- Top of page
- 1. Introduction
- 2. Methods
- 3. Results
- 4. Discussion
- 5. Conclusion
- Supporting Information
 N2O, CH4 and CO2 soil-atmosphere exchange and controlling environmental factors were studied for a 3-month period (dry-wet season transition) at the Kakamega Rain forest, Kenya, Africa, using an automated measurement system. The mean N2O emission was 42.9 ± 0.7 μg N m−2 h−1 (range: 1.1–324.8 μg N m−2 h−1). Considering the duration of dry and wet season the annual N2O emission was estimated at 2.6 ± 1.2 kg N ha−1 yr−1. Large pulse emissions of N2O were observed after the first rainfall events of the wet season, and the magnitude of N2O emissions steadily declined thereafter. A comparable trend in soil CO2 emissions (mean: 71.8 ± 0.3 mg C m−2 h−1) indicates that the rapid mineralization of litter accumulated during the dry period produced the high N2O emissions at the start of the wet season. Manual N2O emission measurements at four additional rain forest sites were comparable to those measured at the main site, whereas N2O emissions measured at a regrowth site were significantly lower. Spatial differences in N2O emissions could be explained by differences in soil texture and topsoil C:N-ratio (CO2: subsoil C and N concentrations), whereas the temporal variability of N2O and CO2 emissions was primarily driven by soil moisture. Soils predominantly acted as sinks for CH4 (−56.4 ± 0.8 μg C m−2 h−1). For some chamber positions, episodes of net CH4 release were observed, which could be due to high WFPS and/or termite activity. CH4 fluxes were weakly correlated with soil moisture levels but showed no relation to temperature, texture, pH, carbon or nitrogen contents.
- Top of page
- 1. Introduction
- 2. Methods
- 3. Results
- 4. Discussion
- 5. Conclusion
- Supporting Information
 Following carbon dioxide (CO2) and methane (CH4), and despite its low atmospheric concentration of 318.6 ppbv (global mean concentration 12/2004 [World Meteorological Organization (WMO), 2006]), nitrous oxide (N2O) is the third most important radiatively active greenhouse gas, contributing approximately 6% to the total observed global warming at present [WMO, 2006]. Soils are the major source of N2O emissions and the contribution of soils to the total atmospheric N2O budget is estimated at 57% [Mosier et al., 1998]. A major part of these soil-based N2O emissions originates from tropical rain forest regions, which are also considered to be the largest natural terrestrial source [Mosier et al., 1998; Kroeze et al., 1999]. On the basis of the available field measurements, the global contribution of tropical forest soils to the annual N2O budget was estimated to range between 14 and 23% [Intergovernmental Panel on Climate Change, 2001; Mosier et al., 1998]. By applying a soil classification system related to substrate availability, the N2O source strength of moist tropical forest ecosystems was estimated to be in the range of 2.4–3.5 Tg N2O-N a−1 [Matson and Vitousek, 1990; Breuer et al., 2000]. However, it has to be stressed that these estimates are based on very simple empirical upscaling approaches.
 It is generally accepted that, despite their importance, N2O emissions from tropical rain forest ecosystems are still poorly characterized [Serca et al., 1994; Breuer et al., 2000; Kiese et al., 2005]. Furthermore, the majority of N2O measurements have been made in the Amazonian and Central American region [e.g., Matson et al., 1990; Steudler et al., 1991; Keller and Reiners, 1994; Riley and Vitousek, 1995; Verchot et al., 1999] and most of our knowledge is still based on a relatively small number of individual flux measurements (as described by Breuer et al. ). The only data set of N2O emissions from tropical rain forest soils of the African continent was published by Serca et al. , who worked in the Congo region. To our knowledge, since then, no other attempt has been made to investigate N2O emissions from tropical rain forest soils in Africa. The same partly applies to the Asian region, for which N2O emission measurements have been published only in recent years [Ishizuka et al., 2002, 2005a, 2005b; Hadi et al., 2005; Hall et al., 2004; Purbopuspito et al., 2006]. However, the number of investigations is still small compared to the size and heterogeneity of the region. Long-term N2O flux measurements of high (subdaily-daily) temporal resolution have only been obtained from the Australian “wet tropics” [Breuer et al., 2000; Butterbach-Bahl et al., 2004; Kiese and Butterbach-Bahl, 2002; Kiese et al., 2003] and recently from a seasonally dry rain forests of southwest China [Werner et al., 2006].
 Advanced techniques, namely computational upscaling approaches, which link detailed geographic information systems (GIS) to mechanistic biochemical models like CASA [Potter et al., 1993], CENTURY [Parton et al., 1988] or PnET-N-DNDC [Li et al., 2000; Stange et al., 2000] to calculate regional or global emission inventories [Kesik et al., 2005; Kiese et al., 2005; Potter et al., 1996] have the potential to further improve our current understanding of the soil contribution to the atmospheric budgets of the environmental important of soil-based emissions of trace gases such as N2O, CH4 and CO2 [e.g., Davidson et al., 1998; Li, 2000; Butterbach-Bahl et al., 2001, 2004]. However, models operating on a daily time step (e.g., PnET-N-DNDC, DayCENT) require trace gas flux measurements of a high temporal resolution and from a variety of sites for adequate model testing [Kiese et al., 2005].
 Suitable data sets for model testing are provided by automatic measurement systems that can measure soil-atmosphere greenhouse gas (GHG) fluxes in subdaily resolution. The high resolution and continuity of these flux measurements means that short-term variability in flux rates in response to changing environmental conditions can provide direct insights into the factors governing N2O emissions from the soil to the atmosphere [Butterbach-Bahl et al., 2004].
 In view of the fact that GHG fluxes in tropical rain forest systems of Africa have been poorly studied, we deliberately carried out our study in Kenya. Our main aim was to quantify the magnitude of soil N2O emissions, but also CO2 and CH4 fluxes for sites with different land use histories (primary forest and artificial reforestation) in the defined region of the tropical rain forest of Kakamega, Kenya, during the beginning of the rainy season. Furthermore, we aimed to determine whether the factors governing the temporal and spatial variability of GHG fluxes in earlier studies, i.e., soil properties and soil moisture [e.g., Verchot et al., 1999; Breuer et al., 2000], are of the same importance in Kenya.
- Top of page
- 1. Introduction
- 2. Methods
- 3. Results
- 4. Discussion
- 5. Conclusion
- Supporting Information
 To our knowledge, the reported N2O, CH4 and CO2 fluxes obtained from April to June 2004 in the Kakamega National Forest in western Kenya represent the first high-detail data set of soil-atmosphere trace gas exchange from tropical forest ecosystems on the African continent. We were able to continuously record a total of 3637 N2O fluxes from twelve chamber positions at the site S1 with the automated measurement system. To characterize the spatial variability of N2O soil-atmosphere gas exchange, additional manual measurements were conducted at four rain forest plots (S2, C1, C2 and I1) and one artificial regrowth site (I2) by making four replicate chamber measurements at each site on several occasions throughout the field campaign. For these manual samples, a total of 38, 36, 40, 37 and 20 N2O emissions were recorded for the sites S2, C1, C2, I1 and I2, respectively.
 With mean N2O emissions ranging from 34.3–67.0 μg N m−2 h−1 for site Salazar 1, and 18.7–32.1 μg N m−2 h−1 for the manually measured rain forest sites, the soils of the Kakamega forest emitted comparable levels of N2O as reported by Serca et al.  for the Mayombe Forest in Congo (mean flux rainy season 1991: 19.6 μg N m−2 h−1 [number of flux measurements = 8]; mean flux at the end of a rainy reason 1991: 207.0 μg N m−2 h−1 [n = 6]). While the annual rainfall amount was comparable (Congo, Mayombe Forest: 1400 mm; Kakamega: 1662 mm), the carbon and nitrogen stocks of the topsoil layer at the Mayombe Forest, Congo, were lower (1.7–4.5% SOC, 0.1–0.3% total N) than those at our sites (7.9–20% SOC, 0.5–1.6% total N), and the C:N-ratio (15:1) approximately 45% greater. However, it has to be noted that the N2O measurements reported by Serca et al.  were done during campaigns lasting 3–7 days each, so that the spatial and temporal dynamics of N2O fluxes may not be well represented.
 In our study, we recorded individual N2O fluxes of up to 324.8 μg N m−2 h−1 (maximum six-chamber average: 163 μg N m−2 h−1), which is of a similar magnitude to the reported maximum N2O emissions of 492.1 μg N m−2 h−1 and 570.8 μg N m−2 h−1 for Australian rain forest soils by Breuer et al.  and Kiese and Butterbach-Bahl . Nitrous oxide emissions were observed to vary on the spatial and temporal scale (see Figures 4 and 7 and Table 2). The mean N2O emission at the main rain forest site (S1) was 42.9 μg N m−2 h−1, which is close to the mean N2O emission calculated from the data obtained under comparable hygric conditions (literature review by Breuer et al. : min: 1.7, mean: 49.3; max: 123.5 μg N m−2 h−1).
 It has been shown in various field and laboratory studies of temperate forest soils that a strong positive correlation between temperature and N2O emissions exists [e.g., Brumme, 1995; Papen and Butterbach-Bahl, 1999]. However, for tropical rain forest ecosystems it could be demonstrated that such a relationship is weak [Breuer et al., 2000] (r2 = 20%) or even not existent [Kiese and Butterbach-Bahl, 2002], since the daily and seasonal temperature amplitude in tropical climates is small. Our results on the temperature dependency of N2O emissions, revealed that soil temperature (15 cm) could explain <1% of the N2O emissions variability, which is in agreement with previous emission studies in the tropics.
 Since soil microbial activity is highly affected by soil moisture levels, which in turn also determines soil aeration, microbial based nitrogen emissions in tropical environments are predominantly governed by WFPS [e.g., Linn and Doran, 1984; Firestone and Davidson, 1989; Davidson, 1991; Kiese and Butterbach-Bahl, 2002]. Two main processes, nitrification and denitrification, are involved in N2O production, consumption and emission. Nitrification, an aerobic process, is optimal at near field capacity conditions, whereas denitrification, an anaerobic process, increases greatly above a WFPS of 80%. However, N2 instead of N2O is the main form of N-trace gas production under near, or complete, saturation conditions [Linn and Doran, 1984; Bateman and Baggs, 2005]. On the basis of these findings, maximum N2O emissions can be expected at WFPS between 50 to 80% or 60 to 90%, depending on soil physical properties [Davidson, 1991; Bouwman, 1998; Bateman and Baggs, 2005]. This general textbook understanding of N2O production is also reflected in our detailed measurements at the main rain forest site (S1), where N2O emissions were highest at WFPS levels of 65% and decreased with further increases in soil moisture.
 Figure 9 illustrates the N2O emission response to observed WFPS values for this study, as compared to other studies in rain forests in Australia, Brazil, China and Costa Rica (see Table 5 for site details). Although a quantitative comparison is hampered by differing sampling durations, whole year cycles (Kauri Creek, Bellenden Ker, La Selva, Pará) or single seasons (e.g., transition period, Xishuangbanna, China; end of dry season–early rainy season, Kakamega, Kenya), and different sampling frequencies (subdaily, daily average, monthly), a universal dependency of N2O emissions on WFPS levels can be observed (see Table 5 and Figure 9). WFPS above 30–50% led to strong increases of N2O emissions on all sites, though the absolute level of N2O emission differs significantly among the sites.
Table 5. Comparison of Site Characteristics Used for the Histogram of WFPS Classes and Corresponding N2O Emission in Figure 9a
|Site||Altitude, m a.s.l||MAP, mm yr−1||Soil||Flux Measurements||Source|
|Texture, %||SOC, %||C:N-Ratio||Duration||n||N2O, μg N m−2 h−1|
|Kakamega Forest (Kenya)||1600||1662||43||23||34||3.50||10.4||Apr–Jun 2004||64b||8.3–130.9||this study|
|Lake Eacham (Australia)||790||1500||68||11||21||2.34||15.8||May–Jun 1997||177c||0.9–192.0||Breuer et al. |
|Kauri Creek (Australia)||790||1594||68||9||23||3.22||14.6||Jan–Dec 2000||44b||5.8–125.8||Kiese and Butterbach-Bahl |
|Bellenden Ker (Australia)||80||4395||57||21||22||3.11||12.1||Nov 2001 to Oct 2002||50b||1.2–32.7||Kiese et al. |
|Pará (Brazil)||200||1850||n.d.||n.d.||n.d.||2.45||11.1||Feb 1995 to May 1996||14d||6.3–83.0||Verchot et al. |
|La Selva (Costa Rica)||100||3962||n.d.||n.d.||n.d.||n.d.||n.d.||Oct 1990 to Nov 1991||10d||6.9–154.3||Keller and Reiners |
|Xishuangbanna (China)||770||1490||59||23||18||1.90||10.0||Feb–Apr 2005||53b||2.3–9.0||Werner et al. |
 The dependency of N2O emissions to changes in WFPS were reported to follow a linear as well as exponential relationships in Australian rain forest soils (WFPS levels ranging from 10 to 50% [Breuer et al., 2000; Kiese et al., 2003; Butterbach-Bahl et al., 2004]). For our data set, a peak function (using WFPS) was able to explain 68% of the observed variability in N2O emissions (note that the first two weeks of N2O measurements were excluded for this analysis; see Figure 6). Since we did not encounter any WFPS levels above 75% (where a shift in denitrification products from N2O to N2 would be expected), our observations may well fit into the broader N2O:WFPS-emission-dependency models as described by Bouwman , Bateman and Baggs  or Ridolfi et al. , and the N2O emission results from Australian soils reported above. However, as reported by Butterbach-Bahl et al.  for the sites in Australia, and by Werner et al.  for a seasonally dry rain forest in southwest China, this N2O emission dependency on WFPS levels is further affected by the availability of substrates for nitrification and denitrification.
 Given a sufficient number of flux measurement, the short-term variation in N2O emission from tropical forest soils was reported to depend mainly on soil moisture, whereas the long-term or seasonal pattern can often be explained by decomposition rates and the resulting changes in available soil nitrogen [e.g., Davidson et al., 1993; Kiese et al., 2003]. Highest N2O emissions from rain forest soils were found during the transition period from the dry to wet season, and during the wet season [e.g., Breuer et al., 2000; Butterbach-Bahl et al., 2004; Davidson et al., 1993, 2004; Keller and Reiners, 1994; Kiese and Butterbach-Bahl, 2002; Kiese et al., 2003; Vasconcelos et al., 2004]. In the transition period, accumulated litter (above and below ground) is often rapidly mineralized within the first weeks of soil rewetting, leading to large pulse emissions of N2O, but also NO emissions [Davidson et al., 1993; Butterbach-Bahl et al., 2004]. We also observed marked N2O emission pulses following precipitation events during the first two weeks of the measurements, i.e., shortly after the start of the rainy season. During this period, the increase in N2O emissions in response to elevated WFPS was more pronounced than that in the following periods of measurements (see Figures 4 and 5). We therefore assume that in the first weeks of measurements, the high N2O emissions reflected accelerated mineralization activity which slowed down over time. This interpretation is inline with the observed trend in soil CO2 emission (Figure 4; N2O and CO2 emissions were positively correlated [r2 = 0.65; P < 0.01; data not shown]) as well as with the soil moisture corrected trend in N2O emissions (Figure 5), which shows that for a given WFPS range, N2O emissions decreased toward the end of the measurements. Both observations can be explained by decreasing availability of mineralized substrate.
 While the short-term variability of N2O emissions is generally controlled by changes of soil temperature, soil moisture, nutrient availability and microbial activity, the general emission potential is predominantly controlled by (1) soil texture which defines the aeration of the soil and thus the environmental conditions for the microbial biomass and processes and (2) carbon and nitrogen stocks in the soil [e.g., Li et al., 2005]. For instance, microbial N biomass and mineralization are positively correlated to soil C and N concentrations and negatively correlated to the C:N-ratio [Booth et al., 2005]. The importance of different soil parameters for explaining the spatial variability of N2O emissions in our study was assessed with a multiple linear regression analysis. On the level of individual chambers, differences in the magnitude of N2O emissions could best be explained by differences in the fraction of sand [%] and the C:N-ratio in the organic topsoil (Table 4). Site differences in N2O emissions between the different rain forest sites and the reforestation site could be explained mainly by differences in the C:N-ratio (negatively correlated) of the organic topsoil and, furthermore by differences in the clay content of the topsoil (negatively correlated) (Table 4). The importance of the C:N-ratio as a scalar to explain site differences in N2O emissions is in agreement with previous observations by Breuer et al.  and Kiese and Butterbach-Bahl  for Australian rain forest soils, Davidson et al.  for different rain forest sites in Central and South America and by Klemedtsson et al.  for forested drained Histosols in northern Europe.
 There were striking differences in the soil properties and N2O emissions of our rain forest plots and those of the artificial regrowth plot, Isecheno 2 (Table 1 and Figure 7). The average N2O emission of 8.8 ± 2.9 μg N m−2 h−1 at the regrowth site (I2) was significantly (53 to 75%) lower than those observed at all rain forest sites (Table 3). In the topsoil samples, significantly lower carbon concentrations (7.9%) and the lowest nitrogen concentrations (0.53%) were measured at site I2, while the texture was similar to the other sites. The C:N-ratios at the regrowth site (I2) were greater than those of the rain forest sites (topsoil: 24–35%; litter layer: 80–130%). These changes in soil properties and litter quality have obviously altered C- and N-trace gas exchange. If we use the C:N-ratio of the litter as an indicator of nitrogen availability at the site scale as proposed by Davidson et al. , the observed reduction in N2O emissions can easily be explained by a degradation of the site and a reduction in N cycling.
 In summary, one can conclude that the driving factors for N2O emissions in the rain forest system in Kenya were comparable to those observed in other studies of N2O emissions from tropical rain forest systems. Also, the weighting of individual factors, i.e., dominance of soil moisture over temperature effects, was comparable to those of earlier studies.
 For estimating the annual N2O emission rate we used a simple approach based on mean N2O emission representative for different hygric conditions (e.g., applied in most of the cases compiled by Breuer et al. ). The annual N2O emission of a site is calculated by weighting the average N2O emission of the dry season and the wet season with the respective durations (5 months dry season and 7 months wet season; see Figure 2). We used the average of daily N2O emissions from 6 April to 10 June (45.5 ± 20.1 μg N m−2 hr−1/10.9 ± 4.8 g N ha−1 day−1) as an approximation for the average N2O emission level under wet season conditions. A representative mean dry season emission (8.5 ± 5.0 μg N m−2 hr−1/2.0 ± 1.2 g N ha−1 day−1) was estimated by taking into account only the last seven days of measurements when rainfall and soil moisture levels were lowest. N2O emissions of around 10 μg N m−2 h−1 were reported in several other studies as typical emission level during dry season conditions (e.g., compilation of Breuer et al. ). Using this approach, the annual N2O emission for the main primary rain forest site (S1) can be estimated to be 2.6 kg N ha−1 yr−1. To give an indication for the level of uncertainty in these calculated annual N2O emissions, the same weighted calculation was performed using the standard deviation of the calculated mean flux rates for wet and dry season conditions (1.2 kg N ha−1 yr−1). The estimated annual N2O emission for site S1 may therefore range between 1.4 and 3.8 kg N ha−1 yr−1, which is in the range of annual estimates for other tropical rain forests worldwide (between 1 and 3 kg N ha−1 yr−1 [e.g., Riley and Vitousek, 1995; Verchot et al., 1999; Breuer et al., 2000; Melillo et al., 2001; Kiese et al., 2005]).
 The soil-atmosphere exchange of methane is the result of simultaneously occurring production and consumption processes in soils, and is thus controlled by CH4-producing methanogens operating at anaerobic conditions and CH4-consuming methanotrophs that depend on oxygen as a terminal electron acceptor [Topp and Pattey, 1997]. Activity and population sizes of these microbes are depending on a multitude of soil factors, like aeration of the soil profile, substrate availability, pH, soil moisture and soil temperature [e.g., Chan and Parkin, 2001; Conrad, 1996; Khalil and Baggs, 2005; Smith et al., 2003; Topp and Pattey, 1997]. Since methane production usually requires prolonged periods of waterlogging, which is rarely encountered in upland soils, tropical upland forest soils predominantly act as sinks for atmospheric CH4 [e.g., Butterbach-Bahl et al., 2004; Delmas et al., 1992; Ishizuka et al., 2002; Keller et al., 1986; Keller and Reiners, 1994; Kiese et al., 2003; Weitz et al., 1998; Werner et al., 2006].
 We observed a mean CH4 uptake rate of 56.4 ± 0.8 μg C m−2 h−1 (n = 1458) and maximum CH4 uptake rate of 146.9 μg C m−2 h−1 at the site S1. The mean CH4 uptake rate for the site S1 is higher than previously reported mean CH4 uptake rates for other tropical rain forest ecosystems of Asia and South and Central America, which are in a range of 29.4–39.4 μg C m−2 h−1 [e.g., Keller and Reiners, 1994; Kiese et al., 2003; Verchot et al., 2000; Weitz et al., 1998; Werner et al., 2006]. However, this difference may be explained by the seasonality of CH4 exchange, sampling frequencies, spatial coverage and differences in soil properties such as texture. Atmospheric CH4-uptake by soils is largely controlled by gas diffusion resistance within the soil. Therefore the structure of the forest floor layer [e.g., Dong et al., 1998; Brumme and Borken, 1999], which is mostly missing or only rudimentary developed in rain forest ecosystems, and the texture of the mineral soil [e.g., Dörr et al., 1993; Boeckx et al., 1997], have a huge effect on the magnitude of CH4 uptake rates in forest soils. Even though we have not measured the diffusivity of the soil at our study site S1, one can assume that the high sand content of 43% provides sufficient aeration of the topsoil and does not inhibit CH4 oxidation activity.
 Because of its effect on gas diffusion, soil moisture is the dominant factor controlling the seasonality of CH4 uptake in tropical systems [e.g., Keller and Reiners, 1994; Verchot et al., 2000; Kiese et al., 2003; Werner et al., 2006]. However, in our study the effect of soil moisture changes on CH4 uptake rates was less pronounced than that in previous studies. Only at the beginning of the measurements, when WFPS values exceeded 60%, was there a pronounced reduction in CH4 uptake.
 Even though our site was generally functioning as a sink for atmospheric CH4, occasionally when WFPS was great, some chamber positions showed surprisingly strong CH4 emissions of up to 99.7 μg C m−2 h−1. Obviously, increased soil moisture and, thus, reduced O2 penetration into the soil profile, effected the soil at these chamber positions in such a way that the soil switched from an atmospheric CH4 sink to a source of CH4. Moreover, while taking soil samples at the end of our measurements, we found a crumbled soil structure in sections of the relevant chamber positions suggesting termite activity. Termite mounds were present 200 m away from our plot at S1. It is well known that termites can produce considerable amounts of CH4 during their digestion processes [MacDonald et al., 1998; Sanderson, 1996; Bignell et al., 1997]. Therefore the sporadic CH4 emission activity at some of our measuring positions may also be due to the combined effect of termite activity [Eggleton et al., 1999; MacDonald et al., 1998, 1999] and increased anaerobiosis resulting from elevated soil moisture.
 The variation in soil-atmosphere exchange of CH4 at site S1 did not change significantly during the measurement campaign, even though the number of successful flux measurements, decreased toward the end of our field campaign (Figure 4). We therefore calculated the annual CH4 soil-atmosphere exchange rate for the main primary rain forest site (S1) by multiplying the average CH4 exchange rate (−54.6 ± 7.9 μg C m−2 h−1/−13.1 ± 1.9 g C ha−1 day−1) by 365 days. Using this approach, the cumulative annual soil-atmosphere exchange of CH4 at site S1 is −4.8 ± 0.7 kg C ha−1 yr−1.
 Previously, Ishizuka et al. , Kiese and Butterbach-Bahl  and Werner et al.  reported CO2 emissions of 51.3–93.7 mg C m−2 h−1, 20.3–247.7 mg C m−2 h−1 and 18.1–131.6 mg C m−2 h−1 for primary rain forest soils of Indonesia, Australia and southwest China, respectively. Sotta et al.  described the mean annual CO2 efflux from soils of the Amazon region to range between 44.6–76.3 mg C m−2 h−1, while soil CO2 emissions were considerably lower (20.2–40.4 mg C m−2 h−1) during the dry season and higher (>85 mg C m−2 h−1) during the wet season. At the Kakamega Forest of western Kenya we recorded a mean soil respiration rate of 71.8 mg C m−2 h−1 (range: 22.3–155 mg C m−2 h−1), which is consistent with previously reported values. Our coefficients of variation of 16.2–26.7% were in good agreement with results from La Scala et al.  and Kiese and Butterbach-Bahl , who reported values of 21.1–31.7% and 11.5–36.7%, respectively. Measurements of soil CO2 emissions further suggested that most mineralization activity happened at the beginning of the measurements, i.e., at the onset of the rainy season. Toward the end of the measurements, soil CO2 emissions declined, most likely because of the decreased availability of easily degradable substrate, rather than moisture limitation. Using total carbon and nitrogen concentrations of the subsoil, we were able to explain 89% of the observed variation in CO2 flux between the ten chamber positions, while the other input parameters were rejected by the multiple linear regression model because of insignificance.
 The cumulative CO2 emission for one year ranges between 4.5 and 6.5 t C ha−1 (5.5 ± 1.0 t C ha−1) when the same upscaling approach, as used for N2O, is applied.