Prediction of Changes in Soil Organic Carbon with Climate Using CENTURY 5 and ROTH C Ruben Sakrabani & John Hollis National Soil Resources Institute, Cranfield University, Silsoe, Bedfordshire, MK45 4DT, UK. Tel: +44 (0) 1525 863045 Fax: +44 (0) 1525 863253
[email protected];
[email protected] Abstract Soil forms an important carbon stock in nature but the stocks are dynamic and changes in land-use, land use management and climate can all have significant impacts. The dynamics of SOC are complex and imperfectly understood and although scientists have developed models for predicting future changes, most have only been validated using individual site data. The National Soil Inventory for England and Wales includes a unique national dataset quantifying changes in topsoil organic carbon under arable, grassland and semi-natural vegetation between the periods 19781983 and 1994-2000. We are using the CENTURY 5 and ROTHC models to predict changes in SOC between 1978 and 2000 using input weather data for 1978 – 2000 from the UK Meteorological Office and soil property input data derived from the National Soil Inventory. Predicted changes in soil organic carbon from the model simulation will then be validated using the re-sampled Inventory data for the period 1994-2000. Once this utility is established, the models will be used to predict national-level climate change-induced changes in soil organic carbon based on the UKCIP02 scenarios for the 2020’s, 2050’s and 2080’s, each of which comprise four emissions scenarios (high, low, medium-high and medium-low), associated with different socio-economic scenarios. CENTURY5 will be used to simulate SOC changes in both arable and grassland land use classes, whereas ROTHC will be used to predict SOC changes in arable land use only. The advantages and disadvantages of the two models are discussed. Introduction One of the effects of global warming will be to accelerate the decomposition of soil organic matter, thereby releasing CO2 to the atmosphere, which will further enhance the warming trend. Soil forms an important carbon stock and there is about twice as much carbon in the top metre of soil as in the atmosphere (Jenkinson et al., 1991). Climate change can influence the stock of soil organic matter in two ways: by altering plant growth, thus altering the annual return of plant debris to the soil; and by changing the rate at which this input decays in or on the soil. As part of a project to develop soil property databases and tools to support climate change impact studies in England and Wales, we are using the CENTURY 5 model from Colorado State University (USA) and the ROTHC model from Rothamsted Research (UK) to estimate the changes in soil organic carbon as a result of climate change. CENTURY 5 and ROTHC are two of the mostly widely used SOM (soil organic matter) models and have been evaluated at the site scale under many conditions and also in some regional applications (Falloon et al., 2002).
As part of this project, soil input parameters (chemical and physical) to drive these models are obtained from the National Soil Inventory (NSI) for England and Wales. These input parameters will be modelled for the UKCIP02 (United Kingdom Climate Impacts Programme 2002) scenarios for the 2020’s, 2050’s and 2080’s for all soil series in the 1:250, 000 scale National Soil Map database. For initial model calibration however, ten soil series have been selected for each of two different land uses: arable and permanent (managed) grassland. The selected series represent a range of the most common soil types under each land use. In this paper results from two of these representative series are presented. Simulations from CENTURY5 and ROTHC are compared to determine if the models are able to predict the measured changes in soil organic carbon between the NSI initial and resampled events and to evaluate differences in the predictions of the two models for organic carbon stocks under future climate conditions. Table 1 summarises the broad characteristics of each selected soil series – land use combination. Table 1: Summary of the selected soil series for arable and permanent grassland Soil Series Andover
Texture 1
Depth
Silty clay Loam (calcareous)
Shallow
Permeable
Deep
Slowly permeable Seasonally below 50 cm depth waterlogged in winter (III & IV)
Brickfield Clay loam
1
Permeability
Drainage (wetness class) 1 Well drained (I)
Parent material Chalk
Landuse Arable
Glacial Till Permanent Grassland
After Hodgson, 1997.
Model description CENTURY The CENTURY agroecosystem model has been developed by Parton et al. (1987) to simulate C, N, P, and S dynamics through an annual cycle over time scales of centuries and millennia. Its aim is to embody the best understanding to date of the biogeochemistry of carbon, nitrogen, phosphorus, and sulphur. The primary purposes of the model are to provide a tool for ecosystem analysis, to test the consistency of data and to evaluate the effect of changes in management and climate on ecosystems. CENTURY comprises a series of submodels which may be a grassland/crop, forest or savanna system, with the flexibility of specifying potential primary production curves representing the site-specific plant community. The model was especially developed to deal with a wide range of cropping system rotations and tillage practices for system analysis of the effects of management and global change on productivity and sustainability of agroecosystems. The grassland/crop and forest systems have different plant production submodels which are linked to a common soil organic matter submodel. The savanna model uses the grassland/crop and forest subsystems and allows for the two subsystems to interact
through shading effects and nitrogen competition. The soil organic matter submodel simulates the flow of C, N, P, and S through plant litter and the different inorganic and organic pools in the soil. The model runs with a monthly time step. The major input variables for the model include: 1. 2. 3. 4. 5. 6. 7.
monthly average maximum and minimum air temperature, monthly precipitation and evapo-transpiration, lignin content of plant material, plant N, P, and S content, soil texture, atmospheric and soil N inputs, and initial soil C, N, P, and S amounts.
The input variables are available for most natural and agricultural ecosystems and can generally be estimated from existing literature. Version 4 of the model integrated the effects of climate and soil driving variables and agricultural management to simulate carbon, nitrogen, and water dynamics in the soilplant system. Simulation of complex agricultural management systems including crop rotations, tillage practices, fertilization, irrigation, grazing, and harvest methods is now possible. Version 5 includes a layered soil physical structure, and new erosion and deposition submodels, which have not been used in the simulations presented here. Figure 1 shows the various components of the soil organic carbon pools and the interaction between them.
Figure 1: Various components of the soil organic carbon pools in CENTURY
ROTHC ROTHC is a model of the turnover of organic carbon in non-waterlogged soils that allows for the effects of soil type, temperature, moisture content and plant cover on the turnover process. It uses a monthly time-step to calculate total organic carbon (t ha-1), microbial biomass carbon (t ha-1) and ∆14C (from which the radiocarbon age of the soil can be calculated) on a year to centuries timescale. ROTHC was written by IACR (Institute of Arable Crops Research)-Rothamsted (formerly known as Rothamsted Experimental Station), UK. The input data required to run the model are average monthly rainfall (mm), average monthly open pan evaporation (mm), average monthly air temperature (°C), clay content of the soil (%), an estimate of the decomposability of the incoming plant material, soil cover for each month (between 0 = bare and 1 = vegetated), monthly input of plant residues (t C/ha), and monthly input of farmyard manure (FYM) (t C/ha) (if applicable) and the depth of soil sample (cm). The soil organic carbon in tonnes/ha at the start of the ROTHC simulation is divided into decomposable plant material (DPM) and resistant plant material (RPM), both of which decompose, by first-order processes to give CO2 (lost from the system), microbial biomass (BIO) and humified organic matter (HUM). Both BIO and HUM decompose at their characteristic rates by first-order processes to give more CO2, biomass and humified matter. The soil is also assumed to contain a small organic compartment that is inert to biological attack which is known as IOM (inert organic matter) (Jenkinson et al., 1991). The structure of the model is shown in Figure 2.
DPM Organic Inputs
CO2 decay
BIO
RPM
CO2 decay
HUM
BIO decay
RPM = resistant plant material
HUM
IOM
DPM = decomposable plant material
IOM = inert organic matter
BIO = microbial biomass
HUM = humified OM
Figure 2 : Structure of the Rothamsted Carbon Model The carbon input is split between DPM and RPM, depending on the DPM/RPM ratio of the particular incoming plant material. For example, for most agricultural and improved grassland, a DPM/RPM ratio of 1.44 is used (i.e. 59% of the plant material is DPM and 41% is RPM). In ROTHC, all incoming plant material passes through these two compartments only once. Both DPM and RPM decompose to form CO2 (lost from the system), BIO and HUM. The proportion that goes to CO2 and to BIO + HUM is determined by the clay content of the soil. BIO and HUM both decompose to
form more CO2, BIO and HUM. FYM is assumed to be more decomposed than normal plant material (Coleman & Jenkinson, 1990). Derivation of Input data Soil parameter datasets used to drive both models were obtained from the soil series profile datasets held within NSRI’s Land Information System, LandIS (Hallett et al, 1996). A ‘soil profile analytical database’ comprises measurements of particle-size fractions, organic carbon contents and pH for some 5,000 soil horizons taken from over 1,500 profiles sampled to characterise soil series during detailed field survey. Additional measurements of bulk density and volumetric water contents at 5 kPa, 10 kPa, 40 kPa, 200 kPa and 1500 kPa pressure are available for almost 1,600 soil horizons, whereas measurements of volumetric water content at 0 kPa pressure and mean saturated hydraulic conductivity are available for about 150 and 80 horizons respectively (Thomasson & Carter, 1992). In addition, a ‘National Soil Inventory analytical database’ comprises 5,692 sets of analysed values of soil chemical (organic carbon, pH, extractable heavy metals & nutrients etc.) and mineral particle-size properties from 15 cm deep topsoil samples taken at 5 km grid intersect points across England and Wales (McGrath & Loveland, 1992) during a period from 1978 - 1983. This dataset provides a soil geochemical baseline for the late 1970s in England and Wales. In order to characterise changes over time, statistically valid subsets of the National Soil Inventory sites were re-sampled and analyzed during 1994-95 (904 Arable sites), 1995-96 (780 Grassland sites) and 2002-2003 (598 Non-agricultural sites). Mineral particle-size data were calculated directly from measurements held in LandIS. For some series there was only one set of data per soil horizon, but for the majority, multiple datasets were available to characterise the particle size fractions in terms of mean values and a standard deviation. Topsoil organic carbon content and pH were derived from the analytical data from the initial National Soil Inventory. Because both parameters are very dependent on land use, even within soil series, the data was stratified into each of four land use categories; Arable, Ley (short term rotational) grassland, Permanent (long term managed) grassland and 'Other' land under seminatural vegetation or recreational use. Statistical analysis of this dataset gave 1970’s ‘baseline’ series-mean values and standard deviations of organic carbon content and pH for all relevant land use / soil series combinations. Data on topsoil organic carbon content and pH for the 1990’s for each representative soil series – land use combination was derived from the relevant National Soil Inventory re-sampled dataset. Bulk density and soil water retention characteristics are also properties that depend, at least partly, on land use. The analytical data held in LandIS is insufficient to directly characterise all combinations of series and land use and values for individual soil horizon/land use combinations were therefore predicted using pedotransfer functions, a set of empirical regression equations relating bulk density and water retention characteristics to some combination of organic carbon, clay and silt content. These pedotransfer functions were derived from analysis of the measured data held within LandIS (Thomasson & Carter, 1992, Simota & Mayr, 1996, Mayr & Jarvis, 1999). When using CENTURY5, the soil organic carbon is fractioned into 4 carbon pools – surface active (2%), active (2%), slow/intermediate (63%) and passive (33%) and the
bulk organic carbon data from the NSI has been subdivided into these fractions based on Kelly et al. (1997). This is used an initial step to start the CENTURY simulation for 2000 years until the system reaches equilibrium. Then the output of the simulations results is retrieved and a new ratio is obtained between the 4 carbon pools. However for ROTHC, a DPM/RPM ratio of 1.44 (i.e. 59% DPM and 41% RPM) is used as a typical approach for most agricultural and improved grassland. The model adjusts for soil texture by altering the partitioning between CO2 evolved and BIO+HUM formed during decomposition. The ratio CO2/(BIO+HUM) is calculated from the clay content of the soil using the following equation : x = 1.67 (1.85 + 1.60 exp (-0.0786 % clay)) where x = ratio CO2/(BIO+HUM) Then x/(x+1) is evolved as CO2 and 1/(x+1) is formed as BIO+HUM. The BIO + HUM is then split into 46% BIO and 54% HUM (Coleman & Jenkinson, 1990). Weather data from 1978 - 1995 from the UK Meteorological Office was used to drive the model simulations for calibration purposes, in order to compare model predictions with the measured changes in topsoil organic carbon corresponding to the original National Soil Inventory (NSI) and the re-sampling exercises. Weather data to drive the model simulations of climate change scenarios were derived from the UKCIP02 datasets for 2020’s (2011 – 2040), 2050’s (2041 – 2070) and 2080’s (2071 – 2100) under the four emissions scenarios (i.e. high, low, medium-high and medium-low). The four UKCIP02 climate change scenarios are explicitly linked to the four different and coherent storylines of future changes in global socioeconomic conditions and population published by the IPCC (Intergovernmental Panel on Climate Change) in 2000 (Hulme et al., 2002).
Results Andover Arable 1978-2000 4500
250
SOM, gC/m2 (Active surface & active pool)
3500 3000
150
2500 2000
100
1500 1000
50
SOM, gC/m2 (Slow and passive pool)
4000 200
500 0 1975
1980
1985
1990
1995
2000
0 2005
Time, year Active surface pool
Active pool
Slow pool
Passive pool
Andover Hi 2020-2050 4500
250
3500 3000
150
2500 2000
100
1500 1000
50
SOM, gC/m2 (Slow & passive pool)
SOM, gC/m2 (Active surface & active pool)
4000 200
500 0 2015
2020
2025
2030 2035 2040 Time, years
Active surface pool
Active pool
2045
2050
Slow pool
0 2055 Passive pool
200
4500
180
4000
160
3500
140
SOM, gC/m2 (Slow and passive pool)
SOM, gC/m2 (Active surface and active pool)
Brickfield 1978-2000
3000
120
2500
100 2000
80
1500
60 40
1000
20
500
0 1975
1980
1985
1990
1995
2000
0 2005
Time, years Active surface pool
Active pool
Slow pool
Passive pool
Brickfield Hi 2020-2050 1600
SOM, gC/m2 (Active surface & active pool)
1400
10000
1200 8000
1000 800
6000
600
4000
400 2000
200 0 2015
SOM, gC/m2 (Slow and passive pool)
12000
2020
2025
2030
2035
2040
2045
2050
0 2055
Time, years Active surface pool
Active pool
Slow pool
Passive pool
Figure 3 : Comparison of CENTURY5 simulations for Andover and Brickfield for 1978-2000 and 2020-2050 (Hi Emission)
Andover Arable 2020 - 2050 12000
10000
10000 SOM, gC/m 2
SOM, gC/m 2
Andover Arable 1978-2000 12000
8000 6000 4000 2000 0 1975
8000 6000 4000 2000
1980
1985
1990
1995
Tim e, years
2000
2005
0 2010
2020
2030 2040 Tim e, years
2050
Figure 4 : Comparison of ROTH C simulation for Andover for 1978-2000 and 2020-2050 (Hi Emission) Discussions Figure 3 shows the comparison of the CENTURY5 simulation for Andover and Brickfield soil series for an arable and permanent grassland landuse scenario respectively for 1978-2000 and 2020-2050 (Hi emission). For the Andover the active surface carbon pool depleted rapidly while the active pool initially increases but gradually depletes. The slow carbon pool depletes gradually during the simulation years. The passive carbon pool remains almost constant throughout the simulation years for the past and future climate scenarios. However the simulation for Andover shows that for 2020-2050 the trends of the carbon pools remain the same but the final carbon level is lower than the current reported values. The active surface and passive carbon pool do not change significantly for the past and future climate scenarios. However the active carbon pool had an initial level of 172 gC/m2 during 1978-2000 and will decline to 167 gC/m2 during 2020-2050 (3% reduction in carbon pool). The slow carbon pool also declined from 2930 gC/m2 in 1978-2000 to 2775 gC/m2 in 2020-2050 (5% reduction in carbon pool). The percentage reduction in the slow carbon pool is comparable to the active carbon pool. The slow carbon pool comprises the highest ratio (63%) from the total organic carbon stock and it will contribute to a 5% reduction in carbon pool. For the Brickfield soil series, the soil carbon pools trends are opposite to Andover with the exception of the active surface pool. The active surface pool will decrease during 2020-2050 but the active, slow and passive pools will show an increase in the carbon pool. However this observation is only for the high emission scenario and may not be similar to the other scenarios. This slight increase in soil carbon can be attributed to the positive feedback mechanism between climate and the carbon cycle which had also been cited by Jones et al. (2004), The simulation from ROTHC shows the decline in soil carbon when comparing the simulation years of 1978-2000 and 2020-2050. ROTHC only shows a small decrease in organic carbon of 3170 gC/m2 in 2000 compared to 3150 gC/m2 in 2050. The decline in carbon that is simulated by ROTHC is not comparable to CENTURY5. This is because during the simulation the carbon pools are fractionated differently for both the models. Table 2 shows that CENTURY5 is able to simulate better the soil
2060
organic carbon content in the Andover (arable) than Brickfield (permanent grassland). However ROTHC simulates lower soil organic carbon level in Andover than CENTURY5. Table 3 compares the carbon pools between CENTURY5 and ROTHC. Table 2: Summary of CENTURY5 and ROTHC simulation results
Measured initial C, %
Standard deviation measured initial C
Andover
3.15
Brickfields
5.24
Predicted final C, % (CENTURY5)
Standard deviation predicted final C (CENTURY5)
Predicted final C, % (ROTHC)
Standard deviation predicted final C (ROTHC)
0.518
2.52
0.19
1.58
0.688
1.377
2.8
0.12
-
Measured final C, %
Standard deviation measured final C
0.967
2.63
2.361
4.10
Table 3: Comparison of soil organic carbon pools between CENTURY and ROTHC Carbon pool Active Slow Passive
CENTURY Turnover rates Months – years 20 – 50 years 400 – 2000 years
Ratio (Kelly et al., 1997)
Carbon pool
ROTHC Decomposition rate constants, years-1
4% 63% 33%
DPM RPM BIO HUM
10.0 0.3 0.66 0.02
Ratio (Coleman & Jenkinson, 1990) 59% 41%
In CENTURY5 the initial carbon stock is fractionated into 4 pools when compared to only 2 pools in ROTHC. Falloon & Smith (2002) also found that the carbon inputs estimated by ROTHC were in general lower than those estimated by CENTURY, since the soil organic carbon (SOC) in CENTURY tends to turnover faster than SOC in ROTHC. Conclusions This current work is part of an on going bigger project. The initial result suggest that, at least for the high emission future climate scenario, soil organic carbon in arable land will deplete up to the 2050’s, whereas there may be an increase in soil organic carbon under permanent grassland due to the positive feedback mechanism between climate and the carbon cycle. CENTURY5 is able to simulate the carbon dynamics differently compared to ROTHC due to the different approach to the initial soil carbon fractionations. Acknowledgements This project is funded by the Department for Environment, Food & Rural Affairs (DEFRA) under contract CC0375. The authors wish to thank Ian Bradley for providing data on crop rotation, cultivation, harvest and related land management practices for the selected soil series. Initial help on the use of ROTHC from Pat Bellamy is deeply appreciated. The authors also wish to specially thank Cindy Keough from Colorado State University for her continuous help and advice on the use of CENTURY 5. ET data provided by Jerry Knox and Tim Hess from IWE, Cranfield University is also gratefully acknowledged.
References Coleman K. & Jenkinson D.S. (1990), ROTHC-26.3 – A model for the turnover of carbon in soil, Model description and users guide, IACR-Rothamsted, Harpenden. Falloon P., Smith P., Szabó J. & Pásztor L. (2002), Comparison of approaches for estimating carbon sequestration at the regional scale, Soil Use and Management, 18, 164-174. 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, 18, 101-111 Kelly R.H., Parton W.J., Crocker G.J., Grace P.R., Klir J., Körschens M., Poulton P.R. & Richter D.D. (1997), Simulating trends in soil organic carbon in long-term experiments using the CENTURY model, Geoderma 81, 75-90 Parton, W.J., D.S. Schimel, C.V. Cole, and D.S. Ojima. (1987), Analysis of factors controlling soil organic matter levels in Great Plains grasslands, Soil Science Society of America Journal 51 :1173-1179. 465. Hallett S.H., Jones R.J.A. and Keay C.A. (1996). Environmental Information Systems Developments for Planning Sustainable Land Use. International Journal of Geographical Information Systems, 10, 1 pp 47-64. Hodgson, J.M. (1997). Soil Survey Field Handbook: Describing and sampling Soil profiles. Soil survey Technical Monograph No. 5. 3rd Edition. Soil Survey and Land Reesearch Centre, Silsoe, Beds. UK 116 pp. Jenkinson D.S., Adams D.E. & Wild A. (1991), Model estimates of CO2 emissions from soil in response to global warming, Nature 351, 304-306 Jones C., McConnell C., Coleman K., Cox P., Falloon P., Jenkinson D. & Powlson D. (2004), Global climate change and soil carbon stocks : predictions from two contrasting models for the turnover of organic carbon in soil (to be published). Mayr, T.R. and Jarvis, N.J. (1999) Pedotransfer functions to estimate soil water retention parameters for a modified Brooks-Corey type model. Geoderma 91:1-9 McGrath S. P. & Loveland P. J. (1992), The soil geochemical atlas of England and Wales, Blackie Academic and Professional. Simota C. and Mayr T.R. (1996) Predicting the soil water retention curve from readily-available data obtained during soil surveys. International Agrophysics, 10(3), 185-188. Thomasson, A.J. & Carter, A.D. (1992). Current and future uses of the UK Soil Water Retention Dataset. In: van Genuchten, M.Th. & Leij, F.J. (Eds.) Proceedings of the International Workshop on Indirect Methods for estimating the hydraulic properties of unsaturated soils. Riverside, California, October 11-13, 1989. pp. 355358.
