Roberto Quiroz, Emerging techniques for soil carbon measurements (presentation from Mitigation session at CCAFS Science Workshop, December 2010)

1. Emerging techniques for soil
carbon measurements
D. Milori, A. Segnini, W. Da Silva, A. Posadas, V. Mares, R. Quiroz, & L. Martin-Neto
& contributions from L. Claessens & K. Shepherd

2. OUTLINE
•Emerging techniques for…
•Quick overview of selected emerging techniques
•Examples of field measurements
•Data input for SC modeling
•A “synthetic” scenario
•Summary

3. Emerging SC measuring
techniques for...
•Geospatial baseline
•Quantity and quality of SC stocks
•Field-base measurements
•Better input for models
•Assessing tradeoffs

4. Mostly used SOM techniques in developing countries
&/or

5. Examples of emerging techniques for
SOC measurements
45 0-2.5 cm
2.5-5 cm
40 5-10 cm
10-20 cm
LIF intensity (a.u.) / C (g kg )
-1
20-30 cm
35
30
25
20
15
10
5
460 480 500 520 540 560 580 600 620 640 660
λ (nm)

6. Infrared Spectroscopy for rapid soil
characterization
• Rapid, Low cost Parameter
Total N
R2
0.9
PCs
8
• Reproducible Total C
Organic C
0.92
0.92
6
6
pH 0.89 10
• Predicts many soil functional properties Ca 0.95 9
Source: K. Shepherd (ICRAF) K 0.81 10

7. LIBS System
Source: Da Silva et al., 2008

8. LIF Emission spectrum
soil
3
calcinate and treated soil λexcitation = 458 nm
Humification Degree:
HLIF = LIF Area/total carbon
Intensity (a.u.)
2
1
0
400 450 500 550 600 650 700
λ (nm)
Milori et al., SSSAJ, 2006.; González-Pérez et al., Geoderma, 2007

9. Bench and portable LIF correlate well with
EPR findings
5.0
R=0.93; P<0.0001
4.5
LIF bench system: HLIF (a.u.)
4.0
3.5
3.0
2.5
2.0
2 3 4 5 6 7 8 9
-1 17
EPR [(spins g C) x 10 ]
Electron Paramagnetic Resonance (EPR)
EMBRAPA Lab.

10. SOM characterization with
13C-NMR
Nuclear Magnetic Resonance
EMBRAPA Lab

11. 9
0-2.5 cm
8 2.5-5 cm
5-10 cm
10-20 cm
7 20-30 cm
spins (x 10 ) g C
-1
6
17
5
4
3
2
A B
Bofedales (wetlands)
Source: Segnini et al., 2011

12. On-going analysis in Kenya
Forest Tea Degraded
Native veg.
vegetation

13. Results from EMBU-Kenya
CARBON STOCKS# (kg m-2)
Area 1 Area 2 Area 3
sites Forest Tea Coffee + Coffee Native Rotation Native Rotation
depth (cm) eucalyptus vegetation crops vegetation crops
0-2.5 1.8 ±0.1 0.6 ±0.0 0.6 ±0.0 0.5 ±0.0 0.3 ±0.0 0.7 ±0.1 1.0 ±0.0 0.5 ±0.1
2.5-5 1.3 ±0.1 0.3 ±0.0 0.6 ±0.1 0.5 ±0.0 0.2 ±0.0 0.7 ±0.1 0.8 ±0.0 0.5 ±0.1
5-10 2.4 ±0.1 1.2 ±0.1 1.3 ±0.3 1.0 ±00 0.5 ±0.0 1.3 ±0.1 1.4 ±0.0 0.9 ±0.1
10-20 4.1 ±0.6 2.1 ±0.0 2.1 ±0.1 1.8 ±0.2 0.8 ±0.1 2.1 ±0.4 2.8 ±0.1 2.0 ±0.3
20-30 3.1 ±0.3 2.1 ±0.0 1.9 ±0.1 1.8 ±0.2 0.8 ±0.2 1.7 ±0.2 1.8 ±0.1 1.3 ±0.1
Total (0-30) 12.7 ±1.2 6.3 ±0.1 6.4 ±0.5 5.6 ±0.4 2.6 ±0.4 6.5 ±0.9 7.8 ±0.3 5.1 ±0.6

14. LIF results:Kenya
Humification degree or carbon stability (HLIF) of whole soils obtained
through Laser Induced Fluorescence (LIF) spectroscopy.
90
80
70
60
LIF inde x (a.u.) 50
(x1000) 40
30 0 - 2.5
20
2.5 - 5
10 20 - 30
0 5 - 10
5 - 10
depth (cm )
forest (1)
10 - 20
tea (1)
0 - 2.5
coffee + eucalyptus (1)
coffee (1)
natural vegetation (2)
rotation (2)
natural vegetation (3)
20 - 30
rotation (3)
Land us e
# HLIF can be estimated through the ratio area under fluorescence emission
(excitation range 350 - 480 nm) / total organic carbon content.

15. Modeling Carbon Dynamics in Soils:
Weather data used to
run the model:
Rainfall: essential
Air temperature:
essential
Temporal resolution of
weather data:
Monthly: essential
Spatial resolution of
weather data:
Local scale: essential
Extraction of soil and climate parameters from agro-ecological cells or polygons
for model parameterization
Source: FAO

16. Space-time scaling weather/climate data
(ppm)
HUANCANE
50
40
m.m.
30
20
10
0
1-Jan-99 20-Jul-99 5-Feb-00 23-Aug-00 11-Mar-01 27-Sep-01 15-Apr-02 1-Nov-02
Días

17. AfSIS
✓60 primary sentinel sites
9,600 sampling plots
19,200 “standard” soil samples
~ 38,000 soil spectra
3,000 infiltration tests
~ 1,000 Landsat scenes
~ 16 TB of remote sensing data to

18. Sampling-transect to assess carbon contents and stocks in Southern Peru.
Source: Segnini et al., 2010

19. Selected characteristics of the sampling sites.
sites Ilo Moquegua Torata Puno San Juan del
Oro
Agro eco Arid Coast Arid low Arid high Semi-Arid humid valley
zones valley valley high plateau
Altitude (m) 135 960 2,200 3,830 1,350
Cropping Maize, olive Maize, potato, Avocado, Potato, oat, Coffee, potato,
system grape, orange, potato, maize, alfalfa, maize, coca,
alfalfa, onion, alfalfa, cassava grasslands, citrus
beans peat lands
Precipitation 5 15 51 690-834 2133
(mm)
T mean ( °C) 19°C 17°C 14°C 8 °C 20°C
Soil class loam loam loam clay loam loam

20. Carbon stocks in diverse
Andean soils

21. LIF results: Andes
Humification degree or carbon stability (HLIF) of whole soils obtained
through Laser Induced Fluorescence (LIF) spectroscopy.
40
35
30
25
LIF index (a.u.) 20 0 - 2.5
15 2.5 - 5
10 5 - 10
5 10 - 20
0 10 - 20 20 - 30
Maize
Olive
Alfalfa I
depth (cm)
Potato I
Grape
0 - 2.5
Avocado
Alfalfa II
Coffee
Forest
Potato II
Land use
# HLIF can be estimated through the ratio area under fluorescence emission
(excitation range 350 - 480 nm) / total organic carbon content.

22. Changes in potential potato (improved and native) in Peru: 2000-2050

23. As temperature and presence of pest increase in the
Andes Potatoes are planted in higher grounds
1975:
(4000-4150msnm)
2005:
(4150-4300msnm)
S. De Haan & H. Juarez, CIP (2008)

24. Peatlands and other
land uses in the
Andean high
plateau

25. Potential loss of soil carbon stocks due to cropping
peatlands and grasslands in Peru & Bolivia
Peatlands to potato
350
300
Gigagrams (10x9)
250
200
150
100
50
0
2000 Scenarios 2050
Bolivia Peru
Grasslands to potato
12000
10000
Gigagrams (10x9)
8000
6000
4000
2000
0
2000 Scenarios 2050
Bolivia Peru

26. Summary
•Emerging SC measuring techniques / tools & MRV
•Further field testing under different agroecological conditions &
creation of spectral libraries needed (C-contents & stability)
•Better input for SC modeling
•Better assessment of tradeoffs
•Synergy with complementary tools e.g. remote sensing