carbon stocks: a summary of Australian Soil Carbon Research Program · · 2013-02-21the...
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Transcript of carbon stocks: a summary of Australian Soil Carbon Research Program · · 2013-02-21the...
Australian soil carbon stocks: a summary of the Australian Soil Carbon Research Programthe Australian Soil Carbon Research ProgramLAND AND WATER/SUSTAINABLE AGRICULTURE FLAGSHIP
Soil Carbon Research Program (SCaRP)ObjectivesObjectives
Apply consistent methodology to quantify soil carbon stocks
Assess MIR as a rapid and cost‐effective means for quantifying soil carbon k dstocks and composition
Test automated devises for measuring soil bulk density
Quantify soil carbon stocks under different land management strategies at regional levels
Provide temporal soil carbon stock data for FullCAM/NGGI development
Quantify the inputs of carbon to soils under perennial pasture systemsQ y p p p y
Issues beyond the scope of SCaRP• The sampling methodology used in SCaRP was not appropriate to:The sampling methodology used in SCaRP was not appropriate to:
• quantify soil carbon stocks in a paddock
• quantify rates or amounts of carbon sequestration in Australian soils
Background ‐ Composition of soil carbon and definitions
Soil carbon ≤2 mm
OC = organic carbon Carbon accounting is IC = inorganic carbon
TC = Total carbon = (OC + IC)
focused on OC, may Australian soils contain IC
Soil organic carbon ≤2 mm – complex mixture of many materials
POC = particulate organic carbon (2000–50 µm excluding charcoal)
HOC = humus organic carbon (≤50 µm excluding charcoal)
ROC = resistant organic carbon (≤2000 µm charcoal)
Why are we interested in fractions of soil carbon?
• Quantifying fractions is not a requirement for soil carbon accounting
• Provides data for initialising and calibrating FullCAM ‐ used in the NGGI
• Provides an indication of the vulnerability of soil carbon to subsequent change
Vulnerability (V)POC
V
POC HOC ROC
VHOC ROC
POCV
HOCHOC
Composition of POC and HOC
POCHOC
Index of extent of decomposition(Alkyl C/O‐Alkyl C)
Sampling locations and soil samples collected
Samples collected and analysed by SCaRP
‐ 17 721 samples17,721 samples‐ 3,836 sites
Additi l lAdditional samples‐ 2774 samples‐ 690 sites
Totals‐ 20 495 samples20,495 samples‐ 4,526 sites
>92% from farmer paddocks
Soil sampling methodology
Some variance in the process used to select sampling locationsSome variance in the process used to select sampling locations
Once the locations of sampling sites were defined – everything was consistent from that pointp
Sampling siteProcessing and Analyses
Air dryCrushSieve ≤2 mmSplit ≤2 mm subsamples using iffl briffle boxes
Fine grind– TC, OC, IC, TN and MIR– Fractions– Fractions
– POC (2000‐50µm)– HOC (<50µm)– ROC (<2000µm)( µ )
Variations in 0‐30 cm soil carbon stocks 0.25
0.20
uency
All sites0 16
0.10
0.15
ative freq
u
0.12
0.14
0.16
ency
NSW sites
0 8
0.00
0.05
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Rel
0.06
0.08
0.10
ative freq
ue
0 12
0.14
0.16
0.18
ncy
Central TablelandsNSW
0 20 40 60 80 100
120
140
160
180
200
220
240
260
280
300
Soil OC stocks (Mg C/ha)
0.00
0.02
0.04Rela
0 06
0.08
0.10
0.12
tive freq
ue
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Soil OC stocks (Mg C/ha)
0 00
0.02
0.04
0.06
Relat
0.00
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Soil OC stocks (Mg C/ha)
Variations in 0‐30 cm soil carbon stocks
0.25
0.30
y
0.20
freq
uency
Central Tablelands, NSW
Central Slopes, NSW
l l i
0.10
0.15
Relative
Central Plains, NSW
0.05
0.0010 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100
Soil OC stocks (Mg C/ha)
Creation of cumulative probability distributions
100
Central Tablelands
60
80
bability (%
) NSW
40
lative prob
40% of the time <38 Mg C/ha60% of the time >38 Mg C/ha
20Cumu
00 20 40 60 80 100 120
Soil OC stocks (Mg C/ha)
Assessing the ability of MIR/PLSR to predict soil C and its allocation to different forms
MIR as rapid method of analysis for soil organic carbon
MIR as rapid method of analysis for TC, OC, IC and TN
TC IC
OC TN
MIR as rapid method of analysis for soil OC fractions
OCPOC
OC
HOCROC
Rapid assessment of bulk density – gamma radiometrics
WA Project – soil surface CSIRO – core scanner
• Impact of NDM vs cores on soil C stocks small•Bulk density accounted for <4% of variation in C stock
•Required correction for water content•NIR predicted water contents sufficed•Potential to take this technology to the field
Soil carbon under perennial pasture : C3/C4 transition
Regional SOC sequestration rates:50
SA - FP + KI Regional SOC sequestration rates:
• 0.9 ± 0.3 Mg C/ha/y for kikuyu in WA
• No trend for panic/Rhodes in WAMg
C h
a-1)
20
30
40SA FP KIWA - NDWA - SD
p /
• 0.3 ± 0.1 Mg C/ha/y for kikuyu in SA
SO
C (M
20
-10
0
10
• Kikuyu more responsive than pastures with a mix of panic/Rhodes grasses
• Approximately 80% of change due to
-20
a-1) 20
25
• Approximately 80% of change due to C4‐SOC
4-C
(Mg
C h
a
5
10
15
0 10 20 30 40 50
C4
0
5
Perennial pasture age (yr)
Input of carbon to soil under kikuyu perennial pasture: fate of 14C CO2‐C2
2 1 6 2 1 1
0 5 10 15 20 25 30 35
10 d
% of 14C CO2 fed to pastureSoil Depth
Time since
labelling
25.1
17.9
7.2
6.2
6.4
7.5
1.1
1.2
1.2
10 days
6 wks
1 year
10 days
0-10cm>2mm Roots
POM fractiony
6 wks
1 year
10 days
10-20cm <50µm fraction (humus)
6 wks
1 year
10 days
6 ks
>2mm Roots
POM fraction
20-30cm
30-50cm
Annual addition:
POC + HOC = 1052 kg/ha6 wks
1 year
10 days
6 wks
POM fraction
<50µm fraction (humus)
50-70cm
HOC = 160 kg/ha
1 year
Murray CMA – soils of the slopes and plains
Sl i t d d d l t• Slopes: introduced and voluntary pastures contained more carbon than cropping
Si ifi t i ti fi d t 0• Significant variations were confined to 0‐10cm
• Increasing trend with rainfall, decreasing t d ith A O t t ttrend with Apr‐Oct temperature
NSW – Northwest slopes and plains
• SOC stocks higher in pastures than cropping
• Tillage differences were not significant
• Pasture type – may be an impact of land use history
• Natural gradients are importantg p• Correlations were found with soil type, clay content, rainfall, temperature and elevation
Queensland cropping lands
Hermitage long‐term trial (1981‐2008)
• No evidence that no‐till or stubble retention can increase soil carbon stocks
• NT and stubble retention decreased extent of loss for 0‐10 cm layer but not 0‐30 cm layerlayer
Queensland rangeland systems
• Non linear trends with increasing shoot dry matter production, NDVI, and annual rain for 0‐10 cm SOC stocks
• Soil type was also important
• Potential for remote sensing to provide key information• Potential for remote sensing to provide key information
South Australia – dry land cropping soils
60
70
tock
e60
70
tock
e)
20
30
40
50
60
ganic carbon
st
0 cm
, tonnes/hectare
20
30
40
50
60
ganic carbon
st
0 cm
, tonnes/hectare
0
10
350 400 450 500 600
Soil org
0‐30
0
10
0
Soil org
(0‐30
cropped crop‐pasture pasture
Mid‐North Eyre PeninsulaRainfall zone, < mm
Victoria – soil carbon in cropping and pasture systems
Location Management practicesDuration
(y)SOC difference(Mg OC/ha)(y) ( g / )
HamiltonP rate and grazing intensity
27 nsd
Ararat Gra ing management 5 nsdArarat Grazing management 5 nsd
Horsham, LR1 Cropping systems 94 ≤5
Horsham, SCRIME Cropping systems 13 ≤3
WalpeupCropping systemsCultivation
2727
≤2nsdCultivation 27 nsd
nsd= no statistical difference
Western Australia
200
250
Albany Sand Plain
150
rganic Carbon
ha; 0
‐0.3 m)
• Some pasture systems are at or above modelled attainable soil carbon stocks
Modelled attainable carbon
50
100
Soil Or
(t C/h carbon stocks
• Cropping and mixed crop/livestock were lower than pasture systems and generally
0350 400 450 500 550 600 650 700 750 800
Annual Rainfall (mm)
p y g y50% of modelled attainable values
Continuous cropping Mixed crop/livestockAnnual pasturePerennial pasture
Summary and future directions
• Significant progress in measurement technologies• Ability to generate a suite of soil carbon data with one analysis (assess
vulnerability of soil carbon change, provide input to models)• How to extend the capability developed?• Need to develop a coordinated nationally consistent approach – central MIR
spectral library accessible to regional labs• We need to catch and analyse samples that do not fit current calibrations –
build the prediction system through time• How do we optimise predictions and enhance certainty?
• Sampling was not comprehensive• Some important regions managements soil types were not included• Some important regions, managements, soil types were not included• New management strategies have not been assessed
Summary and future directions• Temporal measurements are required to quantify sequestrationTemporal measurements are required to quantify sequestration
• Establishment of monitoring system• Verification requirements – expensive ongoing requirement (are there
alternatives)alternatives)
• More to be extracted from the data collected and collation with other datasets
• Creation of a national repository for data and new data• Further examination of covariates and ability to predict spatial distributions
of soil organic carbon stocks and composition.of soil organic carbon stocks and composition.
• Many regions did not show a statistically significant effect of defined management practices on soil carbon stocks
• At least partially due to variability that existed within management classes • Are we doing the right thing by binning up on broad management classes –
should we be considering alternative metrics?
h kThank youLand and Water/ Sustainable Agriculture FlagshipJeff BaldockResearch Scientist
t +61 8 8303 8537e [email protected] www.csiro.au/lorem
LAND AND WATER/SUSTAINABLE AGRICULTURE FLAGSHIP