1. Estimates of C changes in US agricultural soils: IPCC and Century approaches
Keith Paustian
Mark Easter, Marlen Eve, Kendrick Killian, Steve Ogle,
Mark Sperow, Steve Williams
Colorado State University
R. Follett
USDA – Agricultural Research Service
Presentation at ‘Forestry and Agricultural Greenhouse Gas Modeling Forum’, Shepardstown, WV – Oct. 1-3, 2001

2. Objectives
Background on national level C inventory/projection methods.
Discuss estimates of soil C changes in US agricultural soils for the period , as a function of management changes.
Evaluate projections of spatial distribution of soil C changes.
Comparison of alternative approaches: strengths and weaknesses
Issues regarding ecosystem-economic model interactions.
Outline and objects of the presentation

3. Past Agricultural Practices
Erosion
Intensive tillage
CO2
Soil organic
matter
Residue removal
Low Productivity
Soil organic matter levels are determined by the relative balance of inputs of C, derived from plant residues (derived from uptake of CO2 through photosynthesis) and their subsequent decomposition, leading to release of CO2. Past (and to some extent current!) agricultural practices and their consequences tended to increase the rate of decomposition of the native soil organic matter (originally formed under forests and prairies) with low rates of C returned to the soil, resulting in widespread depletion of soil organic matter by 30-50% or more in most areas.

4. Improved Agricultural Practices
Conservation buffers
Conservation tillage
CO2
Cover crops
Soil organic
matter
Improved rotations
Improved agricultural practices, which have become increasingly used over the past several years, have characteristics that tend to enhance productivity (which has steadily increased in the US since the 1950’s) and amount of C returned to soil in crop residues and at the same time reduce decomposition potentials through reduced tillage intensity and more efficient water use. Thus these practices are capable of reversing past trends and act towards rebuilding previously lost soil C stocks, effectively removing CO2 from the atmosphere and storing it in soil organic matter.

5. Practices for C sequestration
Reduced and zero tillage
Set-asides/conversions to perennial grass
Reduction/elimination of summer-fallow
Winter cover crops
More hay in crop rotations
Higher residue (above- & below-ground) yielding crops
The practices that tend to enhance storage of C in soil are well known.

6. Trends in land use and cropland management
Several recent trends in land use and management are of significance to the agricultural soil C balance.

7. Crop yields (upper graph) have shown a steady increase since the 1940’s. Likewise, inputs of C through plant residues have also increased. Data are from the National Agricultural Statistics Service and on an extensive analysis of residue:grain ratios derived from studies in the literature. Residue input calculations include the effects of increasing harvest indices (I.e. grain:aboveground biomass) that have occurred through crop breeding (eg. increasing harvest index tends to decrease the amount of residue per unit grain produced).

8. Maps showing increase in the adoption of no-till, which was nil prior to 1982, and the area of land enrolled in the Conservation Reserve Program (CRP) where annual cropland is converted to perennial grasses or trees. Data from the National Resource Inventory (NRI).

9. Maps showing some reduction in the prevalence of summer fallow (particularly in the Northern Great Plains) since Over the same period land area in hay has increased slightly (noticeable in the Southern Appalachians) but less dramatically. Data from the National Resource Inventory (NRI).

10. Map showing the increase in irrigated agriculture between 1982 and Data from the National Resource Inventory (NRI).

11. National level soil C assessment
Modified IPCC national inventory method
Century model based approach
Soil C emission/sink inventories for the US were performed using two contrasting approaches: a) using a modification of Revised IPCC Guidelines for National Greenhouse Gas Inventories and b) using the Century ecosystem model. Both approaches used input data from the same sources (although the ways in which the climate and soil properties are handled by the two methods differ substantially) to facilitate comparison of the methods.

12. Validation and Uncertainty Analysis
DATABASES
Spatial
Inventory/survey
USDA-NRCS Major Land Resource Areas
USDA-NRCS / OSU PRISM Climatic Data
USDA-NRCS STATSGO Soils Data
USDA-NRCS National Resources Inventory
Conservation Technology Information Center - Crop Residue Management Survey
USDA-ERS Cropping Practices Survey
USDA-NASS Agricultural Statistics
USDA-NRCS Pedon soils data
Listing of the primary data sources used in the analyses.
Validation and Uncertainty Analysis
Long-term field experiment data
Comprehensive search of peer-reviewed literature

13. USDA-NRCS National Resources Inventory (NRI) Data
Over 800,000 field sites across the conterminous U.S.
Data collected every 5 years
Associated soils database linked to NRI
Contains data on:
Land use
Cropping history (I.e. crop rotation)
Soils
Irrigation
Land set aside
Other information
The NRI was the primary source for land management and management change data.

14. DISSECTING THE LANDSCAPE
Figure depicts how detailed information on the distribution of land use and management by soil type can be derived from the NRI. The top diagram show the distribution of land uses within a Major Land Resource Area (MLRA), which were the primary spatial units used in both analysis. The total cropland in an MLRA can be broken down into the area on soils having different attributes (soil texture shown in middle figure). Going further, the cropland on a given soil can be broken down by crop rotation, and with supplemental data from other sources (see below) and tillage type, yielding quite specific information about the area of land within the MLRA, by soil type and management regime.
~5.3 Mha cropland in 102B
~1.25 Mha dominated by LOAM surface texture
~114,000 ha continuous cropped corn under no-till

15. IPCC method designed as default national inventory procedure.
Estimates stock changes over a 20-year inventory period.
C(t) = C(n)*LUC_factor*input_factor*tillage_factor*area
C = C(t) – C(t-20)
Native (reference) C stock and LUC factors (representing land use conversions) are soil and climate specific.
Input factor relates to level of C inputs (e.g. crop residues, manure, perennial vs annual crops.
Tillage factor relates to tillage intensity (i.e. intensive, reduced and no-till).
The IPCC method calculates C stocks changes over a fixed time period (default is 20 yrs) as a function of factor values (for previous land use, tillage and level of C input) that adjust a climate-soil type specific baseline C stock (using estimates of native, uncultivated soils as the baseline condition). Thus it approximates a static ‘step change’ in C stocks as a consequence of changes in management. If management is unchanged (ie. Factor values and area remain constant) over the period then the net change in carbon stocks is zero. The methodology was devised as a simple ‘default’ methodology that could be applied in all countries having basic land use and natural resource data for purposes of reporting requirements under the UN Framework Convention on Climate Change.

16. Climatic Regions of the U.S.
Delineated using PRISM average precipitation and temperature
summarized by MLRA according to the IPCC region definitions.
Cool Temperate Dry
Cool Temperate Moist
Warm Temperate Moist
Warm Temperate Moist
The IPCC defines broad climatic zones which influence the factor values and native C stock levels.
Warm Temperate Dry
Sub-Tropical Moist
Sub-Tropical Dry

17. LAND USE Groupings Agricultural Land Rangeland Forest Urban Land Water
Irrigated Cropland
Continuous Row Crops
Cont. Row Crops/Small Grains
Continuous Small Grains
Row Crop - Fallow
Row Crop/Small Grain - Fallow
Small Grains - Fallow
Small Grains - Small Grains - Fallow
Row Crop - Hay/Pasture
Row Crop/Small Grains - Hay/Pasture
Small Grains - Hay/Pasture
Continuous Hay
Continuous Pasture
Vegetables in Rotation
Rice in Rotation
Low Residue Annuals (ie cotton, tobacco)
Perennial and/or Horticultural Crops
Conservation Reserve Program (CRP)
Agricultural Land
Rangeland
Forest
Urban Land
Water
Misc. Non Cropland
Federal Land
“No-Till”
“Reduced Till”
and
“Conventional
Till”
Within each of the major land use categories, a limited number of management systems were defined and matched to NRI designations, according to crop type, rotation and tillage, in order to compute the appropriate factor values.

18. Century method
Dynamic simulation model of C stocks and fluxes for whole ecosystem; utilizes monthly time step.
Simulates cropland, grassland, forest and savanna – capable of representing land use and land management changes
Incorporates comprehensive suite of management activities and factors (i.e. crop type, fertilizer, residue mgmt, irrigation, drainage, manuring, grazing, burning, system conversion).
Incorporates changes in yields and C inputs over time as a potential major factor in soil C balance.
The Century model approach uses a dynamic simulation approach to track soil C changes continuously through time as a function of management changes, trends in productivity, climate, etc. Come attributes of the approach and the model capabilities are summarized.

19. Diagram of the soil organic C submodel in Century showing the individual C pools and fluxes and the major factors influencing different C transformations (show as the ‘bow ties’). Soil C is simulated as multiple ‘pools’ of organic matter having different characteristic residence times and controlling factors.

20. Example of Century model validation showing predicted vs simulated soil C levels across a variety of long-term experiments including different fertilizer and tillage treatments for continuous corn and corn-soybean rotations. A uniform parameterization is used across all sites and treatments (I.e. the model has not been calibrated to individual sites or treatments).

21. Conceptual View of Dynamic Modeling using Century
MODELED SCENARIOS
INPUT DATA
Climatic Data
Monthly Temperature
Monthly Precipitation
Tillage Changes
No Till
Reduced Tillage
Conventional Tillage
MLRA 108
Soil Characteristics
Texture
Drainage
Land Use Changes
CRP
Abandoned farmland
Converted to grassland
Native Vegetation
Rotation Changes
Depiction of data sources used as input to the Century model. Climate was defined at the MLRA (delineated above) level (some larger MLRA were subdivided). Within an MLRA all major soil types and cropping systems were simulated as described earlier, based on NRI surveys from 1982 to 1997, along with numerous ancillary data sets as shown in slide # 12.
Historical Cropping Practices
Recent Cropping Practices
Crop Rotation
Tillage
Fertilizer
Irrigation
Background image shows all MLRA’s that have more than 5% agricultural cropland.

22. Comparison of inventory estimates
Comparison of the IPCC and Century derived inventories.

23. Mineral vs. Organic Soils
Estimated Annual C Sequestration in U.S. Agricultural Lands
Mineral vs. Organic Soils
1997 Inventory
The IPCC method, employing the default factor and baseline soil values, shows a net sequestration of about 20 million metric tonnes (MMT) C per year on mineral (I.e. non-organic) soils for cropland and about 7 MMTC/yr for grazing lands. On managed organic soils(I.e. histosols) net losses of 6-7 MMTC are estimated, almost of which is from cultivated annual cropland. The values reflect annual average stock changes over the inventory period ( ).

24. Carbon Sequestration in U.S. Agricultural Soils
IPCC Inventory Approach 1982 to 1997 Analysis
Show the distribution of C stock changes (left figure) and the areas where management has changed into management categories which are mainly responsible for the change in C stocks (I.e. hay, pasture, reduced summer fallow, CRP and conservation [reduced till and no-till] tillage). The blue bars show the ‘total’ change in C stock and area for lands coming into each category, while the brown bars show the net change, that is, including areas that were previously (in 1982) in those systems but then changed to other categories during the inventory period.

25. Aggregate Century results
Shows the net change in soil C stocks for highly aggregated categories of land use and management. Note that the increase for ‘conventional-till annual cropland’ is a result of changes in practices other than tillage, such as reductions in fallow frequency, increased use of hay in rotation, as well as overall increases in crop productivity and residue inputs that have been occurring over the past several decades.

26. Average rate of C change from 1982, ‘to’ management systems in 1997
Annual rates by ‘system’ changes
Average rate of C change from 1982, ‘to’ management systems in 1997
to CRP
to CRP
to NT
to NT
to hay
to hay
stay as RT
to RT
stay as CT
stay as hay
to NT
to RT
to CT
Average rates C change (tonnes/ha/year) from 1982 to 1997 (the NRI period of record) for transitions from systems that were in a) conventional annual cropland, b) annual cropland with reduced tillage and c)hay in 1982, to other tillage systems, hay or CRP management.
From annual crops,
conventional till
From annual crops,
reduced till
From hay

27. Example of specific simulations results, for corn-soybean rotations on clay-loam, non-hydric soils in MLRA 108 (located in the Corn Belt), with no change in rotation or tillage (pink line), converting to no-till (blue line) or CRP (black line). ‘Y’ axis values are change in soil C stocks over the period.

28. Example of specific simulations results, for wheat-fallow rotations on clay-loam, non-hydric soils in MLRA 54(located in the Northern Great Plains), with no change in rotation or tillage (pink line), converting to no-till (blue line) or CRP (black line). ‘Y’ axis values are change in soil C stocks over the period.

29. Example of specific simulations results, for alfalfa hay on clay-loam, non-hydric soils in MLRA 108 (located in the Corn Belt), converted to conventional-tilled corn-soybean-hay rotation for 5 years, followed by conversion to a) continuous corn under no-till (blue line), b) corn-soybean with reduced tillage (pink line) and c) corn-soybean with conventional, intensive tillage (black line). ‘Y’ axis values are cumulative change in soil C stocks over the period.

30. Century IPCC 21.2 MMTC yr-1 on 149 Mha cropland 20 MMTC yr-1
Estimates of net soil C sequestration on cropland soils (mean of stock changes from 1982 to 1997) based on the Century ecosystem model and the IPCC inventory methodology. The IPCC estimates include some crops (e.g. vegetables, potatoes, sugar beets, sugar cane, rice perennial crops) not included in the Century analysis. In addition, Major Land Resource Regions (MLRA’s) having <5% agricultural land were omitted from the Century-based analysis. Results are aggregated by MLRA but are based on individual calculations for the ca. 1 million NRI inventory points.
IPCC
20 MMTC yr-1
on 168 Mha cropland

31. … on national-level quantification of soil C emissions/sinks
Development of soil C stock monitoring network (incl. new measurement technologies) - integration with models
More data on fluxes from cultivated organic soils
Continued model development and validation
Formal model uncertainty analysis
Integration with top-down estimates (e.g. inverse modeling, flux-tower) at varying scales. Requires combining bottom-up estimates from all land use (forest, ag., grassland, urban) and energy emission sources.
Suggested research priorities and on-going/future steps for improving national-level estimates of soil C emissions and sequestration.

32. …on integrated assessments for policy
Economic/behavioral data for the systems of most importance (which may be new, unconventional)
Issues of scaling – what level is necessary to capture key interactions between, e.g. soils, management and economics ? For example, if no-till is prevalent on poorer, erosion-prone areas?
Can we develop formal uncertainty/confidence estimates for farmer or sector behavior in response to policy and economic signals – e.g. through analysis of past events?
Suggested research needs and future steps for improving integrated assessment of mitigation policy options using linked ecosystem and economic models.