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Application of RothPC-1 to soil carbon profiles in cracking soils under minimal till cultivation
Geoderma 207–208 (2013) 144–153
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Application of RothPC-1 to soil carbon profiles in cracking soils under minimal till cultivation T. Wells a,⁎, G.R. Hancock b,1, C. Dever b,1, C. Martinez b,1 a b
School of Engineering, The University of Newcastle, Callaghan, NSW 2308, Australia School of Environmental and Life Sciences, Geology Building, The University of Newcastle, Callaghan, NSW 2308, Australia
a r t i c l e
i n f o
Article history: Received 10 December 2012 Received in revised form 19 May 2013 Accepted 20 May 2013 Available online 11 June 2013 Keywords: Soil carbon Vertical transport RothPC-1 Cracking soil
a b s t r a c t This study examines soil organic carbon (SOC) profiles in two neighbouring field sites (‘Dog’ and ‘Shed’ paddocks) which share a similar land use history but are characterised by different soil types (euchrozem and vertosol). SOC inventories to 30 cm depth at the two sites were similar however enhanced transport of SOC in the cracking vertosol soils of the Shed paddock produced a significantly flatter SOC profile and higher whole profile SOC inventories at this site. No clear relationship was observed between clay content and SOC distribution at either sample site. Modelling of SOC turnover using RothPC-1 yielded a satisfactory fit to the observed SOC profiles however the soil moisture and temperature values calculated within the model were found to be at odds with 5 year field observations reported from the site. When field measured values for the moisture and temperature were substituted into the model the fit to the observed SOC profiles was significantly poorer indicating that the purely convective transport approach used to model SOC movement within RothPC-1 may not be sufficient to model vertical SOC transport in cracking soils. The results highlight the need for a cautious approach when using RothPC-1 in arid, cracking soil environments. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.
1. Introduction There is currently considerable interest in the factors that impact on the vertical distribution of soil organic carbon (SOC) throughout the soil column. These factors include climate and vegetation (Jobbágy and Jackson, 2000), land management practices and soil type (Meersmans et al., 2009; Schlesinger, 2000; Young et al., 2005) as well as the manner in which SOC is transported down the soil profile (Wells et al., 2012). In this study the vertical distribution of SOC down to bedrock is compared in two neighbouring field sites which share a similar land use history of minimal till agriculture. The soils at both sites have a medium to high clay content however they experience significantly different levels of cracking behaviour. One aim of this study is to investigate the possible relationship between SOC distribution down the soil profile and the corresponding soil clay content. While the links between SOC and soil clay content have been examined extensively in the upper reaches of the soil profile, the relationship between the vertical distribution of SOC and the corresponding clay content of the soil profile has received less attention (Wells et al., 2012). While it is a widely held belief that the level of
⁎ Corresponding author. Tel.: +61 2 4921 5741; fax: +61 2 4921 6991. E-mail addresses: [email protected] (T. Wells), [email protected] (G.R. Hancock). 1 Tel.: +61 2 4921 5090; fax: +61 2 4921 5877.
SOC preservation increases as clay content increases (Hassink, 1997; Ladd et al., 1985), it has been observed that the relationship between SOC and clay content is complex (Plante et al., 2006; Six et al., 2002; Thomsen et al., 1999) as soil texture acts directly and indirectly on various protection mechanisms (for example via its effect on the soil water regime). Consequently clay content may not be a universal predictor of whole profile carbon inventory. By comparing the vertical distribution of SOC and clay content at both sites we seek to add to our understanding of this complex relationship. This study will also examine the impact of soil cracking on the transport of SOC down the soil column. A recent finite element analysis of SOC movement in a sandy soil carried out in conjunction with 137 Cs/210Pbex analysis (Wells et al., 2012), indicated that SOC transport includes a significant diffusional component (possibly resulting from bioturbation). In this study we will attempt to model the SOC distributions observed at each field site using a recently proposed subsoil SOC turnover model, RothPC-1 (Jenkinson and Coleman, 2008; Jenkinson et al., 2008), which incorporates a convective transport mechanism only. While the RothC-26.3 soil carbon model (Coleman et al., 1997) is in common use in predicting the dynamics of carbon in the upper (normally 0–23 cm or 0–30 cm) soil layer (e.g. Falloon and Smith, 2002; Paul and Polglase, 2004), there have been few if any studies testing the application of the RothPC-1 model since it was originally proposed. In this study we are interested to determine if the convection-only transport component included in the RothPC-1 model is sufficient to model the observed SOC transport at the field sites examined.
0016-7061/$ – see front matter. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.geoderma.2013.05.018
T. Wells et al. / Geoderma 207–208 (2013) 144–153
2. Study site The two field sites sampled (‘Dog’ and ‘Shed’ paddocks), are located on the Illogan property which is situated in the Krui River catchment area. The Krui River catchment is one of 12 major sub-catchments of the greater Goulburn River system (6540 km2), which lies in the Upper Hunter region of New South Wales, Australia (Fig. 1). The first sampling pit (Dog paddock), was excavated 10 m to the east of a permanently mounted weather and soil moisture monitoring station (‘K1’, see Rüdiger et al., 2007). A second sampling site was established ~1.5 km to the west in the Shed paddock (Fig. 1). The Krui catchment extends from 31°49′S to 32°13′S and 150°02′E to 150°21′E, with elevations ranging from approximately 200 m in the south (Merriwa Plateau) to 1200 m in the north (Liverpool Range). The region is located in the temperate zone of eastern Australia. Average annual rainfall in the study area is 624 mm (the 139 year average recorded at the Cassilis monitoring station located 20 km from the Illogan property; Australian Bureau of Meteorology, 2012). Average annual potential evaporation is approximately 1200 mm. The highly fertile, basaltic soils of the Krui area have significantly influenced land use practices within the region, with grazing and cropping activities dominating. The Illogan property which is the focus of this study has predominantly red basaltic clays (Euchrozems, upon which the Dog paddock site is located) and black earths (Vertosols, upon which the Shed paddock site is located). Cracking of the soil at both sites has been observed on many occasions during dry periods however the width, depth and concentration of cracks at the Shed paddock site are significantly greater than that observed at the Dog paddock site. The slope (1%), aspect and elevation of each site however are similar. There is no evidence at either site of erosion/deposition or any disturbance other than that produced by cultivation practices associated with minimum tillage cereal and grain production. The Illogan property has been owned by the same family for over 50 years. Prior to the 1950's the local landscape was open grassy woodland characterised by widely spaced eucalypt trees with very little shrub cover and sparse ground cover (McRae and Cooper, 1985). In the mid 1950's both sites examined in this study were cleared and the native vegetation replaced by improved pasture which was grazed until 1970. Since 1970 the two field sites have predominantly supported
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cereal cropping activities, including barley, oats, and wheat. Between 1970 and 1990 the soil at both sites was lightly tilled to 10 cm depth. Since 1990 minimal tillage practices have been employed at both sites (maximum depth of disturbance b5 cm for seeding and fertiliser application). 3. Methodology In this study soil cores were collected down to bedrock for determination of SOC content and soil texture. The soils excavated from the Dog and Shed paddock sites are representative of the two major soil types present on the Illogan property and broadly representative of soils used for cropping in the region. Both sites were in fallow between crop rotations when sampled in May 2008. 3.1. Soil sampling and analysis A backhoe was used to cut 3 m long soil trenches down to bedrock at each site. Soil depth at both sites was approximately 1.4 m (including ~0.1 m of weathered bedrock or saprolite). Four individual vertical profiles were sampled from the walls of the Dog paddock trench and three from the Shed paddock trench. Each vertical profile was sampled using 100 mm long by 65 mm ID cores which were hammered horizontally into the side wall of the trench at regular intervals in a vertical line from the soil surface down to bedrock. The exception to this was the uppermost core which was collected vertically from the surface. Seven to eight core samples were taken for each vertical profile in the Dog paddock trench (31 samples in total) and 8–10 cores for each Shed paddock profile (27 samples in total). After collection soil samples were immediately weighed then air dried at 40 °C for 2 to 3 days. The dried samples were gently disaggregated with a mortar and pestle and passed through a 2 mm sieve and the coarse (> 2 mm) fraction separated. The b2 mm fraction was further disaggregated with a mortar and pestle and weighed. The bulk density of each sample was calculated using the dried soil mass and volume of each core. The b 2 mm soil fraction was ground in a mill to a fine powder and the total carbon content measured using a LECO 2000 analyser. LECO carbon results were corrected for inorganic carbon content determined
Fig. 1. Location map of Illogan study site (A) soil map and (B) Illogan property as viewed from QuickBird satellite (July, 2005) showing locations of the two sample sites. (Note: trench dimensions shown are not to scale.)
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by monitoring CO2 evolution following FeCl and HCl digestion of the soil sample. The hydrometer method outlined by Smith and Atkinson (1975) was employed to establish the particle size distribution of the b2 mm soil fraction. Soil colour was determined on both wet and dry samples.
ðCO2 Þ=ðBIO þ HUMÞ ¼ pðZ þ 1Þ−1:
ð2Þ
The partitioning coefficient, Z, for each soil layer is a function of the clay content of the layer (as in RothC-26.3), i.e.:
3.2. Modelling of the data The data obtained at the two field sites allows us to test the applicability of the carbon subsoil turnover model, RothPC-1, proposed by Jenkinson (Jenkinson and Coleman, 2008). The model is an extension of RothC-26.3 (Coleman and Jenkinson, 1999) which models carbon turnover in the upper soil layer (nominally 0–23 cm depth). Readers are directed to Jenkinson and Coleman (2008) for a detailed description of RothPC-1 however some of the important aspects of the model's implementation will be discussed here briefly. RothPC-1 utilises the same multi-pool structure as RothC-26.3. Incoming organic carbon is partitioned between decomposable plant material (DPM) and resistant plant material (RPM) both of which decompose via a first order process to produce CO2, humus (HUM) and microbial biomass (BIO). HUM and BIO in turn decompose by further first order processes to form more CO2, BIO and HUM. The rate of decomposition of each carbon pool is dictated by a characteristic rate constant which is modified by soil temperature, moisture and for the upper soil layer, the level of vegetation cover. Calculation of the decomposition rates in RothPC-1 generally follows the procedures used in RothC-26.3 however there are some important points to note in implementing the RothPC-1 model, namely: 1) The characteristic decay rate constant for the BIO carbon pool is set to 1.5 year−1 (not 0.66 year−1 as in RothC-26.3). 2) The decomposition is modified for temperature in all five soil layers using the monthly average air temperature (a contentious oversimplification as pointed out by Jenkinson and Coleman themselves). 3) Decomposition is also modified for soil water content after calculating an accumulated soil moisture deficit throughout the year and comparing this to a maximum soil moisture deficit (MaxSMD). MaxSMD of each soil layer is calculated in the same manner as in RothC-26.3 using the clay content characteristic of that layer. (If the soil is bare MaxSMD is divided by 1.8.) When monthly potential evaporation exceeds rainfall, each layer starting from the upper layer dries out until it reaches MaxSMD. When rainfall exceeds evaporation, each layer, starting at the upper layer, wets up until field capacity is reached. 4) The decay rate constants for all carbon pools are assumed to decrease with depth. This is facilitated by multiplying the carbon pool decomposition rate constant by a factor, N, which is calculated using the following sigmoid function: N ¼ ð−1=ð1 þ ð expð−sðF−f ÞÞÞÞÞ=ð−1=ð1 þ ð expð−sð−f ÞÞÞÞÞ
the ratio of CO2 to (BIO + HUM) formed when a carbon pool decomposes, (=Z in RothC-26.3), is modified as follows:
ð1Þ
where s is a constant (cm−1) which is optimised to provide the best fit to the data, F is the distance from the middle of the top layer to the mid-depth of the soil layer in question (cm) and f is the distance from the surface to the mid-depth of the top layer (cm). 5) The downward movement of carbon from each pool is described using a convection like transport term, p, (−). At the end of each month a fraction, (1 − p), of the mobilised (decomposed) material from each pool is transported to the soil layer below. If for example, p = 1, then no material is transported to the lower soil layers and RothPC-1 essentially reverts to the RothC-26.3 model. As the value of p decreases the fraction of material transported down the soil column increases. 6) To ensure that RothPC-1 predictions of newly formed BIO and HUM in the upper soil layer each month match that predicted in RothC-26.3
Z ¼ 1:67ð1:85 þ 1:6 expð−0:0786ð%clayÞÞÞ:
ð3Þ
7) In an overall sense carbon is moved down the soil profile at the expense of CO2 being released. One consequence of this restriction is that the transport parameter, p, is limited in range to values between 1 and pmin where pmin is defined by: p min ¼
1 : Zþ1
ð4Þ
3.2.1. Other modelling considerations In this study it was assumed that the climate operating at the two sites was identical as they are separated by less than 2 km. The monthly average rainfall and air temperature data were sourced from meteorological records of the nearby weather station of Cassilis (20 km distant, 139 year rainfall average and 60 year temperature averages) while open pan evaporation rates were obtained from data reported for the township of Scone (49 km distant, 45 year averages) (Australian Bureau of Meteorology, 2012). Prior to 1956 the Dog and Shed paddock sites were predominantly open scrubland with widely spaced trees (McRae and Cooper, 1985). In 1956 both sites were cleared and between 1956 and 1970 were devoted to grazing on improved pasture. From 1970 to the time of sampling the two sites were dedicated to cereal cropping (generally 1 crop per year of wheat, oats or barley) with both sites fallow every 4th year. During the cropping years it was assumed that the sites were fallow for the months January through June. DPM/RPM split of the incoming plant carbon was set at 0.67 for the period prior to 1956 (as per the value suggested for unimproved grassland and scrub; Coleman and Jenkinson, 1999), and 1.44 thereafter (as per the suggested value for agricultural crops and improved pasture). All incoming carbon (resulting from the decomposition of surface litter and root material) was assumed to enter the soil column via the upper (0–23 cm) soil layer only. To best assess the performance of the RothPC-1 model it was not only necessary to know the vertical SOC distribution at the time of sampling but also estimate the SOC profile at the commencement of agricultural activity (i.e. the b 1956 profiles). As no soil data was available for this period of time the 1956 profiles at each site were determined indirectly as follows: (1) Dog paddock site 1956 SOC profile. SOC profiles were obtained from a neighbouring property located less than 500 m from the Dog paddock site in 2008. The neighbouring property shares the same euchrozem soil type and structure as the Dog paddock site and it is naturally vegetated having never been subject to cropping and only minimally grazed. It was therefore assumed that the SOC profiles observed at this neighbouring site are a reasonable approximation of the SOC profile at the Dog paddock site prior to clearing, grazing and cropping. (2) Shed paddock site. The 1956 soil carbon profile for the Shed paddock site was based on the SOC profile reported for the ‘Donald's Ridge’ location in the nearby Liverpool Ranges by Young et al. (2005). The soil type (high clay content, black vertosol), climate and vegetation (grassy open woodland) reported for the Donald's Ridge location are thought to be similar to that present at the Shed paddock site prior to 1956.
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The soil carbon data for each surrogate 1956 profile were aggregated into the 5 soil layers used in the modelling procedure (0–23, 23–46, 46–69, 69–92 and 92–115 cm, Fig. 2). The RothPC-1 model was first run to equilibrium (a run of 10,000 years) for the two field sites and the pre-1956 annual carbon input to the soil at each site adjusted until the predicted total carbon content of the uppermost (0–23 cm) soil layer matched the 0–23 cm 1956 profile stocks at the two sites. Once the 1956 SOC profiles were estimated the model was then run for the periods 1956–1970 (grazing period) and 1970–2008 (cereal cropping period) and the transport factor, p, decomposition damping factor, s, and annual carbon input during the grazing and cropping periods were optimised to provide the best fit to the observed 2008 SOC profile at each site. The ratio of carbon inputs during the grazing (Cin,1956–1970) and cropping period (Cin,1970–2008) were fixed to best reflect the expectation that carbon input during the cropping period was lower than that during the period of grazing on improved pasture. Schlesinger (1977) suggests that the carbon input in grassland systems is likely to be in the order of 4.2 tC/ha. In a separate study by the authors (Wells and Hancock, submitted for publication) carbon inputs during the cereal cropping period (based on harvest yields and root to shoot ratios typical of wheat, oats and barley), have been estimated to be approximately 1 tC/ha. Thus while the magnitude of the carbon inputs for these two periods of time was allowed to vary the ratio Cin,1956–1970 : Cin,1970–2008 was fixed at 4.2:1.
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4. Results 4.1. Sampling profile characteristics Four profiles were sampled at the Dog paddock site and 3 at the Shed paddock site. The Dog paddock profiles were separated by 0.1, 1.5 and 1.6 m while the Shed paddock profiles were separated by 0.2 and 3 m. There was little profile-to-profile variation in clay and rock content, colour, or SOC levels within a given trench. The two sites were sampled in May 2008 after a prolonged dry period. Despite the lack of recent rain subsoil moisture levels at both locations were close to field capacity (~ 0.3 v/v at >30 cm depth, Fig. 3). Despite this, cracking of the soil profile was observed at both sites. At the Dog paddock site fine cracks, while absent on the surface, were numerous down the soil profile. Cracking of the black vertosol soil at the Shed paddock site however was significantly more extensive with numerous cracks up to 50 mm wide observed on the surface and down the soil profile. At the Dog paddock site small amounts of wheat stubble were present on the soil surface and traces of organic matter were observed down to a depth of 50 to 70 cm while sorghum stubble was present in small amounts on the soil surface at the Shed paddock location. No strong horizons or colour contrasts were present in the Dog Paddock soil profile (Table 1). A range of soil colouring was observed at the Shed paddock trench but strong contrasts down the profile were not found suggesting consistent soil properties and an aerobic environment at this site (Table 1). The maximum depth of soil including saprolite at both sample sites was approximately 140 cm at which point large core stones and bedrock were encountered preventing the backhoe from digging further. Minimal rock was present in either profile until a depth of approximately 90 cm was reached whereupon rock content, particularly at the Dog paddock site, increased sharply (Fig. 4). Distinct differences were observed in the clay content at the two sites (Fig. 5). At the Dog paddock site clay increases with depth until a maximum is reached at approximately 80 cm depth. At greater depths the clay content declines as the soil becomes coarser and transitions to saprolite and ultimately bedrock. Clay content at the Shed paddock is approximately constant down to 80 cm depth at which point clay content declines in response to the presence of the weathering front. Average clay content at the Shed paddock (vertosol) was 66%, slightly higher than that observed at the Dog paddock (euchrozem, 56%). 4.2. SOC distribution and inventory The SOC depth profiles at the two sample sites also differ significantly (Fig. 6). At the Dog paddock surface SOC concentrations are
Fig. 2. SOC profiles used to represent the 1956 profile in RothPC-1 modelling of the (A) Dog paddock site and (B) Shed paddock site.
Fig. 3. Gravimetric moisture content of soil core samples as a function of depth.
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Table 1 Soil colour at the two field sites. Sample
Dry sample Munsell notation
Dog paddock 5 cm 2.5 YR 4/4 15 cm 5 YR 3/4 30 cm 5 YR 3/6 45 cm 5 YR 4/6 65 cm 5 YR 5/6 85 cm 5 YR 4/4 110 cm 5 YR 5/4 130 cm 5 YR 5/6 Shed paddock 5 cm 7.5 YR 4/2 10 cm 10 YR 4/2 25 cm 10 YR 4/2 40 cm 10 YR 4/2 55 cm 10 YR 4/2 70 cm 10 YR 4/2 85 cm 10 YR 4/3 100 cm 10 YR 4/3 120 cm 7.5 YR 4/3 135 cm 10 YR 4/3
Wet sample Munsell's soil colour Munsell name notation
Munsell's soil colour name
Reddish brown Dark reddish brown Dark reddish brown Yellowish red Yellowish red Reddish brown Reddish brown Yellowish red
5 YR 5 YR 5 YR 5 YR 5 YR 5 YR 5 YR 5 YR
Very dark reddish brown Very dark reddish brown Very dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown
Dark brown Dark greyish brown Dark greyish brown Dark greyish brown Dark greyish brown Dark greyish brown Brown Brown Dark brown Brown
7.5 YR 2/2 10 YR 2/2 7.5 YR 2/3 10 YR 3/3 10 YR 2/3 10 YR 3/4 10 YR 3/4 10 YR 3/4 5 YR 4/4 10 YR 4/4
2/4 2/4 2/4 3/6 3/6 3/6 3/6 3/6
Brownish black Very dark brown Very dark brown Dark brown Brownish black Dark Yellowish brown Dark Yellowish brown Dark Yellowish brown Reddish brown Dark Yellowish brown
approximately 2.5% but declines rapidly in an exponential fashion so that SOC levels are b 0.5% at depths greater than ~ 40 cm. The surface concentration of SOC at the Shed paddock is considerably lower (~ 1.5–2%), however the decline of SOC concentration with depth is less pronounced and proceeds in a more linear fashion so that SOC concentrations >0.5% are still observed down to depths of 80 cm. The flatter SOC profile at the Shed paddock site results in a median SOC depth of 31 cm compared to 21 cm at the Dog paddock site. The SOC inventories for each sampling profile at each field site are listed in Table 2. While the average 0–30 cm SOC inventories for the two sites are essentially the same (56 and 58 tC/ha) the flatter SOC depth profile observed at the Shed paddock site results in a ~ 25% higher inventory at this site when the entire soil carbon profile down to bedrock is considered (128 tC/ha versus 102 tC/ha). A comparison between the 0–30 cm and full profile SOC inventories determined in this study and elsewhere (Table 3) suggests that the carbon stocks observed at the Dog and Shed paddocks are consistent with values reported in the surrounding region for similar soil types. 4.3. Use of clay content to predict SOC distribution SOC distribution was compared to clay content down the soil profile at each sampling site. The Shed paddock site with its slightly higher
average clay content (66% compared to 56% in the Dog paddock), also had a higher SOC inventory (~25% higher than the Dog paddock, Table 2), a result in general agreement with the hypothesis that clay particles act to protect SOC from decomposition (Jenkinson, 1990). However an examination of the SOC and the clay content of the individual cores (Fig. 7A and B), failed to reveal any clear relationship between SOC and clay levels down the soil profile. Indeed the individual sample data from the two sites show conflicting trends suggesting that either there is no consistent relationship between SOC and clay content or that other processes such as crack facilitated vertical transport of SOC and depth dependent decomposition rates are dominant factors in determining vertical SOC distribution at the two sites. 4.4. Modelling of the soil carbon profile with RothPC-1 To facilitate the application of RothPC-1 the individual SOC profiles observed at each site were averaged and aggregated into 5 layers of 23 cm depth from the soil surface down to a depth of 115 cm. The small amount of soil carbon present below 115 cm depth was ignored in the modelling work. Clay content in each soil layer was determined from the data shown in Fig. 5. Average soil bulk densities for each soil layer were calculated from gravimetric bulk density measurements of cores taken during the soil sampling survey. RothPC-1 carbon inputs, the transport parameter, p, and the decomposition parameter, s, were optimised to produce the best fit to the 1956 0–23 cm inventory and observed 2008 SOC profiles (Figs. 8 and 9). A close fit to the observed 2008 profiles was obtained for the Dog and Shed paddock sites with the predicted 2008 SOC profiles largely falling within the range of SOC stocks observed at all depths. To achieve the best fit, carbon inputs were set to 2.0 tC/ha (b1956), 2.1 tC/ha (1956–1970) and 0.5 tC/ha (1970–2008)) for the Dog paddock site with slightly lower inputs for the Shed paddock site (1.6 tC/ha (b1956), 1.7 tC/ha (1956–1970) and 0.4 tC/ha (1970–2008)). The optimised values of the decomposition constant, s, were −0.03 (Dog paddock) and −0.01 (Shed paddock). These values are lower than those reported by Jenkinson and Coleman (2008) for sites at Rothamsted suggesting that the decline in decomposition rates with increasing depth was less pronounced at the two sites investigated in this study. Optimised values for the transport parameter, p, were 0.81 and 0.63 for the Dog paddock and Shed paddock sites respectively. 5. Discussion There are significant questions concerning the appropriate SOC sampling depth for carbon inventory calculations (Anderson et al., 2010; Jobbágy and Jackson, 2000; Malamoud et al., 2009; Young et al., 2005). Current carbon accounting guidelines generally recommend sampling
Fig. 4. Rock content for individual sampling profiles; Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
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Fig. 5. Clay content for individual sampling profiles: Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
the upper 30 cm of the soil profile thereby encompassing the ‘actively’ changing soil carbon pool. Processes such as erosion/deposition of soil material as well as diffusional transport and the bulk movement of organic matter down the soil profile particularly in cracking soils however can seriously impact SOC estimates within such shallow soil depths (McKenzie et al., 2000). Consequently McKenzie et al. recommend characterising the entire soil profile if it is less than 1 m deep, and at least the top 1 m of deeper soils. Post et al. (2001) observes that while a sampling depth of 30 cm may be appropriate in many croplands, greater depths may be necessary under perennial vegetation and particularly in grasslands. The importance of quantifying the entire SOC profile was also highlighted in a study by Young et al. (2005) who examined SOC stocks at a number of different land use sites in north-western New South Wales, Australia. The study demonstrated that the sampling depth employed significantly affected how land use is perceived to influence carbon stocks. It is clear from Fig. 6 that the SOC is more uniformly spread through the soil profile in the Shed paddock than the Dog paddock despite similar farming practices (and surface carbon inputs) over the past five decades. With comparable surface carbon inputs and climatic conditions operating at the two sampling locations it is likely that site specific soil properties are responsible for the difference in SOC distribution. Possible factors include differences in the distribution of soil moisture (and hence microbial activity) down the soil profile and differences in the rate of vertical transport of organic material brought about as a result of increased soil cracking density in the Shed paddock vertosol soils. The more open structure of the Shed
paddock Vertosols may also result in root penetration to greater depths which in turn extends the depths to which carbon enters the soil profile (via root death or exudation). Inspection of Fig. 3 suggests that the Shed paddock soil moisture levels were only marginally higher than Dog paddock levels down to 50 cm and essentially the same at greater depths. While long term soil moisture records are not available for the two sites the 5 year data available suggests that the difference in soil moisture distribution between the two sites is not a major cause of the observed difference in vertical SOC distribution. It is more likely that enhanced transport of SOC down the soil profile is the cause of the more uniform Shed paddock SOC profile. This is corroborated by analysis of the distribution of the environmental tracer, 137 Cs, at the same site (see Wells and Hancock, submitted for publication). An inspection of the trench walls at the Shed paddock site revealed the presence of numerous shear faces, a substantial degree of subsurface cracking as well as extensive (>25 mm) cracking of the vertosol soil surface, features which were observed to a far lesser degree in the euchrozem soils of the Dog paddock site. It is likely that the cracking nature of the vertosol soil at the Shed paddock and to a lesser extent at the Dog paddock site allows organic material (in the form of surface litter and dissolved organic compounds) to be more efficiently transported to greater soil depths thereby shifting a greater proportion of the SOC inventory to >30 cm soil depths (55% of total SOC stocks at the Shed paddock site versus 43% at the Dog paddock site). The enhanced transport of SOC at the Shed paddock site is reflected in the results of the RothPC-1 simulation. Optimised values for the
Fig. 6. Individual SOC profiles: Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
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Table 2 SOC inventory (tC/ha) at the two field sites. Dog paddock SOC (tC/ha)
Profile 1
Profile 2
Profile 3
Profile 4
Average
Std. Dev.
0–30 cm 0–bedrock
63 116
50 90
71 121
48 81
58 102
11 20
Shed paddock SOC (tC/ha)
Profile 1
Profile 2
Profile 3
Average
Std. Dev.
0–30 cm 0–140 cm
54 115
54 123
62 142
56 126
5 14
transport parameter, p, were 0.81 and 0.63 for the Dog and Shed paddock sites respectively, suggesting that almost twice the amount of mobilised carbon from each pool is transported to the lower soil layers at the Shed paddock site (37%) than at the Dog paddock site (19%). RothPC-1 was able to model the SOC profiles at both field sites reasonably well and provided a means of quantitatively assessing the relative levels of SOC transport down the soil profile at the two sites (Figs. 8 and 9). The carbon inputs needed to provide the best fit to the observed SOC profiles however were approximately half that calculated from considerations of harvest yields, root to shoot ratios and literature data reported for grassland systems. Other issues were noted in running the RothPC-1 simulation of the field data. The most significant of these were the subsoil moisture levels and temperatures calculated within the model. Soil moisture content is calculated within the RothPC-1 model by considering both the rainfall and potential evaporation rates (as it is in the RothC-26.3 model). As Jenkinson and Coleman (2008) themselves note, in areas where evaporation exceeds rainfall throughout a majority of the year (as is the case in this study) the model should be used with great caution. At the two sites examined in this study RothPC-1 predicts soil moisture levels at, or close to, the maximum soil moisture deficit in all soil layers throughout the year (with the exception of June and July in the surface layer). Direct observation of the soil moisture content over a 5 year period (2003–2008), at a monitoring site situated in the Dog paddock (site ‘K1’, see Rüdiger et al., 2007), however suggests that subsoil moisture levels are generally close to field capacity for most of the year particularly in the deeper soil layers (Fig. 10A). As average annual rainfall over the same 5 year period was close to the long term average (629 mm versus the 139 year average of 624 mm recorded at Cassilis Station 20 km from the Illogan property, Australian Bureau of Meteorology, 2012) it is likely that the elevated soil moisture levels shown in Fig. 10A are indicative of long term levels. A further complication arises from the use of air temperature as a surrogate for soil temperature. A comparison of the 5 year soil temperature Table 3 SOC stock estimates for a range of published studies and the current study site. Study site and literature source
Maximum depth (m)
Liverpool Plains, NSW, Australia (Young et al., 2005) Brown Vertosols 1.4 Black Vertosols 2.0 Merriwa, Stanley property, NSW, Australia (Martinez, 2009) Red Vertosols/Euchrozems 1.06 Black Vertosols, creek flats 2.74 Merriwa, Roscommon property, NSW, Australia (Martinez, 2009) Euchrozems 0.2 Illogan, NSW, Australia (This study) Euchrozems, cropping 0.3 Euchrozems, cropping 1.4 Black Vertosols, cropping 0.3 Black Vertosols, cropping 1.4
SOC stock (tC/ha)
72 115–200
27.5–160 25.8–140
30–50
48–71 81–121 54–62 115–142
Fig. 7. Relationship between SOC and clay content. (A) Individual core samples—Dog paddock trench; (B) individual core samples—Shed paddock trench; (C) average values for individual profiles in each trench. Dashed lines represent linear best fit models.
trends recorded at 15 cm depth at the K1 monitoring site against air temperatures recorded over the same period (Fig. 10B) reveals that this can lead to discrepancies as high as 5 °C at various times of the year. Given the disparity between observed soil moisture and temperature levels and those calculated within the RothPC-1 model it was decided to re-run RothPC-1 using soil moisture and temperatures derived from measured field data. In the second application of the model, soil moisture deficits were calculated for each of the 5 model soil layers from data interpolated from the 5 year soil moisture data recorded at the K1 monitoring site. Subsoil temperature profiles were estimated from 15 cm soil
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Fig. 8. RothPC-1 SOC profile prediction for the Dog paddock trench; p = 0.81, s = −0.03. Grey columns represent aggregated observed SOC stocks and dashed lines show RothPC-1 predictions.
temperature data recorded at the K1 monitoring site and the sinusoidal relationship proposed by Kang et al. (2000): " T ðz;tÞ ¼ T a þ A0 exp −z
π ps κ s
1 = # 2
sin
1 = ! 2 2π π t−z ps ps κ s
ð5Þ
where T(z,t) is the subsoil temperature at depth, z, and time, t; Ta is the soil temperature averaged over all depths over the 5 year monitoring period; ps is the number of seconds in a year; κs is the soil thermal diffusivity (set to 2 × 10−7 m2/s for both sites as suggested for swelling clay soils at 0.3 v/v; Ross and Bridge, 1987) and A0 is the amplitude of the temperature wave at the soil surface. The value of A0 was optimised to produce the best fit between the predictions of Eq. (5) and the average annual soil temperature cycle recorded at the K1 monitoring site at 15 cm depth. Eq. (5) was then used to calculate the average monthly soil temperature in each of the 5 subsoil layers. The carbon inputs, transport parameters, p, and decomposition parameters, s, were once again optimised to produce the best fit to the 1956 0–23 cm inventory and the observed 2008 SOC profiles at each site. The optimised model outcomes are shown in Figs. 11 and 12. Increasing the levels of subsoil moisture had the effect of significantly increasing the rate of carbon decomposition at all soil depths. To compensate for the increased rates of decomposition, predicted carbon inputs into the soil had to be increased significantly to 2.9 tC/ha
(b 1956), 4.2 tC/ha (1956–1970) and 1.0 tC/ha (1970–2008) for the Dog paddock trench and 4.1 tC/ha (b 1956), 5.0 tC/ha (1956–1970) and 1.2 tC/ha (1970–2008) for the Shed paddock trench. Interestingly the new carbon input values are now close to values estimated from land management considerations (4.2 tC/ha for the grazing period 1956–1970 and 1.0 tC/ha for the cropping period 1970–2008). The fraction of mobilised carbon transported down the soil profile also increased (p = 0.45 and p = 0.44 for the Dog and Shed paddock respectively), while the decline in decomposition rates with depth was predicted to be negligible (s is approximately 0 at both sites). The overall fit to the 2008 SOC profiles using the more realistic values for soil moisture and temperature (Figs. 11 and 12), however was significantly poorer than the original RothPC-1 predictions (Figs. 8 and 9). The problems encountered in the RothPC-1 simulation of the Illogan SOC profile data suggests that there may be a question mark over its application in high clay, cracking soils in arid or semi-arid environments. Soil moisture and temperature levels calculated within RothPC-1 (particularly for deeper soils) did not reflect values observed in the field. When more realistic values for these parameters were included in the model the convective transport term used in RothPC-1 could not reproduce the observed SOC profiles. This finding is largely in agreement with other studies of vertical SOC transport (Elzein and Balesdent, 1995; Wells et al., 2012), which suggest that diffusional transport terms are needed if SOC transport processes are to be adequately simulated.
Fig. 9. RothPC-1 SOC profile predictions for the Shed paddock; p = 0.64, s = −0.01. Grey columns represent aggregated observed SOC stocks and dashed lines show RothPC-1 predictions.
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Fig. 10. Monthly average soil moisture and temperature data recorded over a 5 year period. (A) Monthly average soil moisture levels at 0–30 cm, 30–60 cm, and 60–90 cm depth. (B) The discrepancy between the monthly average air temperature and the soil temperature at 15 cm depth. (Air temperature data recorded at climate monitoring station ‘S2’ and remainder of data recorded at station ‘K1’ in the Dog paddock—for details see Rüdiger et al., 2007.)
6. Conclusions Soil organic carbon (SOC) concentrations and clay content have been determined from the soil surface down to bedrock at two neighbouring field sites with different soil types (Dog paddock—euchrozem and Shed paddock—vertosol), but a similar land use history of grazing followed by a period of minimal tillage cereal cropping. SOC inventory down to 30 cm depth at the Dog and Shed paddock were found to be essentially the same however the SOC profile was significant flatter at the Shed paddock site resulting in 25% higher SOC stocks when sampling inventory was extended down to bedrock. As the two sites share a similar land use history (and therefore a similar historical pattern of carbon inputs into the soil and soil tillage) the flatter SOC profile at the Shed paddock site is thought to be the result of the specific nature of the soil at this site. As a core by core comparison ruled out any clear relationship between clay content and SOC concentration it was concluded that the flatter profile was the result of enhanced SOC transport down the soil profile resulting from the more extensive cracking of the vertosol soil present at the Shed paddock site.
Modelling of SOC dynamics using RothPC-1 met with mixed success. RothPC-1 simulation of SOC turnover using soil moisture and soil temperature values calculated via the RothPC-1 approach yielded a satisfactory fit to the observed SOC profiles but the soil moisture and temperature levels generated within the model were found to be at odds with 5 year field observations. When more realistic values for soil moisture and temperature were substituted into the model the fit to the observed SOC profiles was significantly poorer indicating that the convective transport approach used to model SOC movement may not be adequate where cracking soils are present. Acknowledgments The Goodear family of Illogan are thanked for their support and unfailing generosity during this study. Ian Jeans and Simon Livingstone are thanked for the technical support in sample collection and preparation. A special thanks is also extended to Kevin Coleman who answered our (numerous) queries regarding the implementation of the RothPC-1 and RothC models with great patience and courteousness. This research
Fig. 11. RothPC-1 SOC profile prediction for the Dog paddock trench using soil moisture and temperatures based on field observations; p = 0.45, s = −0.003. Grey columns represent observed values and dashed line shows RothPC-1 predictions.
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Fig. 12. RothPC-1 SOC profile prediction for the Shed paddock trench using soil moisture and temperatures based on field observations; p = 0.44, s = −0.003. Grey columns represent observed values and dashed line shows RothPC-1 predictions.
was largely supported by an Australian Research Council Discovery Grant (DP 0556941: ‘Carbon, nutrient and sediment dynamics in a semi-arid catchment’) and a Faculty of Science and Information Technology, The University of Newcastle, Strategic Initiative Research Grant. References Anderson, R.H., Prues, A.G., Kravitz, M.J., 2010. Determination of the biologically relevant sampling depth for terrestrial ecological risk assessments. Geoderma 154, 336–339. Australian Bureau of Meteorology, 2012. Climate Data Online. http://www.bom.gov.au (Retrieved January 21st, 2012). Coleman, K., Jenkinson, D.S., 1999. ROTHC-26.3. A Model for the Turnover of Carbon in Soil: Model Description and Windows Users Guide. IACR, Rothamsted, Harpenden, Herts, UK. Coleman, K., Jenkinson, D.S., Crocker, G.J., Grace, P.R., Klír, J., Körschens, M., Poulton, P.R., Richter, D.D., 1997. Simulating trends in soil organic carbon in long-term experiments using RothC-26.3. Geoderma 81, 29–44. Elzein, A., Balesdent, J., 1995. Mechanistic simulation of vertical distribution of carbon concentrations and residence times in soils. Soil Science Society of America Journal 59, 1328. Falloon, P., Smith, P., 2002. Simulating SOC changes in long-term experiments with RothC and CENTURY: model evaluation for a regional scale application. Soil Use and Management 101–111. Hassink, J., 1997. The capacity of soils to preserve organic C and N by their association with clay and silt particles. Plant and Soil 191, 77–87. Jenkinson, D.S., 1990. The turnover of organic carbon and nitrogen in soil. Philosophical Transactions of the Royal Society of London, Series B 329, 361–367. Jenkinson, D.S., Coleman, K., 2008. The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover. European Journal of Soil Science 59, 400–413. Jenkinson, D.S., Poulton, P.R., Bryant, C., 2008. The turnover of organic carbon in subsoils. Part 1. Natural and bomb radiocarbon in soil profiles from the Rothamsted longterm field experiments. European Journal of Soil Science 59, 391–399. Jobbágy, E.G., Jackson, R.B., 2000. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecological Applications 10, 423–436. Kang, S., Kim, S., Oh, S., Lee, D., 2000. Predicting spatial and temporal patterns of soil temperature based on topography, surface cover and air temperature. Forest Ecology and Management 136, 173–184. Ladd, J.N., Amato, M., Oades, J.M., 1985. Decomposition of plant material in Australian soils. 111. Residual organic and microbial biomass C and N from isotope-labelled legume material and soil organic matter, decomposing under field conditions. Australian Journal of Soil Research 23, 603–611. Malamoud, K., McBratney, A.B., Minasny, B., Field, D.J., 2009. Modelling how carbon affects soil structure. Geoderma 149, 19–26.
Martinez, C., 2009. Soil carbon dynamics at hillslope and catchment scales. PhD Thesis School of Environmental and Life Sciences.University of Newcastle, Australia. McKenzie, N., Ryan, P., Fogarty, P., Wood, J., 2000. Sampling, measurement and analytical protocols for carbon estimation in soil, litter and coarse woody debris. National Carbon Accounting System Technical Report No. 14. Australian Greenhouse Office. McRae, R.H.D., Cooper, M.G., 1985. Vegetation of the Merriwa area, New South Wales. Cunninghamia 1, 351–369. Meersmans, J., van Wesemael, B., De Ridder, F., Van Molle, M., 2009. Modelling the three-dimensional spatial distribution of soil organic carbon (SOC) at the regional scale (Flanders, Belgium). Geoderma 152, 43–52. Paul, K.I., Polglase, P.J., 2004. Calibration of the RothC model to turnover of soil carbon under eucalypts and pines. Australian Journal of Soil Research 42, 883–895. Plante, A.F., Conant, R.T., Stewart, C.E., Paustian, K., Six, J., 2006. Impact of soil texture on the distribution of soil organic matter in physical and chemical fractions. Soil Science Society of America Journal 70, 287. Post, W.M., Izaurralde, R.C., Mann, L.K., Bliss, N., 2001. Monitoring and verifying changes of organic carbon in soil. Climatic Change 51, 73–99. Ross, P.J., Bridge, B.J., 1987. Thermal properties of swelling clay soils. Australian Journal of Soil Research 25, 29–41. Rüdiger, C., Hancock, G., Hemakumara, H.M., Jacobs, B., Kalma, J.D., Martinez, C., Thyer, M., Walker, J.P., Wells, T., Willgoose, G.R., 2007. Goulburn River experimental catchment data set. Water Resources Research 43, W10403. Schlesinger, W.H., 1977. Carbon balance in terrestrial detritus. Annual Review of Ecology and Systematics 8, 51–81. Schlesinger, W.H., 2000. Carbon sequestration in soils: some cautions amidst optimism. Agriculture, Ecosystems & Environment 82, 121–127. Six, J., Conant, R.T., Paul, E.A., Paustian, K., 2002. Stabilization mechanisms of soil organic matter: implications for C-saturation of soils. Plant and Soil 241, 155–176. Smith, R.T., Atkinson, K., 1975. Techniques in Pedology: A Handbook for Environmental and Resource Studies. Paul Elec, London, UK. Thomsen, I.K., Schjønning, P., Jensen, B., Kristensen, K., Christensen, B.T., 1999. Turnover of organic matter in differently textured soils: II. Microbial activity as influenced by soil water regimes. Geoderma 89, 199–218. Wells, T., Hancock, G., 2013. Comparison of the vertical transport of 137Cs and organic carbon in agricultural cracking soils. Geoderma (submitted for publication). Wells, T., Hancock, G.R., Dever, C., Murphy, D., 2012. Prediction of vertical soil organic carbon profiles using soil properties and environmental tracer data at an untilled site. Geoderma 170, 337–346. Young, R., Wilson, B.R., McLeod, M., Alston, C., 2005. Carbon storage in the soils and vegetation of contrasting land uses in northern New South Wales, Australia. Australian Journal of Soil Research 43, 21–31.
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Application of RothPC-1 to soil carbon profiles in cracking soils under minimal till cultivation T. Wells a,⁎, G.R. Hancock b,1, C. Dever b,1, C. Martinez b,1 a b
School of Engineering, The University of Newcastle, Callaghan, NSW 2308, Australia School of Environmental and Life Sciences, Geology Building, The University of Newcastle, Callaghan, NSW 2308, Australia
a r t i c l e
i n f o
Article history: Received 10 December 2012 Received in revised form 19 May 2013 Accepted 20 May 2013 Available online 11 June 2013 Keywords: Soil carbon Vertical transport RothPC-1 Cracking soil
a b s t r a c t This study examines soil organic carbon (SOC) profiles in two neighbouring field sites (‘Dog’ and ‘Shed’ paddocks) which share a similar land use history but are characterised by different soil types (euchrozem and vertosol). SOC inventories to 30 cm depth at the two sites were similar however enhanced transport of SOC in the cracking vertosol soils of the Shed paddock produced a significantly flatter SOC profile and higher whole profile SOC inventories at this site. No clear relationship was observed between clay content and SOC distribution at either sample site. Modelling of SOC turnover using RothPC-1 yielded a satisfactory fit to the observed SOC profiles however the soil moisture and temperature values calculated within the model were found to be at odds with 5 year field observations reported from the site. When field measured values for the moisture and temperature were substituted into the model the fit to the observed SOC profiles was significantly poorer indicating that the purely convective transport approach used to model SOC movement within RothPC-1 may not be sufficient to model vertical SOC transport in cracking soils. The results highlight the need for a cautious approach when using RothPC-1 in arid, cracking soil environments. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved.
1. Introduction There is currently considerable interest in the factors that impact on the vertical distribution of soil organic carbon (SOC) throughout the soil column. These factors include climate and vegetation (Jobbágy and Jackson, 2000), land management practices and soil type (Meersmans et al., 2009; Schlesinger, 2000; Young et al., 2005) as well as the manner in which SOC is transported down the soil profile (Wells et al., 2012). In this study the vertical distribution of SOC down to bedrock is compared in two neighbouring field sites which share a similar land use history of minimal till agriculture. The soils at both sites have a medium to high clay content however they experience significantly different levels of cracking behaviour. One aim of this study is to investigate the possible relationship between SOC distribution down the soil profile and the corresponding soil clay content. While the links between SOC and soil clay content have been examined extensively in the upper reaches of the soil profile, the relationship between the vertical distribution of SOC and the corresponding clay content of the soil profile has received less attention (Wells et al., 2012). While it is a widely held belief that the level of
⁎ Corresponding author. Tel.: +61 2 4921 5741; fax: +61 2 4921 6991. E-mail addresses: [email protected] (T. Wells), [email protected] (G.R. Hancock). 1 Tel.: +61 2 4921 5090; fax: +61 2 4921 5877.
SOC preservation increases as clay content increases (Hassink, 1997; Ladd et al., 1985), it has been observed that the relationship between SOC and clay content is complex (Plante et al., 2006; Six et al., 2002; Thomsen et al., 1999) as soil texture acts directly and indirectly on various protection mechanisms (for example via its effect on the soil water regime). Consequently clay content may not be a universal predictor of whole profile carbon inventory. By comparing the vertical distribution of SOC and clay content at both sites we seek to add to our understanding of this complex relationship. This study will also examine the impact of soil cracking on the transport of SOC down the soil column. A recent finite element analysis of SOC movement in a sandy soil carried out in conjunction with 137 Cs/210Pbex analysis (Wells et al., 2012), indicated that SOC transport includes a significant diffusional component (possibly resulting from bioturbation). In this study we will attempt to model the SOC distributions observed at each field site using a recently proposed subsoil SOC turnover model, RothPC-1 (Jenkinson and Coleman, 2008; Jenkinson et al., 2008), which incorporates a convective transport mechanism only. While the RothC-26.3 soil carbon model (Coleman et al., 1997) is in common use in predicting the dynamics of carbon in the upper (normally 0–23 cm or 0–30 cm) soil layer (e.g. Falloon and Smith, 2002; Paul and Polglase, 2004), there have been few if any studies testing the application of the RothPC-1 model since it was originally proposed. In this study we are interested to determine if the convection-only transport component included in the RothPC-1 model is sufficient to model the observed SOC transport at the field sites examined.
0016-7061/$ – see front matter. Crown Copyright © 2013 Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.geoderma.2013.05.018
T. Wells et al. / Geoderma 207–208 (2013) 144–153
2. Study site The two field sites sampled (‘Dog’ and ‘Shed’ paddocks), are located on the Illogan property which is situated in the Krui River catchment area. The Krui River catchment is one of 12 major sub-catchments of the greater Goulburn River system (6540 km2), which lies in the Upper Hunter region of New South Wales, Australia (Fig. 1). The first sampling pit (Dog paddock), was excavated 10 m to the east of a permanently mounted weather and soil moisture monitoring station (‘K1’, see Rüdiger et al., 2007). A second sampling site was established ~1.5 km to the west in the Shed paddock (Fig. 1). The Krui catchment extends from 31°49′S to 32°13′S and 150°02′E to 150°21′E, with elevations ranging from approximately 200 m in the south (Merriwa Plateau) to 1200 m in the north (Liverpool Range). The region is located in the temperate zone of eastern Australia. Average annual rainfall in the study area is 624 mm (the 139 year average recorded at the Cassilis monitoring station located 20 km from the Illogan property; Australian Bureau of Meteorology, 2012). Average annual potential evaporation is approximately 1200 mm. The highly fertile, basaltic soils of the Krui area have significantly influenced land use practices within the region, with grazing and cropping activities dominating. The Illogan property which is the focus of this study has predominantly red basaltic clays (Euchrozems, upon which the Dog paddock site is located) and black earths (Vertosols, upon which the Shed paddock site is located). Cracking of the soil at both sites has been observed on many occasions during dry periods however the width, depth and concentration of cracks at the Shed paddock site are significantly greater than that observed at the Dog paddock site. The slope (1%), aspect and elevation of each site however are similar. There is no evidence at either site of erosion/deposition or any disturbance other than that produced by cultivation practices associated with minimum tillage cereal and grain production. The Illogan property has been owned by the same family for over 50 years. Prior to the 1950's the local landscape was open grassy woodland characterised by widely spaced eucalypt trees with very little shrub cover and sparse ground cover (McRae and Cooper, 1985). In the mid 1950's both sites examined in this study were cleared and the native vegetation replaced by improved pasture which was grazed until 1970. Since 1970 the two field sites have predominantly supported
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cereal cropping activities, including barley, oats, and wheat. Between 1970 and 1990 the soil at both sites was lightly tilled to 10 cm depth. Since 1990 minimal tillage practices have been employed at both sites (maximum depth of disturbance b5 cm for seeding and fertiliser application). 3. Methodology In this study soil cores were collected down to bedrock for determination of SOC content and soil texture. The soils excavated from the Dog and Shed paddock sites are representative of the two major soil types present on the Illogan property and broadly representative of soils used for cropping in the region. Both sites were in fallow between crop rotations when sampled in May 2008. 3.1. Soil sampling and analysis A backhoe was used to cut 3 m long soil trenches down to bedrock at each site. Soil depth at both sites was approximately 1.4 m (including ~0.1 m of weathered bedrock or saprolite). Four individual vertical profiles were sampled from the walls of the Dog paddock trench and three from the Shed paddock trench. Each vertical profile was sampled using 100 mm long by 65 mm ID cores which were hammered horizontally into the side wall of the trench at regular intervals in a vertical line from the soil surface down to bedrock. The exception to this was the uppermost core which was collected vertically from the surface. Seven to eight core samples were taken for each vertical profile in the Dog paddock trench (31 samples in total) and 8–10 cores for each Shed paddock profile (27 samples in total). After collection soil samples were immediately weighed then air dried at 40 °C for 2 to 3 days. The dried samples were gently disaggregated with a mortar and pestle and passed through a 2 mm sieve and the coarse (> 2 mm) fraction separated. The b2 mm fraction was further disaggregated with a mortar and pestle and weighed. The bulk density of each sample was calculated using the dried soil mass and volume of each core. The b 2 mm soil fraction was ground in a mill to a fine powder and the total carbon content measured using a LECO 2000 analyser. LECO carbon results were corrected for inorganic carbon content determined
Fig. 1. Location map of Illogan study site (A) soil map and (B) Illogan property as viewed from QuickBird satellite (July, 2005) showing locations of the two sample sites. (Note: trench dimensions shown are not to scale.)
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by monitoring CO2 evolution following FeCl and HCl digestion of the soil sample. The hydrometer method outlined by Smith and Atkinson (1975) was employed to establish the particle size distribution of the b2 mm soil fraction. Soil colour was determined on both wet and dry samples.
ðCO2 Þ=ðBIO þ HUMÞ ¼ pðZ þ 1Þ−1:
ð2Þ
The partitioning coefficient, Z, for each soil layer is a function of the clay content of the layer (as in RothC-26.3), i.e.:
3.2. Modelling of the data The data obtained at the two field sites allows us to test the applicability of the carbon subsoil turnover model, RothPC-1, proposed by Jenkinson (Jenkinson and Coleman, 2008). The model is an extension of RothC-26.3 (Coleman and Jenkinson, 1999) which models carbon turnover in the upper soil layer (nominally 0–23 cm depth). Readers are directed to Jenkinson and Coleman (2008) for a detailed description of RothPC-1 however some of the important aspects of the model's implementation will be discussed here briefly. RothPC-1 utilises the same multi-pool structure as RothC-26.3. Incoming organic carbon is partitioned between decomposable plant material (DPM) and resistant plant material (RPM) both of which decompose via a first order process to produce CO2, humus (HUM) and microbial biomass (BIO). HUM and BIO in turn decompose by further first order processes to form more CO2, BIO and HUM. The rate of decomposition of each carbon pool is dictated by a characteristic rate constant which is modified by soil temperature, moisture and for the upper soil layer, the level of vegetation cover. Calculation of the decomposition rates in RothPC-1 generally follows the procedures used in RothC-26.3 however there are some important points to note in implementing the RothPC-1 model, namely: 1) The characteristic decay rate constant for the BIO carbon pool is set to 1.5 year−1 (not 0.66 year−1 as in RothC-26.3). 2) The decomposition is modified for temperature in all five soil layers using the monthly average air temperature (a contentious oversimplification as pointed out by Jenkinson and Coleman themselves). 3) Decomposition is also modified for soil water content after calculating an accumulated soil moisture deficit throughout the year and comparing this to a maximum soil moisture deficit (MaxSMD). MaxSMD of each soil layer is calculated in the same manner as in RothC-26.3 using the clay content characteristic of that layer. (If the soil is bare MaxSMD is divided by 1.8.) When monthly potential evaporation exceeds rainfall, each layer starting from the upper layer dries out until it reaches MaxSMD. When rainfall exceeds evaporation, each layer, starting at the upper layer, wets up until field capacity is reached. 4) The decay rate constants for all carbon pools are assumed to decrease with depth. This is facilitated by multiplying the carbon pool decomposition rate constant by a factor, N, which is calculated using the following sigmoid function: N ¼ ð−1=ð1 þ ð expð−sðF−f ÞÞÞÞÞ=ð−1=ð1 þ ð expð−sð−f ÞÞÞÞÞ
the ratio of CO2 to (BIO + HUM) formed when a carbon pool decomposes, (=Z in RothC-26.3), is modified as follows:
ð1Þ
where s is a constant (cm−1) which is optimised to provide the best fit to the data, F is the distance from the middle of the top layer to the mid-depth of the soil layer in question (cm) and f is the distance from the surface to the mid-depth of the top layer (cm). 5) The downward movement of carbon from each pool is described using a convection like transport term, p, (−). At the end of each month a fraction, (1 − p), of the mobilised (decomposed) material from each pool is transported to the soil layer below. If for example, p = 1, then no material is transported to the lower soil layers and RothPC-1 essentially reverts to the RothC-26.3 model. As the value of p decreases the fraction of material transported down the soil column increases. 6) To ensure that RothPC-1 predictions of newly formed BIO and HUM in the upper soil layer each month match that predicted in RothC-26.3
Z ¼ 1:67ð1:85 þ 1:6 expð−0:0786ð%clayÞÞÞ:
ð3Þ
7) In an overall sense carbon is moved down the soil profile at the expense of CO2 being released. One consequence of this restriction is that the transport parameter, p, is limited in range to values between 1 and pmin where pmin is defined by: p min ¼
1 : Zþ1
ð4Þ
3.2.1. Other modelling considerations In this study it was assumed that the climate operating at the two sites was identical as they are separated by less than 2 km. The monthly average rainfall and air temperature data were sourced from meteorological records of the nearby weather station of Cassilis (20 km distant, 139 year rainfall average and 60 year temperature averages) while open pan evaporation rates were obtained from data reported for the township of Scone (49 km distant, 45 year averages) (Australian Bureau of Meteorology, 2012). Prior to 1956 the Dog and Shed paddock sites were predominantly open scrubland with widely spaced trees (McRae and Cooper, 1985). In 1956 both sites were cleared and between 1956 and 1970 were devoted to grazing on improved pasture. From 1970 to the time of sampling the two sites were dedicated to cereal cropping (generally 1 crop per year of wheat, oats or barley) with both sites fallow every 4th year. During the cropping years it was assumed that the sites were fallow for the months January through June. DPM/RPM split of the incoming plant carbon was set at 0.67 for the period prior to 1956 (as per the value suggested for unimproved grassland and scrub; Coleman and Jenkinson, 1999), and 1.44 thereafter (as per the suggested value for agricultural crops and improved pasture). All incoming carbon (resulting from the decomposition of surface litter and root material) was assumed to enter the soil column via the upper (0–23 cm) soil layer only. To best assess the performance of the RothPC-1 model it was not only necessary to know the vertical SOC distribution at the time of sampling but also estimate the SOC profile at the commencement of agricultural activity (i.e. the b 1956 profiles). As no soil data was available for this period of time the 1956 profiles at each site were determined indirectly as follows: (1) Dog paddock site 1956 SOC profile. SOC profiles were obtained from a neighbouring property located less than 500 m from the Dog paddock site in 2008. The neighbouring property shares the same euchrozem soil type and structure as the Dog paddock site and it is naturally vegetated having never been subject to cropping and only minimally grazed. It was therefore assumed that the SOC profiles observed at this neighbouring site are a reasonable approximation of the SOC profile at the Dog paddock site prior to clearing, grazing and cropping. (2) Shed paddock site. The 1956 soil carbon profile for the Shed paddock site was based on the SOC profile reported for the ‘Donald's Ridge’ location in the nearby Liverpool Ranges by Young et al. (2005). The soil type (high clay content, black vertosol), climate and vegetation (grassy open woodland) reported for the Donald's Ridge location are thought to be similar to that present at the Shed paddock site prior to 1956.
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The soil carbon data for each surrogate 1956 profile were aggregated into the 5 soil layers used in the modelling procedure (0–23, 23–46, 46–69, 69–92 and 92–115 cm, Fig. 2). The RothPC-1 model was first run to equilibrium (a run of 10,000 years) for the two field sites and the pre-1956 annual carbon input to the soil at each site adjusted until the predicted total carbon content of the uppermost (0–23 cm) soil layer matched the 0–23 cm 1956 profile stocks at the two sites. Once the 1956 SOC profiles were estimated the model was then run for the periods 1956–1970 (grazing period) and 1970–2008 (cereal cropping period) and the transport factor, p, decomposition damping factor, s, and annual carbon input during the grazing and cropping periods were optimised to provide the best fit to the observed 2008 SOC profile at each site. The ratio of carbon inputs during the grazing (Cin,1956–1970) and cropping period (Cin,1970–2008) were fixed to best reflect the expectation that carbon input during the cropping period was lower than that during the period of grazing on improved pasture. Schlesinger (1977) suggests that the carbon input in grassland systems is likely to be in the order of 4.2 tC/ha. In a separate study by the authors (Wells and Hancock, submitted for publication) carbon inputs during the cereal cropping period (based on harvest yields and root to shoot ratios typical of wheat, oats and barley), have been estimated to be approximately 1 tC/ha. Thus while the magnitude of the carbon inputs for these two periods of time was allowed to vary the ratio Cin,1956–1970 : Cin,1970–2008 was fixed at 4.2:1.
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4. Results 4.1. Sampling profile characteristics Four profiles were sampled at the Dog paddock site and 3 at the Shed paddock site. The Dog paddock profiles were separated by 0.1, 1.5 and 1.6 m while the Shed paddock profiles were separated by 0.2 and 3 m. There was little profile-to-profile variation in clay and rock content, colour, or SOC levels within a given trench. The two sites were sampled in May 2008 after a prolonged dry period. Despite the lack of recent rain subsoil moisture levels at both locations were close to field capacity (~ 0.3 v/v at >30 cm depth, Fig. 3). Despite this, cracking of the soil profile was observed at both sites. At the Dog paddock site fine cracks, while absent on the surface, were numerous down the soil profile. Cracking of the black vertosol soil at the Shed paddock site however was significantly more extensive with numerous cracks up to 50 mm wide observed on the surface and down the soil profile. At the Dog paddock site small amounts of wheat stubble were present on the soil surface and traces of organic matter were observed down to a depth of 50 to 70 cm while sorghum stubble was present in small amounts on the soil surface at the Shed paddock location. No strong horizons or colour contrasts were present in the Dog Paddock soil profile (Table 1). A range of soil colouring was observed at the Shed paddock trench but strong contrasts down the profile were not found suggesting consistent soil properties and an aerobic environment at this site (Table 1). The maximum depth of soil including saprolite at both sample sites was approximately 140 cm at which point large core stones and bedrock were encountered preventing the backhoe from digging further. Minimal rock was present in either profile until a depth of approximately 90 cm was reached whereupon rock content, particularly at the Dog paddock site, increased sharply (Fig. 4). Distinct differences were observed in the clay content at the two sites (Fig. 5). At the Dog paddock site clay increases with depth until a maximum is reached at approximately 80 cm depth. At greater depths the clay content declines as the soil becomes coarser and transitions to saprolite and ultimately bedrock. Clay content at the Shed paddock is approximately constant down to 80 cm depth at which point clay content declines in response to the presence of the weathering front. Average clay content at the Shed paddock (vertosol) was 66%, slightly higher than that observed at the Dog paddock (euchrozem, 56%). 4.2. SOC distribution and inventory The SOC depth profiles at the two sample sites also differ significantly (Fig. 6). At the Dog paddock surface SOC concentrations are
Fig. 2. SOC profiles used to represent the 1956 profile in RothPC-1 modelling of the (A) Dog paddock site and (B) Shed paddock site.
Fig. 3. Gravimetric moisture content of soil core samples as a function of depth.
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Table 1 Soil colour at the two field sites. Sample
Dry sample Munsell notation
Dog paddock 5 cm 2.5 YR 4/4 15 cm 5 YR 3/4 30 cm 5 YR 3/6 45 cm 5 YR 4/6 65 cm 5 YR 5/6 85 cm 5 YR 4/4 110 cm 5 YR 5/4 130 cm 5 YR 5/6 Shed paddock 5 cm 7.5 YR 4/2 10 cm 10 YR 4/2 25 cm 10 YR 4/2 40 cm 10 YR 4/2 55 cm 10 YR 4/2 70 cm 10 YR 4/2 85 cm 10 YR 4/3 100 cm 10 YR 4/3 120 cm 7.5 YR 4/3 135 cm 10 YR 4/3
Wet sample Munsell's soil colour Munsell name notation
Munsell's soil colour name
Reddish brown Dark reddish brown Dark reddish brown Yellowish red Yellowish red Reddish brown Reddish brown Yellowish red
5 YR 5 YR 5 YR 5 YR 5 YR 5 YR 5 YR 5 YR
Very dark reddish brown Very dark reddish brown Very dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown Dark reddish brown
Dark brown Dark greyish brown Dark greyish brown Dark greyish brown Dark greyish brown Dark greyish brown Brown Brown Dark brown Brown
7.5 YR 2/2 10 YR 2/2 7.5 YR 2/3 10 YR 3/3 10 YR 2/3 10 YR 3/4 10 YR 3/4 10 YR 3/4 5 YR 4/4 10 YR 4/4
2/4 2/4 2/4 3/6 3/6 3/6 3/6 3/6
Brownish black Very dark brown Very dark brown Dark brown Brownish black Dark Yellowish brown Dark Yellowish brown Dark Yellowish brown Reddish brown Dark Yellowish brown
approximately 2.5% but declines rapidly in an exponential fashion so that SOC levels are b 0.5% at depths greater than ~ 40 cm. The surface concentration of SOC at the Shed paddock is considerably lower (~ 1.5–2%), however the decline of SOC concentration with depth is less pronounced and proceeds in a more linear fashion so that SOC concentrations >0.5% are still observed down to depths of 80 cm. The flatter SOC profile at the Shed paddock site results in a median SOC depth of 31 cm compared to 21 cm at the Dog paddock site. The SOC inventories for each sampling profile at each field site are listed in Table 2. While the average 0–30 cm SOC inventories for the two sites are essentially the same (56 and 58 tC/ha) the flatter SOC depth profile observed at the Shed paddock site results in a ~ 25% higher inventory at this site when the entire soil carbon profile down to bedrock is considered (128 tC/ha versus 102 tC/ha). A comparison between the 0–30 cm and full profile SOC inventories determined in this study and elsewhere (Table 3) suggests that the carbon stocks observed at the Dog and Shed paddocks are consistent with values reported in the surrounding region for similar soil types. 4.3. Use of clay content to predict SOC distribution SOC distribution was compared to clay content down the soil profile at each sampling site. The Shed paddock site with its slightly higher
average clay content (66% compared to 56% in the Dog paddock), also had a higher SOC inventory (~25% higher than the Dog paddock, Table 2), a result in general agreement with the hypothesis that clay particles act to protect SOC from decomposition (Jenkinson, 1990). However an examination of the SOC and the clay content of the individual cores (Fig. 7A and B), failed to reveal any clear relationship between SOC and clay levels down the soil profile. Indeed the individual sample data from the two sites show conflicting trends suggesting that either there is no consistent relationship between SOC and clay content or that other processes such as crack facilitated vertical transport of SOC and depth dependent decomposition rates are dominant factors in determining vertical SOC distribution at the two sites. 4.4. Modelling of the soil carbon profile with RothPC-1 To facilitate the application of RothPC-1 the individual SOC profiles observed at each site were averaged and aggregated into 5 layers of 23 cm depth from the soil surface down to a depth of 115 cm. The small amount of soil carbon present below 115 cm depth was ignored in the modelling work. Clay content in each soil layer was determined from the data shown in Fig. 5. Average soil bulk densities for each soil layer were calculated from gravimetric bulk density measurements of cores taken during the soil sampling survey. RothPC-1 carbon inputs, the transport parameter, p, and the decomposition parameter, s, were optimised to produce the best fit to the 1956 0–23 cm inventory and observed 2008 SOC profiles (Figs. 8 and 9). A close fit to the observed 2008 profiles was obtained for the Dog and Shed paddock sites with the predicted 2008 SOC profiles largely falling within the range of SOC stocks observed at all depths. To achieve the best fit, carbon inputs were set to 2.0 tC/ha (b1956), 2.1 tC/ha (1956–1970) and 0.5 tC/ha (1970–2008)) for the Dog paddock site with slightly lower inputs for the Shed paddock site (1.6 tC/ha (b1956), 1.7 tC/ha (1956–1970) and 0.4 tC/ha (1970–2008)). The optimised values of the decomposition constant, s, were −0.03 (Dog paddock) and −0.01 (Shed paddock). These values are lower than those reported by Jenkinson and Coleman (2008) for sites at Rothamsted suggesting that the decline in decomposition rates with increasing depth was less pronounced at the two sites investigated in this study. Optimised values for the transport parameter, p, were 0.81 and 0.63 for the Dog paddock and Shed paddock sites respectively. 5. Discussion There are significant questions concerning the appropriate SOC sampling depth for carbon inventory calculations (Anderson et al., 2010; Jobbágy and Jackson, 2000; Malamoud et al., 2009; Young et al., 2005). Current carbon accounting guidelines generally recommend sampling
Fig. 4. Rock content for individual sampling profiles; Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
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Fig. 5. Clay content for individual sampling profiles: Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
the upper 30 cm of the soil profile thereby encompassing the ‘actively’ changing soil carbon pool. Processes such as erosion/deposition of soil material as well as diffusional transport and the bulk movement of organic matter down the soil profile particularly in cracking soils however can seriously impact SOC estimates within such shallow soil depths (McKenzie et al., 2000). Consequently McKenzie et al. recommend characterising the entire soil profile if it is less than 1 m deep, and at least the top 1 m of deeper soils. Post et al. (2001) observes that while a sampling depth of 30 cm may be appropriate in many croplands, greater depths may be necessary under perennial vegetation and particularly in grasslands. The importance of quantifying the entire SOC profile was also highlighted in a study by Young et al. (2005) who examined SOC stocks at a number of different land use sites in north-western New South Wales, Australia. The study demonstrated that the sampling depth employed significantly affected how land use is perceived to influence carbon stocks. It is clear from Fig. 6 that the SOC is more uniformly spread through the soil profile in the Shed paddock than the Dog paddock despite similar farming practices (and surface carbon inputs) over the past five decades. With comparable surface carbon inputs and climatic conditions operating at the two sampling locations it is likely that site specific soil properties are responsible for the difference in SOC distribution. Possible factors include differences in the distribution of soil moisture (and hence microbial activity) down the soil profile and differences in the rate of vertical transport of organic material brought about as a result of increased soil cracking density in the Shed paddock vertosol soils. The more open structure of the Shed
paddock Vertosols may also result in root penetration to greater depths which in turn extends the depths to which carbon enters the soil profile (via root death or exudation). Inspection of Fig. 3 suggests that the Shed paddock soil moisture levels were only marginally higher than Dog paddock levels down to 50 cm and essentially the same at greater depths. While long term soil moisture records are not available for the two sites the 5 year data available suggests that the difference in soil moisture distribution between the two sites is not a major cause of the observed difference in vertical SOC distribution. It is more likely that enhanced transport of SOC down the soil profile is the cause of the more uniform Shed paddock SOC profile. This is corroborated by analysis of the distribution of the environmental tracer, 137 Cs, at the same site (see Wells and Hancock, submitted for publication). An inspection of the trench walls at the Shed paddock site revealed the presence of numerous shear faces, a substantial degree of subsurface cracking as well as extensive (>25 mm) cracking of the vertosol soil surface, features which were observed to a far lesser degree in the euchrozem soils of the Dog paddock site. It is likely that the cracking nature of the vertosol soil at the Shed paddock and to a lesser extent at the Dog paddock site allows organic material (in the form of surface litter and dissolved organic compounds) to be more efficiently transported to greater soil depths thereby shifting a greater proportion of the SOC inventory to >30 cm soil depths (55% of total SOC stocks at the Shed paddock site versus 43% at the Dog paddock site). The enhanced transport of SOC at the Shed paddock site is reflected in the results of the RothPC-1 simulation. Optimised values for the
Fig. 6. Individual SOC profiles: Dog paddock trench (A) and Shed paddock trench (B). Solid lines are included for clarity only.
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Table 2 SOC inventory (tC/ha) at the two field sites. Dog paddock SOC (tC/ha)
Profile 1
Profile 2
Profile 3
Profile 4
Average
Std. Dev.
0–30 cm 0–bedrock
63 116
50 90
71 121
48 81
58 102
11 20
Shed paddock SOC (tC/ha)
Profile 1
Profile 2
Profile 3
Average
Std. Dev.
0–30 cm 0–140 cm
54 115
54 123
62 142
56 126
5 14
transport parameter, p, were 0.81 and 0.63 for the Dog and Shed paddock sites respectively, suggesting that almost twice the amount of mobilised carbon from each pool is transported to the lower soil layers at the Shed paddock site (37%) than at the Dog paddock site (19%). RothPC-1 was able to model the SOC profiles at both field sites reasonably well and provided a means of quantitatively assessing the relative levels of SOC transport down the soil profile at the two sites (Figs. 8 and 9). The carbon inputs needed to provide the best fit to the observed SOC profiles however were approximately half that calculated from considerations of harvest yields, root to shoot ratios and literature data reported for grassland systems. Other issues were noted in running the RothPC-1 simulation of the field data. The most significant of these were the subsoil moisture levels and temperatures calculated within the model. Soil moisture content is calculated within the RothPC-1 model by considering both the rainfall and potential evaporation rates (as it is in the RothC-26.3 model). As Jenkinson and Coleman (2008) themselves note, in areas where evaporation exceeds rainfall throughout a majority of the year (as is the case in this study) the model should be used with great caution. At the two sites examined in this study RothPC-1 predicts soil moisture levels at, or close to, the maximum soil moisture deficit in all soil layers throughout the year (with the exception of June and July in the surface layer). Direct observation of the soil moisture content over a 5 year period (2003–2008), at a monitoring site situated in the Dog paddock (site ‘K1’, see Rüdiger et al., 2007), however suggests that subsoil moisture levels are generally close to field capacity for most of the year particularly in the deeper soil layers (Fig. 10A). As average annual rainfall over the same 5 year period was close to the long term average (629 mm versus the 139 year average of 624 mm recorded at Cassilis Station 20 km from the Illogan property, Australian Bureau of Meteorology, 2012) it is likely that the elevated soil moisture levels shown in Fig. 10A are indicative of long term levels. A further complication arises from the use of air temperature as a surrogate for soil temperature. A comparison of the 5 year soil temperature Table 3 SOC stock estimates for a range of published studies and the current study site. Study site and literature source
Maximum depth (m)
Liverpool Plains, NSW, Australia (Young et al., 2005) Brown Vertosols 1.4 Black Vertosols 2.0 Merriwa, Stanley property, NSW, Australia (Martinez, 2009) Red Vertosols/Euchrozems 1.06 Black Vertosols, creek flats 2.74 Merriwa, Roscommon property, NSW, Australia (Martinez, 2009) Euchrozems 0.2 Illogan, NSW, Australia (This study) Euchrozems, cropping 0.3 Euchrozems, cropping 1.4 Black Vertosols, cropping 0.3 Black Vertosols, cropping 1.4
SOC stock (tC/ha)
72 115–200
27.5–160 25.8–140
30–50
48–71 81–121 54–62 115–142
Fig. 7. Relationship between SOC and clay content. (A) Individual core samples—Dog paddock trench; (B) individual core samples—Shed paddock trench; (C) average values for individual profiles in each trench. Dashed lines represent linear best fit models.
trends recorded at 15 cm depth at the K1 monitoring site against air temperatures recorded over the same period (Fig. 10B) reveals that this can lead to discrepancies as high as 5 °C at various times of the year. Given the disparity between observed soil moisture and temperature levels and those calculated within the RothPC-1 model it was decided to re-run RothPC-1 using soil moisture and temperatures derived from measured field data. In the second application of the model, soil moisture deficits were calculated for each of the 5 model soil layers from data interpolated from the 5 year soil moisture data recorded at the K1 monitoring site. Subsoil temperature profiles were estimated from 15 cm soil
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Fig. 8. RothPC-1 SOC profile prediction for the Dog paddock trench; p = 0.81, s = −0.03. Grey columns represent aggregated observed SOC stocks and dashed lines show RothPC-1 predictions.
temperature data recorded at the K1 monitoring site and the sinusoidal relationship proposed by Kang et al. (2000): " T ðz;tÞ ¼ T a þ A0 exp −z
π ps κ s
1 = # 2
sin
1 = ! 2 2π π t−z ps ps κ s
ð5Þ
where T(z,t) is the subsoil temperature at depth, z, and time, t; Ta is the soil temperature averaged over all depths over the 5 year monitoring period; ps is the number of seconds in a year; κs is the soil thermal diffusivity (set to 2 × 10−7 m2/s for both sites as suggested for swelling clay soils at 0.3 v/v; Ross and Bridge, 1987) and A0 is the amplitude of the temperature wave at the soil surface. The value of A0 was optimised to produce the best fit between the predictions of Eq. (5) and the average annual soil temperature cycle recorded at the K1 monitoring site at 15 cm depth. Eq. (5) was then used to calculate the average monthly soil temperature in each of the 5 subsoil layers. The carbon inputs, transport parameters, p, and decomposition parameters, s, were once again optimised to produce the best fit to the 1956 0–23 cm inventory and the observed 2008 SOC profiles at each site. The optimised model outcomes are shown in Figs. 11 and 12. Increasing the levels of subsoil moisture had the effect of significantly increasing the rate of carbon decomposition at all soil depths. To compensate for the increased rates of decomposition, predicted carbon inputs into the soil had to be increased significantly to 2.9 tC/ha
(b 1956), 4.2 tC/ha (1956–1970) and 1.0 tC/ha (1970–2008) for the Dog paddock trench and 4.1 tC/ha (b 1956), 5.0 tC/ha (1956–1970) and 1.2 tC/ha (1970–2008) for the Shed paddock trench. Interestingly the new carbon input values are now close to values estimated from land management considerations (4.2 tC/ha for the grazing period 1956–1970 and 1.0 tC/ha for the cropping period 1970–2008). The fraction of mobilised carbon transported down the soil profile also increased (p = 0.45 and p = 0.44 for the Dog and Shed paddock respectively), while the decline in decomposition rates with depth was predicted to be negligible (s is approximately 0 at both sites). The overall fit to the 2008 SOC profiles using the more realistic values for soil moisture and temperature (Figs. 11 and 12), however was significantly poorer than the original RothPC-1 predictions (Figs. 8 and 9). The problems encountered in the RothPC-1 simulation of the Illogan SOC profile data suggests that there may be a question mark over its application in high clay, cracking soils in arid or semi-arid environments. Soil moisture and temperature levels calculated within RothPC-1 (particularly for deeper soils) did not reflect values observed in the field. When more realistic values for these parameters were included in the model the convective transport term used in RothPC-1 could not reproduce the observed SOC profiles. This finding is largely in agreement with other studies of vertical SOC transport (Elzein and Balesdent, 1995; Wells et al., 2012), which suggest that diffusional transport terms are needed if SOC transport processes are to be adequately simulated.
Fig. 9. RothPC-1 SOC profile predictions for the Shed paddock; p = 0.64, s = −0.01. Grey columns represent aggregated observed SOC stocks and dashed lines show RothPC-1 predictions.
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Fig. 10. Monthly average soil moisture and temperature data recorded over a 5 year period. (A) Monthly average soil moisture levels at 0–30 cm, 30–60 cm, and 60–90 cm depth. (B) The discrepancy between the monthly average air temperature and the soil temperature at 15 cm depth. (Air temperature data recorded at climate monitoring station ‘S2’ and remainder of data recorded at station ‘K1’ in the Dog paddock—for details see Rüdiger et al., 2007.)
6. Conclusions Soil organic carbon (SOC) concentrations and clay content have been determined from the soil surface down to bedrock at two neighbouring field sites with different soil types (Dog paddock—euchrozem and Shed paddock—vertosol), but a similar land use history of grazing followed by a period of minimal tillage cereal cropping. SOC inventory down to 30 cm depth at the Dog and Shed paddock were found to be essentially the same however the SOC profile was significant flatter at the Shed paddock site resulting in 25% higher SOC stocks when sampling inventory was extended down to bedrock. As the two sites share a similar land use history (and therefore a similar historical pattern of carbon inputs into the soil and soil tillage) the flatter SOC profile at the Shed paddock site is thought to be the result of the specific nature of the soil at this site. As a core by core comparison ruled out any clear relationship between clay content and SOC concentration it was concluded that the flatter profile was the result of enhanced SOC transport down the soil profile resulting from the more extensive cracking of the vertosol soil present at the Shed paddock site.
Modelling of SOC dynamics using RothPC-1 met with mixed success. RothPC-1 simulation of SOC turnover using soil moisture and soil temperature values calculated via the RothPC-1 approach yielded a satisfactory fit to the observed SOC profiles but the soil moisture and temperature levels generated within the model were found to be at odds with 5 year field observations. When more realistic values for soil moisture and temperature were substituted into the model the fit to the observed SOC profiles was significantly poorer indicating that the convective transport approach used to model SOC movement may not be adequate where cracking soils are present. Acknowledgments The Goodear family of Illogan are thanked for their support and unfailing generosity during this study. Ian Jeans and Simon Livingstone are thanked for the technical support in sample collection and preparation. A special thanks is also extended to Kevin Coleman who answered our (numerous) queries regarding the implementation of the RothPC-1 and RothC models with great patience and courteousness. This research
Fig. 11. RothPC-1 SOC profile prediction for the Dog paddock trench using soil moisture and temperatures based on field observations; p = 0.45, s = −0.003. Grey columns represent observed values and dashed line shows RothPC-1 predictions.
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Fig. 12. RothPC-1 SOC profile prediction for the Shed paddock trench using soil moisture and temperatures based on field observations; p = 0.44, s = −0.003. Grey columns represent observed values and dashed line shows RothPC-1 predictions.
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