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SENSITIVITY OF THE CENTURY MODEL FOR ESTIMATING SEQUESTERED SOIL CARBON USING COARSE- AND FINE-SCALE MAP DATA SOURCES IN NORTH CENTRAL MONTANA : 

SENSITIVITY OF THE CENTURY MODEL FOR ESTIMATING SEQUESTERED SOIL CARBON USING COARSE- AND FINE-SCALE MAP DATA SOURCES IN NORTH CENTRAL MONTANA   Ross Bricklemyer M.S. Candidate Land Resources and Environmental Science

Slide2: 

Background Global CO2 C sequestration Century model Effects of soil texture Century Sensitivity Analysis Methods Field Component Modeling Component Results Conclusions Recommendation and knowledge gaps

Slide3: 

Graph adapted from the Whitehouse Initiative on Global Climate Change. 

Slide4: 

Graph adapted from the Whitehouse Initiative on Global Climate Change. 

Global Temperature Changes (1880-2000): 

Global Temperature Changes (1880-2000) Atmospheric concentrations of carbon dioxide can be lowered either by reducing emissions or by removing carbon dioxide out of the atmosphere and storing in it terrestrial, oceanic, or freshwater aquatic ecosystems. (USDA GLOBAL CHANGE FACT SHEET http://www.usda.gov/oce/gcpo/sequeste.htm

Carbon Sequestration in Terrestrial Systems: 

Carbon Sequestration in Terrestrial Systems Definition: Net removal of CO2 from the atmosphere into long-lived pools of soil carbon Process: CO2 removed from atmosphere by plants via photosynthesis Plant material converted to organic matter through microbial biochemical reactions and stored in soil McConkey et al. 1999

Management to increase carbon: 

Management to increase carbon Increase C inputs and decrease degradation of organic matter Adequate fertilization C:N ratio is crucial for C sequestration Increase cropping intensity i.e. Reduction of fallow frequency Reduction/elimination of tillage i.e. Adoption of no-till Lal et al. 1998

Slide8: 

Tillage VS No-Till (Paustian et al. 1997; Campbell et al. 1996, 2000) Breaks soil aggregates Reduces crop residue Promotes erosion Promotes degradation of organic matter Promotes aggregation Retains crop residue Reduces erosion Increases organic matter

Carbon Credits: 

Carbon Credits CO2 emitters purchase credits to meet reduction targets. Production agriculture in a position to capitalize on carbon credit trading.

CENTURYSoil Organic Matter Model: 

CENTURY Soil Organic Matter Model Processes Soil and Plant Properties Driving Variables Management Precipitation Min/Max Air Temperature Soil texture Cultivation Crop type Fertilizer use Grazing Fire Soil bulk density Initial soil C, N, P, S Plant N, P, S Plant lignin content

Texture Effects: 

Texture Effects Water holding capacity Fine > medium > coarse Erosion potential Fine ≈ coarse > medium Leaching environment Coarse > medium >Fine Soil Carbon Storage Fine > medium > coarse

Texture Effects on SOC: 

Texture Effects on SOC Generally accepted that finer textured soils store more carbon than coarse textured soils Effect of texture on carbon stored due to the adoption of no-till unclear. No meaningful relationship in 11 long-term (10yr) paired no-till conventional till experiments (Paustian et al. 1997) nor in 130 short-term (3 yr) field sites (McConkey, unpublished data) Campbell et al. 1996 found a strong relationship in long-term (12-14 yr) plots.

Objective: 

Objective Understand the sensitivity of the CENTURY model to different scales of soil texture input data for modeling soil carbon change in response to the adoption of no-till. How do estimated soil organic carbon values from the Century model change when clay content and related soil properties change? Century Sensitivity Analysis

Methods: 

Methods Field Component Site Selection Site Characteristics Sampling Design Field Sampling Sample Analysis Statistical Analysis

Site Selection: 

Site Selection Located 6 suitable pairs of no-till (NT) and conventional till (CT) fields. Criteria: In 2001 produced same wheat No-till management for a minimum of 6 years Crop production for last 20 years or more. NT/CT pair separated by anthropogenic boundary NT/CT pair has the same soil-landscape association under both tillage practices

Site Locations: 

Site Locations Padbury et al. 2002 AJ 94:251

Site Characteristics: 

Site Characteristics

Sampling Design: 

Sampling Design NOT TO SCALE

Field Sampling: 

Field Sampling Depth Increments: 0-10 cm 10-20 cm 20-50 cm 50-100 cm

Sample Analysis: 

Sample Analysis Particle size analysis Total C and total N Leco C/N/S 2000 analyzer Inorganic C Modified pressure calcimeter method (Sherrod et al. 2002) SOC = total C – inorganic C SOC calculated on an equivalent mass basis rather than a concentration (Ellert and Bettany 1995)

Statistical Analysis: 

Statistical Analysis Nested design to test tillage effect on soil organic carbon ANOVA (all depths) Only 0 to 20 –cm data shown No meaningful differences occurred below 20 cm Field Component

Century Sensitivity Analysis: 

Century Sensitivity Analysis Modeling Component Initial model setup Sensitivity Initialization Sensitivity Analysis

Initial model setup: 

Initial model setup Equilibrate model to “natural” grassland Site-specific inputs {soil texture, soil bulk density, crop types, fertilizer (type and amt.), tillage equipment, and weather} Site-specific timing (month) of management operations {tillage, fertilizing, seeding, and harvest}

Soil Texture Data Sources: 

Soil Texture Data Sources State soil geographic (STATSGO) database (1:250,000 scale) Soil survey geographic (SSURGO) database (1:24,000 scale) Field scale or measured soil texture

Sensitivity Initialization: 

Sensitivity Initialization Soil texture (i.e. % clay) and bulk density values reported by STATSGO and SSURGO databases. Beginning with lowest STATSGO reported % clay and bulk density value, clay content was increased by 5% increments and bulk density proportionally. Plant available water at field capacity and wilting point was estimated using an equation developed by Rawls et al. (1982). All remaining site-specific inputs constant.

Sensitivity Analysis: 

Sensitivity Analysis Century SOC predictions for each field compared to measured values. Calculated implied SOC change due to adoption of no-till as SOC(nt) – SOC(ct) using measured and modeled values. 95% prediction interval built around modeled values. Compared measured implied change to modeled implied change.

Results: 

Results Measured SOC (0 to 20-cm)

Results: 

Results Predicted SOC (Century model) using site-specific input data

ResultsTexture effect on predicted soil carbon: 

Results Texture effect on predicted soil carbon Predicted No-till (STATSGO) Predicted Tilled (STATSGO) Measured No-till Measured Tilled Predicted No-till (site specific) Predicted Tilled (site specific)

Results: 

Results Predicted (STATSGO) Regression 95% PI Measured Predicted (site specific) Texture effect on predicted soil carbon change due to no-till Effect of texture on carbon stored due to the adoption of no-till is not well understood!!

Results: 

Results

Conclusions: 

Conclusions Significant differences in SOC occurred due to the elimination of tillage. Century has been validated for use in modeling SOC dynamics in north central Montana. Century adequately modeled SOC using site-specific data. Century model was sensitive to the effects of soil texture when predicting the amount of SOC in fields managed with and without tillage. Century model was not sensitive to the effects of soil texture when predicting SOC change due to the adoption of no-till. Existing soil databases are limited in their applicability for field level modeling. STATSGO (1:250,000 scale) and the SSURGO (1:24,000 scale) soil databases did not consistently predict the soil textures across the six sites sampled in this study. STATSGO and SSURGO databases did not provide adequate soil textural information for use in the Century model.

Recommendation and Knowledge gaps: 

Recommendation and Knowledge gaps Site-specific soil information is recommended for use with the Century model when estimating SOC change at the field/farm level. Gain a better understanding of the effect of soil texture on carbon sequestration due to no-till. Better understanding of the effect of no-till on soil properties (ex. aggregate and macropore development). Further examination of how changes in cropping systems effect C sequestration (i.e. increased cropping intensity and use of pulse crops in rotation). Modeling and field research need to complement the efforts of each other.

Acknowledgements: 

Acknowledgements Consortium for Agricultural Soils Mitigation of Greenhouse Gases (CASMGS) Upper Midwest Aerospace Consortium - Public Access Resource Center (UMAC-PARC) Montana State University- Agricultural Experiment Station (MSU-AES) Colorado State University Natural Resource Ecology Laboratory Advisory Committee: Perry Miller PhD MSU-LRES Tom Keck PhD USDA/NRCS Keith Paustian PhD CSU-NREL John Antle PhD MSU-Ag Economics Jerry Nielsen PhD MSU-LRES Special Thanks Brian McConkey PhD Agiculture Agri-Food Canada (SPARC) Phil Turk PhD candidate MSU - Statistics Rosie Wallander MS MSU - LRES Lester Johnson Steve Keil Steve Matheson Carl and Janice Mattson Bob Mattson Hugh Mc Farland Steve McIntosh Brian Morse Mark Peterson Ken Romain Glen Stewart

Questions?: 

Questions?

Why Equivalent Mass: 

Why Equivalent Mass Soil Depth (cm) Bulk Density = mass/vol Bulk Density may be lower in tilled field Differences in layer of SOC accumulation may occur with tillage To make accurate comparisons, the mass of the samples must be equivalent Portions of the lower sample used to make up the difference 800g 700g 100g