Plant Soil (2008) 309:211–226 DOI 10.1007/s11104-008-9545-0

REGULAR ARTICLE

Site specific and regional estimates of methane uptake by tropical rainforest soils in north eastern Australia R. Kiese & S. Wochele & K. Butterbach-Bahl

Received: 28 August 2007 / Accepted: 7 January 2008 / Published online: 25 January 2008 # Springer Science + Business Media B.V. 2008

Abstract Methane flux from rainforest soils in northeast Queensland, Australia, was investigated using a combination of laboratory, field and simulation modelling. In aerobic laboratory incubations, CH4 uptake in the top 0.1 m of the soil (−2.5 to −7.3 μg CH4 kg−1 SDW day−1) is approximately one order of magnitude higher than CH4 production under anaerobic conditions. The highest CH4 uptake, as well as potential CH4 production is found in the uppermost C rich soil layers. Detailed measurements from three contrasting rainforest sites identified the soils to be functioning as sinks for atmospheric CH4. Fifteen months continuous measurement at one of the lowland rainforest sites showed that the seasonality of CH4 uptake was mainly driven by changes in soil moisture rather than by temperature changes. Maximum CH4 uptake (109 μg CH4 m−2 h−1) was observed during dry season conditions, whereas during the wet season, CH4 uptake decreased significantly to near zero. Based on our laboratory experiments and on published literature we developed a semi-empirical CH4 module for the biogeochemical model ForestDNDCtropica. Tests at several sites showed the robustness of our modelling Responsible Editor: Ute Skiba. R. Kiese : S. Wochele : K. Butterbach-Bahl (*) Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Forschungszentrum Karlsruhe, Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, Germany e-mail: [email protected]

approach with mean simulated values within 12% of observed values. To estimate regional CH4 uptake by rainforest soils in the region of the ‘Wet Tropics’, Queensland, Australia, we linked CH4 uptake and production algorithms to a regional GIS database. We estimated that the lowland and montane rainforest soils in northeast Queensland, Australia, were a net sink for CH4 with a mean uptake rate of −2.89 kg CH4 ha−1 year−1 during July 1996 to June 1997 period. Keywords CH4 oxidation . Depth profile . Biogeochemical model . GIS

Introduction Within the global atmospheric CH4 budget, uptake of atmospheric CH4 by upland soils is estimated to be 30 Tg year−1, which is equivalent to 5% of all sinks for atmospheric CH4 (~90% oxidation with OH radicals, ~5% stratospheric loss). This estimate is rather uncertain with best estimates ranging between 20– 51 Tg CH4 year−1 (e.g. Smith et al. 2000). Methane uptake by soils can be influenced by land use and management (Smith et al. 2000; Castaldi et al. 2007) and does depend on environmental conditions such as soil properties and climatic conditions (e.g. Adamsen and King 1993; Boeckx et al. 1997; Steinkamp et al. 2001). The exchange of CH4 between soils and the atmosphere is the net result of simultaneous microbial production of CH4 in predominantly anaerobic zones

212

Plant Soil (2008) 309:211–226

of the soil and microbial oxidation of CH4 in predominantly oxic zones of the soil (Conrad 1996). Therefore, predominantly anaerobic soils such as e.g. hydromorphic or submerged soils tend to be netsources for CH4, whereas predominantly well aerated soils are usually sinks for CH4 in a range of 1–10 kg CH4–C m−2 h−1. Since CH4 uptake is largely dependent on the diffusion of oxygen and CH4 to the sites of activity, soil moisture and texture are the predominant controls of CH4 uptake in natural and seminatural ecosystems (e.g. Borken et al. 2006). It is not well understood if upland tropical rain forest soils are potential sinks or sources in the global atmospheric CH4 budget. The prevailing moist conditions, in often fine textured soils, as well as the rapid mineralization of organic material in the top soil may favour anaerobic conditions and, thus, may hamper increased CH4 oxidation. Recent measurements for different tropical rainforest sites in Australia, tropical China and Kenya, suggest, that even under wet season conditions CH4 uptake may be significant (Kiese et al. 2003; Werner et al. 2006, 2007). To contribute to a better understanding of CH4 uptake activity in tropical rain forest soils and to estimate the regional sink strength of tropical rain forest soils in Queensland, Australia, we combined field measurements on CH4 exchange with laboratory experiments on CH4 oxidation and production.

Results of both approaches were used to develop a simplified CH4 uptake simulation module for a complex biogeochemical model. This model was then coupled with a geographic information systems (GIS) to calculate a regional inventory of CH4 uptake activity for the region of the “Wet Tropics”, Queensland, Australia.

Materials and methods Study area Field measurements of fluxes, soil sampling for additional parameterisation data and regional modelling of CH4 uptake was centred on the World Heritage area of the ‘Wet Tropics’ in northeast Queensland Australia. The study area (approximately 9,000 km2; Kiese et al. 2005) comprises the largest block of rainforest in Australia (4,011 km2 of rainforests) and includes lowland tropical rainforests along the coast (0–80 m a.s.l.) as well as montane tropical rainforest (700–900 m a.s.l.) on the Atherton Tablelands. In this study we included three measuring sites, two in the coastal lowlands (Bellenden Ker and Pin Gin Hill) and one on the Atherton Tablelands (Kauri Creek). Site characteristics are provided in Table 1, with further details found in Breuer et al. (2000) and Kiese

Table 1 Location and main characteristics of the different measuring sites and periods of field measurements

Coordinates Mean annual precipitation (mm) Mean annual temperature (°C) Soil type pH±SE Bulk density 0–5 cm (g cm−3) C/N ratio Organic C content (%) Soil texture Field measurement periods

Kauri Creek

Bellenden Ker

Pin Gin Hill

145°38′E 17°17′S 1,594a 20.9a Ustochrept 5.2±0.08 1.05±0.05 14.6 2.93–3.51b Sandy clay loam 19/11/00–15/12/00

145°54′E 17°16′S 4,395b 24.3b Ustochrept 4.1±0.03 1.09±0.03 12.1 3.11 Sandy clay loam 17/11/01–18/10/02

145°58′E 17°33′S 3,609a 24.1a Krasnozem 4.7±0.06 0.79±0.02 13.8 9.15 Clay 20/10/00–12/11/00

For further information see Breuer et al. (2000) and Kiese and Butterbach-Bahl (2002). All soil parameters are given for 0–10 cm soil depth. a

Spain et al. (1989)

b

Data from Bureau of Meteorology, Brisbane

Plant Soil (2008) 309:211–226

and Butterbach-Bahl (2002). Significant differences in climate conditions exist between the sites. The mean annual temperature at the Coastal Lowland sites (Bellenden Ker and Pin Gin Hill) is approx. 3.5°C higher and the mean annual precipitation (>3,600 mm) is more than twice that at the Kauri Creek site. At Bellenden Ker and Kauri Creek sites, soil texture is a sandy clay loam, whereas at the Pin Gin Hill site the soil texture is clay. Further differences between the sites exist with regard to the vegetation type (complex mesophyll vine forest at the lowland sites versus complex notophyll vine forest at the Atherton Tableland site), soil pH, soil organic carbon and C/N ratio (Table 1). Field measurements of CH4 exchange At all three sites, CH4 exchange at the soil–atmosphere interface was measured with an automated closed chamber system, consisting of five chambers, an automated sampling unit and a gas chromatograph with a Hayesep Q analytical column and a flame ionisation detector for CH4 detection. All of this was controlled via the IDAS software (IMK-IFU data acquisition software) installed on a laptop (Breuer et al. 2000; Kiese et al. 2003). The exact measurement periods are outlined in Table 1. Methane flux calculations were based on the linear change in headspace CH4 concentrations as derived from four measurements per chamber when the chambers were closed. Since the closure time of the chambers was 100 min, followed by 100 min opening time, up to seven flux measurements could be obtained per day. The system was automatically recalibrated with standard gas (1.8 ppm; Messer Griesheim, Germany) in at least hourly intervals. For further details on the system and analytical conditions see Kiese et al. (2003). Flux measurements were supplemented with daily measurements of rainfall and air temperature (1 m height) directly at the measuring sites, using manual samplers (rainfall) and PT100 sensors (temperature). Parameterisation of CH4 exchange In order to determine rates of CH4 production and consumption in different soil depths and in relation to changes in temperature, stratified soil samples were taken at the Bellenden Ker and Kauri Creek sites in May 2005, i.e. shortly after the start of the dry season.

213

Samples were taken for six different soil horizons: 0– 0.05 m, 0.05–0.1 m, 0.1–0.2 m, 0.2–0.3 m, 0.3–0.5 m and 0.5–0.7 m. Soil samples were air dried, transferred to the laboratory of IMK-IFU and processed within 7 weeks. Soil samples of 30 g (dry weight) were preincubated in 300 ml glass flasks at the respective incubation temperatures (15, 20 or 30°C) and soil moisture was adjusted in all experiments to 45% water holding capacity by adding distilled water 2 days prior to the start of the measurements. For each soil horizon, at least three samples were incubated at each temperature under both aerobic (net exchange) and anaerobic (CH4 production capacity) conditions. Following the two days of pre-incubation, the flasks were closed with butyl rubber stoppers. For anaerobic incubation the headspace air was exchanged with a high purity N2 atmosphere immediately after closure as described by Butterbach-Bahl et al. (1997) and Butterbach-Bahl and Papen (2002), whereas for aerobic incubation the headspace remained unchanged. The change in concentration of CH4 in the headspace of each flask was monitored for the next 6–12 h, involving at least four headspace gas samplings. Air samples were immediately analysed for CH4 using a gas chromatograph equipped with a FID (for details see Butterbach-Bahl and Papen 2002). Production or consumption rates were calculated on a soil dry weight basis (SDW) from the linear increase/decrease of CH4 headspace concentrations with time (Butterbach-Bahl and Papen 2002). Modelling of CH4 exchange with ForestDNDCtropica For simulating CH4 uptake by tropical rainforest soils with ForestDNDCtropica we used a comparable semiempirical approach as developed by Del Grosso et al. (2000) for the DayCent model. In this approach the magnitude of CH4 oxidation depends on soil temperature and moisture as well as on the bulk density of the topsoil (0–0.1 m). Algorithms forming a new CH4 module within the ForestDNDCtropica model were developed from previously published measurements and new data of CH4 exchange from this study as well as data from other tropical rainforest sites world wide (Keller and Reiners 1994; Kiese et al. 2003; Werner et al. 2006). ForestDNDCtropica originated from PnET-N-DNDC, a mechanistic model for prediction of soil carbon and nitrogen biogeochemistry,

214

including N-trace gas emissions, in temperate forest ecosystems (Li et al. 2000; Stange et al. 2000; Butterbach-Bahl et al. 2001). Required modifications for simulating C and N turnover and associated N2Oemissions from tropical rainforest ecosystems are described in detail in Kiese et al. 2005, and Werner et al. 2007. For evaluating the capability of the newly developed, semi-empirical CH4 module in the ForestDNDCtropica model to simulate CH4 exchange at the site scale, the model was applied to five different tropical rainforest sites from Australia, China and Costa Rica. Calculation of CH4 exchange at the regional scale For the calculation of a regional inventory of CH4 exchange for the study area of the “Wet Tropics” (4,011 km2 of tropical rainforests) we coupled the ForestDNDCtropica model, in which the equations given above were implemented, to a detailed GIS. The GIS held all relevant information on soil, vegetation and climate for initialising and driving the model. The simulation area includes lowland tropical rainforests along the coast as well as montane tropical rainforest on the Atherton Tablelands. Meteorology Data on daily rainfall and temperature for the years 1996–1997 were obtained from 61 meteorological stations within the study area from the Bureau of Meteorology, Brisbane, Australia. In view of the complex topography, the spatial interpolation of precipitation data was based on the map (grid size 80 m) of mean annual rainfall within the study area (Houlder et al. 1999). This map was superimposed with the location of 61 available climate stations to define representative polygons of precipitation using a cost-distance approach (Kiese et al. 2005). The same polygons were also used for the spatial distribution of daily temperature values. The annual sum of rainfall was variable across the study area, with values ranging from 844–8,963 mm (mean value, 2,892 mm) for the period July 1, 1996– June 30, 1997. Maximum rainfall was measured for the climate station at the summit of Mt. Bellenden Ker, located in the centre of the study area. Rainfall was significantly lower for the Atherton Tablelands (mean value, 1,685 mm) and the southern parts of the study area (mean value, 2,424 mm). Maximum annual temperatures were recorded for the tropical lowland

Plant Soil (2008) 309:211–226

areas close to the coast (24.2°C), whereas temperatures at the Atherton Tablelands were approx. 3.5°C lower. Soils Information on soil properties in the study area is detailed, with digital soil series maps for specific regions such as Townsville, Ingham, Cardwell-Tully, Babinda-Cairns, Mossman, Atherton and Ravenshoe. Information on soil properties in the uppermost 10 cm of the mineral soil, i.e. soil organic carbon (SOC), C/N ratio, soil pH, stone fraction (>2 mm) and texture were derived from various reports (Cannon et al. 1992; Heiner and Grundy 1994; Laffan 1988; Murtha 1986, 1989; Murtha et al. 1996; Malcolm et al. 1999; Wilson and Baker 1990) for each specific region. Soil properties across the study area vary significantly, e.g. pH values from 4.1 to 7.0 and SOC in a range of 0.5 to 5.9%. Rainforest distribution Rainforest distribution was derived from a digital vegetation map (Tracy 1982). In our regional simulations we only considered the following forest classifications as true rainforests: complex notophyll, notophyll, simple notophyll, complex mesophyll, mesophyll, semideciduous mesophyll, simple microphyll vine forest, mesophyll vine forest with dominant palms, simple microphyll vinefern forest, simple microphyll vine-fern thicket, deciduous microphyll vine thicket. We excluded sclerophyll forests dominated by Eucalyptus spp. as well as sites which were cleared since the early twentieth century. Information on climate, soil properties and vegetation was superimposed, with 7,538 different polygons covering a total area of 4,011 km2. For initialization of the vegetation pools across the study area we used the following estimates: 380 t of wood C ha−1, 5.6 t of leaf C ha−1 and 3.4 t of fine root C ha−1. Estimates were provided by the Tropical Forest Research Centre, Atherton, Australia. Statistical analysis Statistical analysis was performed using SPSS 8.0 (SPSS Inc., Chicago, USA) and/or Origin 7.0 (OriginLab Corp., USA) software packages. ANOVA was applied for testing for significant differences between different soil depths and sites. Model performance was documented using coefficient of determination 2 (r2), model efficiency (reff ) and normalized root mean

Plant Soil (2008) 309:211–226

215

square prediction error (RMSPEn) using the following equations: P ð ðxmod
xmod Þ*ðxmeas
xmeas ÞÞ2 2 r ¼P P 2 ðxmod
xmod Þ2 * ðxmeas
xmeas Þ P reff 2 ¼ 1


P
P

RMSPEn ¼

ðxmod
xmeas Þ2

Results

! Stratification of CH4 oxidation and production

ðxmeas
xmeas Þ2 ðxmod
xmeas Þ2 n

1=2

sd

where xmod is the simulated value, xmod is the average of all simulated values, xmeas is the value obtained from field data, xmeas is the average and SD the standard deviation of measured field data. To further evaluate the uncertainty of the ForestDNDCtropica we performed a series of sensitivity tests on the regional scale. Model sensitivity was calculated as variation of predicted average CH4 fluxes over a 1 year simulation period in response to changes in all major input and driving parameters. Each parameter P was individually increased (P1) or decreased (P0) in a range which represents the site/regional uncertainty of the respective parameter (rainfall ±30%; temperature ±10%, soil clay content ±20%; soil bulk density ±10%). The sensitive index was calculated based on the formula given by Friend et al. (1993): β¼

sign of β indicates if the correlation is positive or negative.

CH14
CH04 P1
P0 = P0 CH04

The distance of the β value from zero is proportional to the sensitivity of a given parameter and the

Under aerobic incubation conditions soil samples from both sites and for all soil depths and temperatures showed a net CH4 uptake. At both sites, the highest CH4 uptake activity was found in the uppermost soil layer(s) within the range of −2.7 to −7.5 μg CH4 kg−1 SDW day−1 (Table 2). Methane uptake decreased with increasing soil depth and was close to zero at all temperatures investigated at a soil depth of 0.6 m (Figs. 1 and 2, Table 2). For most soil layers CH4 uptake activity was positively correlated with temperature, with the highest CH4 uptake found at an incubation temperature of 30°C. To identify potential CH4 production, soil samples from different soil depths of both sites were incubated under anaerobic conditions. Figures 1 and 2 show that at both sites CH4 production in the uppermost 0.3 m was (for all temperatures) approximately one order of magnitude lower than CH4 uptake activity under aerobic incubation conditions. At both sites, the highest CH4 production potential was found for the uppermost soil layer, decreasing with soil depth, and in tendency, a relative increase of CH4 production in the lowest (60 cm) soil layer investigated (Table 3). Only a weak effect of incubation temperature on CH4 production was found. The temperature effect could be positive or negative, thus, indicating that without

Table 2 Mean CH4 uptake (±SE, N≥3) under aerobic incubation conditions for different soil layers and incubation temperatures for the sites Kauri Creek (montane) and Bellenden Ker (lowland) Soil depth (cm)

Kauri Creek 15°C

2.5 7.5 15 25 40 60

−3.4±0.15 −2.5±0.10 −2.2±0.03 −1.9±0.10 −0.3±0.01 −0.1±0.01

aAa bA cA dA eA eA

Bellenden Ker 20°C

30°C

−4.3±0.24 aA −3.9±0.17 abA −3.1±0.55 acAB −3.5±0.45 abB −2.3±0.11 cBa −0.9±0.14 dA

−5.6±1.67 −4.5±1.19 −4.8±1.03 −4.1±0.64 −2.0±0.46 −0.8±0.55

aA abA aB acB bcB cA

15°C

20°C

30°C

−2.7±0.10 aAa −1.7±0.57 bA −1.7±0.49 bA −1.9±0.14 abA −0.3±0.03 cA −0.03±0.02 cA

−4.2±0.19 aAB −3.8±0.15 abAB −2.9±0.17 cdA −3.4±0.16 bcAB −2.8±0.15 dBa −1.1±0.11 eB

−7.2±1.73 −7.3±1.65 −6.3±1.49 −4.9±1.20 −2.6±0.58 −1.0±0.19

aB aB abB acB bcB cB

Lower case letters indicate significant differences (p≤0.05) between layers for a given site and incubation temperature, whereas uppercase letters are used for indicating significant effects of temperature on CH4 uptake for a given layer at a site. a

Indicate significant site differences for a given soil layer and a given temperature.

216

0 10 20

Soil depth [cm]

Fig. 1 CH4 consumption/ production for different soil depths and different incubation temperatures under aerobic/anaerobic incubation for the lowland rainforest site Bellenden Ker. Provided are mean values of at least three replicates ±SE

Plant Soil (2008) 309:211–226

30 40 50 aerobic aerobic aerobic

60 70 -10,0

-7,5

anaerobic [15°C] anaerobic [20°C] anaerobic [30°C]

-5,0

-2,5

0,0

0,5

-1

1,0

-1

CH4-uptake [µg CH4kg SDW day ]

substrate additions CH4 production was close to its detection limit. CH4 exchange at the field scale At the lowland rainforest site at Bellenden Ker CH4 fluxes were measured continuously from mid November 2001 to end of January 2003 (Fig. 3). For the entire measuring period the site always functioned as a sink for atmospheric CH4. Highest CH4 uptake (up to −109 μg CH4 m−2 h−1) was observed during dry season conditions (June–November). During the wet 0 10 20

Soil depth [cm]

Fig. 2 CH4 consumption/ production for different soil depths and different incubation temperatures under aerobic/anaerobic incubation for the montane rainforest site Kauri Creek. Provided are mean values of at least three replicates ±SE

season (November/December–April), periods with pronounced rainfall episodes led to sharp decreases of CH4 uptake (Fig. 3). Figure 4 also indicates pronounced spatial variability in CH4 uptake, with uptake values in the individual chambers differing by a factor of three at times. The average CH4 uptake over the entire observation period was −35.1±0.2 μg CH4 m−2 h−1. Further details on CH4 fluxes at the Bellenden Ker site are described by Kiese et al. (2003) and Butterbach-Bahl et al. (2004). Automated CH4 flux measurements at the montane rainforest site Kauri Creek and the lowland rainforest

30 40 50 aerobic aerobic aerobic

60 70 -10,0

-7,5

anaerobic [15°C] anaerobic [20°C] anaerobic [30°C]

-5,0

-2,5

0,0

0,5 -1

1,0 -1

CH4 consumption/production [µg CH4kg SDW day ]

Plant Soil (2008) 309:211–226

217

Table 3 Mean CH4 production (±SE, N≥3) (μg CH4 kg−1 SDW day−1) under anaerobic incubation conditions for different soil layers and incubation temperatures for the sites Kauri Creek (montane) and Bellenden Ker (lowland) Soil depth (cm)

2.5 7.5 15 25 40 60

Kauri Creek

Bellenden Ker

15°C

20°C

30°C

15°C

20°C

0.6±0.16 aA 0.3±0.10 abA 0.2±0.07 bA 0.3±0.07 abA 0.5±0.04 aA 0.5±0.11 aA

0.3±0.10 aA 0.1±0.08 aA 0.1±0.05 abA 0.1±0.02 abA 0.04±0.02 abA 0.1±.0.10 abB

0.5±0.06 abA 0.7±0.1 aB 0.2±0.02 bA 0.3±0.05 bA 0.4±0.20 bA 0.2±0.04 bB

0.5±0.12 aA 0.5±0.12 abA 0.3±0.15 bA 0.2±0.11 bA 0.3±0.25 bA 0.3±011 abA

0.6±0.21 0.3±0.08 0.2±0.07 0.3±0.06 0.1±0.09 0.3±0.13

30°C aA abA bA bA bA abA

0.3±0.18 0.7±0.19 0.3±0.06 0.2±0.04 0.2±0.14 0.1±0.03

aA bA aA aA aA aA

Lower case letters indicate significant differences (p≤0.05) between layers for a given site and incubation temperature, whereas uppercase letters are used for indicating significant effects of temperature on CH4 uptake activity for a given layer at a site.

site Pingin Hill cover the transition period from dry to wet season of the year 2000 (Fig. 4). The measuring period is rather short, i.e. 3 weeks for Kauri Creek and approximately 4 weeks at Pingin Hill, respectively. For Kauri Creek no clear temporal trend in CH4 uptake activity was observed. The mean CH4 uptake was −36.0±0.5 (range, −16 to −63) μg CH4 m−2 h−1. Data for Pingin Hill show that a major rainfall event did reduce CH4 uptake. For this site the mean CH4 uptake was −43.5±0.6 (range, −12.6–74.7) μg CH4 m−2 h−1.

the ForestDNDCtropica. To evaluate the dependency of CH4 uptake with bulk density we used previously published measurements and new data of CH4 exchange from the study area as well as data from other tropical rainforest sites world wide (Keller and Reiners 1994; Kiese et al. 2003; Werner et al. 2006). Maximum observed CH4 uptake rates for different sites decrease with increasing top soil bulk density (Fig. 5). Mathematically, this dependency can be described by the following Eq. 1: MaxCH4 Uptake½g CH4 ha
1 day
1 

Simulation of CH4 fluxes using ForestDNDCtropica

(1)

p < 0:005 bd = bulk density (g cm−3) 200

30

150

25

100

20

50 0 0

-20

-20

-40

-40

-60

-60

-2

CH4-flux

-1

[µg CH4 m h ]

0

-80 1 Nov 2001

-80

1 Jan 2002

1 Mar

1 May

1 Jul

1 Sep

1 Nov

1 Jan 2003

Precipitation [mm]

Fig. 3 Air temperature, precipitation and CH4 fluxes at the Bellenden Ker site. CH4 fluxes were measured with five static chambers in sub-daily resolution. Provided are individual chamber fluxes (dots) as well as the simulated CH4 flux (line) using ForestDNDCtropica

Air temperature [°C]

For simulating CH4 exchange of tropical rainforest soils and the atmosphere we implemented a semiempirical approach using soil temperature and moisture as well as the bulk density of the topsoil (0–0.1 m) into

¼
13:4
14:0 bd þ13:2bd2 ; r 2 ¼ 0:981;

150

25

100

20

50

15 16 Nov 20 Nov 24 Nov 28 Nov

2 Dec

0

6 Dec

20

50

0 15 18 Oct 22 Oct 26 Oct 30 Oct 3 Nov 7 Nov 11 Nov 15 Nov

-25

CH4-flux [µg CH4 m-2 h-1]

-25

-75

150

100

0

-50

P ingin Hill (lowland rainforest)

25

0

-50

-75

-100

-100

16 Nov 20 Nov 24 Nov 28 Nov 2000

The maximum bulk density dependent CH4 uptake was multiplied with reduction factors for temperature, moisture and soil depth for calculating the actual CH4 uptake. Daily values of soil moisture and temperature throughout the soil profile were simulated using the biogeochemical ForestDNDCtropica model (Kiese et al. 2005), to which the CH4 module was finally coupled.

2 Dec

18 Oct 22 Oct 26 Oct 30 Oct 3 Nov 7 Nov 11 Nov 15 Nov 2000

6 Dec

Depth function In our simulations we used a soil depth of 0.3 m, with the maximum CH4 uptake rate equally divided between all layers. This does imply that in the model CH4 uptake can only occur in the first 0.3 m, even though our laboratory experiments show methantrophic/ methanogenic activity down to >0.5 m. Since our

-5

-1

-1

Max. CH4 uptake [g CH4 ha day ]

Fig. 5 Dependency of maximum observed CH4 uptake rates at different tropical rainforest soils worldwide from the topsoil (0–0.1 m) bulk density. Data for Pingin Hill, Bellenden Ker and Kauri Creek, Australia, are from this study. Data for La Selva, Costa Rica, Kakamega, Kenya, and Xishuangbanna, China, were taken from Keller and Reiners (1994) and Werner et al. (2006, 2007), respectively

30

Air temperature [°C]

Kauri Creek (montane rainforest)

Precipitation [mm]

CH4-flux [µg CH4 m-2 h-1]

30

Precipitation [mm]

Fig. 4 Air temperature, precipitation and CH4 fluxes at the sites Kauri Creek (left) and Pingin Hill (right). CH4 fluxes were measured with five static chambers in sub-daily resolution. Provided are individual chamber fluxes (dots) as well as the simulated CH4 flux (line) using ForestDNDCtropica

Plant Soil (2008) 309:211–226 Air temperature [°C]

218

Xishuangbanna, China

-10

Bellenden Ker, Australia Kauri Creek, Australia

-15 Pingin Hill, Australia La Selva, Costa Rica

0,50

0,75

1,00

1,25 -3

Topsoil bulk density [g cm ]

1,50

Plant Soil (2008) 309:211–226

219

laboratory measurements found the CH4 uptake activity to be highest in the uppermost 0.1 m and declining significantly down to 0.3 m, we introduced a soil depth dependent reduction factor (SDepth_red). This factor describes the linear reduction of CH4 uptake activity with soil depth: SDepth

red ½
¼

1:2
1:5*SDepth

ð2Þ

SDepth = soil depth (m) Moisture function The flux of CH4 into the soil profile is largely controlled by soil porosity and by soil moisture, i.e. high soil moisture values will negatively affect the diffusion of atmospheric CH4 into the soil profile and, thus to the sites of methanotrophic activity (Borken et al. 2000). However, it has also been reported that the metabolic activity of methanotrophs decrease if drought stress occurs at periods when soil moisture is low (e.g. Liu et al. 2007; Dannenmann 2007). To account for the effect of soil moisture on CH4 uptake activity we adopted the formula developed by Del Grosso et al. (2000) to calculate a dimensionless moisture factor (moist_fact), which is allowed to vary in the range from 0 to 1: If WFPS < 0:9 : moist fact   0:1  WFPS  100
a 0:4 ¼ ð b
aÞ   0:1  WFPS  100
c 0:7  ð b
cÞ If WFPS≥0.9: a–c: WFPS:

this, data were normalized in such a way that for each site the observed CH4 uptake at 30°C was set to 1.0: temp fact ¼
0:736 þ 0:098  temp
0:0012  temp2

temp = temperature (°C) Methane production

Methane exchange at the soil–atmosphere interface is the product of simultaneous production and consumption processes. Our field measurements showed that under water saturated conditions, tropical upland forest soils may even change from being a sink to being a weak net source for CH4. Using our laboratory data on CH4 production under anaerobic conditions we developed a simplified algorithm to describe CH4 production in dependency on soil moisture: CH4 prod ½g CH4 ha
1 day
1 layer
1  ¼

0:6  WFPS  l height ðmÞ  104  bd 106  S Depth

0.6:

WFPS: ð3Þ

moist–fact=0 form parameters (a=−2.0; b=2.57; c=9.0) water filled pore space (output from ForestDNDCtropica)

ð4Þ

l_height: 104: bd: SDepth_red: 106:

red

(5)

mean maximum CH4 production μg CH4 kg−1 SDW day−1 as derived from laboratory experiments at the sites Kauri Creek and Bellenden Ker (see below) water filled pore space (output from ForestDNDCtropica) height of the simulated layer within ForestDNDCtropica conversion factor from m2 to hectare bulk density (kg m−3) Soil depth depended reduction factor (see above) Conversion factor from microgram to gram

Methane flux

Temperature function

Taking into account all equations as outlined above the net exchange of CH4 at the soil–atmosphere interface [CH4flux] was calculated as followed:

Our laboratory experiments revealed that the CH4 uptake in tropical forest soils is significantly dependent on temperature. To describe the temperature dependency of CH4 uptake (temp_fact) we fitted a second order polynomial curve to our laboratory data. For

CH4 flux ½g CH4 ha
1 day
1  ¼ MaxCH4 uptake  SDepth red  moist fact X CH4 prod  temp fact


ð6Þ

−38.7±0.3 −64.4 −17.1 0.82 −35.1±0.4 −68.7 −6.2

0.30 0.36 Keller and Reiners (1994) 0.33 0.40 −42.4±0.7 −64.4 −23.9 0.79 9/monthly 15.01–15.09.2001

−44.6±6.7 −68.7 −6.2

0.10 0.20 Werner et al. (2006) −28.2±0.2 −31.9 −24.9 0.94 56/daily 25.02–21.04.2005

−29.3±0.2 −38.9 −19.2

0.23 0.26 This study −32.5±0.3 −42.3 −31.3 0.90 26/daily 19.11–14.12.2000

−36.7±0.3 −44.6 −27.9

24/daily 20.10−12.11.2000

−44.8±0.4 −59.1 −22.03 −40.6±1.9 −50.7 −21.7 0.89

0.19 0.31 Kiese et al. (2003) and this study 0.17 0.54 This study −35.5±0.3 −48.5 −17.1 0.90 −35.8±0.1 −52.6 −17.5 387/daily 17.11.2001−25.01.2003

Lowland rainforest at Bellenden Ker, Australia Lowland rainforest at Pingin Hill, Australia Montane rainforest at Kauri Creek Montane rainforest at Xishuangbanna, China Lowland rainforest at La Selva, Costa Rica Total (all data sets)

Reference for dataset r2 2 RMSPEn reff

Max Min

Model performance Simulated CH4 fluxes (μg CH4 m−2 h−1)

Mean Max Min Duration of measurement Number of data Mean Resolution, n

For calculation of the regional sink strength of tropical rainforest soils for atmospheric CH4 in the region of the ‘Wet Tropics’, Queensland, Australia, the ForestDNDCtropica model was linked to a detailed GIS database holding all relevant information for initialising and driving the model. Figure 7 shows that simulated CH4 uptake for the year 07/1996–06/1997 ranged from 1.3–4.6 kg CH4 ha−1 year−1. Highest uptake rates with values >3 kg CH4 ha−1 year−1 were predicted for the south and north parts of the study region as well as for the Atherton Tablelands. In these areas the topsoil bulk density is predominantly <1.1 g cm−3 and observed annual rainfall <3,000 mm

Site

CH4 uptake for the ‘Wet Tropic’ region of Queensland, Australia

Measured CH4 fluxes (μg CH4 m−2 h−1)

For evaluating the capability of the newly developed, semi-empirical CH4 module in the ForestDNDCtropica model to simulate CH4 exchange at the site scale, the model was applied to five different tropical rainforest sites from Australia, China and Costa Rica, for which information on CH4 fluxes and climate as well as information on soil and vegetation properties was available (Table 4). Simulated CH4 fluxes for the three tropical rainforest sites in Queensland, Australia (Figs. 3 and 4) are well in the wide range of observed fluxes, and match the observed, mainly rainfall driven seasonality. For the lowland rainforest site at Bellenden Ker (Fig. 3), the model tended to underestimate dry season (end of May–mid August) CH4 uptake rates. Summary statistics evaluating model performance at the different sites are outlined in Table 4. For all 2 sites the model efficiency (reff ) values were between 2 0.1 and 0.33, r were in the range of 0.2–0.54, whereas the RMSPEn varied in a range from 0.79 to 0.94. Across all sites the model performance measures 2 were: r2 =0.4, reff ¼ 0:33 and RMSPEn=0.82 all significant at least with P<0.01). In view of the observed variability between individual chambers at a given site (see also Kiese et al. 2003; or Werner et al. 2006) this indicates that the CH4 module for the ForestDNDCtropica model was capable of describing site and seasonal differences in CH4 fluxes. This can also be concluded when comparing simulated and measured daily mean values for the respective measuring periods (Fig. 6). For all sites, the deviation of simulated mean values from actual measurements was <12% (Table 4).

Plant Soil (2008) 309:211–226

Table 4 Compilation of results for CH4 fluxes for the different field sites as derived from model simulations with ForestDNDCtropica and field measurements

220

Plant Soil (2008) 309:211–226 -25

Xishuangbanna China Kauri Creek Australia

-30

-2

-1

Simulated CH4 flux [µg CH4 m h ]

Fig. 6 Measured and modelled CH4 fluxes for five tropical rainforest sites in Australia, China and Costa Rica. For further details on datasets and modelling results see Table 4. Please note that for model comparison daily aggregated values were used

221

Bellenden Ker Australia

-35

Pin Gin Hill Australia -40

La Selva Costa Rica

-45

-50 e

1

1:

lin

-55 -55

-50

-45

-40

-35

-30 -2

-25

-1

Measured CH4 flux [µg CH4 m h ]

year−1. Lowest CH4 uptake was simulated for lowland rainforest regions in the centre of the study region and for the east facing coastal mountain range. Thus, low CH4 uptake rates coincided with high rates of annual precipitation as well as with soils having bulk density >1.1 g cm−3 (Fig. 7). For the period 07/1996–06/1997 (mean annual rainfall: 2504 mm; mean annual temperature 23.7°C) the average CH4 uptake for rainforest soils in our study region was calculated to be 2.89 kg Fig. 7 Simulated CH4 uptake (a), annual sum of precipitation (b) and regional distribution of topsoil bulk density (c) in the study region ‘Wet Tropics’ Queensland, Australia. Provided flux and rainfall data are for the period 07/1996– 06/1997. Highlighted are only those regions which are covered by tropical rainforests (approximately 4,011 km2)

CH4 ha−1 year−1, whereas a slightly higher average CH4 uptake rate of 2.99 kg CH4 ha−1 year−1 was simulated for the period 07/1997–06/1998 (rainfall: 2680 mm; mean annual temperature 23.2°C; Table 5). To further evaluate the uncertainty of the ForestDNDCtropica we conducted a sensitivity study at regional scale by changing rainfall, temperature, clay content and bulk density, which are the major drivers and parameters affecting our developed CH4 flux

222

Plant Soil (2008) 309:211–226

Table 5 Mean, Min, and Max CH4 uptake activity (±SD) and total CH4 uptake by rainforests soils (total area 4,011 km2) of the study region ‘Wet Tropics’, Queensland, Australia, for two different simulation periods, each covering one full year as well as results of the sensitivity study addressing changes in rainfall, temperature, clay content and bulk density on regional scale CH4 uptake (kg CH4 ha−1 year−1)

07/96–06/97 07/97–06/98 Sensitivity studyb +30% rainfall −30% rainfall +10% temperature −10% temperature +20% clay content −20% clay content +10% bulk density −10% bulk density Min combinationc Max combinationd a

Total CH4 uptake (t CH4 annum−1)

Min

Mean±SD

Max

−1.41 −1.47

−2.89±0.70 −2.99±0.72

−4.72 −4.86

−1.36 −1.50 −1.65 −1.16 −1.21 −1.45 −1.04 −1.86 −0.62 −2.27

−2.79±0.67 −3.04±0.73 −3.23±0.77 −2.52±0.63 −2.60±0.68 −2.94±0.73 −2.47±0.72 −3.34±0.61 −1.76±0.58 −3.91±0.71

−4.62 −4.88 −5.15 −4.21 −4.41 −4.68 −4.45 −4.93 −3.53 −5.46

βa −1,110 −1,140 −0.1 1.3 −0.5 −1.2

−1,119 −1,219 −1,295 −1,010 −1,043 −1,179 −991 −1,340 −708 −1,567

β is a sensitivity index provided by Friend et al. (1993) described in “Materials and methods” section

b

The sensitivity study was based on the climate conditions for the year 07/96–06/97

c

+30% rainfall, −10% temperature, +20% clay, +10% bulk density

d

−30% rainfall, +10% temperature, −20% clay, −10% bulk density

model. We found temperature to be positively correlated and precipitation, clay content as well as bulk density to be negatively correlated with changes in regional CH4 uptake. Model sensitivity expressed by the index β was highest for changes in temperature > bulk density > clay content > rainfall (Table 5). Using the combination of increased rainfall, clay content and bulk density as well as decreased temperature the regional mean regional CH4 uptake rate decreased from 2.89 kg CH4 ha−1 year−1 (normal settings for 07/ 1996–06/1997) to 1.76 kg CH4 ha−1 year−1 whereas the inverse maximum combination resulted in a mean uptake rate of −3.91 kg CH4 ha−1 year−1 (Table 5).

Discussion To study the dynamic of CH4 oxidation and production within the soil profile of a montane and a lowland rainforest, stratified soil samples were either incubated aerobically or anaerobically. The experiments revealed that under aerobic incubation conditions, all soil samples always functioned as net sinks for atmospheric CH4, with highest uptake rates (range −2 to −8 μg CH4 kg−1 SDW day−1) for the uppermost

soil layers. The observed rates of CH4 uptake under aerobic conditions and at atmospheric CH4 concentration are at the lower end of observed CH4 uptake activities in topsoils of temperate forests (Saari et al. 1997; Steinkamp et al. 2001; Butterbach-Bahl and Papen 2002), whereas for tropical soils such data has not been published yet. Saari et al. (1997) measured a CH4 uptake of −34.4 μg CH4 kg−1 SDW day−1 for a loamy topsoil of a temperate coniferous forest, i.e. approximately four times higher as the maximum rates observed in this work. However, maximum CH4 uptake in the uppermost mineral layer of a spruce forest in South Germany (Butterbach-Bahl and Papen 2002), which is exposed to high rates of atmospheric N deposition, was approximately 12 μg CH4 kg−1 SDW day−1 relatively close to the rates observed for the lowland rainforest at Bellenden Ker. Of particular note is the fact that maximum CH4 uptake was found in the uppermost soil layer of our sites, whereas in studies for temperate spruce and beech forest soils, peak methanotrophic activity was often found to be in the 0.05–0.15 m depth of the mineral soil (Steinkamp et al. 2001; Butterbach-Bahl and Papen 2002). This difference may be due to the lack or only sporadic formation of an organic layer on top of the mineral

Plant Soil (2008) 309:211–226

soil for tropical rainforests (Spain 1984), however, which mostly can be found for temperate forest soils. Monoterpene production within such organic layers (Amaral and Knowles 1998) as well as leaching of mineral N into the uppermost mineral soil following increased mineralization activity (e.g. Reay and Nedwell 2004; Butterbach-Bahl and Papen 2002) may potentially be the reason for the shift of the most active layer to deeper soil horizons. The observed temperature effect on CH4 uptake activity is in agreement with observations by Steinkamp et al. (2001) who observed a positive temperature effect on CH4 oxidation capacity for soil samples taken from a temperate spruce forest for a temperature range from 0–15°C. Above this temperature range, the effect was insignificant. This is in contrast to our experiments where we could still stimulate CH4 uptake when increasing the temperature from 20°C to 30°C. This difference in temperature response of methanotrophic activity may be due to differences in native microbial communities between the tropical and temperate ecosystems. Whilst no direct evidence exists between forest types, differences in the microbial responses in crop and forest system have been reported by Mohanty et al. (2007). Under anaerobic incubation conditions, soils from both rainforest sites showed a weak, but significant CH4 production at all soil depths, with the highest CH4 production in the uppermost soil layers. This is in accordance with findings for temperate forest soils, where the organic layer and SOC rich uppermost mineral layers which immediately show methanogenic activity and net emission of CH4 if oxygen becomes limited (Saari et al. 1997; Butterbach-Bahl and Papen 2002). This indicates that methanogenic activity is ubiquitous in upland soils, especially in C rich microhabitats, supporting active mineralization associated with O2 consumption and in turn anaerobiosis at the microscale (Khalil et al. 2001; Khalil and Baggs 2005). In addition to our laboratory incubation experiments, our intensive field measurements at all sites identified a net uptake of atmospheric CH4, even during the wet season. The observed rates for these upland tropical rainforest soils are in agreement with earlier observations for various tropical rainforest soils worldwide (e.g. Keller and Reiners 1994; Steudler et al. 1996; Kiese et al. 2003; Ishizuka et al. 2005; Werner et al. 2006, 2007). Our approx. 1.5 years continuous measurements of CH4 fluxes at Bellenden Ker confirmed, that at a given tropical forest site and

223

for given soil properties, CH4 uptake at the site scale is mainly controlled by changes in soil moisture i.e. the proportion of air and water filled pores, affecting gas diffusion conditions (Khalil and Baggs 2005; Borken et al. 2006). This is in contrast to temperate forest sites or temperate grassland sites, where temperature controls seasonal fluxes and moisture moderates the shorter term (daily) dynamics of CH4 uptake (e.g. Borken et al. 2000, 2006; ButterbachBahl and Papen 2002; Liu et al. 2007). Based on our laboratory experiments we developed a simplified semi-empirical module for the ForestDNDCtropica model (Kiese et al. 2005; Werner et al. 2007) to describe CH4 fluxes for the soil–atmosphere interface of tropical rainforest soils, which included a simplified description of CH4 production. Major drivers of our CH4 module are changes in soil moisture and, only secondary, changes in temperature, which is similar to the approaches of Del Grosso et al. (2000) and Borken et al. (2000). In addition, we included bulk density (0–10 cm) in the algorithms as a proxy for potential gas diffusion in soils. Even though the parameterisation of the CH4 module was developed from data of only two field sites, the subsequent validation included data from geographically dissimilar regions of the world. The derivation between mean simulated and measured CH4 fluxes across five tropical rainforest sites was <12% (Table 4) and confirmed the conclusion of Borken et al. (2000) that the dynamics of CH4 uptake can be well described using mainly information on soil porosity, matrix potential (~soil moisture) and soil temperature. 2 Model performance measures of r2 and reff varied between 0.10 and 0.54, indicating a poorer agreement between the more dynamic pattern of daily measured and simulated values. One reason for the poorer fit of daily CH4 fluxes could be induced by the meteorological data used to drive the model, since these data were obtained from stations approximately 20 km away from the measuring sites. Deviation from site rainfall can be expected, especially in tropical regions, were rainfall is mainly of convective character. A further uncertainty might be related to the dynamic change of the groundwater table between dry and wet season, and thus, the potential of changes in CH4 production in deeper soil layers, which the model is not accounting for at present. Since the CH4 module linked to the ForestDNDCtropica model was robust and performed well

224

for the different test sites, we finally linked the ForestDNDCtropica to a GIS in order to estimate the CH4 sink strength of tropical rainforest soils of the ‘Wet Tropic’ region of Queensland, Australia. Our calculations suggest that the area weighted mean CH4 uptake of tropical rainforest soils in this region is approximately 3 kg CH4 ha−1 year−1 (Table 5). Driven by the spatial variability in climate and soil properties uptake rates ranged from 1.4–4.9 kg CH4 ha−1 year−1 (Fig. 7). To further explore the predictive capability of the ForestDNDCtropica a regional sensitivity study was performed. For this input parameters of bulk density and clay content as well as the model drivers rainfall and temperature were changed in the range of their regional uncertainty. Table 5 indicates that simulated CH4 uptake was most sensitive to changes in temperature and bulk density and less to rainfall and clay content. A more detailed analysis of the temperature effect revealed that CH4 uptake increased not only due to increased biological activity at higher temperatures but even more due lower values of soil moisture following increased evapotranspiration. Our results suggest that regional CH4 uptake is relatively insensitive to changes in the seasonality of rainfall, since dry stress on CH4 uptake is unlikely to occur in tropical rainforest soils even during dry season conditions. The high sensitivity of bulk density can be related to the general regulation of the potential gas diffusion of atmospheric CH4 into the soil via total porosity, which is the rate limiting step for CH4 oxidation in soils (Potter et al. 1996). The uncertainty of the mean regional CH4 uptake based on the 96/97 climate conditions, which were quite comparable to the long term average, and the minimum and maximum combination of parameters used in the sensitivity study was 1.76–3.91 kg CH4 ha−1 year−1 (Table 5). Even the minimum scenario resulted in a higher mean uptake rate than the values provided by Potter et al. (1996) in the framework of a more mechanistic model exercise. Their simulation results revealed a mean sink strength for tropical seasonal forests of 1.7 kg CH4 ha−1 year−1 and tropical rainforest of 1.5 kg CH4 ha−1 year−1. However, for the same ecosystems they also provided CH4 uptake of 2.3–3.8 kg CH4 ha−1 year−1 based on extrapolation of measured fluxes, which agree well with our simulations. The reported CH4 uptake rates of our study are in the range of temperate forest soils (Steinkamp et al. 2001; Butterbach-Bahl and Papen 2002; Borken

Plant Soil (2008) 309:211–226

and Brumme 1997), indicating the significance of tropical forest soils as sink for atmospheric CH4. This is of particular importance since the CH4 uptake is significantly reduced when tropical forests are converted into other land uses such as pastures or cropping systems (Keller and Reiners 1994).

Conclusions Our work shows that laboratory experiments on CH4 uptake/production in different soil layers in concert with detailed field data can provide valuable information for the development of accurate semi-empirical models. Linking the CH4 module to the process oriented model ForestDNDCtropica, provided a suitable platform for simulating daily changes in soil moisture and temperature in response to climate and the ability to scale up CH4 fluxes from field to landscape and regional scales. The regional simulations suggest that this combined laboratory, field and computational approach may significantly improve estimates of CH4 fluxes from tropical rainforest soils worldwide. A similar strategy has also been successfully developed for N2O fluxes from tropical rainforest soils (Werner et al. 2007), confirming the significant potential of GIS coupled simulation modelling of biogeochemical trace gas exchange from terrestrial ecosystems for improving regional and global estimates of atmospheric trace gas emissions. Acknowledgements This research was supported by the Deutsche Forschungsgemeinschaft (DFG) under contract BU 1173-2 and BU 1173-3 and received additional support by the EU IP NitroEurope.

References Adamsen APS, King G (1993) Methane consumption in temperate and subarctic forest soils: rates, vertical zonation and responses to water and nitrogen. Appl Environ Microbiol 59:485–490 Amaral JA, Knowles R (1998) Inhibition of methane consumption in forest soils by monoterpenes. J Chem Ecol 24 (4):723–734 Boeckx P, Van Cleemput O, Villaralvo I (1997) Methane oxidation in soils with different textures and land use. Nutr Cycl Agroecosyst 49:91–95 Borken W, Xu YJ, Brumme R (2000) Effects of prolonged soil drought on CH4 oxidation in a temperate spruce forest. J Geophys Res 105:7079–7088

Plant Soil (2008) 309:211–226 Borken W, Davidson EA, Savage K, Sundquist ET, Steudler P (2006) Effect of summer throughfall exclusion, summer drought, and winter snow cover on methane fluxes in a temperate forest soil. Soil Biol Biochem 38:1388–1395 Breuer L, Papen H, Butterbach-Bahl K (2000) N2O emission from tropical forest soils of Australia. J Geophys Res 105:26353–26367 Butterbach-Bahl K, Papen H (2002) Four years continuous record of CH4-exchange between the atmosphere and untreated and limed soil of a N-saturated spruce and beech forest ecosystem in Germany. Plant Soil 240:77–90 Butterbach-Bahl K, Papen H, Rennenberg H (1997) Impact of gas transport through rice cultivars on methane emission from rice paddy fields. Plant Cell Environ 20:1175–1183 Butterbach-Bahl K, Stange F, Papen H, Li C (2001) Regional inventory of nitric oxide and nitrous oxide emissions for forest soils of Southeast Germany using the biogeochemical model PnET-N-DNDC. J Geophys Res 106:34155– 34166 Butterbach-Bahl K, Kock M, Willibald G, Hewett B, Buhagiar S, Papen H, Kiese R (2004) Temporal variations of fluxes of NO, NO2, N2O, CO2, and CH4 in a tropical rain forest ecosystem. Glob Biogeochem Cycles 18(3):GB3012 Castaldi S, Costantini M, Cenciarelli, P, Ciccioli, P, Valentini R (2007) The methane sink associated to soils of natural and agricultural ecosystems in Italy. Chemosphere 66:723–729 Cannon M, Smith CD, Murtha GG (1992) Soils of the Cardwell-Tully area, North Queensland, Divisional Report No.115. Commonwealth Scientific and Industrial Research Organization, Melbourne, Australia Conrad R (1996) Soil microorganisms as controllers of atmospheric trace gases (H2, CO, CH4, OCS, N2O and NO). Microbiol Rev 60:609–640 Dannenmann M, Gasche R, Ledebuhr A, Holst T, Mayer H, Papen H (2007) The effect of forest management on trace gas exchange at the pedosphere-atmosphere interface in beech (Fagus sylvatica L.) forest stocking on calcareous soils. Eur J For Res 126(2):331–346 Del Grosso SJ, Parton WJ, Mosier AR, Ojima DS, Potter CS, Borken W, Brumme R, Butterbach-Bahl K, Crill PM, Dobbie K, Smith KA (2000) General CH4 oxidation model and comparison of CH4 oxidation in natural and managed systems. Glob Biogeochem Cycles 14:999–1020 Friend AD, Schugart HH, Running SW (1993) Physiologybased GAP model of forest dynamics. Ecology 74:792–797 Heiner IJ, Grundy MJ (1994) Land resources of the Ravenshoe-Mt. Garnet area, North Queensland, Land Resources Inventory, Land Resources Bulletin No.1; Land resources inventory, Land Resources Bulletin. Queensland Department of Primary Industries, Brisbane, Australia Houlder D, Hutchinson M, Nix H, McMahon J (1999) ANUCLIM Version 5.0 User Guide. Centre for Resource and Environmental Studies, Australian National University, Canberra Ishizuka S, Iswandi A, Nakajima Y, Yonemura S, Sudo S, Tsuruta H, Murdiyarso D (2005) The variation of greenhouse gas emissions from soils of various land-use/ cover types in Jambi Province, Indonesia. Nutr Cycl Agroecosyst 71:17–32 Keller M, Reiners W (1994) Soil atmosphere exchange of nitrous oxide, nitric oxide, and methane under secondary

225 succession of pasture to forest in the Atlantic lowlands of Costa Rica. Glob Biogeochem Cycles 8:399–409 Khalil MI, Baggs EM (2005) CH4 oxidation and N2O emissions at varied soil water-filled pore spaces and headspace CH4 concentrations. Soil Biol Biochem 37:1785– 1794 Khalil MI, Boeckx P, Roseani AB, Van Cleemput O (2001) Nitrogen transformations and emission of greenhouse gases from three acid soils of humid tropics amended with N sources and moisture regime. II. Nitrous oxide and methane fluxes. Commun Soil Sci Plant Anal 32:2909– 2924 Kiese R, Butterbach-Bahl K (2002) N2O and CO2 emissions from three different tropical forest sites in the wet tropics of Queensland, Australia. Soil Biol Biochem 34:975– 987 Kiese R, Hewett B, Graham A, Butterbach-Bahl K (2003) Seasonal variability of N2O-emissions and CH4-uptake from/ by a tropical rainforest soil of Queensland, Australia. Glob Biogeochem Cycles 17:1043 Kiese R, Li C, Hilbert W, Papen H, Butterbach-Bahl K (2005) Regional application of PnET-N-DNDC for estimating the N2O source strength of tropical rainforests in the Wet Tropics of Australia. Glob Change Biol 11:128–144 Laffan MD (1988) Soils and land use on the Atherton Tableland, North Queensland, soils and land use series No.61. Commonwealth Scientific and Industrial Research Organization, Melbourne, Australia Li C, Aber J, Stange F, Butterbach-Bahl K, Papen H (2000) A process-oriented model of N2O and NO emissions from forest soils: 1. Model development. J Geophys Res 105: 4369–4384 Liu C, Holst J, Brüggemann N, Butterbach-Bahl K, Yao Z, Yue J, Han S, Han X, Krümmelbein J, Horn R, Zheng X (2007) Winter grazing reduces methane uptake by soils of a typical semi-arid steppe in Inner Mongolia, China. Atmos Environ 41:5948–5958 Malcolm DT, Nagel BK, Sinclair I, Heiner IJ (1999) Soils and agricultural land suitability of the Atherton Tablelands, North Queensland, Land Resource Bulletin. Department of Natural Resources, Brisbane, Australia Mohanty SR, Bodelier PLE, Conrad R (2007) Effect of temperature on composition of the methanotrophic community in rice field and forest soil. FEMS Microbiol Ecol 62:24–31 Murtha GG (1986) Soils of the Tully-Innisfail area, North Queensland, Divisional Report No.82. Commonwealth Scientific and Industrial Research Organization, Melbourne, Australia Murtha GG (1989) Soils of the Mossman Cape Tribulation area, North Queensland, Divisional Report No.102. Commonwealth Scientific and Industrial Research Organization, Melbourne, Australia Murtha GG, Cannon MG, Smith CD (1996) Soils of the Babinda-Cairns area, North Queensland, Divisional Report No.123. Commonwealth Scientific and Industrial Research Organization, Melbourne, Australia Potter SS, Davidson EA, Verchot LV (1996) Estimation of global biogeochemical controls and seasonality in soil methane consumption. Chemosphere 32:2219–2246

226 Reay DS, Nedwell DB (2004) Methane oxidation in temperate soils: effects of inorganic N. Soil Biol Biochem 36:2059– 2065 Saari A, Martikainen PJ, Ferm A, Ruuskanen J, De Boer W, Troelstra SR, Laanbroek HJ (1997) Methane oxidation in soil profiles of Dutch and Finnish coniferous forests with different soil texture and atmospheric nitrogen deposition. Soil Biol Biochem 29:1625–1632 Smith KA, Dobbie KE, Ball BC, Bakken LR, Sitaula BK, Hansen S, Brumme R, Borken WB, Christensen S, Prieme A, Fowler D, MacDonald A, Skiba U, Klemedtsson L, Kasimir-Klemedtsson A, Derorska A, Orlanski P (2000) Oxidation of atmospheric methane in Northern European soils, comparison with other ecosystems, and uncertainties in the global terrestrial sink. Glob Change Biol 6:791–803 Spain AV (1984) Litterfall and the standing crop of litter in three tropical Australian rainforests. J Ecol 72:947–961 Spain AV, Unwin G, Sinclair DF (1989) Soils and vegetation at three rainforest sites in tropical north-eastern Queensland. Division Report 15, Division of Soils, CSIRO, Melbourne Stange F, Butterbach-Bahl K, Papen H, Zechmeister-Boltenstern S, Li C, Aber J (2000) A process oriented model of N2O and

Plant Soil (2008) 309:211–226 NO emissions from forest soils: 2. Sensitivity analysis and validation. J Geophys Res 105:4385–4398 Steudler PA, Melillo JM, Feigl BJ, Neill C, Piccolo MC, Cerri CC (1996) Consequence of forest-to-pasture conversion on CH4 fluxes in the Brazilian Amazon Basin. J Geophys Res 101:18547–18554 Steinkamp R, Butterbach-Bahl K, Papen H (2001) Methane oxidation by soils of a N-limited and N-fertilized spruce forest in the Black Forest, Germany. Soil Biol Biochem 33:145–153 Tracy JG (1982) The vegetation of the humid tropical region of North Queensland. CSIRO, Melbourne Werner C, Zheng X, Tang J, Xie B, Kiese R, Liu K, Butterbach-Bahl K (2006) N2O, CH4 and CO2 emissions from seasonal tropical rainforests and a rubber plantation in South-West China. Plant Soil 289:335–353 Werner C, Butterbach-Bahl K, Haas E, Hickler T, Kiese R (2007) A global inventory of N2O emissions from tropical rainforest soils using a detailed biogeochemical model. Glob Biogeochem Cycles 21:GB3010 Wilson PR, Baker DE (1990) Soils and land suitability of the wet tropical coast of North Queensland: Ingham area, Land Resources Bulletin. Queensland Department of Primary Industries, Brisbane, Australia