NO 3 ) or immediately consumed by plants and microorganisms. The temporal dynamics of the soil mineral N pools are controlled by the simultaneous occurrence of both production and consumption of NHþ 4 and NO3 . Meta-analyses have revealed that elevated CO2 leads to a general stimulation of microbial N immobilization rates (van Groenigen et al., 2006) which in turn may cause a decrease in NHþ 4 oxidation rates (Hungate et al., 1997). The van Groenigen et al. (2006) meta-analysis also showed that total N mineralization is more or less unaffected by elevated CO2. However, this analysis does not take into account the effect of elevated CO2 on
¨ ller et al. / Soil Biology & Biochemistry 41 (2009) 1996–2001 C. Mu
the mineralization of different SOM fractions in soil. An overall nonresponsiveness can also be achieved by a differential increase/ decrease in mineralization rates of various SOM fractions. Wedin and Pastor (1993) showed that models considering at least two SOM pools with different turnover characteristics are adequate to describe N mineralization dynamics under grass monocultures. A change in the mineralization dynamics of a small SOM fraction may have a large effect on the overall N dynamics in the soil (Wedin and ˇ eiro et al., 2006). The production and consumption Pastor, 1993; Pin of NHþ 4 and NO3 and their change under elevated CO2 will ultimately affect the potential availability of mineral N for plant uptake, as well as the production of gaseous N. Positive feedback effects of elevated CO2 on nitrous oxide (N2O) emissions have been observed in long-term N2O emission measurements from the current study site and may off-set a potential increase in C sequestration under elevated CO2 (Kammann et al., 2008). Denitrification may be stimulated by increasing C supply and enhanced anaerobicity due to increased microbial activity and/or water use efficiency under elevated CO2. However, decreasing NO 3 concentrations as a result of increasing NO 3 consumption would lower the potential for N2O production in soil. Indicators for enhanced anaerobicity which may increase the potential for N2O production are processes such as þ dissimilatory NO 3 reduction to NH4 (DNRA), which are limited to strict anoxic conditions in soil (Tiedje, 1988). The advantage of using DNRA as an indicator is that it can be evaluated with 15N tracing experiments that take into account the dynamics of NHþ 4 15 and NO N enrichments (Mu¨ller et al., 2004). To 3 and their quantify the simultaneous gross N transformations we performed a 15N tracing experiment and analysed the data with a 15N tracing model. The main advantage of 15N tracing models over the commonly used dilution technique (Stark, 2000) is that processspecific N rates such as pool specific mineralization, autotrophic and heterotrophic pathways of nitrification or DNRA can be identified simultaneously (Ru¨tting and Mu¨ller, 2007). 2. Materials and methods 2.1. Site description and experimental setup The study was carried out with grassland soil from the Giessen Free Air Carbon dioxide Enrichment (GiFACE) experiment (50 320 N and 8 41.30 E; 172 m a.s.l.) near Giessen, Germany. The soil is classified as a Fluvic Gleysol and has a sandy clay loam texture over a clay layer, with a mean C and N content of 4.5% and 0.45%, respectively and a pH of 6.2. At the time of soil sampling the grassland had been under elevated atmospheric CO2 concentrations for more than 6 years. Soil was taken from the FACE treatment that received þ30% of ambient CO2 all-year-round (Ja¨ger et al., 2003) and from the corresponding ambient control, i.e. from the same plots used by Denef et al. (2007) in a 13C pulse labelling study. The soil was collected from the top 0–10 cm, sieved (<5 mm, care was taken to keep the root fragments and associated fungi in the soil) and mixed. Soil was incubated in jars (WeckÓ, 200 g fresh soil jar1, separate jars for each extraction time) with three repetitions per CO2 treatment (taken from the mixed soil). The soil water content was adjusted to 0.40 g H2O g1 dry soil and incubated for 24 h at 20 C prior to 15N tracer addition. There were two NH4NO3 treatments for each CO2 level where either ammonium (15NH4NO3) or nitrate (NH15 4 NO3) were labelled with 15N at 60 atom% excess. The 15N label was applied evenly in solution (10.5 ml) at a rate of 7.14 mmol N g1 fresh soil 1 as NO (3.57 mmol g1 as NHþ 4 -N and 3.57 mmol g 3 -N). Soil was extracted 24 h before the addition of the 15N label (control) and at 1.5, 25.5, 48.9, 96.1, 215.9 and 335.6 h after 15N application. Initial concentrations and 15N enrichments of NHþ 4 and NO3 were determined by back extrapolation to 0 h (Mu¨ller et al., 2004).
1997
2.2. Determination of mineral N concentration, 15N enrichment and soil respiration All of the soil in each jar was extracted by the blending procedure of Stevens and Laughlin (1995). Ammonium-N and nitrate-N concentrations were analysed using a Technicon continuous flow autoanalyser (Bran & Luebb Co., Germany). The 15N contents of NO 3 and NHþ 4 in the extracts were determined by methods based on their conversion to N2O (Stevens and Laughlin, 1994; Laughlin et al., 1997). Soil respiration was quantified by closing the jars with a lid for periods of 0.5–2 h. Gas samples were taken with a needle via a septum in the lid at time 0 and at the end of the incubation, with 60 ml disposable syringes. Concentrations of CO2 were analysed on a gas chromatograph (Perkin Elmer Inc.) equipped with an electron capture detector (Mosier and Mack, 1980). 2.3.
15
N tracing model
To quantify the simultaneously occurring gross N transformations in soil a process based 15N tracing model was used (Fig. 1) (Mu¨ller et al., 2007). The model considered eight gross N transformations: MNrec, mineralization of recalcitrant organic-N to þ NHþ 4 ; MNlab, mineralization of labile organic-N to NH4 ; INH4 , þ immobilization of NH4 to labile organic-N; RNH4 ads , release of þ adsorbed NHþ 4 ; ONH4 , oxidation of NH4 to NO3 ; ONrec, oxidation of recalcitrant organic-N to NO 3 (heterotrophic nitrification); INO3 , immobilization of NO 3 to recalcitrant organic-N and DNO3 , dissimþ ilatory NO 3 reduction to NH4 . The transformation rates were calculated either by zero- or first-order kinetics (Table 1). The model calculated gross N transformation rates by simultaneously optimizing the kinetic parameters for the various N transformations by minimizing the misfit between modelled and observed (mean standard deviations) NHþ 4 and NO3 concentra15 tions and their respective N enrichments (Mu¨ller et al., 2004). A unique parameter set was optimized for the entire duration of the study. Analyses using this parameter optimization concept in previous studies have shown that the mineralization of two conceptual organic-N pools produced realistic NHþ 4 dynamics (e.g. Mu¨ller et al., 2004; Cookson et al., 2006; Huygens et al., 2007). Parameter optimization was carried out with a Markov chain Monte Carlo Metropolis algorithm (MCMC-MA) which performs a random walk in model parameter space and is very robust against local minima (Mu¨ller et al., 2007). The misfit function between the simulation output and observations, f(m), (see eqt. 3 in Mu¨ller et al., 2007) takes into account the variance of the individual observations. Thus, the uncertainties in the experimental data are taken into account for parameter quantification and can have an impact on the standard deviation of each parameter (Ru¨tting and Mu¨ller, 2007). The optimization procedure samples the probability density
Nlab
Nrec MNlab MNrec
INO3 ONrec
INH4
NH4+ RNH4a
ONH4
NO3-
DNO3
NH4+ads Fig. 1. 15N tracing model to analyze gross soil N transformation rates. Abbreviations are explained in the text and in Table 1.
¨ ller et al. / Soil Biology & Biochemistry 41 (2009) 1996–2001 C. Mu
1998
Table 1 Description of model parameters and optimized values (mean and standard deviations) of a temperate grassland soil (GiFACE study) under ambient and after 6 years of elevated atmospheric CO2. Transformation
MNrec MNlab INH4 INO3 ONH4 ONrec RNH4 ads DNO3 a
Kineticsa
Description
Mineralization of Nrec to NHþ 4 Mineralization of Nlab to NHþ 4 þ Immobilization of NH4 to Nlab Immobilization of NO 3 to Nrec Oxidation of NHþ 4 to NO3 Oxidation of Nrec to NO 3 þ Release of adsorbed NHþ 4 to NH4 Dissimilatory NO reduction to NHþ 3 4
0 1 1 0 0 0 1 0
Parameter values Ambient mean ( 102)
Ambient SD ( 104)
Elevated mean ( 102)
Elevated SD ( 104)
1.25 0.08 6.33 0.21 0.86 0.02 1.41 0.08
2.80 0.65 22.17 1.45 1.35 0.58 8.37 0.22
1.29 0.09 5.93 0.31 0.64 0.00 1.66 0.19
3.09 0.73 17.23 2.19 0.98 0.02 10.32 0.39
Kinetics: 0 ¼ zero order [mmol g1 h1], 1 ¼ first order [h1].
the experimental period, divided by the total time (Ru¨tting and Mu¨ller, 2007). Due to the high number of iterations of the 15N tracing model, statistical tests are inappropriate for the comparison of parameter results (Yoccoz, 1991). We analysed parameter results based on the comparisons of standard deviations and the 95% confidence intervals to distinguish three cases: a) standard deviations overlap: the parameters are not different, b) standard deviations do not overlap but 95% confidence intervals overlap: parameters are not significantly different but show a clear tendency to be different, c) 95% confidence intervals do not overlap: parameters are significantly different. Any other statistical calculations (ANOVA) were carried out with SigmaPlot-SigmaStat 9.01
function (PDF) of parameters, from which parameter averages and standard deviations are calculated. The MCMC-MA routine is programmed in the software MatLab (Version 7.2, The MathWorks Inc.), which calls models that are separately set up in Simulink (Version 6.4, The MathWorks Inc.). A description of all model parameters, the kinetic settings and the parameter values after optimization are presented in Table 1. 2.4. Calculation procedures and statistics For N transformations following first-order kinetics, average gross N rates were calculated by integrating the gross N rates over
-1
b
5 mod obs Ambient CO 2 Elevated CO2
1.5
3 2
0.5
1
c
15
50
0
d NH4NO3 - label
50 40
30
30
20
20
10
10
0
0
e
f
50
50
40
40
30
30
NH415NO3 - label
20
20
10
10
0
0 0
100
200
300
0
100
200
15
40
Nitrate [ N atom% excess]
15
4
1.0
0.0
Ammonium [ N atom% excess]
6
Nitrate [µmol N g-1]
Ammonium [µmol N g ]
a 2.0
300
Time after labelling [h] Fig. 2. Measured and modelled concentrations and concentrations (GiFACE study).
15
N enrichments of ammonium-N and nitrate-N in a permanent grassland soil under ambient and after 6 years of elevated CO2
¨ ller et al. / Soil Biology & Biochemistry 41 (2009) 1996–2001 C. Mu
-1
3. Results 3.1. NHþ 4 and NO3 concentrations
Ammonium-N concentrations decreased within 240 h to background concentrations in both CO2 treatments (Fig. 2a). The NHþ 4 concentrations under elevated CO2 were on average 17% higher (1.6 mmol N g1) than under ambient CO2 (P < 0.001) (Fig. 2a). Nitrate concentrations increased over the course of the experiment in both CO2 treatments. However, at the end of the experimental period (336 h) NO 3 concentrations in the elevated CO2 treatment were more than 1.3 mmol N g1 lower than under ambient CO2 (P < 0.001) (Fig. 2b). The 15N enrichments of NHþ 4 and NO3 were not significantly different between elevated and ambient CO2 treatments. The only significant difference in 15N enrichment between the two CO2 treatments, was in the enrichment of the NHþ 4 pool when NO 3 was labelled (P < 0.001, Fig. 2e), which was higher under elevated CO2. There was good agreement between modelled and observed data (Fig. 2) 3.2. Effect of elevated CO2 on
NHþ 4
dynamics
The total gross N mineralization rate (MNrec þ MNlab) was slightly but not significantly higher under elevated CO2 (Table 2). However, pool specific mineralization rates showed different responses to CO2. Mineralization of recalcitrant organic-N (MNrec) was not significantly affected by elevated CO2 while mineralization of labile organic-N (MNlab) increased by 25% (standard deviations did not overlap) (Table 2). Overall, the contribution from the labile organicN turnover to total gross N mineralization increased from 24 to 28%. Gross NHþ 4 production and consumption increased non-significantly by 8.7% and 7.1%, respectively (standard deviations did not overlap) so that the net NHþ 4 production (production – consumption) and the size of the NHþ 4 pool showed only a small but significant effect due to elevated CO2 (Fig. 2a). However, the specific NHþ 4 consumption þ processes, NHþ 4 immobilization and NH4 oxidation showed significant responses to elevated CO2. Ammonium immobilization increased significantly by 20% and NHþ 4 oxidation decreased significantly by 25% under elevated CO2 (Table 2). 3.3. Effect of elevated CO2 on NO 3 dynamics A significant 27% decrease in total NO 3 production together with a significant 77% increase in NO 3 consumption resulted in Table 2 Gross N transformation rates in a permanent grassland soil under ambient and after 6 years of elevated atmospheric CO2 concentrations (GiFACE study). The gross N transformation rates are presented as averages standard deviations. Ambient CO2
Elevated CO2
Gross N transformation rates (mmol N g1 soil d1) MNrec MNlab INH4 INO3 ONH4 ONrec RNH4 ads DNO3 a b c
20
Carbon dioxide (µg CO2-C g soil)
(Systat Inc.). A t-test was used to compare the cumulative CO2 emissions from the two CO2 treatments.
0.3006 0.0064 0.0971 0.0790 0.5176 0.0178 0.0493 0.0036 0.2056 0.0036 0.0050 0.0014 0.1813 0.0107 0.0193 0.0007
No overlap of 95% confidence intervals. No overlap of standard deviations. Overlap of standard deviations.
0.3099 0.0071c 0.1214 0.0100b 0.6211 0.0178a 0.0750 0.0500a 0.1535 0.0021a 0.0000 0.0000a 0.1728 0.0107c 0.0464 0.0007a
1999
18 Ambient CO2
16
Elevated CO2
14 12 10 8 6 4 2 0 0
100
200
300
Time after start of experiment [h] Fig. 3. Cumulative CO2 emissions under ambient and after 6 years of elevated atmospheric CO2 concentrations (GiFACE study). Data are presented as averages standard deviations.
lower NO 3 concentrations under elevated CO2 (P < 0.001) (Fig. 2b). þ Both NO 3 production processes (oxidation of NH4 , ONH4 and oxidation of organic-N, ONrec) decreased significantly under elevated CO2, while NO 3 immobilization (INO3 ) and DNRA (DNO3 ) increased significantly under elevated CO2 by 52% and 141% respectively (Table 2). 3.4. Effect of elevated CO2 on soil respiration Cumulative CO2 emissions from soil at the end of the incubation were 19% higher under elevated CO2 compared to ambient CO2 (P < 0.001, Fig. 3). 4. Discussion 4.1. Ammonium dynamics under elevated CO2 The lack of any CO2 treatment effect on total gross N mineralization (MNrec þ MNlab, Table 2) agrees with previous observations from other FACE studies (Hungate et al., 1997; Zak et al., 2000; Niklaus et al., 2003; Richter et al., 2003; Pepper et al., 2005; van Groenigen et al., 2006). However, the total gross NHþ 4 production rate in soil is governed by the mineralization dynamics of the various organic-N pools as well as the dynamics of other processes that produce NHþ 4 in soil (e.g. DNRA, cation exchange processes with clay minerals). In particular the dynamics of labile soil organic-N may govern the overall mineralization dynamics and the ˇ eiro et al., 2006). We confirmed this by built-up of NHþ 4 in soil (Pin showing that the mineralization rate of labile SOM (MNlab) increased while the mineralization rate of recalcitrant SOM (MNrec) was not significantly affected by elevated CO2. Wedin and Pastor (1993) have previously shown that labile SOM is important for the N supply in grassland while recalcitrant SOM is predominantly responsible for long-term storage. They concluded from their study that through the influence of plants a shift in mineralization rate from a small SOM pool may be enough to yield a large effect on the overall soil N dynamics. Overall the higher NHþ 4 concentration observed in the soil under elevated CO2 was the result of the interactive effects of NHþ 4 production and consumption processes. A higher net NHþ 4 production was also observed in situ at the GiFACE site (Kammann et al., 2008). The enhanced NHþ 4 immobilization under elevated CO2 was possibly driven by an increasing microbial
2000
¨ ller et al. / Soil Biology & Biochemistry 41 (2009) 1996–2001 C. Mu
demand for N. The increase in soil respiration under elevated CO2 in this study (Fig. 3) indicates that the microbial activity was enhanced under elevated CO2 and may have driven the increase in N consumption. An enhanced microbial activity may be the result of an increase in organic C in the rhizosphere, as observed for this grassland soil under field conditions (Kammann et al., 2008). The combination of a higher NHþ 4 supply together with an increase in NHþ 4 consumption provides a mechanism for a higher þ turnover of NHþ 4 with a small but significant impact on the NH4 pool size (Fig. 2a). The advantage of a faster cycling speed is that the N uptake of various N demanding processes (e.g. plant uptake, microbial uptake) is less constrained by the N supply and more dependent on the interactive effects of the various N demanding processes. Under field conditions, plants are able to out-compete microbes for the available N (Schimel and Bennett, 2004). However, if more mineral N is available for potential N uptake via an increased mineralization activity of labile soil organic matter, both microbes and plants may benefit (Wedin and Pastor, 1993). It is not primarily the size of the readily available N pool but rather how quickly this N pool is replenished, which determines the availability of N for plants and microbes in N-limited ecosystems (Rastetter et al., 1997). The higher NHþ 4 immobilization rate under elevated CO2 may have caused an increased competition for available NHþ 4 and thus led to a decline in NHþ 4 oxidation (Hungate et al., 1997). 4.2. Nitrate dynamics under elevated CO2 Oxidation of NHþ 4 is a key process for ecosystem N availability (Schimel and Bennett, 2004), thus, a decline in that gross rate, if not compensated for by other NO 3 producing processes, might limit NO 3 availability and may be an indicator of PNL. Both the rate of NHþ 4 oxidation and organic-N oxidation declined under elevated CO2, while at the same time the NO 3 consumption increased. This highlights two aspects, 1) NO 3 consumption was not directly related to NO 3 production and 2) the microbial N demand was higher than that supplied to microbes by enhanced NHþ 4 immobilization (Mary et al., 1998). Furthermore, 28 and 38% of the total NO 3 consumption was related to DNRA under ambient and elevated CO2, respectively. The soil water content under field conditions was not different between ambient and elevated CO2 plots (Kammann et al., 2005). Thus the increase in microbial activity in soil under elevated CO2 and associated O2 consumption (Fig. 3) may have promoted anoxic conditions and stimulated processes that operate under anaerobic conditions. Increased NO 3 consumption via DNRA under elevated CO2 indicates that elevated CO2 supports a shift of the available N towards NHþ 4 which is a typical feature of N-limited ecosystems to ¨ tting et al., avoid N losses (i.e. NO 3 leaching, gaseous N losses) (Ru 2008). The increasing importance of NHþ 4 over NO3 under elevated CO2 can increase the efficiency with which N is cycled in the system and is in line with studies that show a preferential NHþ 4 plant uptake under elevated CO2 (Hungate et al., 1996). 4.3. Microbial N dynamics under elevated CO2 The different N dynamics under the two CO2 regimes probably reflects a difference in the structure and activity of the soil microbial community that has developed over the 6 years of elevated CO2 in the field. In the presence of plant uptake we would expect that the demand for available N would increase. The mechanisms we identified in this study, an increase in N turnover and increased immobilization activity, all point to a system that is better adapted to an increased competition for the available N. A generally higher microbial activity would be expected under elevated CO2 which is supported by enhanced soil respiratory fluxes (Fig. 3). The adjustment of the internal N cycle under elevated CO2 may be driven by
plants via their close association with mycorrhizal fungi which are known for their efficiency in N uptake and their involvement in SOM mineralization (Talbot et al., 2008). A 13C pulse labelling study and subsequent 13C-PLFA analysis on the same field plots from where soil was taken in the current study revealed that fungi are the most active organisms for C turnover in this soil, particularly under elevated CO2 (Denef et al., 2007). Thus the changes in the observed N dynamics under elevated CO2 may have been at least partly related to changes in the metabolic activity of fungi. This is supported by a recent 15N tracing study on a similar grassland where it was shown that mineralization of labile SOM, NHþ 4 þ oxidation and heterotrophic oxidation to NO 3 as well as NH4 immobilization were all predominantly related to fungal activity (Laughlin et al., 2008). Also, the more than 2-fold increase in N2O emissions under elevated CO2 on the same grassland site, may be related to a shift in the N transformation dynamics and associated microbial communities under elevated CO2 (Kammann et al., 2008). 5. Conclusions Based on our results we conclude that soil N dynamics are likely to change under elevated CO2. The turnover of the NHþ 4 pool is likely to play an increasingly important role for the ecosystem N supply under elevated CO2. In particular, the response of the mineralization-immobilization turnover (MIT) in the soil will most likely determine if and how rapidly ecosystems will experience a progressive N limitation. Further research is needed to elucidate the microbial community dynamics (in particular the activity of bacteria and fungi) that are responsible for the observed shift in the soil N dynamics under elevated CO2. Acknowledgement M. K. Abbasi is grateful to the Alexander von Humboldt foundation for financial support throughout his study. T. Ru¨tting is currently funded by the NitroEurope IP under the EC 6th Framework Programme (Contract No. 017841).
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Ru¨tting, T., Huygens, D., Mu¨ller, C., van Cleemput, O., Godoy, R., Boeckx, P., 2008. Functional role of DNRA and nitrite reduction in a pristine south Chilean Nothofagus forest. Biogeochemistry 90, 243–258. Schimel, J.P., Bennett, J., 2004. Nitrogen mineralization: challenges of a changing paradigm. Ecology 85, 591–602. Schneider, M.K., Lu¨scher, A., Richter, M., Aeschlimann, U., Hartwig, U., Blum, H., Frossard, E., No¨sberger, J., 2004. Ten years of free-air CO2 enrichment altered the mobilization of N from soil in Lolium perenne L. swards. Global Change Biology 10, 1377–1388. Stark, J.M., 2000. Nutrient transformations. In: Sala, O.E., Jackson, R.B., Mooney, H.A., Howarth, R.W. (Eds.), Methods in Ecosystem Science. Springer, New York, pp. 215–234. Stevens, R.J., Laughlin, R.J., 1994. Determining nitrogen-15 nitrite or nitrate by producing nitrous oxide. Soil Science Society of America Journal 58, 1108–1116. Stevens, R.J., Laughlin, R.J., 1995. Nitrite transformations during soil extraction with potassium chloride. Soil Science Society of America Journal 59, 933–938. Talbot, J.M., Allison, S.D., Treseder, K.K., 2008. Decomposers in disguise: mycorrhizal fungi as regulators of soil C dynamics in ecosystems under global change. Functional Ecology 22, 955–963. Tiedje, J.M., 1988. Ecology of denitrification and dissimilatory nitrate reduction to ammonium. In: Zehnder, A.J.B. (Ed.), Biology of Anaerobic Microorganisms. John Wiley & Sons, New York, pp. 179–244. van Groenigen, K.-J., De Graaff, M.-A., Six, J., Harris, D., Kuikman, P., Van Kessel, C., 2006. The impact of elevated atmospheric [CO 2] on soil C and N dyanamics: a meta-analysis. In: No¨ sberger, J., Long, S.P., Norby, R.J., Stitt, M., Hendrey, G.R., Blum, H. (Eds.), Managed ecosystems and CO2 case studies, processes, and perspectives, Vol. 187. Springer, Berlin-Heidelberg, pp. 373–391. Wedin, D.A., Pastor, J., 1993. Nitrogen mineralization dynamics in grass monocultures. Oecologia 96, 186–192. Yoccoz, N.G., 1991. Use, overuse, and misuse of significance tests in evolutionary biology and ecology. Bulletin of the Ecological Society of America 72, 106–111. Zak, D.R., Pregitzer, K.S., King, J.S., Holmes, W.E., 2000. Elevated atmospheric CO2, fine roots and the response of soil microorganisms: a review and hypothesis. New Phytologist 147, 201–222.
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Effect of elevated CO2 on soil N dynamics in a temperate grassland soil Christoph Mu¨ller a, b, *, Tobias Ru¨tting c, M. Kaleem Abbasi b, d, Ronald J. Laughlin e, Claudia Kammann a, b, Tim J. Clough f, Robert R. Sherlock f, Jens Kattge g, Hans-Ju¨rgen Ja¨ger b, Catherine J. Watson e, R. James Stevens e a
School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland Department of Plant Ecology, Justus-Liebig University Giessen, Heinrich-Buff-Ring 26, 35392 Giessen, Germany c Department of Plant and Environmental Sciences, University of Gothenburg, Box 461, 405 30 Gothenburg, Sweden d Faculty of Agriculture, University of Azad Jammu & Kashmir, Rawalakot, Azad Jammu & Kashmir, Pakistan e Agriculture, Food and Environmental Science Division, Agri-Food and Biosciences Institute, Newforge Lane, Belfast BT9 5PX, Northern Ireland f Agriculture & Life Sciences Division, Lincoln University, PO Box 84, Canterbury, New Zealand g ¨ ll-Str. 10, 07745 Jena, Germany Max-Planck Institute for Biogeochemistry, Hans-Kno b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 December 2008 Received in revised form 29 June 2009 Accepted 2 July 2009 Available online 16 July 2009
The response of terrestrial ecosystems to elevated atmospheric CO2 is related to the availability of other nutrients and in particular to nitrogen (N). Here we present results on soil N transformation dynamics from a N-limited temperate grassland that had been under Free Air CO2 Enrichment (FACE) for six years. A 15N labelling laboratory study (i.e. in absence of plant N uptake) was carried out to identify the effect of elevated CO2 on gross soil N transformations. The simultaneous gross N transformation rates in the soil were analyzed with a 15N tracing model which considered mineralization of two soil organic matter (SOM) pools, included nitrification from NHþ 4 and from organic-N to NO3 and analysed the rate of þ dissimilatory NO 3 reduction to NH4 (DNRA). Results indicate that the mineralization of labile organic-N became more important under elevated CO2. At the same time the gross rate of NHþ 4 immobilization increased by 20%, while NHþ 4 oxidation to NO3 was reduced by 25% under elevated CO2. The NO3 dynamics under elevated CO2 were characterized by a 52% increase in NO immobilization and a 141% 3 increase in the DNRA rate, while NO 3 production via heterotrophic nitrification was reduced to almost þ zero. The increased turnover of the NH4 pool, combined with the increased DNRA rate provided an indication that the available N in the grassland soil may gradually shift towards NHþ 4 under elevated CO2. The advantage of such a shift is that NHþ 4 is less prone to N losses, which may increase the N retention and N use efficiency in the grassland ecosystem under elevated CO2. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: Elevated CO2 15 N tracing Model Progressive N limitation Gross N transformation Temperate grassland
1. Introduction Increasing levels of atmospheric CO2 potentially increase photosynthesis and plant growth. However, the long-term ecosystem response to elevated CO2 also depends on the availability of other nutrients, in particular nitrogen (N) (Hungate et al., 2003). Enhanced inputs of labile carbon (C) under elevated CO2 via root exudation and increased fine root turnover may increase the microbial N demand resulting in increased competition between plants and soil microorganisms for available N. This may lead to a progressive N limitation (PNL) in ecosystems (Luo et al., 2004).
* Corresponding author. School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland. Tel.: þ353 1 7167781; fax: þ353 1 7161102. E-mail address: [email protected] (C. Mu¨ller). 0038-0717/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.soilbio.2009.07.003
The PNL hypothesis is supported by Free Air Carbon dioxide Enrichment (FACE) studies that have considered the effects of various N treatments (Schneider et al., 2004). Progressive N limitation may be alleviated by an increased efficiency of N uptake (van Groenigen et al., 2006), by a tightening of the internal N cycle (Hu et al., 2006), or by an enhanced rate of mineralization of soil organic matter (SOM) to ammonium (NHþ 4 ). Ammonium is further oxidized to nitrate (NO 3 ) or immediately consumed by plants and microorganisms. The temporal dynamics of the soil mineral N pools are controlled by the simultaneous occurrence of both production and consumption of NHþ 4 and NO3 . Meta-analyses have revealed that elevated CO2 leads to a general stimulation of microbial N immobilization rates (van Groenigen et al., 2006) which in turn may cause a decrease in NHþ 4 oxidation rates (Hungate et al., 1997). The van Groenigen et al. (2006) meta-analysis also showed that total N mineralization is more or less unaffected by elevated CO2. However, this analysis does not take into account the effect of elevated CO2 on
¨ ller et al. / Soil Biology & Biochemistry 41 (2009) 1996–2001 C. Mu
the mineralization of different SOM fractions in soil. An overall nonresponsiveness can also be achieved by a differential increase/ decrease in mineralization rates of various SOM fractions. Wedin and Pastor (1993) showed that models considering at least two SOM pools with different turnover characteristics are adequate to describe N mineralization dynamics under grass monocultures. A change in the mineralization dynamics of a small SOM fraction may have a large effect on the overall N dynamics in the soil (Wedin and ˇ eiro et al., 2006). The production and consumption Pastor, 1993; Pin of NHþ 4 and NO3 and their change under elevated CO2 will ultimately affect the potential availability of mineral N for plant uptake, as well as the production of gaseous N. Positive feedback effects of elevated CO2 on nitrous oxide (N2O) emissions have been observed in long-term N2O emission measurements from the current study site and may off-set a potential increase in C sequestration under elevated CO2 (Kammann et al., 2008). Denitrification may be stimulated by increasing C supply and enhanced anaerobicity due to increased microbial activity and/or water use efficiency under elevated CO2. However, decreasing NO 3 concentrations as a result of increasing NO 3 consumption would lower the potential for N2O production in soil. Indicators for enhanced anaerobicity which may increase the potential for N2O production are processes such as þ dissimilatory NO 3 reduction to NH4 (DNRA), which are limited to strict anoxic conditions in soil (Tiedje, 1988). The advantage of using DNRA as an indicator is that it can be evaluated with 15N tracing experiments that take into account the dynamics of NHþ 4 15 and NO N enrichments (Mu¨ller et al., 2004). To 3 and their quantify the simultaneous gross N transformations we performed a 15N tracing experiment and analysed the data with a 15N tracing model. The main advantage of 15N tracing models over the commonly used dilution technique (Stark, 2000) is that processspecific N rates such as pool specific mineralization, autotrophic and heterotrophic pathways of nitrification or DNRA can be identified simultaneously (Ru¨tting and Mu¨ller, 2007). 2. Materials and methods 2.1. Site description and experimental setup The study was carried out with grassland soil from the Giessen Free Air Carbon dioxide Enrichment (GiFACE) experiment (50 320 N and 8 41.30 E; 172 m a.s.l.) near Giessen, Germany. The soil is classified as a Fluvic Gleysol and has a sandy clay loam texture over a clay layer, with a mean C and N content of 4.5% and 0.45%, respectively and a pH of 6.2. At the time of soil sampling the grassland had been under elevated atmospheric CO2 concentrations for more than 6 years. Soil was taken from the FACE treatment that received þ30% of ambient CO2 all-year-round (Ja¨ger et al., 2003) and from the corresponding ambient control, i.e. from the same plots used by Denef et al. (2007) in a 13C pulse labelling study. The soil was collected from the top 0–10 cm, sieved (<5 mm, care was taken to keep the root fragments and associated fungi in the soil) and mixed. Soil was incubated in jars (WeckÓ, 200 g fresh soil jar1, separate jars for each extraction time) with three repetitions per CO2 treatment (taken from the mixed soil). The soil water content was adjusted to 0.40 g H2O g1 dry soil and incubated for 24 h at 20 C prior to 15N tracer addition. There were two NH4NO3 treatments for each CO2 level where either ammonium (15NH4NO3) or nitrate (NH15 4 NO3) were labelled with 15N at 60 atom% excess. The 15N label was applied evenly in solution (10.5 ml) at a rate of 7.14 mmol N g1 fresh soil 1 as NO (3.57 mmol g1 as NHþ 4 -N and 3.57 mmol g 3 -N). Soil was extracted 24 h before the addition of the 15N label (control) and at 1.5, 25.5, 48.9, 96.1, 215.9 and 335.6 h after 15N application. Initial concentrations and 15N enrichments of NHþ 4 and NO3 were determined by back extrapolation to 0 h (Mu¨ller et al., 2004).
1997
2.2. Determination of mineral N concentration, 15N enrichment and soil respiration All of the soil in each jar was extracted by the blending procedure of Stevens and Laughlin (1995). Ammonium-N and nitrate-N concentrations were analysed using a Technicon continuous flow autoanalyser (Bran & Luebb Co., Germany). The 15N contents of NO 3 and NHþ 4 in the extracts were determined by methods based on their conversion to N2O (Stevens and Laughlin, 1994; Laughlin et al., 1997). Soil respiration was quantified by closing the jars with a lid for periods of 0.5–2 h. Gas samples were taken with a needle via a septum in the lid at time 0 and at the end of the incubation, with 60 ml disposable syringes. Concentrations of CO2 were analysed on a gas chromatograph (Perkin Elmer Inc.) equipped with an electron capture detector (Mosier and Mack, 1980). 2.3.
15
N tracing model
To quantify the simultaneously occurring gross N transformations in soil a process based 15N tracing model was used (Fig. 1) (Mu¨ller et al., 2007). The model considered eight gross N transformations: MNrec, mineralization of recalcitrant organic-N to þ NHþ 4 ; MNlab, mineralization of labile organic-N to NH4 ; INH4 , þ immobilization of NH4 to labile organic-N; RNH4 ads , release of þ adsorbed NHþ 4 ; ONH4 , oxidation of NH4 to NO3 ; ONrec, oxidation of recalcitrant organic-N to NO 3 (heterotrophic nitrification); INO3 , immobilization of NO 3 to recalcitrant organic-N and DNO3 , dissimþ ilatory NO 3 reduction to NH4 . The transformation rates were calculated either by zero- or first-order kinetics (Table 1). The model calculated gross N transformation rates by simultaneously optimizing the kinetic parameters for the various N transformations by minimizing the misfit between modelled and observed (mean standard deviations) NHþ 4 and NO3 concentra15 tions and their respective N enrichments (Mu¨ller et al., 2004). A unique parameter set was optimized for the entire duration of the study. Analyses using this parameter optimization concept in previous studies have shown that the mineralization of two conceptual organic-N pools produced realistic NHþ 4 dynamics (e.g. Mu¨ller et al., 2004; Cookson et al., 2006; Huygens et al., 2007). Parameter optimization was carried out with a Markov chain Monte Carlo Metropolis algorithm (MCMC-MA) which performs a random walk in model parameter space and is very robust against local minima (Mu¨ller et al., 2007). The misfit function between the simulation output and observations, f(m), (see eqt. 3 in Mu¨ller et al., 2007) takes into account the variance of the individual observations. Thus, the uncertainties in the experimental data are taken into account for parameter quantification and can have an impact on the standard deviation of each parameter (Ru¨tting and Mu¨ller, 2007). The optimization procedure samples the probability density
Nlab
Nrec MNlab MNrec
INO3 ONrec
INH4
NH4+ RNH4a
ONH4
NO3-
DNO3
NH4+ads Fig. 1. 15N tracing model to analyze gross soil N transformation rates. Abbreviations are explained in the text and in Table 1.
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1998
Table 1 Description of model parameters and optimized values (mean and standard deviations) of a temperate grassland soil (GiFACE study) under ambient and after 6 years of elevated atmospheric CO2. Transformation
MNrec MNlab INH4 INO3 ONH4 ONrec RNH4 ads DNO3 a
Kineticsa
Description
Mineralization of Nrec to NHþ 4 Mineralization of Nlab to NHþ 4 þ Immobilization of NH4 to Nlab Immobilization of NO 3 to Nrec Oxidation of NHþ 4 to NO3 Oxidation of Nrec to NO 3 þ Release of adsorbed NHþ 4 to NH4 Dissimilatory NO reduction to NHþ 3 4
0 1 1 0 0 0 1 0
Parameter values Ambient mean ( 102)
Ambient SD ( 104)
Elevated mean ( 102)
Elevated SD ( 104)
1.25 0.08 6.33 0.21 0.86 0.02 1.41 0.08
2.80 0.65 22.17 1.45 1.35 0.58 8.37 0.22
1.29 0.09 5.93 0.31 0.64 0.00 1.66 0.19
3.09 0.73 17.23 2.19 0.98 0.02 10.32 0.39
Kinetics: 0 ¼ zero order [mmol g1 h1], 1 ¼ first order [h1].
the experimental period, divided by the total time (Ru¨tting and Mu¨ller, 2007). Due to the high number of iterations of the 15N tracing model, statistical tests are inappropriate for the comparison of parameter results (Yoccoz, 1991). We analysed parameter results based on the comparisons of standard deviations and the 95% confidence intervals to distinguish three cases: a) standard deviations overlap: the parameters are not different, b) standard deviations do not overlap but 95% confidence intervals overlap: parameters are not significantly different but show a clear tendency to be different, c) 95% confidence intervals do not overlap: parameters are significantly different. Any other statistical calculations (ANOVA) were carried out with SigmaPlot-SigmaStat 9.01
function (PDF) of parameters, from which parameter averages and standard deviations are calculated. The MCMC-MA routine is programmed in the software MatLab (Version 7.2, The MathWorks Inc.), which calls models that are separately set up in Simulink (Version 6.4, The MathWorks Inc.). A description of all model parameters, the kinetic settings and the parameter values after optimization are presented in Table 1. 2.4. Calculation procedures and statistics For N transformations following first-order kinetics, average gross N rates were calculated by integrating the gross N rates over
-1
b
5 mod obs Ambient CO 2 Elevated CO2
1.5
3 2
0.5
1
c
15
50
0
d NH4NO3 - label
50 40
30
30
20
20
10
10
0
0
e
f
50
50
40
40
30
30
NH415NO3 - label
20
20
10
10
0
0 0
100
200
300
0
100
200
15
40
Nitrate [ N atom% excess]
15
4
1.0
0.0
Ammonium [ N atom% excess]
6
Nitrate [µmol N g-1]
Ammonium [µmol N g ]
a 2.0
300
Time after labelling [h] Fig. 2. Measured and modelled concentrations and concentrations (GiFACE study).
15
N enrichments of ammonium-N and nitrate-N in a permanent grassland soil under ambient and after 6 years of elevated CO2
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-1
3. Results 3.1. NHþ 4 and NO3 concentrations
Ammonium-N concentrations decreased within 240 h to background concentrations in both CO2 treatments (Fig. 2a). The NHþ 4 concentrations under elevated CO2 were on average 17% higher (1.6 mmol N g1) than under ambient CO2 (P < 0.001) (Fig. 2a). Nitrate concentrations increased over the course of the experiment in both CO2 treatments. However, at the end of the experimental period (336 h) NO 3 concentrations in the elevated CO2 treatment were more than 1.3 mmol N g1 lower than under ambient CO2 (P < 0.001) (Fig. 2b). The 15N enrichments of NHþ 4 and NO3 were not significantly different between elevated and ambient CO2 treatments. The only significant difference in 15N enrichment between the two CO2 treatments, was in the enrichment of the NHþ 4 pool when NO 3 was labelled (P < 0.001, Fig. 2e), which was higher under elevated CO2. There was good agreement between modelled and observed data (Fig. 2) 3.2. Effect of elevated CO2 on
NHþ 4
dynamics
The total gross N mineralization rate (MNrec þ MNlab) was slightly but not significantly higher under elevated CO2 (Table 2). However, pool specific mineralization rates showed different responses to CO2. Mineralization of recalcitrant organic-N (MNrec) was not significantly affected by elevated CO2 while mineralization of labile organic-N (MNlab) increased by 25% (standard deviations did not overlap) (Table 2). Overall, the contribution from the labile organicN turnover to total gross N mineralization increased from 24 to 28%. Gross NHþ 4 production and consumption increased non-significantly by 8.7% and 7.1%, respectively (standard deviations did not overlap) so that the net NHþ 4 production (production – consumption) and the size of the NHþ 4 pool showed only a small but significant effect due to elevated CO2 (Fig. 2a). However, the specific NHþ 4 consumption þ processes, NHþ 4 immobilization and NH4 oxidation showed significant responses to elevated CO2. Ammonium immobilization increased significantly by 20% and NHþ 4 oxidation decreased significantly by 25% under elevated CO2 (Table 2). 3.3. Effect of elevated CO2 on NO 3 dynamics A significant 27% decrease in total NO 3 production together with a significant 77% increase in NO 3 consumption resulted in Table 2 Gross N transformation rates in a permanent grassland soil under ambient and after 6 years of elevated atmospheric CO2 concentrations (GiFACE study). The gross N transformation rates are presented as averages standard deviations. Ambient CO2
Elevated CO2
Gross N transformation rates (mmol N g1 soil d1) MNrec MNlab INH4 INO3 ONH4 ONrec RNH4 ads DNO3 a b c
20
Carbon dioxide (µg CO2-C g soil)
(Systat Inc.). A t-test was used to compare the cumulative CO2 emissions from the two CO2 treatments.
0.3006 0.0064 0.0971 0.0790 0.5176 0.0178 0.0493 0.0036 0.2056 0.0036 0.0050 0.0014 0.1813 0.0107 0.0193 0.0007
No overlap of 95% confidence intervals. No overlap of standard deviations. Overlap of standard deviations.
0.3099 0.0071c 0.1214 0.0100b 0.6211 0.0178a 0.0750 0.0500a 0.1535 0.0021a 0.0000 0.0000a 0.1728 0.0107c 0.0464 0.0007a
1999
18 Ambient CO2
16
Elevated CO2
14 12 10 8 6 4 2 0 0
100
200
300
Time after start of experiment [h] Fig. 3. Cumulative CO2 emissions under ambient and after 6 years of elevated atmospheric CO2 concentrations (GiFACE study). Data are presented as averages standard deviations.
lower NO 3 concentrations under elevated CO2 (P < 0.001) (Fig. 2b). þ Both NO 3 production processes (oxidation of NH4 , ONH4 and oxidation of organic-N, ONrec) decreased significantly under elevated CO2, while NO 3 immobilization (INO3 ) and DNRA (DNO3 ) increased significantly under elevated CO2 by 52% and 141% respectively (Table 2). 3.4. Effect of elevated CO2 on soil respiration Cumulative CO2 emissions from soil at the end of the incubation were 19% higher under elevated CO2 compared to ambient CO2 (P < 0.001, Fig. 3). 4. Discussion 4.1. Ammonium dynamics under elevated CO2 The lack of any CO2 treatment effect on total gross N mineralization (MNrec þ MNlab, Table 2) agrees with previous observations from other FACE studies (Hungate et al., 1997; Zak et al., 2000; Niklaus et al., 2003; Richter et al., 2003; Pepper et al., 2005; van Groenigen et al., 2006). However, the total gross NHþ 4 production rate in soil is governed by the mineralization dynamics of the various organic-N pools as well as the dynamics of other processes that produce NHþ 4 in soil (e.g. DNRA, cation exchange processes with clay minerals). In particular the dynamics of labile soil organic-N may govern the overall mineralization dynamics and the ˇ eiro et al., 2006). We confirmed this by built-up of NHþ 4 in soil (Pin showing that the mineralization rate of labile SOM (MNlab) increased while the mineralization rate of recalcitrant SOM (MNrec) was not significantly affected by elevated CO2. Wedin and Pastor (1993) have previously shown that labile SOM is important for the N supply in grassland while recalcitrant SOM is predominantly responsible for long-term storage. They concluded from their study that through the influence of plants a shift in mineralization rate from a small SOM pool may be enough to yield a large effect on the overall soil N dynamics. Overall the higher NHþ 4 concentration observed in the soil under elevated CO2 was the result of the interactive effects of NHþ 4 production and consumption processes. A higher net NHþ 4 production was also observed in situ at the GiFACE site (Kammann et al., 2008). The enhanced NHþ 4 immobilization under elevated CO2 was possibly driven by an increasing microbial
2000
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demand for N. The increase in soil respiration under elevated CO2 in this study (Fig. 3) indicates that the microbial activity was enhanced under elevated CO2 and may have driven the increase in N consumption. An enhanced microbial activity may be the result of an increase in organic C in the rhizosphere, as observed for this grassland soil under field conditions (Kammann et al., 2008). The combination of a higher NHþ 4 supply together with an increase in NHþ 4 consumption provides a mechanism for a higher þ turnover of NHþ 4 with a small but significant impact on the NH4 pool size (Fig. 2a). The advantage of a faster cycling speed is that the N uptake of various N demanding processes (e.g. plant uptake, microbial uptake) is less constrained by the N supply and more dependent on the interactive effects of the various N demanding processes. Under field conditions, plants are able to out-compete microbes for the available N (Schimel and Bennett, 2004). However, if more mineral N is available for potential N uptake via an increased mineralization activity of labile soil organic matter, both microbes and plants may benefit (Wedin and Pastor, 1993). It is not primarily the size of the readily available N pool but rather how quickly this N pool is replenished, which determines the availability of N for plants and microbes in N-limited ecosystems (Rastetter et al., 1997). The higher NHþ 4 immobilization rate under elevated CO2 may have caused an increased competition for available NHþ 4 and thus led to a decline in NHþ 4 oxidation (Hungate et al., 1997). 4.2. Nitrate dynamics under elevated CO2 Oxidation of NHþ 4 is a key process for ecosystem N availability (Schimel and Bennett, 2004), thus, a decline in that gross rate, if not compensated for by other NO 3 producing processes, might limit NO 3 availability and may be an indicator of PNL. Both the rate of NHþ 4 oxidation and organic-N oxidation declined under elevated CO2, while at the same time the NO 3 consumption increased. This highlights two aspects, 1) NO 3 consumption was not directly related to NO 3 production and 2) the microbial N demand was higher than that supplied to microbes by enhanced NHþ 4 immobilization (Mary et al., 1998). Furthermore, 28 and 38% of the total NO 3 consumption was related to DNRA under ambient and elevated CO2, respectively. The soil water content under field conditions was not different between ambient and elevated CO2 plots (Kammann et al., 2005). Thus the increase in microbial activity in soil under elevated CO2 and associated O2 consumption (Fig. 3) may have promoted anoxic conditions and stimulated processes that operate under anaerobic conditions. Increased NO 3 consumption via DNRA under elevated CO2 indicates that elevated CO2 supports a shift of the available N towards NHþ 4 which is a typical feature of N-limited ecosystems to ¨ tting et al., avoid N losses (i.e. NO 3 leaching, gaseous N losses) (Ru 2008). The increasing importance of NHþ 4 over NO3 under elevated CO2 can increase the efficiency with which N is cycled in the system and is in line with studies that show a preferential NHþ 4 plant uptake under elevated CO2 (Hungate et al., 1996). 4.3. Microbial N dynamics under elevated CO2 The different N dynamics under the two CO2 regimes probably reflects a difference in the structure and activity of the soil microbial community that has developed over the 6 years of elevated CO2 in the field. In the presence of plant uptake we would expect that the demand for available N would increase. The mechanisms we identified in this study, an increase in N turnover and increased immobilization activity, all point to a system that is better adapted to an increased competition for the available N. A generally higher microbial activity would be expected under elevated CO2 which is supported by enhanced soil respiratory fluxes (Fig. 3). The adjustment of the internal N cycle under elevated CO2 may be driven by
plants via their close association with mycorrhizal fungi which are known for their efficiency in N uptake and their involvement in SOM mineralization (Talbot et al., 2008). A 13C pulse labelling study and subsequent 13C-PLFA analysis on the same field plots from where soil was taken in the current study revealed that fungi are the most active organisms for C turnover in this soil, particularly under elevated CO2 (Denef et al., 2007). Thus the changes in the observed N dynamics under elevated CO2 may have been at least partly related to changes in the metabolic activity of fungi. This is supported by a recent 15N tracing study on a similar grassland where it was shown that mineralization of labile SOM, NHþ 4 þ oxidation and heterotrophic oxidation to NO 3 as well as NH4 immobilization were all predominantly related to fungal activity (Laughlin et al., 2008). Also, the more than 2-fold increase in N2O emissions under elevated CO2 on the same grassland site, may be related to a shift in the N transformation dynamics and associated microbial communities under elevated CO2 (Kammann et al., 2008). 5. Conclusions Based on our results we conclude that soil N dynamics are likely to change under elevated CO2. The turnover of the NHþ 4 pool is likely to play an increasingly important role for the ecosystem N supply under elevated CO2. In particular, the response of the mineralization-immobilization turnover (MIT) in the soil will most likely determine if and how rapidly ecosystems will experience a progressive N limitation. Further research is needed to elucidate the microbial community dynamics (in particular the activity of bacteria and fungi) that are responsible for the observed shift in the soil N dynamics under elevated CO2. Acknowledgement M. K. Abbasi is grateful to the Alexander von Humboldt foundation for financial support throughout his study. T. Ru¨tting is currently funded by the NitroEurope IP under the EC 6th Framework Programme (Contract No. 017841).
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