Reimo Kindler

Jan Siemens
email: jan.siemens@uni-bonn.de

Klaus Kaiser

David Christopher Walmsley

Christian Bernhofer

Nina Buchmann

Pierre Cellier

Werner Eugster

Gerd Gleixner

Thomas Grünwald

Alexander Heim

Andreas Ibrom

Stephanie K Jones

Mike Jones

Katja Klumpp

Werner Kutsch

Klaus Steenberg Larsen

Simon Lehuger

Benjamin Loubet

Mckenzie

Eddy Moors

Bruce Osborne

Kim Pilegaard

Corinna Rebmann

Michael Wi Schmidt

Marion Schrumpf

Janine Seyfferth

Ute Skiba

Francois Soussana

Mark A Sutton

Cindy Tefs

Bernhard Vowinckel

Matthias J 12 Zeeman

Martin Kaupenjohann

Johann Heinrich

Claire Campbell

Jan Elbers

Wilma Jans

Ottmar Joos

Patricia Laville

Christine Krenkewitz

Dissolved carbon leaching from soil is a crucial component of the net ecosystem carbon balance

Keywords: carbon sequestration, carbon cycle, net biome productivity, net ecosystem exchange, methane, dissolved inorganic carbon, dissolved organic carbon dissolved organic carbon, DOC, dissolved inorganic carbon, DIC, methane, CH 4, 53 net biome productivity, net ecosystem exchange, carbon cycle, carbon sequestration

Uptake and release of CO 2 by terrestrial ecosystems are crucial modulators of the climate 77 system (e.g., [START_REF] Heimann | Terrestrial ecosystem dynamics and climate feedbacks[END_REF]. Reliable estimates of net ecosystem carbon 78 balances [START_REF] Chapin | Reconciling carbon-cycle concepts, terminology, and methods[END_REF] are therefore fundamental to our understanding of global 79 climate change and the development of appropriate mitigation strategies. Net ecosystem 80 carbon balances can be determined by assessing changes in ecosystem carbon stocks over 81 time (e.g., [START_REF] Liski | Increasing carbon stocks in the forest soils of 786 Western Europe[END_REF]Sleutel et al., 2003). This approach is associated with large 82 uncertainties, because annual changes are small compared to stock size, because of error 83 propagation of measurements, spatial heterogeneity within ecosystems, and temporal or 84 spatial extrapolation. A possible strategy to validate large-scale estimates of net ecosystem 85 carbon balances is to compare them with independent estimates of carbon uptake derived 86 from inverse modelling of CO 2 transport in the atmosphere [START_REF] Janssens | Europe's 763 biosphere absorbs 7 to 12% of European anthropogenic carbon emissions[END_REF]Schulze et 87 al., 2009). Such comparisons are hampered by the differing and uncertain system boundaries 88 and the differing types of carbon fluxes measured. Atmosphere-based estimates of carbon 89 uptake rates are often larger than increases in ecosystem carbon stocks because part of the 90 carbon is exported in plant products (e.g. wood, grains, or forage), lost to the atmosphere in 91 volatile organic forms, or leached in soluble forms [START_REF] Janssens | Europe's 763 biosphere absorbs 7 to 12% of European anthropogenic carbon emissions[END_REF][START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF]. 92 93 Siemens (2003) hypothesized that the leaching of dissolved inorganic and organic carbon 94 from soils can explain a large part of the difference between atmosphere-and land-based 95 estimates of the carbon uptake of European terrestrial ecosystems. Similarly, Ritchey et al. 96 (2002), Cole et al. (2007), and [START_REF] Battin | The 711 boundless carbon cycle[END_REF] argued that consideration of inland waters 97 as components of terrestrial carbon budgets is necessary to assess the carbon cycle at the 98 landscape scale. In line with these views, current estimates of carbon balances of European 99 terrestrial ecosystems assume an average loss of 7 g C m -2 yr -1 with drainage, based on 100 measurements of riverine fluxes [START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF]. Linking riverine carbon fluxes to those integrate over a number of transformation processes in aquifers and surface waters, they often 103 also average carbon fluxes from various land use systems within a particular catchment. Thus, 104 better data on leaching from soils could considerably improve estimates of carbon budgets of 105 terrestrial ecosystems. Such data are also essential to further assess the active processing of 106 land-borne carbon in aquifers and inland waters (Cole et al., 2007;[START_REF] Battin | The 711 boundless carbon cycle[END_REF].

107 108
There is evidence that carbon leaching from terrestrial ecosystems varies systematically with 109 land use. [START_REF] Brye | Nitrogen and carbon leaching in 713 agroecosystems and their role in denitrification potential[END_REF] reported a more than five-fold increase in dissolved carbon 110 leaching during four years after the conversion of native tall-grass prairie to maize cultivation 111 with fertilization and ploughing. [START_REF] Parfitt | Soil and solution chemistry under 794 pasture and radiata pine in New Zealand[END_REF] found losses of dissolved inorganic 112 carbon (DIC) of 14.7 g m -2 yr -1 from pasture and 0.7 g m -2 yr -1 from a pine forest under 113 similar climatic conditions, but a reduction in soil pH(H 2 O) from 5.6-5.9 under pasture to 114 5.3-5.5 under pine as a result of more intense acidification in the forest. Leaching of 115 dissolved organic carbon (DOC) seems to be affected by ploughing and crop type (Vinther et 116 al., 2006). A better understanding of land use effects on dissolved carbon leaching is 117 important because i) net ecosystem carbon balances are often grouped according to land use 118 classes (e.g., cropland, grassland, forest;[START_REF] Janssens | Europe's 763 biosphere absorbs 7 to 12% of European anthropogenic carbon emissions[END_REF] and ii) trends in riverine 119 dissolved carbon fluxes seem to be related to land use (e.g., [START_REF] Raymond | Increase in the export of alkalinity from America´s largest river[END_REF].

120 121
Carbon is dissolved in water not only as DOC and DIC but also as dissolved methane (CH 4 ).

122

Despite its high global warming potential, dissolved CH 4 is commonly not included in 123 measurements of dissolved carbon concentrations and has only been investigated in a small 124 number of studies. For the Brocky Burn moorland catchment in Scotland, CH 4 -C fluxes with 125 stream water were less than 0.04% of CO 2 -C fluxes (Dawson et al., 2004). Even when 126 considering a global warming potential factor of 25 for CH 4 (IPCC, 2007), its contribution to fluxes of CO 2 -C equivalents was smaller than 1%. Fiedler et al. (2006) found that CH 4 export 128 (in CO 2 -C equivalents) from a catchment in the Black Forest, Germany, was approximately 129 8% of the CO 2 export. The small contribution of CH 4 to overall carbon losses with stream 130 water or spring water is due its poor solubility in water (1.5 10 -5 mol l -1 kPa -1 at 20°C). positions (e.g., slope and hollow at Easter Bush). Suction cups and gas probes were installed 147 horizontally from a soil pit by inserting them into boreholes. Half the number of probes were 148 installed beneath the A horizon (at approximately 30 cm depth), the other half was installed as 149 deep as possible (65-120 cm depth; Table 1). Suction cups were connected to 2-liter glass 150 bottles in an insulated aluminium box placed into the soil pit. Soil water was extracted by 151 applying a vacuum of 40 kPa to the glass bottles after each sampling. In order to correctly 152 measure DIC, degassing of CO 2 was minimized by using a headspace-free sample collection 153 system similar to the one described by Suarez (1986). In this system, the soil water from the 154 suction cup first flows through a 20-ml gas-tight vial before entering the evacuated 2-l bottle In carbonate-free soils, respiratory CO 2 will react with silicates (e.g., feldspars) to form clay 193 minerals and bicarbonate, which in this case is solely from soil respiration (e.g., eq. [2];

194 Amiotte-Suchet et al., 1999). In these soils, the fraction of DIC from respiration should 195 therefore be close to 100%. Dissolved inorganic carbon concentrations beneath topsoils of forest sites (2.5-23.9 mg l -1 ; 312 mean: 8 mg l -1 , median: 4 mg l -1 ; Fig. 2a) tended to be smaller than those of cropland (22.7-313 50.5 mg l -1 ; mean: 35 mg l -1 , median: 33 mg l -1 ; Fig 2c, p = 0.09, Kruskal-Wallis test). No 314 significant differences were found between mean concentrations of forests and grasslands (6-315 70 mg l -1 ; mean: 28 mg l -1 , median: 17 mg l -1 ; Fig. 2b, p = 0.2, Kruskal-Wallis test). Also 316 subsoil water DIC concentrations tended to increase in the order forest (2.5-67.7 mg l -1 ; 317 mean: 34 mg l -1 , median: 33 mg l -1 ) < grassland (8.0-90.9 mg l -1 ; mean: 42 mg l -1 , median 34 318 mg l -1 ) < cropland (28.3-84.8 mg l -1 ; mean: 57 mg l -1 , median: 57 mg l -1 ), but these 319 differences were not statistically significant (Kruskal-Wallis test). Dissolved inorganic carbon arable fields (median: 14 mg l -1 , mean: 12 mg l -1 , range: 3.9-17.3 mg l -1 , Fig 2c) tended to be 342 smaller than those leached from forest topsoils (median: 24 mg l -1 , mean: 23 mg l -1 ; range: 343 7.1-43.1 mg l -1 , Fig. 2a), but the differences were not statistically significant (p = 0.16, 344 Kruskal Wallis test). A close positive relationship was observed between DOC concentrations 345 at shallow sampling depths and topsoil C/N ratios (Fig. 4).

346 347

Differences between average subsoil DOC concentrations were rather small between the 348 different land use systems: 11 mg l -1 for forests (median: 13 mg l -1 ), 12 mg l -1 for arable 349 fields (median: 14 mg l -1 ), and 9 mg l -1 for grasslands (median: 8 mg l -1 ), with the latter value 350 being somewhat lower due to small DOC concentrations in the Laqueuille Andosol (Fig. 2b). Across all sites, an average of 4.2 g DOC m -2 yr -1 was leached from soils, with rather small 407 differences between land use systems (Table 3). Subtracting DOC leaching from subsoils 408 from DOC fluxes from topsoils indicated that as much as 17 (Wetzstein) to 20 g m -2 yr -1 409 (Loobos) of DOC was retained in acidic forest B horizons (Table 3). Other forest B horizons 410 retained only 2 (Laois) to 9 g DOC m -2 yr -1 (Sorø) and retention in the B horizons of 411 grasslands or arable fields was generally smaller than 5.5 g DOC m -2 yr -1 ( The errors in the estimates of leaching losses, indicated in brackets in tables 3-7, only reflect from the wet funnel surface and wind turbulence [START_REF] Richter | Ergebnisse methodischer Untersuchungen zur Korrektur des systematischen 807 Messfehlers des Hellmann-Niederschlagsmessers[END_REF]. Applying the empirical 462 correction of [START_REF] Richter | Ergebnisse methodischer Untersuchungen zur Korrektur des systematischen 807 Messfehlers des Hellmann-Niederschlagsmessers[END_REF] organic matter. Studies using δ 13 C or 14 C to track sources and turnover of DOC (Schiff et al., 517 1997;Flessa et al., 2000;[START_REF] Hagedorn | A 13 C tracer study to identify the origin of dissolved 751 organic carbon in forested mineral soils[END_REF]Fröberg et al., 2007) being related to the ratio of organic carbon to the sum of oxalate-extractable iron plus 535 aluminium (Fig. 7). Oxalate-extractable iron and aluminium are a measure of the 536 concentration of poorly crystalline iron and aluminium (hydr)oxides with a high specific 537 surface area in soils. These iron and aluminium(hydr)oxides are considered to be the most 538 important sorbents for dissolved organic matter in soils (e.g., [START_REF] Kaiser | Sorption of DOM and DOM fractions to forest 766 soils[END_REF]. The ratio of 539 organic carbon to the concentration of iron and aluminium (hydr)oxides in B horizons is 540 therefore an indicator of the saturation of the available sorption capacity of subsoils for the 541 DOC they receive from topsoils. Hence, the relationship presented in Fig. 7 In contrast to forests or grasslands, all studied croplands were net sources of carbon (Table 5).

595

Carbon losses with drainage were 24-105% of the sum of NEE plus fertilization minus 596 harvest (median: 25% Table 5). [START_REF] Kutsch | The net biome production of full crop rotations in Europe[END_REF] The estimates of [START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF] for average greenhouse gas balances of European land 607 use systems accounted for leaching losses of DOC and DIC by assuming a constant average 608 loss of 7 g C m -2 yr -1 for all land use systems, which is close to the losses of 5.9 g m -2 yr -1 609 reported by [START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF]. Both estimates are considerably smaller than the average (19.5 610 g m -2 yr -1 ) and the median (15.2 g m -2 yr -1 ) of leaching losses we found (Table 5). This Dissolved organic carbon leached from soil may partly be retained in the vadose zone before 621 reaching aquifers (Siemens & Kaupenjohann, 2003). Adsorption or precipitation of DOC may 622 slow down its biodegradation [START_REF] Mikutta | Biodegradation of forest 791 floor organic matter bound to minerals via different binding mechanisms[END_REF][START_REF] Kalbitz | Contribution of dissolved organic matter to carbon storage in 774 forest mineral soils[END_REF]Scheel et al., 623 2008), but the extent of stabilization under field conditions is uncertain (Guggenberger & 624 Kaiser, 2003;Siemens & Kaupenjohann, 2003). As a result of retention in the vadose zone, 625 DOC concentrations in groundwater are often smaller than 5 mg l -1 (e.g., Siemens & 626 Kaupenjohann, 2003). For the range of groundwater recharge of 95-652 mm yr -1 we found in 627 our study, these concentrations would lead to a small (<0.5-3.3 g DOC m -2 yr -1 ), albeit 628 constant flux of DOC into surface waters. Significant additional amounts of DOC reach 629 surface waters with runoff at or near the soil surface during storms (e.g., Hagedorn et al., 630 2000) or with drainage water from peatlands (e.g., Dawson et al., 2004). In lakes and rivers, 631 allochtonous dissolved organic matter will be partly processed by aquatic organisms and 632 finally mineralized to DIC (Tranvik, 1993;Tranvik & Bertilsson, 2001). et al., 2007) and to ~66% of the carbon European rivers receive from terrestrial 642 ecosystems [START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF]. Multiplication of these estimates with our mean carbon 643 leaching loss gives an evasion of 8-13 g C m -2 yr -1 and an evasion of 6-10 g C m -2 yr -1 when Table 1: Land use, soil characteristics, instrumentation, and temperature, of the investigated sites. Mean annual temperatures, mean annual precipitation, and mean drainage is given for the period of the observations of this study. 2007 and 2007/2008 (and 2008/2009 for Irish sites). The summer period started on 1 April and ended on 30 September. For Irish sites, the summer value is the average of summers 2007 and 2008, for all other sites it is the value for summer 2007.

Site

Loss from topsoils Loss from subsoils winter summer total winter summer total (g C m -2 ) (g C m -2 ) (g C m -2 yr -1 ) (g C m -2 ) (g C m -2 ) (g C m -2 yr -1 ) Hainich slope 1.3 (0.1) 0.7 (0.0) 2.0 (0.1) 2.6 (0.0) 0.0 (0.0) 2.6 (0.0) valley 1.8 (0.1) 1.4 (0.0) 3.2 (0.1) 1.9 (0.0) 0.0 (0.0) 1.9 (0.0) Sorø near tree 8.7 (0.3) 7.5 (0. 2007 and 2007/2008 (and 2008/2009 for Irish sites). The summer period started on 1 April and ended on 30 September. For Irish sites, the summer value is the average of summers 2007 and 2008, for all other sites it is the value for summer 2007.

Site

Loss from topsoils Loss from subsoils winter summer total winter summer total (g C m -2 ) (g C m -2 ) (g C m -2 yr -1 ) (g C m -2 ) (g C m -2 ) (g C m -2 yr -1 ) Hainich slope 1.5 (0.2) 0.6 (0.1) 2.1 (0.3) 9.1 (0.0) 0.4 (0.0) 9.4 (0.0) valley 2.5 (0.1) 1.2 (0.0) 3.6 (0.1) 5.9 (0.1) 0.4 (0.0) 6.2 (0.1) Sorø near tree 1.4 (0. Numbers in brackets indicate standard deviations due to spatial variability of concentrations for individual sites and the standard error of the average across sites with the same land use system or across all sites; the errors do not reflect uncertainties associated with the calculation of the biogenic fraction of DIC with the isotope method (see text); n.d.: not detectable; 1 excluding lateral runoff of 3.7 g DIC m -2 yr -1 (Walmsley, 2009). Topsoils reach down to the shallow instrumentation depth, subsoil reach down to the deeper instrumentation depth given in Table 1.

F o r R e v i e w

O n l y 43 Averages were calculated as the arithmetic mean of median concentrations of suction cups and suction plates over time. Topsoils reach down to the shallow depth of instrumentation given in Table 1. The lower value of the biogenic fraction was calculated using a δ 13 C of -28‰ for the biogenic end-member and a δ 13 C of 0‰ for carbonates. The upper value of the biogenic fraction was calculated using the δ 13 C of value of soil air CO 2 at the time of soil water collection and a δ 13 C of 0‰ for carbonates. Use of a δ 13 C of -5‰ for carbonate-C reduced the calculated biogenic fraction on average by 5% (biogenic end-member of -28‰).

(g C m -2 ) (g C m -2 ) (g C m -2 yr -1 ) (g C m -2 yr -1 ) (g C m -2 yr -1 ) (%) (g C m -2 yr -

  is difficult because measurements of riverine fluxes not only 102

  the present work was i) to determine leaching losses of DIC and DOC from soils 133 of typical European land use systems and to relate them to the respective net ecosystem 134 carbon balances and ii) to identify major factors controlling carbon leaching. In order to 135 achieve a full carbon perspective, determinations of DOC and DIC leaching losses were 136 complemented by analyses of CH 4 in soil air and soil water. cups with a pore size <1 µm for soil water collection (ecoTech, Bonn, 140 Germany) and eight Teflon suction cups (ecoTech, Bonn, Germany) for soil gas collection 141 were installed at each of twelve European sites under different land use (Table 1, Fig. 1). 142 Most of these sites were verification sites of the CarboEurope project (www.carboeurope.org) 143 and/or flux sites of the NitroEurope project (Skiba et al., 2009). The probes were divided into 144 two sets of 10 suction cups and 4 gas probes, which allowed for sampling of different 145 treatments (e.g., intensive and extensive grazing at Laqueuille) or different landscape 146

  155 via a cannulae, which penetrates the septum of the vials just deep enough to allow the outflow 156 of solution. At the Hainich and Wetzstein sites, soil water was additionally collected from two 157 glass suction plates installed at 20 cm depth. 158 159 Sample collection started at different dates. Here, we present and discuss data that span the 160 period from 1 October 2006 until 31 March 2008 at all sites except the Irish sites where soil 161 water sampling commenced until 31 March 2009. Fluxes were calculated separately for 162 summer (1 April until 30 September) and winter (1 October until 31 March).

  320 concentrations were insensitive to management intensity at Laqueuille (Fig. 2b) or topography 321 at Hainich, Sorø (Fig 2a), and Carlow grassland (Fig 2b). However, topography was important 322 at Easter Bush, with significantly larger concentrations at the bottom of the valley than at the 323 elevated position (Fig. 2b, shallow cups: p = 0.009; deep cups: p = 0.075, Mann-Whitney U-DIC can be calculated from the partial pressures of soil air CO 2 327and soil solution pH by applying Henry's law and assuming chemical equilibrium between 328 CO 2 in the gas phase and solution H 2 CO 3 equilibrium with partial pressures of soil air CO 2 for the Loobos, Wetzstein, 330 Hainich and Sorø forest sites (Fig.3). Soil waters from all other sites were supersaturated with 331 DIC relative to soil air CO 2 , especially in subsoils, which might be partly due to selective 332 sampling of CO 2 -poor soil air from larger pores. Overall, the measured DIC concentrations 333 were nearly equal to or greater than theoretical concentrations, indicating that outgassing of 334 soil water samples was successfully minimized by the sampling method. concentrations were commonly much larger than DOC 337 concentrations, particularly in subsoils (Fig.2). Exceptions were the acidic soils at the 338 Wetzstein and Loobos forest sites, with DIC representing less than 10% of the total dissolved 339 carbon leached from topsoils and 16-30% in subsoils. Concentrations of DOC leached from 340 topsoils of grasslands (median: 7 mg l -1 , mean: 8 mg l -1 ; range 1.9-17.1 mg l -1 , Fig2b) and 341

351 352

 351 Isotopic signature and sources of dissolved inorganic carbon353The δ 13 C signatures of DIC in samples collected from subsoils clustered into two groups.354 Samples from the Hainich, Sorø, Laois, and Carlow grassland were all characterized by δ 13 C 355 values close to -15‰, with little variation between different suction cups (Fig.5b). At 356 Früebüel, samples from eight suction cups were close to -15‰, while the sample from one 357 cup showed a value of -22‰ (Fig.5b

  443 the uncertainty caused by the spatial variation of DIC, DOC, and dissolved CH 4 444 concentrations. Additional uncertainties arise from the modelling of the water balance, the 445 spatial variation of water fluxes, and the calculation of the biogenic fraction of DIC from its 446 δ 13 C signature. 447 448 We assessed the uncertainty of evapotranspiration measurements using the eddy covariance 449 method by analyzing the energy balance of the Klingenberg site for the years 2006 and 2007 450 (Vowinckel, 2008). A regression between net radiation and the sum of sensible and latent heat 451 flux (assuming a negligible net soil heat flux over long-term periods) showed that 452 approximately 68% of the available energy was consumed by turbulent heat fluxes only. 453 Using the slope of this regression and monthly means of the Bowen ratio as well as the 454 available energy, measured latent heat fluxes were subsequently corrected. Monthly 455 correction factors ranged from 1.01 to 1.89 and averaged 1.66, which means an 456 underestimation of the eddy covariance-based evapotranspiration at the Klingenberg site 457 during our study period from October 2006 to March 2008 by approximately 182 mm. 458 459 This systematic underestimation of evapotranspiration is roughly compensated by a 460 systematic underestimation of precipitation by standard rainfall collectors due to evaporation 461

  associated with rapid runoff could not be calculated because 481 concentrations in that runoff were not assessed. According to[START_REF] Kaiser | Organically bound nutrients in dissolved organic 768 matter fractions in seepage and pore water of weakly developed forest soils[END_REF], leaching 482 losses of DOC from a shallow forest soil (Rendzic Leptosol) via preferential flow paths 483 during heavy rainstorms were similar to mean annual fluxes as determined for soil matrix 484 flow. This potential underestimation of DOC losses due to preferential flow and rapid runoff 485 of soil water might partly have been compensated for in our study by an overestimation of 486 DIC losses since DIC concentrations in soil water rapidly draining through large pores are 487 probably smaller than concentrations in water in slowly draining pores of the soil matrix. We 488 are not aware of any study that has analysed concentrations of DIC in preferential flow. Biogenic DIC concentrations are also subjected to an error associated with the determination 491 of the fraction of carbonate-borne DIC using the DIC δ 13 C signature. The largest source of 492 error is contamination or isotopic exchange of DIC with atmospheric air. Contamination and 493 isotopic exchange with atmospheric air would shift the measured δ 13 C values to less negative 494 values, leading to systematic underestimation of biogenic DIC concentrations. According to 495 the stoichiometry of carbonate dissolution, the fraction of biogenic DIC in soil water of 496 calcareous soils must exceed 50% and, of course, it should be smaller than 100%. This limits 497 the potential underestimation of biogenic DIC concentrations and fluxes from calcareous soils 498 to values of 18-31%. The potential overestimation of biogenic DIC concentrations resulting 499 from the assumption of an average δ 13 C value of 0‰ for carbonates was 1-11% (average 500 5%). Our results indicated greater isotopic exchange between DIC and atmospheric air for 501 samples from carbonate-free subsoils, especially for the acidic forest subsoils at Loobos and 502 Wetzstein. For these subsoils, however, the assumption of 100% biogenic DIC according to 503 the stoichiometry of weathering reactions is safe and the relevance of the small DIC 504 concentrations at these sites for total carbon leaching is limited. 505 506 Factors controlling dissolved carbon concentrations and leaching losses 507The positive correlation between soil C/N ratios and DOC concentrations and fluxes in 508 terrestrial ecosystems across biomes was first published by[START_REF] Aitkenhead | Soil C:N ratio as a predictor of annual riverine DOC 703 flux at local and global scales[END_REF].509In contrast to the observation of[START_REF] Aitkenhead | Soil C:N ratio as a predictor of annual riverine DOC 703 flux at local and global scales[END_REF], DOC concentrations and 510 fluxes in our study correlated only to topsoil C/N ratios (upper 5-40 cm, Table1) and not to 511 C/N ratios of the entire soils down to 65-100 cm depth. Due to the accumulation of organic 512 matter, topsoils and organic layers are regarded as the soil compartments that are the most 513 important for the generation of DOC (e.g.,Guggenberger & Kaiser, 2003). The topsoil C/N 514 ratio is indicative of the litter quality and the intensity of microbial transformation processes. 515 Large C/N ratios indicate poorly degradable litter and a slow transformation and recycling of 516

  611difference is related to the fact that the losses given by[START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF] and Schulze et al. 612 (2009) represent the carbon export with rivers to oceans because these studies aimed at the 613 carbon budget of the whole continent. In the studies of Ciais et al. (2008) and Schulze et al. 614 (2009), the riverine carbon export was divided by the area of the river catchments to derive an 615 average loss per m 2 , whereas our study directly measured leaching from the soil into 616 groundwater. A comparison of our results with the estimates of Ciais et al. (2008) and 617 Schulze et al. (2009) is therefore only possible when considering the downstream fate of 618 dissolved carbon after being leached from soil.

  . Subtraction of this evasion from surface waters from our dissolved carbon 645 flux from soils gives a flux of 5-12 g C m -2 yr -1 from the continent into the ocean. 646 647 A fraction of the carbon that is transferred from terrestrial ecosystems to inland waters is 648 buried in the sediments of lakes and reservoirs. Burial of carbon in the sediments of inland 649 waters has been estimated to equal 12% of inputs from land on a global scale (Cole et al., 650 2007) and 21% of the net ecosystem carbon transfer from European terrestrial ecosystems into 651 rivers[START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF]. Particulate organic matter washed into inland waters due to erosion 652 of soils certainly contributes to this burial of carbon in the sediments of lakes and reservoirs 653(Stallard, 1998). Since we did not include fluxes of organic matter with eroded soil material in 654 our study, the estimates of carbon burial ofCole et al. (2007) and[START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF] are 655 difficult to relate to the fluxes of dissolved carbon reported here. Assuming that all carbon 656 buried in the sediments of lakes and reservoirs derived from dissolved carbon indicates that 657 less than 2-4 g m -2 yr -1 of DOC and DIC leached from soils are probably stored in the 658 sediments of inland waters, which would reduce the carbon lost from soils that reaches the 659 ocean with rivers to 1-10 g C m -2 yr -1 , but this reduction is uncertain. Overall, the carbon 660 leaching losses reported here correspond to a riverine flux of DOC and biogenic DIC of 5.5 g 661 m -2 yr -1 reported for Europe by[START_REF] Ludwig | Atmospheric CO 2 788 consumption by continental erosion: present-day controls and implications for the last 789 glacial maximum[END_REF] and the river carbon fluxes of 5.9 and 662 7 g m -2 yr -1 given by[START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF] and[START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF], respectively, when 663 considering outgassing from inland waters and potential burial in sediments. 664 665Our set of research sites did not include sites from southern, northern, and eastern Europe. In 666 the study of[START_REF] Ciais | 722 The impact of lateral carbon fluxes on the European carbon balance[END_REF], the yield of river carbon fluxes reaching the continental shelf 667 was twice as large for southern Europe (<42° N; 10.8 g m -2 yr -1 ) than for temperate Europe 668 (42-50° N; 5.2 g m -2 yr -1 ). The rather good agreement of riverine carbon fluxes with carbon 669 leaching losses in our study when considering outgassing and sedimentation is probably due 670 effect of high C export from south European catchments on the overall export due 671 to their small area and small river discharge in relation to temperate and northern Europe. 672 673 In summary, leaching represents a comparatively small, but continuous loss of carbon from 674 terrestrial ecosystems. Considering these losses for ecosystem greenhouse gas balances is 675 increasingly important when long time periods are examined and net changes of biomass 676 stocks are small. Leaching losses are especially important to local and plot-scale studies, 677 because outgassing of carbon into the atmosphere from surface waters probably occurs 678 outside the boundaries of the studied systems. Leaching losses are particularly important for 679 the net ecosystem carbon balance of grasslands and croplands where dissolved carbon 680 leaching roughly equalled 25% of NEE plus fertilizer carbon minus harvested carbon. Topsoil 681 C/N ratio, the saturation of the subsoils sorption capacity for organic carbon, and its carbonate 682 content were important factors controlling the magnitude of carbon leaching losses.

Fig. 1 :Fig. 2 :Fig. 3 :Fig. 4 :

 1234 Figure captions

Fig. 5 :

 5 Fig.5: δ 13 C values (box plots and arithmetic mean as white dot) and the biogenic fraction of DIC (black triangles). The lower value of the biogenic fraction was calculated using a δ 13 C of

Fig. 6 :

 6 Fig. 6: Precipitation (a), evapotranspiration (b), measured and modeled soil water volumes (c,

Fig. 7 :

 7 Fig. 7: Retention of DOC in B horizons of soils related to the ratio of organic carbon (OC)

  13 C values of DIC were all below -20‰ at the Wetzstein, Laqueuille, Easter Bush and 362 Klingenberg sites (Fig.5b). Less negative values were found in the subsoil at the Loobos site.

	387	100% for calculating the total biogenic carbon leaching loss from the carbonate-free Loobos,
	388	Wetzstein, Laqueuille, Easter Bush, and Klingenberg soils.
	389
	390	Water balance of the research sites
	366 391	Mean annual precipitation during our study period ranged from 710 mm yr -1 at Grignon to
	367 392	1771 mm yr -1 at Früebüel with an average of 1009 mm yr -1 across all sites (Table 2). The
	368 393	Using a value of -28‰ for the biogenic end-member and a value of 0‰ for carbonate-C, a average loss of water by evapotranspiration equalled 436 mm yr -1 . The average relative
		F o r biogenic DIC fraction of 74-82% was calculated for the calcareous subsoils of the Hainich, r o F deviation of modelled soil water contents from measured ones was 14% for the shallow
		R R
		e v e v
		i e i e
		w w
	379 404	O n l O n l
	380 405	y members -28‰ and 0‰, were much lower than the expected 100%. This might be caused by y
	381 406	more intense isotopic exchange of soil air and DIC with atmospheric air. Indeed, when using Leaching losses of dissolved carbon
	382	measured δ 13 C values of soil air CO 2 in the calculation, the estimated biogenic fraction was
	383	>100% for the Klingenberg site. For the Lobos and Wetzstein sites, however, calculated
		biogenic fractions remained below 100%, which might indicate a contamination of the little
	386
	361
		18

). Soils at Hainich, Sorø, Laois, Carlow, and Früebüel 358 all developed from carbonate-containing parent materials, which is Muschelkalk limestone at 359 the Hainich site and glacial till at the other sites. Soils at the Loobos, Wetzstein, Laqueuille, 360 Easter Bush, and Klingenberg sites developed from carbonate-free parent material. Average

δ 363 In contrast to subsoil, dissolved inorganic carbon from shallow depths of the Sorø and 364 Früebüel sites had more negative δ 13 C values below -20‰, reflecting the dissolution of 365 carbonates in topsoils during soil development (Fig. 5a). 369 Sorø, Laois, and Früebüel sites and used to estimate leaching losses of total biogenic carbon 370 (Fig. 5b, upright triangles). The fraction was reduced by 1-11% if an extreme value of -5‰ 371 was assumed for carbonate-C. Use of the measured δ 13 C of soil air CO 2 increased the 372 calculated biogenic fraction for DIC from the calcareous subsoils to 90-105%. An extreme 373 value of 293% was calculated for the Früebüel site, but this unplausible value likely resulted 374 from a contamination of soil air samples with atmospheric air during the difficult abstraction 375 of air samples from the wet Früebüel soil. 376 377

Contrary to geochemical theory (eq. [2]), the biogenic DIC fractions calculated for the 378 carbonate-free subsoils at the Loobos, Wetzstein, and Klingenberg sites, using the end-384 DIC pool in the acidic samples from these sites with atmospheric CO 2 during sampling and 385 sample handling. In line with geochemical theory (Eq [2]), we used a biogenic DIC fraction of 394 depths and 6% for subsoils (Table

2

). Figure

6 (c, d

) provides a visual impression of the 395 goodness of fit between measured and modelled soil water contents for the Carlow grassland 396 site, where the quality of the model fit was exactly the average of all sites. 397 398 Especially at the sites with clayey soils (Hainich, Laois, and Früebüel), modelled water 399 contents could only be matched to measured ones when large volumes of water (357-489 mm 400 yr -1 ) were discharged by rapid runoff via surface flow or preferential flow paths in the 401 calibrated water balance model (Table

2

). On average 429 mm yr -1 of water were left over for 402 drainage from the soil profile after subtracting evapotranspiration and rapid runoff from 403 precipitation (Table

2

).

Table 3

 3 Retention of DOC in B horizons decreased exponentially with increasing ratio of organic 413 carbon to the sum of oxalate-extractable iron and aluminium present in the bulk soil (Fig.7). C eq m -2 yr -1 when applying a warming potential of 25 (Table6). Leaching of CH 4 was 438 therefore not relevant for the greenhouse gas budget of the investigated sites.

	412

). 421 dissolved carbon leaching from forest soils tended to be smaller than leaching from grasslands 422 or arable fields (Table

5

). Differences, however, were not significant (p = 0.23, Kruskal 423 Wallis test) because the variability between sites under similar land use was large. The overall 424 average biogenic dissolved carbon loss from soils was 19.3 g C m -2 yr -1 . This value was 425 strongly influenced by large losses from the forest at Sorø and the grasslands at Easter Bush 426 and Carlow. Consequently, the median flux across all sites was smaller (15.2 g C m -2 yr -1 ). 427 428 Methane concentrations in soil air and its leaching losses 429 Methane concentrations in soil air at shallow depths were mostly smaller than global average 430 atmospheric concentrations of 1.7 µl l -1 , indicating that most sites could have acted as sinks 431 for atmospheric CH 4 (Table

6

). Exceptions were the Laois and Klingenberg Stagnosols. In 432 subsoils, CH 4 concentrations larger than atmospheric ones were only found in the Laois 433 Stagnosol and the Easter Bush Gleyic Cambisol in the hollow terrain position. 434 435 Leaching losses of CH 4 were <5 mg CH 4 -C m -2 yr -1 at most sites. Even the largest loss of 26 436 ± 2 mg CH 4 -C m -2 yr -1 , measured at Klingenberg, was equivalent to a loss of only 0.23 g

  of the soil water model is the calculated rapid runoff. At Laois, the 467 relevance of lateral water flows could easily be deduced from the clayey soil texture and the

	466
	A major uncertainty 468
	469	occurrence of drainage ditches on the plot. Here, micro-catchments were constructed by
	470	separating areas of 10-12 m 2 by trenches and wooden boards in a way that lateral runoff
	471	could be collected in a down slope trench, so that modelled lateral flows could be matched to
	472	measured water volumes (Walsmley, 2010). No micro-catchments were available at Früebüel
		r o F and Hainich, which were also characterized by clayey soils and rapid runoff. For these sites,
		R
		e v
		i e
		w
		O n l
		y
	465
		22

to precipitation data of the Klingenberg site (assuming that 463 precipitation at temperatures <0°C occurs as snow) indicated an underestimation of the 464 rainfall by 216 mm.

473

the results of our water balance model were compared with results of the BLAU "bucket" 474 model of

[START_REF] Huwe | Ein einfaches Speicherzellenmodell zur Berechnung von Sickerung, 755 Verdunstung und Bodenwasservorratsänderung[END_REF]

, which was extended with a surface runoff routine. For Früebüel, the 475 results of the BLAU model deviated from the results in Table

2

by only 2% for surface/rapid 476 runoff (440 vs. 449 mm) and by 0.3% for drainage from the soil profile (944 vs. 941 mm). A 477 good agreement between results of the two models was also observed for the Hainich site; 478 rapid/surface runoff and drainage from the soil profile deviated by only 4%.

  Plot-scale balances of carbon fluxes of four forest sites in our study were not significantly 568 affected by carbon leaching (Table5). Only for the beech forest at Sorø, carbon leaching 569 equalled 25% of the balance of atmospheric CO 2 fluxes (Table5). Reasons for this large

	543 594	concept of a sorptive control on DOC output from mineral soils (e.g., Guggenberger &
	544	Kaiser, 2003) seems to apply for a wide range of soils and land use systems.
	545 570
	546 571	The close relationship between measured and calculated DIC concentrations leached from fraction are the comparably small NEE and high leaching losses of biogenic DIC due to the
	547 572	topsoils indicates that the partial pressure of CO 2 in soil air and the pH of soil solution control high pH of the calcareous subsoil. Neglecting leaching losses would lead to a substantial
	548 573	DIC concentrations (and fluxes), according to carbonate equilibrium. The almost constant overestimation of the net ecosystem carbon balance of the Sorø forest (+145 g C m -2 yr -1
	549 574	degree of supersaturation of soil waters with respect to equilibrium concentrations probably instead of +108 g C m -2 yr -1 , Table 5). For forest ecosystems, in particular, the temporal scale
	550 575	F o r reflects the diffusion gradient of CO 2 from microbial habitats through soil air into the atmosphere or the kinetic retardation of CO 2 outgassing from soil water into soil air. For F o r of balances is extremely important for estimating the magnitude of carbon sequestration. The forest ecosystem carbon balances in Table 5 cover only few years (<13 years) in relation to a F o r
		R R R
	555	e v e v e v
	556	i e atmospheric air during sampling or sample handling would probably also lead to an i e i e
	557	w underestimation of equilibrium DIC concentrations because CO 2 concentrations in soil air are w w
	558 559 560 583 584 585	O n l commonly much larger than atmospheric concentrations. We did not observe any relationship between the absolute or relative excess of measured O n l Grasslands strongly differed with regard to their balance of aboveground carbon fluxes (Table O n l
	561 586	y compared to calculated DIC concentrations with mean annual precipitation, clay content, air y 5). While the grasslands at Laqueuille, Easter Bush, and Früebüel were characterized by a y
	562 587	capacity of the soils (air-filled pore volume at field capacity), soil water content, or water-positive balance of NEE, fertilizer addition and carbon removal with harvest (indicating a
	563 588	filled pore space. Likely, the connectivity and spatial arrangement of soil (macro)pores rather carbon sink), the Carlow grassland showed a net negative balance due to large harvest of
	564 589	than bulk soil properties control gas exchange with the atmosphere (Lange et al., 2009) and biomass (for silage). At Carlow, net carbon losses nearly doubled from 40 g m -2 yr -1 to 79 g
		the degree of supersaturation of soil waters (Walmsley, 2010). m -2 yr -1 when leaching losses were considered. At the other sites, 5-29% of the net inputs of
	567
	542 593	suggests that the
		25 27

551

subsoils, the degree of supersaturation was larger and more variable than for topsoils, which 552 might reflect the longer diffusion path into the atmosphere and therefore the stronger build-up 553 of disequilibria between CO 2 production in moist soil zones and the partial pressure of CO 2 in 554 soil air in drier zones. On the other hand, any contamination of soil air samples with 565 566 Relevance of DOC plus biogenic DIC leaching for the net ecosystem carbon balance 576 forest's life cycle. Therefore, carbon release as a result of logging or catastrophic events like 577 fire or wind storms are not included. According to the latest estimates, logging reduces the 578 average net carbon uptake of European forests by 63 ± 11 g m -2 yr -1

[START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF]

. 579 Another 5 ± 1 g C m -2 yr -1 are lost through fires. Due to these losses, the long-term average 580 net biome productivity of European forests, excluding leaching losses, is estimated to 82 g C 581 m -2 yr -1

[START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF]

. The average leaching loss of 12 g C m -2 yr -1 we observed for 582 forests equals 14% of the average net biome productivity of forests. 590 carbon into soil were leached. The estimated average net biome productivity of European 591 grasslands, excluding leaching losses, is 64 g C m -2 yr -1

[START_REF] Schulze | Importance of methane and 822 nitrous oxide for Europe´s terrestrial greenhouse-gas balance[END_REF]

. Our average 592 leaching loss for grasslands of 29 g C m -2 yr -1 is almost 50% of that estimate.

  This period was from 1 October 2006 until 30 March 2009 for Laois and Carlow and from 1 October 2006 until 30 March 2008 for all other sites.

	Site Hainich (slope and valley) Sorø (near and far from tree) Laois Loobos Wetzstein Laqueuille (intensive and extensive use) Carlow (g) (slope and valley) Easter Bush (slope and hollow) Früebüel Grignon Klingenberg Carlow (c) 1 down to 60 cm depth, 2 down to 30 cm depth, 3 down to 50 cm depth. Soil organic carbon data for Früebüel from Roth (2006). 6 Infiltration into B horizon excluding a lateral Land use Soil type (WRB) Soil texture Mean Mean annual Soil organic carbon pH of topsoil Sampling depths temperature in observed period temperature in observed period (kg m -2 ) (cm) (°C) (°C) Beech forest Cambisol Loamy clay 11.9 1 5.7 20, 75 7.6 9.2 Beech forest Stagnic Luvisol Loamy sand 9.8 1 4.6 15, 100 8.2 9.6 Spuce forest Stagnosol Clay 2.2 3 5.1 15, 70 9.1 10.9 Pine forest Haplic Arenosol Sand 7.7 2 4.0 5, 120 9.5 10.9 Spuce forest Podzol Sandy loam 8.7 3 3.8 20, 90 5.6 7.3 Grassland Andosol Silt loam 23.1 2 5.4 30, 90 6.6 7.9 Grassland Calcic Luvisol Sandy loam 2.3 3 7.5 20, 65 9.4 9.3 Grassland Gleyic Cambisol Sandy loam 12.3 1 5.4 30, 100 8.1 9.0 Grassland Endogleyic Cambisol Loamy clay 5.8 3 5.5 30, 100 6.6 8.1 Cropland Calcaric Cambisol Silt loam 10.5 1 7.3 40, 90 9.9 11.2 Cropland Stagnosol Silt loam 9.7 1 6.4 35, 75 7.1 8.8 Cropland Eutric Cambisol Sandy loam 7.3 1 6.9 40 9.0 9.3 F o r R e v i e w O n l y
	runoff of 287 mm. Carlow (g): Carlow grassland, Carlow (c): Carlow cropland

Table 2 :

 2 Water balance of the research sites during the investigated period. Drainage from A-horizon denoted fluxes deeper than the upper instrumentation depth given in Table1, drainage from soil profile refers to water fluxes deeper than the lower instrumentation depth of Table1.

							Average relative deviation of
							modelled water contents from
	site	Precipitation	Evapotranspiration	Rapid runoff	Drainage	measured ones
					from A-	from soil
					horizon	profile	shallow	deep
	Cumulative water fluxes during period of observations (mm)
	Hainich	1363	374	589	572	326	14	no sensor
	Sorø	1345	318	141	1086	915	20	no sensor
	Laois	2594	1192	944 2	542 1	441	12	8
	Loobos	1452	819	59	1036	646	24	no sensor
	Wetzstein	1358	466	335	790	508	7	no sensor
	Laqueuille	1757	997	62	952	720	5	4
	Carlow (g)	2236	753	0	1627	1515	14	6
	Easter Bush	966	250	13	752	695	14	no sensor
	Früebüel	2178	797	449	1061	941	5	2
	Grignon	1027	662	189	438	189	17	8
	Klingenberg	1307	289	40	1038	975	17	no sensor
	Carlow (c)	2236	669	0	1595	-	13	-
	Mean annual water fluxes (mm yr -1 )
	Hainich	1008	346	489	335	166	-	-
	Sorø	928	287	112	688	531	-	-
	Laois	1040	561	357 3	202 1	149	-	-
	Loobos	982	609	33	683	406	-	-
	Wetzstein	966	428	252	498	259	-	-
	Laqueuille	1295	773	55	670	486	-	-
	Carlow (g)	894	345	0	620	569	-	-
	Easter Bush	735	141	13	610	584	-	-
	Früebüel	1711	666	399	751	651	-	-
	Grignon	710	523	132	266	95	-	-
	Klingenberg	950	242	33	713	652	-	-
	Carlow (c)	894	308	0	598	-	-	-

Table 3 :

 3 Leaching losses of dissolved organic carbon from topsoils and subsoils of the research sites. The winter period is from 1 October until 30 March. Winter data are the average of winters 2006/

Table 4 :

 4 Numbers in brackets indicate standard deviations due to spatial variability of concentrations for individual sites and the standard error of the average across sites with the same land use system or across all sites; n.d.: not detectable; 1 excluding lateral runoff of 3.0 g DOC m -2 yr -1 . Topsoils reach down to the shallow instrumentation depth, subsoil reach down to the deeper instrumentation depth given in Table1. Leaching losses of total dissolved inorganic carbon from topsoils and subsoils of the research sites. The winter period is from 1 October until 30 March. Winter data are the average of winters 2006/

	3) 16.2 (0.4)	5.7 (0.5)	2.7 (0.2)	8.3 (0.5)

Table 5 :

 5 Leaching losses of DOC plus biogenic DIC in relation to the net ecosystem exchange (NEE) and net ecosystem carbon balance (NECB) of the study sites. Positive numbers indicate net uptake from atmosphere, negative numbers net release of carbon.

	Site	Leaching loss from (sub)soils	Average	NEE +	Leached	NECB
					multi-year	fertilization -	fraction of
					NEE 1	harvest	balance
		Winter	Summer	Total		excluding leaching	including leaching

cropland 13.2 (1.4) 7.7 (1.1) 18.3 (3.5) 253(119) -57(25) 51(27) -75(27) Median cropland 12.5

	Hainich Sorø Laois Loobos Wetzstein Average forest Median forest Laqueuille Carlow (g) Easter Bush Früebüel Average grassl. Median grassland 16.5 7.6 (0.1) 19.8 (1.2) 15.5 (3.9) 0.3 (0.0) 7.0 (1.1) 0.4 (0.1) 1.8 (0.1) 1.2 (0.1) 5.4 (0.6) 0.3 (0.2) 8.3 (3.0) 3.5 (3.0) 7.0 0.4 2.2 (0.3) 4.3 (1.4) 25.8 (2.2) 12.6 (1.6) 18.9 (0.9) 11.1 (0.8) 14.1 (1.1) 28.4 (1.9) 15.3 (5.0) 14.1 (5.1) 11.9 Grignon 12.5 (0.3) n.d. -Klingenberg 16.0 (1.1) 8.7 (0.6) Carlow (c) 11.2 (3.4) 6.6 (2.3) Average 7.7 F o r R e v i e w 8.0 (0.1) +294 2 35.2 (4.1) +143 3 7.4 (1.1) +873 4 3.0 (0.1) +402 5 5.7 (0.7) +177 6 11.9 (5.9) 378(132) 378(132) +294 2 +143 3 +873 4 +402 5 +177 6 7.4 294 294 6.5 (1.5) +181 7 +141 7 38.4 (2.7) +185 7 -40 7 30.0 (1.3) +221 7 +212 7 42.5 (2.1) +320 8 +146 8 29.4 (8.0) 227(32) 115(54) 34.2 203 144 12.5 (0.3) +472 9 -51 9 24.7 (1.2) +64 10 -103 10 17.8 (4.1) +222 4 -17 4 17.8 222 -51 O n l y 3 25 1 1 3 6(5) 3 5 98 14 29 36(21) 22 25 24 105 25	+286 +108 +866 +399 +171 366(134) 286 +135 -79 +182 +104 85(57) 119 -64 -128 -35 -64	1 )
	Total average	11.9 (2.1)	8.1 (2.8)	19.4 (4.0)	296(61)	181(76)	28(10)	162(78)
	Lower quartile	6.6	0.8	7.2	180	-23	3	-42
	Upper quartile	16.7	11.9	31.3	340	232	26	208
	Total median	11.9	6.6	15.2	222	145	19	121

Table 6 :

 6 Concentrations of methane (CH 4 ) in soil air and leaching losses of dissolved CH 4 .Numbers in brackets indicate standard deviations due to spatial variability of concentrations. No data can be given for soil air concentration beneath the Wetzstein topsoil because wild boars destroyed the shallow soil air samplers. Topsoils reach down to the shallow instrumentation depth, subsoil reach down to the deeper instrumentation depth given in Table1.

			pCH 4 beneath	pCH 4 subsoil	CH 4 leaching from	CH 4 leaching from
			topsoil		topsoil	subsoil
			µl l -1	µl l -1	(g CO 2 -C eq m -2 yr -1 )
	Hainich		1.20 (0.13)	0.86 (0.15)	0.005 (0.000)	0.001 (0.000)
	Sorø		0.56 (0.08)	0.66 (0.11)	0.004 (0.001)	0.002 (0.000)
	Laois		4.82 (1.34)	3.26 (0.54)	0.037 (0.045)	0.018 (0.053)
	Loobos		1.18 (0.11)	0.73 (0.06)	0.007 (0.000)	0.004 (0.001)
	Wetzstein		--	0.77 (0.06)	0.007 (0.000)	0.002 (0.000)
	Laqueuille	intensive	1.76 (0.11)	1.53 (0.01)	0.009 (0.001)	0.007 (0.000)
		extensive 1.73 (0.01)	1.73 (0.01)	0.005 (0.000)	0.004 (0.000)
	Carlow (g)		1.51 (0.34)	1.45 (0.43)	0.002 (0.000)	0.002 (0.000)
	Easter Bush slope	1.09 (0.03)	1.71 (0.01)	0.012 (0.002)	0.007 (0.000)
		hollow	1.63 (0.13) 29.45 (27.08)	0.031 (0.006)	0.038 (0.005)
	Früebüel		1.66 (0.11)	2.04 (0.16)	0.014 (0.001)	0.011 (0.000)
	Grignon		0.92 (0.11)	0.69 (0.11)	0.002 (0.000)	0.002 (0.000)
	Klingenberg		5.36 (2.27)	2.04 (0.41)	0.147 (0.008)	0.233 (0.009)
	Carlow (c)		0.78 (0.09)	--	0.001 (0.001)	--

Page 10 of 58 Global Change Biology

Global Change Biology

Total lateral runoff including surface runoff of 349 mm;

Infiltration into B horizon excluding lateral runoff;

Total lateral runoff including surface runoff of 135 mm yr -1 .

net ecosystem exchange = gross primary productivity minus ecosystem respiration excluding C deprivation with harvest, fires etc., Numbers in brackets indicate standard deviations due to spatial variability of concentrations for individual sites and the standard error of the average across sites with the same land use system or across all sites. ;

mean 2000mean -2007 Kutsch et al. (in prep.) Kutsch et al. (in prep.),

mean 1997mean -2008 Pilegaard et al. (in prep.) Pilegaard et al. (in prep.),

mean 2003mean -2007 Saunders et al. (in prep.) Saunders et al. (in prep.),

mean 1997mean -2008 Moors et al. (unpublished data), Moors et al. (unpublished data),

mean 2002mean -2007mean Rebmann et al. (2009), ),

Laqueuille: 2003Laqueuille: - 2006;; Easter Bush: 2004-2007, Carlow: 2003-2007 Klumpp et al. (in prep.),

 8 mean 2006 8 mean -2007 8 mean Zeeman et al. (2010

), 9 mean 2005-2008 Lehuger et al. (

2009), 10 mean of four crop periods 2004/2005-2008; a net loss of -255 g m -2 yr -1 was observed when the application of organic fertilizer to rape in 2004 is excluded from the balance,Prescher et al. (2010).

Acknowledgements

This project was funded by the German Research Foundation (grants SI 1106/2-1, KA 685 1673/7-1) and supported by the CarboEurope and NitroEurope integrated projects and the 686 Infrastructure for Measurements of the European Carbon Cycle (IMECC) program of the 687 European Union. David Walmsley acknowledges funding by the Environmental Protection


Kim Yrjälä
email: kim.yrjala@helsinki.fi

Tero Tuomivirta

Heli Juottonen

Anuliina Putkinen

Kaisa Lappi

Eeva-Stiina Tuittila

Timo Penttilä

Kari Minkkinen

Jukka Laine

Krista Peltoniemi

Hannu Fritze

CH 4 production and oxidation processes in a boreal fen ecosystem after long-term water table drawdown

Keywords: greenhouse gas, peatlands, methanogens, methanotrophs, microbial community, DGGE, T-RFLP greenhouse gas, peatlands, methanogens, methanotrophs, microbial communities, DGGE, T-RFLP

Mires, especially sedge dominated fens, are sources of the greenhouse gas CH4. Climate change scenarios predict a lowering water table (WT) in mires. To study the effect of WT drawdown on CH4 dynamics in a fen ecosystem, we took advantage of a WT drawdown gradient near a ground water extraction plant. Methane fluxes, CH4 production and oxidation potentials, were related to microbial communities responsible for the processes in four mire locations (wet, semi-wet, semi-dry and dry). Principal component analyses (PCA) performed on the vegetation, pH, CH4 and WT results clearly separated the four sampling locations in the gradient. Long-term lowering of WT was associated with decreased coverage of Sphagnum and aerenchymatic plants, decreased CH4 field emissions and CH4 production potential. Based on mcrA T-RF the methanogen community structure correlated best with the methane production and coverage of aerenchymatic plants along the gradient. Methanosarcinaceae and Methanocellales were found at the pristine wet end of the gradient, whereas the Fen cluster

Introduction

In the Northern hemisphere mires extend over vast areas that typically are water-saturated ecosystems where a part of the plant litter production avoids aerobic decomposition and accumulates as peat. The high water table (WT) creates anaerobic microbial habitats where methanogenesis occurs [START_REF] Rydin | The biology of peatlands[END_REF]. Hence boreal mires act as methane (CH 4 ) sources into the atmosphere. Due to climate change, a growing attention has been devoted to these areas, where over one-third of the global terrestrial carbon is stored [START_REF] Gorham | Northern peatlands: role in the carbon cycle and probable responses to climatic warming[END_REF]. The rise of earth temperatures may have profound effects on the microbial life of these ecosystems and thus on microbially-mediated gas emissions (IPCC 2007).

Methane, which is a 25 times more powerful greenhouse gas than carbon dioxide, is produced microbiologically in the final stage of anaerobic degradation of organic matter (Whalen, 2005). Methane is solely produced by methanogens that are classified into Euryarchaeota. Methanogens are highly diverse constituting of four classes and six orders of archaea. Methane-producing archaeal communities have been described from various mire ecosystems [START_REF] Edwards | Microbiological processes in the terrestrial carbon cycle: methane cycling in peat[END_REF][START_REF] Basiliko | Methane biogeochemistry and methanogen communities in two northern peatland ecosystems, New York State[END_REF][START_REF] Galand | Microsite-dependent changes in methanogenic populations in a boreal oligotrophic fen[END_REF]Galand et al. 2005;Galand et al. 2005;[START_REF] Juottonen | Seasonality of rDNA-and rRNAderived archaeal communities and methanogenic potential in a boreal mire[END_REF][START_REF] Putkinen | Archaeal rRNA diversity and methane production in deep boreal peat[END_REF]) including a range of nutrient conditions [START_REF] Juottonen | Methanogen communities and Bacteria along an ecohydrological gradient in a northern raised bog complex[END_REF] and mire successional stages [START_REF] Merilä | Methanogen communities along a primary succession transect of mire ecosystems[END_REF]. Methanogens of Methanosarcinales, Methanomicrobiales, Methanobacteriales and Methanocellales (Rice cluster I) have frequently been detected.

The CH 4 emissions are, however, dependent on the activity and abundance of methaneoxidizing bacteria (MOB) that are able to oxidize CH 4 to CO 2 in aerobic conditions [START_REF] Hanson | Methanotrophic bacteria[END_REF]. The aerobic layer of peat is roughly defined by the WT position (Bubier & Moore, 1993). Low emissions in mires can occur when the CH 4 never reaches the atmosphere because it is consumed by MOB in the uppermost aerobic layer (Whalen, 2005). In this way the CH 4 flux to the atmosphere is the sum of the functionally opposite actions of archaea and bacteria involved in the CH 4 cycle. The highest MOB activity in mires is observed just above the WT, where CH 4 and oxygen levels are adequate for CH 4 oxidation [START_REF] Sundh | Depth distribution of microbial production and oxidation of methane in northern boreal peatlands[END_REF]. While estimates of the oxidation efficiency of the produced CH 4 in different mires vary considerably, estimates of between 20% in Carex dominated fens [START_REF] Popp | Evaluation of methane oxidation in the rhizosphere of a Carex dominated fen in northcentral Alberta, Canada[END_REF] and 78% in Sphagnum dominated bogs [START_REF] Yavitt | Potential Methane Production and Methane Oxidation Rates in Peatland Ecosystems of the Appalachian Mountains, United States[END_REF]) have been given. The latter phenomena is explained by the fact that MOB inhabit Sphagnum species providing the plant CO 2 through CH 4 oxidation under wet conditions [START_REF] Raghoebarsing | Methanotrophic symbionts provide carbon for photosynthesis in peat bogs[END_REF][START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF].

MOB are traditionally divided into two taxonomic groups, type I and II, within the Proteobacteria. Type I MOB includes genera like Methylobacter and Methylomicrobium, which belong to the Gammaproteobacteria. The type II MOB, Methylocystis, Methylosinus, Methylocella and Methylocapsa belong to the Alphaproteobacteria [START_REF] Hanson | Methanotrophic bacteria[END_REF][START_REF] Dedysh | Exploring Methanotroph Diversity in Acidic Northern Wetlands: Molecular and Cultivation-Based Studies[END_REF]. These types differ in their carbon assimilation pathway, phylogenetic affiliation, and intracellular membrane arrangement.

The methanogenic and methanotrophic communities in Finnish mires have been studied by molecular genetic methods. Methanogens were analyzed by using both functional, mcrA (Galand et al. 2002a), and phylogenetic 16S rRNA marker genes [START_REF] Galand | Microsite-dependent changes in methanogenic populations in a boreal oligotrophic fen[END_REF]. MOB have been studied by functional (pmoA) marker gene analysis in a pristine and drained fen and bog within a mire complex [START_REF] Jaatinen | Methane-Oxidizing Bacteria in a Finnish Raised Mire Complex: Effects of Site Fertility and Drainage[END_REF]. The fingerprinting of Finnish fen MOB was improved by modifications of the pmoA reverse primer for DGGE analysis protocols [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF]. Methanogens and methanotrophs in mires have, however, rarely been analyzed within the same study [START_REF] Mcdonald | Molecular ecological analysis of methanogens and methanotrophs in blanket bog peat[END_REF].

The CH 4 turnover in mires is highly dependent on the ecohydrological conditions. In climate change scenarios where the raise of temperature is 3 °C, the summertime WT in northern

F o r R e v i e w O n l y
mires is expected to drop 10-20 cm [START_REF] Gorham | Northern peatlands: role in the carbon cycle and probable responses to climatic warming[END_REF][START_REF] Roulet | Northern fens: methane flux and climatic change[END_REF][START_REF] Gitay | Ecosystems and their goods and services[END_REF]. A WT drawdown of that magnitude (15 cm) has occurred in the northern Suonukkasuo fen where a groundwater extraction plant has generated a WT gradient that has gradually changed part of the wet fen into a forested peatland [START_REF] Jaatinen | Responses of aerobic microbial communities and soil respiration to water-level drawdown in a northern boreal fen[END_REF]. Such a persistent change in the WT influence the plant community structure [START_REF] Weltzin | Response of bog and fen plant communities to warming and water-table manipulations[END_REF][START_REF] Weltzin | Potential effects of warming and drying on peatland plant community composition[END_REF]) that may lead to complete replacement with species better adapted to the new conditions [START_REF] Laine | Long-term effects of water level drawdown on the vegetation of drained pine mires in southern Finland[END_REF][START_REF] Strack | Response of vegetation and net ecosystem carbon dioxide exchange at different peatland microforms following water table drawdown[END_REF]).

The WT gradient was studied combining methane gas flux measurements, environmental data and measurements of microbial communities responsible for CH 4 turnover. This gradient study prompted the formulation of hypotheses concerning CH 4 turnover in relation to detected microbial communities, namely: (1) as the WT drawdown affects the plant cover and stimulate tree growth, the CH 4 emissions are reduced in the resulting dryer conditions; (2) the emissions in WT drawdown conditions decrease primarily as a consequence of decrease in potential CH 4 production and simultaneous decrease in diversity of methanogens; (3) the potential CH 4 oxidation decreases when there is less CH 4 available; (4) the depth is an important factor determining microbial community structure, both that of methanogens and of methanotrophs; (5) there are specific types of methane-producing archaea and MOB that are favored by the WT drawdown.

Materials and methods

Experimental site and sampling

The study site, Suonukkasuo, is a mesotrophic pine fen located in Rovaniemi, northern Finland (66°28′N, 25°51′E) within the aapa mire zone. Mesotrophic pine fens (RhSR in the Finnish mire The average long term water-table (WT) values for the ground-frost free periods of the years 2001-2003 and 2005 expressed as distances from soil surface were 26, 21, 15 and 9 cm for the locations S1 to S4, respectively. The differences in WT between locations were statistically significant, except between locations S1 and S2 (p=0.066). The first-and third-quartile ranges of the WTs were 21-30, 13-30, 10-21 and 5-13 cm for the locations S1 to S4, respectively. The momentary WT at the time of sampling in 2006 was 32, 50, 47 and 23 cm, respectively. The hydrological gradient is reflected in vegetation composition as reported in [START_REF] Jaatinen | Responses of aerobic microbial communities and soil respiration to water-level drawdown in a northern boreal fen[END_REF].

Sampling was conducted in September 2006. Intact triplicate peat cores were taken from the four locations using a corer (size 4 x 6 cm) to a depth of 70 cm. Depth samples were prepared by dividing peat cores at 10 cm intervals. The samples between 0 -50 cm depth were used for estimation of the methanotroph activity and community analyses and the samples between depths 20 -70 cm for the respective analyses for methanogens. For convenience we call the samples between 0 to 10 cm as 0 cm, between 10 to 20 cm as 10 cm and so on. To measure the peat dry weight subsamples were kept at 105 °C for over 12 h and subsequently weighted.

Field CH 4 measurements

Gas efflux measurement plots (n = 3) were installed at each location in June 2001 [START_REF] Dahlin | Methane emissions from a northern boreal pine fen along water table gradient -preliminary results[END_REF]. Collars made of metal tubes (diameter 31.5 cm) were inserted 15-30 cm deep in peat. An aluminum groove was attached on the top of each collar. A closed chamber (height 30 cm) equipped with a fan was placed on the groove filled with water before sampling to seal the chamber. At each sampling occasion, four successive samples of 30 ml were taken from the chamber with plastic syringes during a 35-minute measurement period at 10 minute intervals (5, 15, 25, 35 minutes). The syringes were then taken to laboratory and analyzed for CH 4 concentrations within 24 hours from sampling by a gas chromatograph equipped with a FI detector. CH 4 fluxes were calculated from a linear change of CH 4 concentrations during the sampling period of 35 minutes. Obvious ebullition events were deleted from the data.

Measurements of potential CH 4 production and oxidation

Measurements of potential CH 4 production and oxidation (4.13 µmol in 125 ml infusion bottle) with incubation at 15 o C were carried out as described in [START_REF] Juottonen | Seasonality of rDNA-and rRNAderived archaeal communities and methanogenic potential in a boreal mire[END_REF] and [START_REF] Jaatinen | Methane-Oxidizing Bacteria in a Finnish Raised Mire Complex: Effects of Site Fertility and Drainage[END_REF], respectively.

Analysis of methanogen communities by mcrA-TRFLP

DNA for methanogen community analysis was extracted from 0.25 g of wet mass peat with PowerSoil DNA Isolation Kit (MoBio Laboratories). Methyl coenzyme M reductase (mcrA) gene fragments were amplified with the primers of [START_REF] Luton | The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill[END_REF]. The reactions (50 µl) contained 1 × PCR buffer with 2 mM MgCl 2 (Biotools), 200 µM dNTPs, 0.4 µM of both primers, 1U of DNA polymerase (Biotools), and 1-2 µl of undiluted DNA extract as template. The reaction conditions were initial denaturation (94 °C, 3 min) followed by 31 cycles of 94 °C 45 s, 52 °C 1 min, 72 °C 1 min 30 s, and a final elongation (72 °C, 7 min). In PCR for T-RFLP, the forward primer was 5'-labelled with 6-carboxyfluorescein (FAM). et al. (2008). The range of fragment lengths included in the analysis was 75 to 500 bp. Minimum peak height threshold was 100 fluorescence units. Results are presented based on relative peak area. For identification of T-RFs, three clone libraries (S4 20 cm; S2 30 cm; S1 50cm) were constructed as in [START_REF] Juottonen | Seasonality of rDNA-and rRNAderived archaeal communities and methanogenic potential in a boreal mire[END_REF]. Inserts from clone colonies were re-amplified with mcrA primers (33-54 clone per library) and screened by RFLP with MspI. From RFLP groups with > 5 clones, 2-5 clones from each group were sequenced, and from groups with < 5 clones, one member was sequenced as in [START_REF] Juottonen | Seasonality of rDNA-and rRNAderived archaeal communities and methanogenic potential in a boreal mire[END_REF]. Terminal restriction fragments were identified based on in silico digestion of the sequences and T-RFLP analysis of clones.

Investigation of MOB by DGGE analysis of the pmoA marker gene

DNA for methane-oxidizing bacteria (MOB) community analysis was extracted from ca. 0.5 g wet mass peat using the FastDNA kit for soil (MP Biomedicals, Ohio, USA) according to Yeates & Gillings (1998) modified as in [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF]. A region of subunit α of particulate methane monooxygenase (pmoA) was PCR targeted with the A189f/A621r with a GC-clamp attached to the reverse primer (see Tuomivirta et al. 2009 for details). Also broad specificity A189f/A682r [START_REF] Holmes | Evidence that particulate methane monooxygenase and ammonia monooxygenase may be evolutionarily related[END_REF] primers were applied for reference [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF].

Fingerprinting of the MOB diversity was performed in a denaturing gradient gel electrophoresis (DGGE) described in [START_REF] Jaatinen | Methane-Oxidizing Bacteria in a Finnish Raised Mire Complex: Effects of Site Fertility and Drainage[END_REF]. The DGGE gel photographs were screened for the presence (1) or absence (0) of pmoA bands using the AlphaImager 2.1 program of the AlphaDigiDoc gel documentation system (Alpha Innotech Corp., CA. US). A binary matrix was generated with this data using only the positions of successfully sequenced bands. Single DGGE bands of interest were excised from the gel, purified and sequenced as described in [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF] and [START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF].

Sequence analysis and phylogeny

mcrA and pmoA sequences were compared to database sequences with BLAST [START_REF] Altschul | Gapped BLAST and PSI-BLAST: A new generation of protein database search programs[END_REF]) analysis of the National Center for Biotechnology Information (NCBI). Deduced amino acid sequences of mcrA together with selected reference sequences were aligned with ClustalW [START_REF] Larkin | Clustal W and Clustal X version 2.0[END_REF]). Suitable evolutionary model was selected with ProtTest [START_REF] Abascal | ProtTest: selection of best-fit models of protein evolution[END_REF]. Maximum likelihood trees were constructed with PhyML [START_REF] Guindon | A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood[END_REF] with model LG+G+F. Bootstrap values were generated from 100 replicates in PhyML. Pairwise distance calculations of nucleotide pmoA sequences were analyzed with MEGA 4.0 [START_REF] Tamura | MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0[END_REF]). The mcrA and pmoA sequences have been submitted to the EMBL database under accession nos. FN564006-FN564029 (mcrA) and GQ279342-GQ279346 (pmoA).

Statistical evaluation

Methane fluxes between locations were compared by one-way analysis of variance (ANOVA).

Significance of pairwise differences was assessed by Tukey test. The effect of categorical variables depth, location and their interaction on potential CH 4 production and oxidation were compared with generalized linear models (GLM). Tukey post hoc test was applied to determine which pairs of means differ significantly. Because location and depth had significant interactions, ANOVA followed by Tukey test was performed separately for each depth. Level of significance in all statistical analyses was P=0.05.

We applied principal component analysis (PCA) to compare the four locations based on their environmental variables, i.e., long-term and momentary WT, CH 4 field emission and

Results

Methane emissions

In the years (2001)(2002)(2003)(2004) preceding the sampling for microbial community analysis, the CH 4 emissions from location S4, were substantial, averaging 73 mg m -2 day -1 (Fig. 1). As a result of WT drawdown, the emissions were much smaller in the locations S3 (22 mg m -2 day -1 ), S2 (0.9 mg m -2 day -1 ) and S1 (1.9 mg m -2 day -1 ; Fig. 1). Similarly to long term WT the emissions differed significantly between all pairs of locations (P=0.001-0.004) except for locations S2 and S1.

Methane production and oxidation potential

The wettest location S4 had the highest CH 4 production potential at depths from 20 to 50 cm (P=0.001-0.036, Fig. 2) in correspondence with the flux rates recorded in earlier years. The S4 production was 43.2 nmol g dry weight -1 day -1 compared to 0.4 (S3, p=0.005), 4.0 (S2, p=0.010) and 0.4 (S1, p=0.005) at the depth of 20 cm. The production potential of the three other dryer The highest methane oxidation potential was observed in location S3, 561.2 nmol g dry weight -1 day -1 , but the sampling depth influenced the oxidation potential (p=0.004) in addition to location (p=0.033) (Fig. 2). In the top layer the potential was significantly higher in S3 than in S2, 62.2 nmol g dry weight -1 day -1 (p=0.042) and S1, 28.9 nmol g dry weight -1 day -1 (p=0.031) and second highest in S4, 177,7 nmol g dry weight -1 day -1 . The dry S1 location had the lowest potential oxidation rate. The oxidation potential did not differ between locations in deeper peat layers.

Environmental factors characterizing the WT gradient

Principal component analyses (PCA) performed on the vegetation, potential CH 4 production and oxidation, CH 4 field emissions, pH, and long term and momentary (date of sampling) water-table depth clearly separated the four sampling locations along the first principal axis (PC1 in Fig. 3a).

With the provided measurements the second principal axis (PC2) separated all samples according to depth. Increase in long term WT, coverage of Sphagnum and aerenchymatic plants, high CH 4 field emissions together with CH 4 production potential characterized the pristine end of the PC1 (Fig. 3b). Decreasing momentary WT and CH 4 oxidation potential together with increasing pH characterized the peat layers with increasing depth along PC2.

Microbial communities involved in the CH 4 cycle along the gradient

T-RFLP fingerprinting of mcrA representing methanogens resulted in twelve T-RFs (Table 1). In distinction between them. According to RDA the methanogen community structure showed highest correlation with methane production and coverage of aerenchymatic plants along the gradient (RD1 in Fig. 4a-c). The second RDA axis showed that the pH influenced the community structure according to depth. The first RDA axis separated the four locations when the methanogen communities at different depths were analyzed together with environmental factors (Fig. 4b). The top layers were most variable through the gradient, but deeper down they became more alike.

In the wet end of the gradient with higher CH 4 production potential the methanogen diversity was highest with 8 to 10 T-RFs. The locations S2 and S1 sampled from three depths showed lower diversity with 6 T-RFs.

The occurrence of the T-RFs 115 bp (Methanocellales), 272 bp (putatively Methanosarcinaceae) and 298 bp (Methanosarcinaceae) correlated most strongly with the wet location S4 (Fig. 4c, Fig. 5). In addition to identified methanogens, T-RF 193 bp affiliated with a cluster with no cultured representatives in the phylogenetic tree (Fig. 5). The T-RF 278 bp, representing Methanomicrobiales-associated Fen cluster, was one of two T-RFs prone to the dry end of the gradient despite of overall decrease in methanogen groups along the gradient.

In analysis of MOB communities, the broad specificity pmoA primer set A189f/A682r did not produce correct amplicons [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF]. Five different pmoA alleles (T, S, R, M, and O), all Methylocystis spp according to sequence comparisons, could, however, be isolated from the gradient by PCR-DGGE and sequencing with the A189f/A621r primer set (Table 2). RDA (Fig. 6a) of the pmoA alleles showed that their occurrence was best correlated with CH 4 oxidation potential, pH and vegetation. Similarly to methanogen communities (Fig. 4a) the locations from wet to dry were separated along the first RDA axis, and the second RDA axis characterized the depth of the peat (Fig. 6b). The two wettest locations had similar MOB 13 communities in their whole profile (Fig. 6b). The deep layers (30 -40 cm) of the locations S4, S3 and S2 were also characterized by a similar MOB. The MOB community of the dry location S1 differed from the other sites. The M allele, dominating the wet end of the gradient (Fig. 6a) was identical to a previously detected Finnish fen sequence FJ930087 [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF]) and was most different from the other alleles with 11 to 12 point mutations. The R allele inhabiting the wetter part of the gradient was identical to sequences FJ930090 and FJ930091 of a Finnish fen [START_REF] Tuomivirta | Quantitative PCR of pmoA using a novel reverse primer correlates with potential methane oxidation in Finnish fen[END_REF]), AY309209, a North-American fen (Nold, personal communication), and the sequence GQ121280 [START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF] occurring in methane oxidizing community within Sphagnum mosses. Drying correlated with increasing abundances of alleles O, S and T.

The R allele dominated the pristine location and the upper layer of the peat (Fig. 6a).

Discussion

Generally the study supports the five hypotheses concerning CH 4 turnover in relation to detected microbial communities along WT drawdown gradient. The study of greenhouse gas turnover along a peatland WT gradient showed that drying appeared to cause a dramatic reduction in CH 4 emissions and in potential CH 4 production in agreement with our hypotheses 1 and 2. Despite more oxic conditions the methane oxidation also decreased substantially along the gradient. The phenomena supported our third hypothesis on the superior role of the availability of CH 4 for the potential CH 4 oxidation over the direct WT control. In agreement with the fifth hypothesis drying decreased the diversity of the methanogen communities and brought forth an adapted group of archaea, the Fen cluster methanogens, which was characteristic of dryer conditions. As hypothesized (hypothesis 4) the depth appeared to be an important factor for the community structure of methanogens and of methanotrophs. The depth effect in WT drawdown brought Methylocystis bacteria distributed to specific locations in the gradient. Previously, at the same site, the CO 2 flux increased from location S4 to S1 and fungi and bacteria benefited from the WT drawdown whereas actinobacteria did not [START_REF] Jaatinen | Responses of aerobic microbial communities and soil respiration to water-level drawdown in a northern boreal fen[END_REF].

Separation of the four locations along the WT gradient and the sampling depths (peat layers) was clear and could statistically be explained by eight variables. The WT gradient was best described in PCA by coverage of aerenchymatic plants, high CH 4 emissions at the wet end, coverage of Sphagnum moss and CH 4 production potential in this order. The CH 4 oxidation was reduced as a consequence of WT drawdown but not as clearly as the production. This may well be indicative of the difference in the two processes of production (anaerobic) and the following consumption (aerobic) of CH 4 . The CH 4 oxidation potential indeed correlated positively with the WT of the time of sampling and the coverage of Sphagnum, whereas production correlated with other variables like pH and emissions (Fig. 3b). The high oxidation in wet locations seemed to be coupled with high CH 4 production potential. When more CH 4 is potentially produced by methanogenic archaea, more is simultaneously oxidized by the methanotrophic bacteria.

Very recently methane oxidation was reported from 23 different Sphagnum species originating from a Finnish boreal mire site and the activity was related to a Methylocystis signature similar to the R allele of this study [START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF]. The correlation of the oxidation potential with Sphagnum coverage might be a direct regulation instead of a covariation with more pristine conditions.

The methanogen community structure according to T-RFLP analysis changed with decrease in diversity along the gradient. The maximum CH 4 production potential for each vertical peat core correlated with the diversity of methanogens so that decreasing production was reflected in decreasing diversity. WT gradients have mainly been studied in meso-and [START_REF] Talbot | Assessing long-term hydrological and vegetation changes following drainage in a bog using paleoecological reconstructions and a hydrosequence[END_REF], and as far as we know reports from natural gradients combined with microbial community analysis of the CH 4 are lacking. In agreement with our results from the gradient, experimental field studies in Canada [START_REF] Strack | Effect of water table drawdown on peatland methane dynamics: Implications for climate change[END_REF]) and in Ireland [START_REF] Laine | The effect of altered water level on carbon fluxes in a blanket bog[END_REF]) have shown decrease in CH 4 emission as a result of lowered WT.

F o r R e v i e w O n l y microcosms (see, however,
Short term effects of WT on carbon balance in pore water from acidic, oligotrophic mire have been reported from a mesocosm study [START_REF] Blodau | Carbon turnover in peatland mesocosms exposed to different water table levels[END_REF] where decreased CH 4 production and emission was reported as a result of lower WT. Short term effect of drought (4 week) on the methanogen community structure in a bog and a fen mesocosm could not be observed [START_REF] Kim | Comparative analysis of soil microbial communities and their responses to the short-term drought in bog, fen, and riparian wetlands[END_REF]), but a significant decrease in the mcrA abundance was detected in the fen mesocosm.

Sampling depth has been shown to affect the methanogen community structure in mires (Galand et al. 2002b) where the changing conditions with depth (oxygen and quality of growth substrates for the microbes active in methanogenesis) will select for methanogen groups. The RDA analysis of the methanogen communities together with environmental factors showed nicely how the locations differ at the surface, but become much alike in the deepest sampling layer where the conditions in the gradient apparently are more similar (Fig. 4b). The discrepancy of location S2 to the general trend may well be explained by larger pH variation at this location (results not shown) and lowest emissions telling that this location is the most disturbed one in the gradient.

The methanogen group most strongly associated with the pristine end of the gradient was Methanosarcinaceae. In the drier locations, Methanosarcinaceae T-RFs were less abundant or absent. This finding was surprising considering that many members Methanosarcinaceae are versatile methanogens that are able to use several different substrates for growth [START_REF] Garcia | Taxonomic, phylogenetic, and ecological diversity of methanogenic Archaea[END_REF]. They also possess enzymes for detoxification of oxygen, which could favor their occurrence in the dry end of the gradient, which is the opposite of what was observed. Additional data, such as availability of methanogenic substrates along the gradient, would be required to better explain the disappearance of Methanosarcinaceae at the dry end. A minor group also found primarily at the wet end was an uncultured cluster (Mx cluster in Fig. 5) which has been detected in other wetland ecosystems [START_REF] Juottonen | Methanogen communities and Bacteria along an ecohydrological gradient in a northern raised bog complex[END_REF][START_REF] Castro | Phylogenetic characterization of methanogenic assemblages in eutrophic and oligotrophic areas of the Florida Everglades[END_REF][START_REF] Smith | Structure and function of methanogens along a short-term restoration chronosequence in the Florida Everglades[END_REF]) and in animal feces [START_REF] Ufnar | Methanobrevibacter ruminantium as an indicator of domesticated-ruminant fecal pollution in surface waters[END_REF], and it has been proposed to form an entirely new order of methanogens [START_REF] Mihajlovski | A putative new order of methanogenic Archaea inhabiting the human gut, as revealed by molecular analyses of the mcrA gene[END_REF]. Only two methanogenic groups were typical to the dry end of the gradient, and they were affiliated with the Fen cluster which has commonly been found in Finnish mires [START_REF] Juottonen | Seasonality of rDNA-and rRNAderived archaeal communities and methanogenic potential in a boreal mire[END_REF]. One member of this cluster, Methanoregula boonei, was isolated from an acidic bog and has the lowest pH optimum known for a methanogen [START_REF] Bräuer | Isolation of a novel acidiphilic methanogen from an acidic peat bog[END_REF]. It is tempting to say that the Fen cluster/Methanoregula-type hydrogenotrophic methanogens are well adapted to the conditions of boreal fens characterized by changing WT and low pH.

All detected MOBs were by pmoA sequence analysis found to be of the Methylocystis genus, but differed by minute changes, point mutations, in the gene (Table 2). This suggests a phylogenetically very narrow MOB population of this fen. RDA showed that the occurrence of the five alleles was clearly dependent on location and peat layer in the gradient. It can be assumed that before WT drawdown, when the whole site was botanically a homogenous fen, all the locations had a similar MOB population with dominating alleles R and T in surface peat and then changing to T and M alleles in the deeper peat. Continual drainage of the fen has a selective pressure on MOB. The R allele was lost upon drying since methanotrophy in Sphagnum mosses is only related to high WT [START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF]. For reasons we do not know the most different Methylocystis was a dominating genus also in Russian and German bogs, which showed that 60-95% of MOB belonged to type II with Methylocystis being the dominant genus [START_REF] Dedysh | Differential detection of type II methanotrophic bacteria in acidic peatlands using newly developed 16S rRNA-targeted fluorescent oligonucleotide probes[END_REF]. A study, in which stable isotope probing (SIP) with PLFA, mRNA and microarray methods were used, revealed the dominance of type II genera Methylocystis and Methylosinus in blanket peat samples from England [START_REF] Chen | Revealing the uncultivated majority: combining DNA stable-isotope probing, multiple displacement amplification and metagenomic analyses of uncultivated Methylocystis in acidic peatlands[END_REF]. Bearing in mind that also Sphagnum species possess Methylocystis [START_REF] Larmola | The role of Sphagnum mosses in the methane cycling of a boreal mire[END_REF], one can say that it most likely dominates in northern peatlands.

With regard to climate change effect on boreal fens, the average drop in WT between location S4 (wet fen) and location S3 (semi-wet) was ca. 6 cm. This was accompanied by a statistically significant drop in potential CH 4 production together with a reduction in emissions from previous years. The potential oxidation changed in the other direction with increasing amounts of CH 4 oxidized at location S3 as compared to location S4. This would indicate that already a small, 6 cm, WT drawdown will change the CH 4 turnover. The methanogen community structure most clearly shifted between locations S3 and S2 and the distribution of the methanotrophic allele types is also changing most clearly in this part of the gradient. It can, however, be stated that as the underlaying microbial communities are changing with a 12 cm drop in WT their activity is already altered after the 6-cm initial drop in WT.

Comparison of behavior of methanogens and methanotrophs in the WT gradient using CH 4 production and oxidation measurements showed a difference in sensitivity to changing conditions. Much of the methanogenic activity is evidently lost already in the semi-wet location S3 and after that decreases drastically, whereas the methanotroph potential activity is high in the wet locations and decreases much less in the dryer locations. This can be explained by more oxic As a general conclusion, we have been able to show that even a minor WT drawdown, mimicking the climate change impact affects the dynamics of CH 4 production and oxidation in a mire. This study thus shows how ecohydrology shapes the dynamics of mires changing the plant community structures, and has a drastic effect on the microbial communities that are the basis for the environmentally important function of greenhouse gas turnover.

F

  end. The methane-oxidizing bacterial (MOB) community consisted exclusively of Methylocystis bacteria, but interestingly of five different alleles (T, S, R, M, and O) of the particulate methane monooxygenase marker gene pmoA. The M allele was dominant in the wet locations, and the occurrence of alleles O, S and T increased with drainage. The R allele that characterized the upper peat layer correlated with CH4 oxidation potential. These results advance our understanding of mire dynamics after long-term WT drawdown and of the microbiological bases of methane emissions from mires.

  nomenclature of[START_REF] Laine | Suotyypit ja niiden tunnistaminen[END_REF]) are typically sites where wet lawns and drier hummocks form a mosaic-like vegetation pattern. A groundwater extraction plant on an esker bordering the mire downstream has affected the WT at the study site since 1959, resulting in a clear hydrological gradient where the pristine wet fen (location S4) becomes semi-wet (location S3), semi-dry (location S2), and finally a dry pine dominated mesotrophic peatland forest (MtkgII, location S1).

  RFLP, approximately 25-50 ng of PCR products was digested with 3 U of MspI (Fermentas) at 37 °C overnight. The T-RFLP analysis was carried out as described in Juottonen

  potential, coverage of Sphagnum and aerenchymatic plants, and pH. To examine variation in methanogen and MOB communities, we first applied detrended correspondence analysis (DCA). Based on the DCA showing rather small compositional variation, (ter Braak & Prentice 1988) we applied redundancy analysis (RDA) to test which environmental variables best explained variation in methanogen and MOB communities. The significance of the above listed explanatory factors was assessed using Monte Carlo permutation test. The multivariate analyses were carried out with Canoco for Windows (ter Braak & Smilauer 2002).

  lower and did not differ between the locations at any depth. The laboratory measurements showed that location and depth significantly affected the CH 4 production potential through the WT gradient (p<0.001).

  the RDA T-RFs 468 and 471 were combined since the large size of T-RFs prohibited reliable

  shift in methanotroph populations showing specific pmoA allele types of

M

  allele, in respect to other ones, disappears in WT drawdown and is replaced by the O and S alleles through out the peat layer. The S allele could originate from the generalist T through a mutation in pmoA. The O has probably been introduced to the location as it contains four silent point mutations in respect with S.

  favor these aerobic bacteria. The drop is best explained by the lack of substrate; CH 4 .

Fig. 2

 2 Fig. 2 (a) The potential methane production, (b) the potential methane oxidation in the four

Fig. 4

 4 Fig. 4 (a) Redundancy analysis (RDA) of statistically significant environmental factors and

Fig. 5

 5 Fig. 5 Maximum likelihood tree of partial mcrA sequences (128 aa) from Suonukkasuo fen clones

Table 1

 1 Identification of T-RFs detected in analysis methanogens in the mires forming a water table (WT) gradient. The occurrence of PCR-T-RFLP detected methanogens in the WT gradient formed by the four locations S4-S1 and the relative abundance of T-RFs in each location.

	o
	r
	R e v i e w
	O n
	l y

b Includes T-RFs 468 and 471 bp.

Table 2

 2 Number of point mutations (integers) between different pmoA allele sequences and standard errors (in parenthesis) of pairwise distance calculations. Accession numbers in Genbank Fig. 1 Average methane emission 2001-2004 from the four locations forming a water table (WT) gradient, from wet fen location S4 to dry forested location S1.

	are GQ279342 (T), GQ279343 (S), GQ279344 (R), GQ279345 (M) and GQ279346 (O),
	respectively.
	Sequence
	of pmoA
	O	5	4	7	11
	M	12	11	12
	R	2	3
	S	1
	T
		T	S	R	M	O
	T		[0.00198 ]	[0.00286 ]	[0.00977 ]	[0.00513 ]
	S	0.00122		[0.00376 ]	[0.00918 ]	[0.00455 ]
	R	0.00244	0.00367		[0.01011 ]	[0.00648 ]
	M	0.01518	0.0139	0.01522		[0.00944 ]
	O	0.00616	0.00492	0.00867	0.01382

Global Change Biology

Acknowledgements

We thank Sirpa Tiikainen for the valuable laboratory help with MOB. This study was financed by the Academy of Finland (project number 109816).