Quiroz - techniques for measuring soil C
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Transcript of Quiroz - techniques for measuring soil C
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
OUTLINE
•Emerging techniques for…
•Quick overview of selected emerging techniques
•Examples of field measurements
•Data input for SC modeling
•A “synthetic” scenario
•Summary
Emerging SC measuring techniques for...
•Geospatial baseline
•Quantity and quality of SC stocks
•Field-base measurements
•Better input for models
•Assessing tradeoffs
Mostly used SOM techniques in developing countries
&/or
Examples of emerging techniques for SOC measurements
460 480 500 520 540 560 580 600 620 640 660
5
10
15
20
25
30
35
40
45
LIF
inte
nsity
(a.u
.) / C
(g k
g-1)
λ (nm)
0-2.5 cm 2.5-5 cm 5-10 cm 10-20 cm 20-30 cm
Infrared Spectroscopy for rapid soil characterization
• Rapid, Low cost
• Reproducible
• Predicts many soil functional properties
Parameter R2 PCs
Total N 0.9 8
Total C 0.92 6
Organic C 0.92 6
pH 0.89 10
Ca 0.95 9
K 0.81 10
Mg 0.92 10
Source: K. Shepherd (ICRAF)
LIBS System
Source: Da Silva et al., 2008
LIF Emission spectrum
400 450 500 550 600 650 700
0
1
2
3
soil calcinate and treated soil
Inte
nsity
(a.u
.)
λ (nm)
Milori et
al., SSSAJ, 2006.; González-Pérez et
al., Geoderma, 2007
λexcitation
= 458 nm
Humification Degree:HLIF
= LIF Area
/total carbon
Bench and portable LIF correlate well with EPR findings
Electron Paramagnetic Resonance (EPR)EMBRAPA Lab.
2 3 4 5 6 7 8 9
2.0
2.5
3.0
3.5
4.0
4.5
5.0R=0.93; P<0.0001
LIF
benc
h sy
stem
: HLI
F (a.
u.)
EPR [(spins g-1C) x 1017]
SOM characterization with 13C-NMR
Nuclear Magnetic ResonanceEMBRAPA Lab
Source: Segnini et al., 2011
A B2
3
4
5
6
7
8
9
spin
s (x
1017
) g-1 C
Bofedales (wetlands)
0-2.5 cm 2.5-5 cm 5-10 cm 10-20 cm 20-30 cm
Forest Tea Degradedvegetation Native veg.
On-going analysis in Kenya
CARBON STOCKS# (kg m-2)
Area 1 Area 2 Area 3
sites depth (cm)
Forest Tea Coffee + eucalyptus
Coffee Native vegetation
Rotationcrops
Native vegetation
Rotationcrops
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
Results from EMBU-Kenya
LIF results:Kenya
#
HLIF
can be estimated through the ratio area under fluorescence emission (excitation range 350 -
480 nm) / total organic carbon content.
Humification degree or carbon stability (HLIF) of whole soils obtained through Laser Induced Fluorescence (LIF) spectroscopy.
fore
st (1
)
tea
(1)
coffe
e +
euca
lypt
us (1
)
coffe
e (1
)
natu
ral v
eget
atio
n (2
)
rota
tion
(2)
natu
ral v
eget
atio
n (3
)
rota
tion
(3)
0 - 2.55 - 10
20 - 300
102030405060708090
LIF index (a.u.) (x1000)
Land use
depth (cm)
0 - 2.5
2.5 - 5
5 - 10
10 - 20
20 - 30
Extraction of soil and climate parameters from agro-ecological cells or polygons for model parameterization
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
Source: FAO
HUANCANE
01020304050
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
m.m
.
(ppm)
Space-time scaling weather/climate data
✓60 primary sentinel sites9,600 sampling plots19,200 “standard” soil samples~ 38,000 soil spectra3,000 infiltration tests~ 1,000 Landsat scenes~ 16 TB of remote sensing data to date
AfSIS
Sampling-transect to assess carbon contents and stocks in Southern Peru.Source: Segnini et al., 2010
Selected characteristics of the sampling sites.
loamclay loamloamloamloamSoil class
20°C8 °C14°C17°C19°CT mean ( °C)
2133690-83451155Precipitation (mm)
Coffee, potato, maize, coca,
citrus
Potato, oat, alfalfa,
grasslands, peat lands
Avocado, potato, maize, alfalfa, cassava
Maize, potato, grape, orange, alfalfa, onion,
beans
Maize, oliveCropping system
1,3503,8302,200960135Altitude (m)
humid
valleySemi-Arid
high
plateauArid high
valley
Arid low
valley
Arid CoastAgro eco zones
San Juan del Oro
PunoTorataMoqueguaIlosites
Carbon stocks in diverse Andean soils
Mai
ze
Oliv
e
Alfa
lfa I
Pot
ato
I
Gra
pe
Avo
cado
Alfa
lfa II
Cof
fee
Fore
st
Pot
ato
II
0 - 2.5
10 - 2005
1015
2025
30
35
40
LIF index (a.u.)
Land use
depth (cm)
0 - 2.52.5 - 55 - 1010 - 2020 - 30
LIF results: Andes
#
HLIF
can be estimated through the ratio area under fluorescence emission (excitation range 350 -
480 nm) / total organic carbon content.
Humification degree or carbon stability (HLIF) of whole soils obtained through Laser Induced Fluorescence (LIF) spectroscopy.
Changes in potential potato (improved and native) in Peru: 2000-2050
S. De Haan & H. Juarez, CIP (2008)
1975:(4000-4150msnm)
2005:(4150-4300msnm)
As temperature and presence of pest increase in the Andes Potatoes are planted in higher grounds
Peatlands and other land uses in the Andean high plateau
Peatlands to potato
050
100150200250300350
2000 2050Scenarios
Gig
agra
ms
(10x
9)
Bolivia Peru
Grasslands to potato
0
2000
4000
6000
8000
10000
12000
2000 2050Scenarios
Gig
agra
ms
(10x
9)
Bolivia Peru
Potential loss of soil carbon stocks due to cropping peatlands and grasslands in Peru & Bolivia
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