Monitoring Soil Carbon Stock Changes - Pete Smith

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Monitoring Soil Carbon Stock Changes - Pete Smith

  1. 1. Modelling Soil Carbon Stock Changes Pete SmithRoyal Society-Wolfson Professor of Soils & Global Change, FSB, FRSEInstitute of Biological & Environmental Sciences,School of Biological Sciences,University of Aberdeen,Scotland, UKE-mail: pete.smith@abdn.ac.uk EPA Modelling Workshop, 24th November 2010, Dublin, Ireland
  2. 2. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  3. 3. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  4. 4. Models we use regularlyRothC DayCent / CENTURYDNDC ECOSSE
  5. 5. Example publications on each model• RothC – Smith, J.U. et al. 2005. Projected changes in mineral soil carbon of European croplands and grasslands, 1990-2080. Global Change Biology 11, 2141–2152.• DayCent – Yeluripati, J.B. et al. 2009. Bayesian calibration as a tool for initialising the carbon pools of dynamic soil models. Soil Biology & Biochemistry 41, 2579- 2583.• DNDC – Hastings, A.F. et al. 2010. Uncertainty propagation in soil greenhouse gas emission models: An experiment using the DNDC model at the Oensingen cropland site. Agriculture, Ecosystems & Environment 136, 97-110.• ECOSSE – Smith, J.U. et al. 2010a. Estimating changes in national soil carbon stocks using ECOSSE – a new model that includes upland organic soils. Part I. Model description and uncertainty in national scale simulations of Scotland. Climate Research (in press) doi: 10.3354/cr00899. – Smith, J.U. et al. 2010b. Estimating changes in national soil carbon stocks using ECOSSE – a new model that includes upland organic soils. Part II. Application in Scotland Climate Research (in press) doi: 10.3354/cr00902.
  6. 6. Available (global) data:Model development Flux data Isotope natural abundance Soil representation in models: data Long-term soil C experiment networks Soil respiration data N. America: Europe: 86 Experiments 10 Experiments 20 Models 7 Models Asia: 10 Experiments 1 Model S. America: 3 Experiments DGVMs Soil models Ecosystem models Africa: 3 Experiments Australasia: e.g. e.g. RothC e.g. CENTURY, 8 Experiments 3 Models JULES, DNDC DayCent, DNDC Isotope pulse labelling data ECOSSE CENTURY Model evaluation: 2002 100 25 management b 90 a) 60.00 b 80 c passive 50.00 temperature 20 b 40.00 c slow 30.00 global radiation% C Remaining 70 20.00 10.00 15 RMSE 60 c active 0.00 precipitation -10.00 a 50 40 c metab atmospheric CO2 concentration 10 a a a a a Improved 30 20 c struct pH bulk density clay content 5 Process 10 0 0 1 2 3 4 5 Year 6 7 8 9 10 0 RothC CANDY DNDC DAISY CENTURY SOMM ITE NCSOIL Verberne Description:
  7. 7. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  8. 8. RothC co 2 RESIDUE soil surface DPM RPM BIO HUM k=10 y -1 k=0.3 y -1 k=0.66 y -1 k =0.02 y -1 IOM
  9. 9. RothC application to UK LULUCF InventoryFalloon et al. (2006)
  10. 10. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  11. 11. Climate data: 2080-1990 temperature Note: 2080 and 1990 are 30 year averages of 2051-2080 and 1961-1990 respectively
  12. 12. Climate data: 2080-1990 water balance Note: 2080 and 1990 are 30 year averages of 2051-2080 and 1961-1990 respectively
  13. 13. Soils data – SOC
  14. 14. Soils data – Clay %
  15. 15. Data• NPP and litter input data – NPP calculated using LPJ-DGVM for ATEAM grid (g C m-2) and used directly for croplands and grasslands
  16. 16. Climate-only impact on cropland and grassland SOC - (effect of different climate scenarios) (HadCM3) 100 95 SOC stock (t C ha-1) Grassland 90 85 Cropland 80 75 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 Year A1FI B1 B2 A2 J.U. Smith et al. (2005)
  17. 17. Change in grassland SOC – climate only J.U. Smith et al. (2005)
  18. 18. Change in cropland SOC – climate only J.U. Smith et al. (2005)
  19. 19. Change in SOC- climate only Temperature SOC Water balance Note: 2080 and 1990 are 30 year averages of 2051-2080 and 1961-1990 respectively
  20. 20. Comparing climate-only with climate&NPP effects for croplands & grasslands (HadCM3-A2) 110 105 Grassland 100SOC stock (t C ha-1) 95 90 85 Cropland 80 75 70 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 Year Climate Only Climate and NPP J.U. Smith et al. (2005)
  21. 21. Effect of technology in croplands & grasslands (HadCM3-A2) 110 110 105 105 100 GrasslandSOC stock (t(t C ha-1) C ha -1) 100 95 95 90 SOC stock 90 85 85 Cropland 80 80 75 75 70 70 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 Year Year Minimum Climate Only Climate & NPP Climate & NPP & Tech Maximum J.U. Smith et al. (2005)
  22. 22. Change in grassland SOC – climate&NPP&technology Climate only J.U. Smith et al. (2005)
  23. 23. Change in grassland SOC – climate&NPP&technology Climate&NPP&technology J.U. Smith et al. (2005)
  24. 24. Change in cropland SOC – climate&NPP&technology Climate only J.U. Smith et al. (2005)
  25. 25. Change in cropland SOC – climate&NPP&technology Climate&NPP&technology J.U. Smith et al. (2005)
  26. 26. Climate impact on mineral SOC• Our results suggest that increased productivity due to climate change will counteract its negative impacts• Inclusion of improved technology (in arable and cropland) suggests that SOC in mineral soils might increase in Europe over the next 75 years• Even in the worst case, climate change could account for a maximum of 10% of the SOC loss reported by Bellamy et al. (2005).
  27. 27. CO2 sink (t CO2 ha-1 yr-1) -20 0 20 40 60 80 100 120 140 160 Cropland - agronomy Cropland - nutrients Cropland - tillage&residue Cropland - water Cropland - setaside&LUC Cropland - agroforestry Practice section… Grazing land - nutrient&grazing&species Degraded land restoration Manure application Sequestration under energy crops Organic soil restoration More work on organic soils needed. Organic soil restoration vs. mineral soil sequestration. See nextData from: Smith et al. (2008)
  28. 28. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  29. 29. ECOSSESoil C & N, mineral, organo-mineral and organic soilSOC change and GHG fluxes. Developed specificallyfor the soils of Scotland & Wales. Now part ofJULES. Very suitable for Irish soils?
  30. 30. Independent evaluation – CO2 release 70 60 Soil 50 Soil with litter with litter and fertiliser 40 30 Respiration (mgCO2-C kg-1 soil) 20 10 20 0 measured simulatred Soil only 15 Soil with fertiliser 10 5 0 0 50 100 150 200 250 0 50 100 150 200 250 time (days)Respiration rate during laboratory incubation (Foereid et al., 2004)
  31. 31. Independent evaluation – soil ammonium and nitrate in a peat in Finland 2D Graph 1 120 100 simulated NO3- simulated NH4+ 80 nitrogen (kg/ha) measured NO3- 60 measured NH4+ fertiliser application 40 20 0 0 20 40 60 80 100 120 140 160 time (weeks)Ammonium and nitrate simulated by ECOSSE for a peat cultivated with spring barley insouthern Finland (60o49’N, 23o30’E).
  32. 32. Independent evaluation – soil ammonium in a cultivated peat in Finland Potatoes NH4 30 25 20kg/ha Measured 15 Modelled 10 5 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141 146 151 156 161 166 171 176 181 WeekSoil NH4 in a peat cultivated with spring barley in Southern Finland (60o49’N, 23o30’E)(Regina et al, 2004). Calculations by M.Aitkenhead, UoA
  33. 33. Independent evaluation – nitrous oxide emissions from a cultivated peat in Finland Barley N2O 5 4.5 4 3.5 3 kg/ha Measured 2.5 Modelled 2 1.5 1 0.5 0 1 6 11 16 21 26 31 36 41 46 51 56 61 66 71 76 81 86 91 96 101 106 111 116 121 126 131 136 141 146 151 156 161 WeekN2O emissions for a peat cultivated with spring barley in Southern Finland (60o49’N, 23o30’E)(Regina et al, 2004). Calculations by M.Aitkenhead, UoA
  34. 34. Independent evaluation – Mass loss & N from litter bags – more to do 120 2.2 2.0 100 Red pine Red pine 1.8 80 1.6 1.4 60 1.2 40 1.0 in pine in pine in hardwood 0.8% mass remaining in hardwood simulated 20 % nitrogen in material simulated 0.6 0 0.4 2.2 100 2.0 Red maple Red maple 80 1.8 1.6 60 1.4 40 1.2 1.0 20 0.8 0 0.6 88 89 90 91 92 93 94 95 96 88 89 90 91 92 93 94 95 96 time (year) time (year) Mass loss from litterbag experiment in Nitrogen content in remaining materialHarvard forest, US (Magill & Aber, 1998) from litterbag experiment in Harvard forest, US (Magill & Aber, 1998) Calculations by B. Foereid, UoA
  35. 35. Data used to run the model New data on land use change 20km2 NCMS (National Countryside Monitoring Scheme) MLC (Monitoring Landscape Change)Spatial scale: Counties (1971) Spatial scale: LA groupingsTime periods: 1947-1969,1969-1980 Time periods: 1947-1973, 1973-1988
  36. 36. Wales Scotland 2000-2009 2000-2009al. (2010a)Jo Smith et -2 -2 Change in soil C (kt C (20km) (10yrs) -1 Change in soil C (kt C (20km) (10yrs) -1 0 10 20 30 0 10 20 30 -50 -40 -30 -20 -10 -60 -50 -40 -30 -20 arable -10 arable grassland grassland forestry forestry to arable to arable natural semi-nat arable arable grassland grassland ECOSSE ECOSSE forestry forestry to grassland to grassland natural semi-nat CEH CEH arable arable grassland grassland forestry forestry to forestry to forestry natural semi-nat arable arable grassland grassland forestry forestry to semi-natural to semi-natural natural semi-nat ECOSSE simulation of change in soil C ECOSSE simulation of change in soil C -2 -2 (kt C (20km) (10yrs) -1 (kt C (20km) (10yrs) -1 -100 -100 -80 -80 -60 -60 -40 -40 -20 -20 20 40 60 80 100 20 40 60 80 100 0 0 -80 -60 -40 -20 -80 -60 -40 -20 -100 -100 0 0 20 20 40 40 (kt C (20km)-2 (10yrs) -1 (kt C (20km)-2 (10yrs) -1 :1 :1 R2 = 0.9666 R2 = 0.982 60 60 1 Line 1 Line CEH estimates of change in soil C CEH estimates of change in soil C 80 80 100 100 National simulations compare well with LULUCF inventory
  37. 37. ECOSSE run for whole UKSimulated changes in(a)soil carbon(kt C 20km-2 (10 years)-1) Richards et al. (2010) Jo Smith et al. (2010b)Tier 3 modelling. Baseline runs, runs with mitigation measures applied – in allcases with uncertainty quantified
  38. 38. Outline• Model development and application• Case study 1: RothC application in the UK• Case study 2: RothC application in Europe• Case study 3: ECOSSE application using UK LULUCF Inventory data• Conclusions
  39. 39. Conclusions• There are a range of tier 3 models that can be used for LULUCF inventories to estimate SOC change, including RothC, DayCent, DNDC and ECOSSE• Some of these models (DayCent, DNDC, ECOSSE) also simulate GHG fluxes• ECOSSE was developed to work on the more organic soils found in Scotland and Wales (as well as mineral soils) – more suitable for Irish soils?
  40. 40. Thank you for your attention

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