1. Using the Soil Conditioning Index to Assess Management Effects on Soil Carbon USDA Natural Resources Conservation Service Soil Quality National Technology Development Team

2. Lesson Objectives Introduce the Soil Conditioning Index –Discuss the tool’s background –Explain how the model works Convey the current and potential uses of SCI Highlight the SCI considerations in RUSLE2

3. Water & Nutrient Holding Benefits of Soil Carbon Time Soil Quality Aggregation & Infiltration Productivity Air & Water Quality; Wildlife Habitat Soil Carbon

4. Historic Loss of Soil Carbon Conventional Tillage Reduced Tillage 53% of 1907 61% of 1907 (Lal et al., 1998)

5. The Soil Conditioning Index (SCI): Expresses the effects of the system on organic matter trends as a primary indicator of soil conditionExpresses the effects of the system on organic matter trends as a primary indicator of soil condition Provides a means to evaluate and design conservation systems that maintain or improve soil conditionProvides a means to evaluate and design conservation systems that maintain or improve soil condition

6. SCI Timeline 1950 1960 1970 1980 1990 2000 Origins trace back to 1950’s ARS research in Renner, Texas SQI and NSSC make changes to OM maintenance levels (2000) SQI adds soil texture component (2001) SQI and NSSC calibrate to US using coefficients for climate & decomposition in RUSLE (2002) NSSC Agronomists further develop model and apply it to 1980’s practice criteria

7. SCI Potential Uses: Automatic output from RUSLE2 Based on actual conservation plan Can help landowner with decision-making Valid at the field scale Based on NRI data Holds promise for watershed, MLRA, state & national uses Currently, part of CSP and Resource Quality Criteria Field Office Tool Performance Measure

8. Soil Conditioning Index (SCI=Soil Disturbance+Plant Production+Erosion) + 1- 1 Improving Degrading Sustaining SCI Carbon (lbs)

9. (OM x 0.4) + (FO x 0.4) + (ER x 0.2) =SCI The SCI formula is: (OM x 0.4) + (FO x 0.4) + (ER x 0.2) =SCI OM accounts for organic material returned to the soil (as a function of biomass produced)OM accounts for organic material returned to the soil (as a function of biomass produced) FO represents field operation effectsFO represents field operation effects ER is the sorting and removal of surface soil material by sheet, rill and/or wind erosionER is the sorting and removal of surface soil material by sheet, rill and/or wind erosion Where:

10. SCI Model Variables: Field Operations Biomass Production Erosion Biomass Production

11. OM =(RP - MA) / MA OM subfactor calculation: OM =(RP - MA) / MA RP is average annual above and below ground biomass returned to the soilRP is average annual above and below ground biomass returned to the soil –includes mulch or manure –expressed as REV (corn equivalent) MA is Maintenance OM Level (REV) for the locationMA is Maintenance OM Level (REV) for the location Where:

12. Location

13. SCI Model Variables: Field Operations Biomass Production Erosion Field Operations

14. Soil Tillage Intensity Rating (STIR)

15. Aggrading Degrading Steady State FIELD OPERATIONS (FO) SUBFACTOR

16. SCI Model Variables: Field Operations Biomass Production Erosion

17. TABLE 4 EROSION (ER) SUBFACTOR EROSION (ER) SUBFACTOR Aggrading Degrading Steady State

18. NSSC and Long-term OM Research Sites

19. SCI Outcomes at NSSC initial calibration sites

20. SCI Validation using systems across the U.S.

22. Regression of SCI Outcomes and Measured Carbon Change

23. Running SCI in RUSLE2

24. RUSLE2 Features Affecting SCI User addition of irrigation water User addition of wind- and irrigation-induced erosion User-adjustable crop yield User-adjustable residue burial amount User-adjustable mulch or external residue application

27. Add wind erosion from WEQ and irrigation induced erosion.

28. SCI Summary Easy to use tool to estimate soil condition Validated using long term research data SCI is being used nationally for conservation assessment in CSP & CEAP Now part of RUSLE2 and coming to a field office near you!!

29. Soil Conditioning Index in RUSLE2 http://fargo.nserl.purdue.edu/ rusle2_dataweb/RUSLE2_Index.htm

30. The Ultimate Goal The End