egu 2016 - simulating soil carbon stability
TRANSCRIPT
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SIMULATING SOIL C STABILITY: a multisite comparison of measured fractions and modelled poolsANDY ROBERTSON1,5, NIALL MCNAMARA2, PETE SMITH3,
CHRISTIAN DAVIES4, LUCRETIA SHERROD5, LIWANG MA5, LAJPAT AHUJA5, MEAGAN SCHIPANSKI1
1 – COLORADO STATE UNIVERSITY, FORT COLLINS, USA2 - NERC CENTRE FOR ECOLOGY & HYDROLOGY, LANCASTER, UK3 - SCHOOL OF BIOLOGICAL SCIENCES, UNIVERSITY OF ABERDEEN, UK4 - SHELL INTERNATIONAL EXPLORATION AND PRODUCTION INC., USA5 – USDA-ARS, FORT COLLINS, USA
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Simulating the response of arable soil carbon to changing climate/management
• Models vs Measurements – relatable?
• How much parameterisation is needed?
• Can we simulate stability?
RESEARCH SCOPE AND AIMS
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INTRODUCTIONAgricultural context
◦ Carbon sequestration in soils is an essential part of sustainably managing ag land
◦ Arable land in particular covers ~11 % global land area (14 million km2 – 1.4 bn hectares)
◦ Determining a site/crop’s most effective management strategy requires model sims
◦ Relating measured to modelled carbon is key to validating the accuracy of simulations
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Modelling soil carbon• Model structures range from simple empirical
functions to complex mechanistic relationships
INTRO
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Modelling soil carbon• RothC - monthly timestep soil-only model
Decomposition rates influenced by:
INTRO
• Temperature• Moisture• Clay content
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Modelling soil carbon• DayCent – daily timestep ecosystem model
Decomposition rates influenced by:
INTRO
• Temperature• Moisture• Soil texture
• Input lignin content• Soil C, N, P, S
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Modelling soil carbon• RZWQM – daily timestep ecosystem model
Decomposition rates influenced by:
INTRO
• Temperature• Moisture• Soil pH
• Input C:N• Initial soil C, N• O2 concentration
• H+ concentration
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Measuring soil carbon
Cambardella and Elliott, 1992. SSSAJ. 56:777-783Franzluebbers et al., 2000. SSSAJ. 64: 613-623
Dispersed in (NaPO3)6
Sieve to 53 μm
Incubate at 30ºC for 3 days
Convert to microbial C
3 fractions isolated:POM
Particulate Organic MatterMAOC
Mineral Associated Organic CSMBC
Soil Microbial Biomass C
INTRO
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Measuring soil carbon
Zimmermann et al., 2007. EJSS. 58:658–667
Sieve to 63 μm
1.8 g/cm3 density separation
Oxidation with NaOCl
5 fractions isolated:DOC
Dissolved Organic CarbonS+C
Silt and ClaySA
Sand and AggregatesPOM
Particulate Organic MatterrSOC
Resistant Soil Organic Carbon
INTRO
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Measuring soil carbon
INTRO
RothCPOM = Decomp + Resistant
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Measuring soil carbon
INTRO
RothCPOM = Decomp + ResistantSMBC = Microbial BiomassMAOC = Inert + Humified
DayCentPOM = Surface C poolsSMBC = Microbial Soil CMAOC = Slow + Passive
RZWQM2POM = Surface C pools
SMBC = Fast Organic MatterMAOC = Intermediate + Slow
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Models vs Measurements – relatable?Measurements are unlikely to match model simulations
exactly
How much parameterisation is needed?Simulations will hopefully be close to measurements
without much parameterisation
Can we simulate stability?Fractions that represent labile or stable carbon are not
discrete whereas pools are
RESEARCH AIMS AND HYPOTHESES
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Validation data sitesCOLORADO, USA• Dryland wheat-fallow rotation• Fertilised clay loam• Simple fractionation• 24 years measured data
LINCOLN, UK• Commercial Miscanthus plantation in UK• Unfertilised clay loam• Complex fractionation• 8 years measured data
METHOD
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Total soil carbon comparison
RESULTS
UK Site - total soil stock
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RESULTS
USA Site – total soil carbon
Total soil carbon comparison
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Stable fraction vs stable pool(s)
RESULTS
UK Site -
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Total soil carbon comparison
RESULTS
USA Site -
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DISCUSSION POINTS◦ Models are capable of getting total soil carbon
close to measured data but not that close
◦ Models don’t necessarily even get the correct trend and sometimes contradict each other
◦ Novel crops and atypical sites may need substantial parameterisation
◦ Fractions are not directly relatable to any model pool(s) – are ‘transformations’ the next step?
◦ Inherent uncertainty highlights the need to use existing and long-term datasets
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Conclusions and what next?• These models are a long way off being able
to accurately simulate stable C dynamics
• Current simulations may require extensive site-specific parameterisation before seeing realistic results
• Model development is happening constantly but more focus is needed to relate existing soil fractionation data to model pools
• A standard validation framework is needed
WHATNEXT?
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Thank you for listening Any questions?
Acknowledgements:
Sean CaseSimon OakleyAidan Keith
Marta DondiniPat BartlingSaran Sohi
Rebecca RoweDaffyd Elias
THANKYOU!
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Modelling procedure
• ‘Default’ model simulations were run using only the essential inputs for each model
• All model soil C pools were initialised using data from spin-up simulations of 1000 years
• The UK and US sites were simulated for 20 and 25 years using known management routines and yields were used to check adequate operation
• Modelled vs measured data (total and fractions) were compared using standard metrics
METHOD
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Measuring soil carbon
INTRO
RothCPOM = Decomp + ResistantSMBC = Microbial BiomassMAOC = Inert + Humified
DayCentPOM = Surface C poolsSMBC = Microbial Soil CMAOC = Slow + Passive
RZWQM2POM = Surface C pools
SMBC = Fast Organic MatterMAOC = Intermediate + Slow
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Measuring soil carbon
INTRO
RothCDOC + POM = Decomp +
ResistantSA + S+C = Microbial + Humified
rSOC = Inert
DayCentDOC + POM = Surface poolsSA + S+C = Mic. Soil + Slow
rSOC = Passive
RZWQM2DOC + POM = Surface C pools
SA + S+C = Fast and IntermediaterSOC = Slow
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Fractionation model accuracyRothC -
R2 = 0.97RMSE = 3.44EF = 0.95d ratio = 0.99
RESULTS
0 5 10 15 20 25 30 35 40 450
5
10
15
20
25
30
35
40
45
R² = 0.980828784044326
R² = 0
USA
Measured C (t/ha)
Mod
elle
d C
(t/h
a)
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Measured vs modelled soil C
RESULTS
UK Site -
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Measured vs modelled soil C
RESULTS
USA Site -
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Models = useless???• Models are very rarely accurate when used
without extensive parameterisation
• More and more projects require model simulations to extend findings beyond measurable spatial and temportal scales
WHATNEXT?
Next steps• Resources need allocating to model development
providing better ‘out-of-the-box’ simulations
• Rethink definitions of soil pools and consider a more mechanistic link with other macronutrients
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What about N-mineralisation• Carbon is intrinsically linked to nitrogen but most
models simply tie N to C through fixed C:N ratios
• An assessment of ‘base’ N-min rates for soil types under certain climates may help modify k values
WHATNEXT? (kg/ha)
Grassland Prairie
Wheat-Fallow
Wheat-Corn-Fallow
Wheat-Corn-Millet-Fallow
Measured* 45.7 ± 20.8
53.9 ± 35.2 62.1 ± 42.1 …
RothC - - - -
DayCent 15.1 ± 0.4 20.5 ± 0.5 34.4 ± 0.9 …
RZWQM2 … … … …
* - Estimated from measured soil NO3- and NH4+ data