1	Advances in Soil Carbon Measurement, Monitoring and Verification Technologies R. César Izaurralde Joint Global Change Research Institute Charles W. Rice Kansas State University 3^rd USDA Symposium on Greenhouse Gases & Carbon Sequestration in Agriculture and Forestry Baltimore, MD 21-24 March 2005
2	Acknowledgements CSiTE (Carbon Sequestration in Terrestrial Ecosystems) Research Consortium –DOE http://csite.esd.ornl.gov CASMGS (Consortium for Agricultural Soils Mitigation of Greenhouse GaSes) – USDA http://www.casmgs.colostate.edu
3	Agricultural management plays a major role in greenhouse gas emissions and offers many opportunities for mitigation Cropland Reduced tillage Rotations Cover crops Fertility management Erosion control Irrigation management Rice paddies Irrigation Chemical and organic fertilizer Plant residue management
4	Adoption of no-till worldwide estimated at 70 Mha by 2000
5	Global potential and rates of soil organic C sequestration
6	Examples of feasibility and pilot projects on soil carbon sequestration
7	Measuring and monitoring soil C sequestration: a new challenge?
8	On baselines, soil C sequestration and avoided C loss
9	Soil organic matter affects soil bulk density and thus temporal comparisons of soil C stocks
10	Spatial variability influences estimates of soil organic C 100 samples to detect 2-3% change in SOC 16 samples to detect 10-15 % change in SOC
11	Sampling protocol used in the Prairie Soil Carbon Balance (PSCB) project Use “microsites” (4 x 7 m) to reduce spatial variability Three to six microsites per field Calculate SOC storage on an equivalent mass basis Analyze samples taken at different times together Soil C changes detected in 3 yr 0.71 Mg C ha^-1 – semiarid 1.25 Mg C ha^-1 – subhumid
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13	Geostatistical techniques can be used to estimate soil C stocks 64-ha fields in Nebraska: (1) irrigated continuous maize, (2) irrigated corn-soybean rotation, and (3) a dryland corn-soybean rotation Sampling at about 250 locations per field Geostatistical modeling: various types of kriging Simulate lower sampling densities to identify approaches that minimize cost and uncertainty Can improved soil management justify the cost of intensive sampling?
14	Quantitative mapping of soil organic C Hypothesis: Field scale variability often predictable from topographic data Available GIS data (remote sensing, terrain models, soil maps, precision farming) can be used to map large areas with a minimum number of samples Carbon strongly predicted from terrain (wetness index) in Iowa (glacially-derived Mollisolls) Relationships between C and topography are much weaker in older soils (Ultisolls) from Ohio and Maryland
15	Determination of soil organic C concentration: standard methods Wet combustion Soil sample treated with acid dichromate solution CO₂ generated evaluated with titrimetric or gravimetric methods Recovery is incomplete (avg. 81%) Dry combustion High temperature (1000 – 1500 C) CO₂ generated assessed with spectrophotometric, volumetric, titrimetric, gravimetric, or conductimetric techniques Very accurate, minimal variability, low operational errors Corrections needed when samples contain carbonates National and international efforts needed to cross-calibrate methods against standard (soil) samples
16	Emerging technologies for measuring soil C: LIBS Laser Induced Breakdown Spectroscopy (LIBS) Developed at Los Alamos National Laboratory Based on atomic emission spectroscopy Plasma emits light characteristic of elemental composition Minimal sampling volume Analysis time < 1 min Daily throughput > 200 samples Measurements more variable in soil low in organic matter (interference with iron)
17	Emerging technologies for measuring soil C: MIR / NIR Mid Infrared / Near Infrared Spectroscopy (MIR / NIR) Non-destructive method measurement of C in soils based on the reflectance spectra of illuminated soil Spectral regions NIR: 400–2500 nm MIR: 2500–25000 nm Excellent potential for assessment of spatial distribution of belowground C
18	Emerging technologies for measuring soil C: INS Inelastic Neutron Scattering (INS) Developed at Brookhaven National Laboratory (Wielopolski et al. 2002) Based on neutron emission and gamma ray detection C concentration proportional to C peak in gamma spectrum Calibration curve required Detection: 100 mg C m^-2 with 5% precision Non destructive but large volume required How to compare against other methods?
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20	Several satellite and airborne sensors can estimate LAI, NPP, crop yields, and litter cover Traditional sources of land cover data: AVHRR and Landsat Increased resolution being obtained with MODIS Good temporal resolution MODIS and AVHRR Excellent spatial detail provided by Landsat and SPOT IKONOS and Quickbird offer excellent spatial and temporal resolution Two airborne sensors AVIRIS LIDAR
21	CSiTE and CASMGS terrestrial ecosystem models Century Century DayCent C-STORE EPIC EPIC APEX
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23	Testing EPIC with historical site data: Simulated and observed average above and below ground big bluestem biomass (Mg/ha)
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29	Summary Large scale adoption of no till practices Impact on soil C sequestration? Methods for measuring and monitoring soil C changes Based on best available science Use systems perspective Be verifiable and comparable Report uncertainty