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

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

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

Modelling soil carbon• Model structures range from simple empirical

functions to complex mechanistic relationships

INTRO

Modelling soil carbon• RothC - monthly timestep soil-only model

Decomposition rates influenced by:

INTRO

• Temperature• Moisture• Clay content

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

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

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

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

Measuring soil carbon

INTRO

RothCPOM = Decomp + Resistant

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

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

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

Total soil carbon comparison

RESULTS

UK Site - total soil stock

RESULTS

USA Site – total soil carbon

Total soil carbon comparison

Stable fraction vs stable pool(s)

RESULTS

UK Site -

Total soil carbon comparison

RESULTS

USA Site -

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

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?

Thank you for listening Any questions?

Acknowledgements:

Sean CaseSimon OakleyAidan Keith

Marta DondiniPat BartlingSaran Sohi

Rebecca RoweDaffyd Elias

THANKYOU!

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

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

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

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)

Measured vs modelled soil C

RESULTS

UK Site -

Measured vs modelled soil C

RESULTS

USA Site -

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

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