Rapid Assessment and Trajectory Modeling of Soil Carbon Across a Southeastern Landscape Sabine Grunwald

Project Goals: Modeling of soil carbon along pedo-climatic trajectories across diverse ecosystems in Florida

Funding source: National Research Initiative Competitive Grant no. 2007-35107-18368 USDA NIFA - AFRI

Core Project of theNorth American Carbon Program

PD: S. GrunwaldCo-PIs: W.G. Harris, N.B. Comerford and G.L. BrulandPost-Docs: D.B. Myers and D. SarkhotGraduate students: G.M. Vasques, X. Xiong and W.C. Ross Field and lab staff: A. Stoppe, L. Stanley, A. Comerford and S. Moustafa

Rationale and Significance

Crutzen, 2002. Nature;Steffen et al., 2005. Global Change and the Earth System; Rockström et al., 2009. Nature;Grunwald et al., 2011. Soil Sci. Soc. Am. J.

Global issues & priorities Global estimates of terrestrial carbon stocks

UNEP-WCMC. http://www.carbon-biodiversity.net/GlobalScale/MapScharlemann et al. (2009): Harmonized World Soil Database (2009)-SOC values up to 1 m depth (1 km spatial resolution) & Ruesch and Gibbs (2008): Biomass carbon map using IPCC Tier 1 methodology and GLC 2000 land cover data.

• Lack in understanding of soil carbon (C) variability• Assessments rely on historic/ legacy soil C data• Soil C – a sink or source ?• Soil C – linkages to processes ?• Total soil C – C pools ?

Historic and current within ≤ 30m

Historic and current within ≤ 300m

Current (2008/2009)

• Resampling of 453 historic sites (out of 1,288 historic pedons – FL Soil Database); 1965-1996 (Soil and Water Science Dept., UF & NRCS)

• In 2008/2009 soil sampling at 1014 sites (0-20 cm) based on stratified-random sampling design (land use – soil suborder strata):

- TC- SOC - IC- HC- RC- BD- TN and TP

SOC Observations (FL)

N: 1,099Data source: Florida Soil Characterization Database (FSCD)

Modeling ofHistoric SOC (1 m) – FL

Block KrigingBlock size: 250 x 250 mTarget: Ln-SOC kg m-2

Nugget: 0.61Sill: 0.86Range: 101,088 mME: -0.0040 ln[kg m-2] (~ 0.10 kg m-2)

Class Pedo-transfer function (PTF)SOC = f {LU, order}

SSURGO-Soil Data Mart (NRCS) 1:24,000

STATSGO2-Soil Data Mart (NRCS) 1:250,000

< 5 5 – 1010 – 1515 – 2020 – 50 > 50Not mapped

Vasques G.M. and S. Grunwald. 201_. Global Env. Change J. (in prep.)Presented at the World Congress of Soil Sciences (2010)

SOC statistic(depth to 1 m)

SSURGO STATSGO2 FSCD obser-vations

FSCD block kriging

FSCD PTF

Map unit 655,155 map units

2,823 map units

1,099 points 2,282,843 250-m cells

7 soil orders

Minimum (kg m-2) 0.67 4.01 0.13 2.82 7.70

Maximum (kg m-2) 291.77 264.32 207.98 116.19 144.17

Median (kg m-2) 7.90 27.05 6.32 9.00 14.75

Mean (kg m-2) 24.17 58.44 12.85 13.95 32.84

Std. dev. (kg m-2) 39.31 62.67 23.69 12.28 45.63

Total mapped area (km2)

128,788 142,681 N/A 142,678 142,626

Total stock (Pg) 3.518 6.820 N/A 1.990 4.112

Mean stock (kg m-2)

27.32 47.80 N/A 13.95 28.83

Map

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aEstimates of SOC stocks to 1 m in Florida based on different data/methods was 4.110 ± 1.01 Pg (mean ± std. error)

Vasques G.M. and S. Grunwald. 201_. Global Env. Change J. (in prep.)

Grunwald S., J.A. Thompson & J.L.Boettinger. 2011. SSSAJ. In press.

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• Predicts the spatially-explicit evolution and behavior of Soil Pixels / Voxels

• Explicitly incorporates anthropogenic forcings• Incorporates bio-, topo-, litho-, pedo- and hydrosphere• Provides temporal context to account for ecosystem

processes and forcings• Fuses empirical and process-based knowledge

Conceptual Modeling Framework: STEP-AWBH (“STEP-UP”)

)};,(),,(),,(),,,(({),,( cxcxcxcx

n

jcx tpPtpEtpTtpzSftpzSA

Soil pixel (SA):

STEP variables:• Soil• Topographic• Ecological /

geographic• Parent material

AWBH variables: • Atmosphere / climate• Water• Biota: LU/LC• H(uman)

+

Spatially & temporally explicit environmental matrix (FL): ~2 TB of data

N: 200+ variables

…..

Soil observations+

• PLSR• CART • Ensemble regression trees • … and others

Model development:

Predict soil-environmentalproperties: • TC • SOC • SOC seq. • Carbon pools• TN, TP• … and more

Model validation:Uncertainty assessment

Data source: NRCS-USDA, Soil Geographic Database / Soil Data Mart.

Soil Taxonomic Classes – FL

Histosol

Time period: 2000 – 2005; data source: MODIS satellite data

Net Primary Productivity – FL

Spodosol

JanuaryFebruaryMarch

Data source: PRISM

35 – 5533 – 7575 – 5555 – 7575 – 9595 – 115115 – 135135 – 155155 – 175175 – 195195 – 215215 – 235

Avg. Monthly Precipitation(mm) [1971-2000]

AprilMayJuneJulyAugustSeptemberOctoberNovemberDecember

Climatic Data – FL

Time frame: 1971 – 2000Data source: PRISM

Climatic Data – FL

1990

1995

2003

Data sources: Land use / land cover 1970: USGS; 1990 and 1995: Water Management Districts & FL Department of Transportation2003: Florida Fish and Wildlife Conservation Commission

1970

1970 to 2003:↑ Urbanization (5.4% - 12.1% - 11.0%)

↓ Agriculture (21.9% - 7.4% - 8.6%)

↓ ↑ Rangeland (8.8% - 4.7% - 8.2%) ↓ ↑ Forest (29.9% - 23.2% - 26.2%)

↓ Wetland (21.7% - 4.4% - 5.8%)

Land Use Change (1970 – 2003)Based on Satellite Data

?

Inputs (predictor variables): STEP-AWBH environmental variables

Predict SOC stocks ),,( cx tpzSA

Modeling of Current SOC (0-20 cm) – FL

Methods: Ensemble regression trees (RT) and other data mining methods

Total N: 1,014; Randomized 70/30 calibration/validation split of dataset

R2 RMSE RPDRegression trees (RT) 0.49 3.2 1.34

Bootstrapped RT 0.63 2.6 1.64

Boosted RT 0.61 2.7 1.59

Random Forest 0.64 2.6 1.66

Support Vector Machine 0.60 2.8 1.55

Modeling of Current (2009) SOC Stocks (0-20 cm) – FL

Validation results – STEP-AWBH Modeling (kg C m-2)

Myers D.B., S. Grunwald et al. 201_. Global Change Biology J. (in prep.)

Modeling of Current (2009) SOC Stocks (kg m-2) (0-20 cm) – FL

Predictor variables of importance:• Available water capacity 50 cm 1.0• Soil Great Group 0.85• Land cover / land use (NLCD) 0.83• Land cover / land use (FFWC, 2003) 0.74• Ecologic region 0.50• Soil Order 0.25• Soil Suborder 0.22• … and more

Method: Random ForestIndependent validation (N: 304)

Myers D.B., S. Grunwald et al. 201_. Global Change Biology J. (in prep.)

Modeling ofCurrent (2009) SOC Stocks (20 cm) – FL

Myers D.B., S. Grunwald et al. 201_. Global Change Biology J. (in prep.)

SOC (kg m-2)

Spatial resolution: 30 m

SOC sequestration(g C m-2 yr-1)

SOC Sequestration in Florida (1965 – 2009)

Historic & current sites ≤ 30 m (N: 194)

Grunwald et al., 201_. Front Ecol. Env. J. (in prep.)

SOC sequestration (g C m-2 yr-1)• Mean: 11.6; Median: 17.7• STDev: 93.3• Max: 511.3Time frame of sequestration (yrs)• Mean: 30.3; Median: 29.6• STDev: 5.3• Max: 43.5

Predictor variables of importance:• Surficial geology 100• Land use 1995 75.4• Long-term max. temp. May 75.4• Long-term max. temp. March 62.9• Long-term max. temp. April 35.9• Soil Great Group 27.3• Land use 1970 25.9• MODIS EVI (day 137) 22.8• MODIS EVI (day 169) 22.7• Landsat Bd. 3 20.6• Forest canopy cover 17.5• …. and more

Modeling of SOC Sequestration Rates (g C m-2 yr-1) (0-20 cm) – FL

Methods: Ensemble trees (bagging mode) 10% V-fold cross-validation

Grunwald et al., 201_. Front Ecol. Env. J. (in prep.)

STEP-AWBHmodel evaluation (g C m-2 yr-1):MSE = 85.93MAD = 47.61

Significance of research:

• Predict high-resolution soil C pixels across large landscapes

• Reduce the uncertainty of soil C assessment• Model spatial variability of soil C (C pools and

nutrients) along climate and land use trajectories• Model soil change in dependence of anthropogenic

induced stressors

Soil attributes = f (VNIR)

Rapid and cost-effective sensing of Soil C and Pools using visible/near-infrared (VNIR) diffuse reflectance spectroscopy

Soil attributes = f (VNIR; MIR)

Spectral soil C modeling

Authors Spectra Type

Area N Properties R2 Cal. R2 Val.

Vasques et al. 2008. Geoderma

VNIR SFRW 554 TC 0.98 0.86

Vasques et al. 2009. SSSAJ

(Ahn et al., 2009. Ecosystems)

VNIR SFRW 102 TCRCSCHCMC

0.930.930.890.920.87

0.860.820.400.700.65

Vasques et al. 2010. JEQ

VNIR FL (hist.)

7120 SOC 0.97 0.79

Myers et al. 2011. in prep.

VNIR FL (2009)

1014 SOC (RC, HC)

0.93 0.89

McDowell et al. 2011. in prep.

VNIR & MIR

Hawaii 306 SOC 0.93 (VNIR)0.97 (MIR)

V-fold cross-validation

Sarkhot et al., 2011. Geoderma

VNIR TX 514 TCHCSOCIC

0.940.960.950.93

0.850.770.860.81

Research Results VNIR & MIR

Follow-up Research Project(NRCS, Grunwald – UF & McBratney – U Sydney)

• Rapid soil C assessment across the U.S. • Soil C ↔ Land use/land cover, ecoregion, climate, …• Soil C ↔ VNIR

Apply research methodology tested in FL to U.S.

FL

http://soils.ifas.ufl.edu/faculty/grunwaldsabgru@ufl.edu

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