Sectorial Budgets: Methods, Quantities, Issues - Agriculture

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Sectorial Budgets Methods, Quantities, Issues -
Agriculture
Pete Smith
School of Biological Sciences, University of
Aberdeen, UK
Regional Carbon Budgets from methodologies to
quantification. Beijing, China. 15-18 November
2004
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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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Distribution of croplands globally
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Distribution of croplands in Europe
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Why croplands?

• European croplands (for Europe as far east as the
  Urals) lose 300 Mt C y-1 (Janssens et al., 2003)
• Mean figure for the European Union (EU15)
  estimated to be 78 (SD 37) Mt C y-1
  (Vleeshouwers Verhagen, 2002)
• Largest biospheric source of carbon lost to the
  atmosphere in Europe each year
• Highest uncertainty of all European fluxes
• There is significant potential to decrease the
  flux of carbon to the atmosphere from cropland,
  and for cropland management to sequester soil
  carbon.

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Carbon fluxes in SOC in Europe (t C ha-1 y-1) in
the 1st commitment period (business as usual
scenario)
Using mean soil organic carbon content minus S.D.
Using mean soil organic carbon content
Using mean soil organic carbon content plus S.D.
Vleeshouwers Verhagen (2002)
Croplands
Grasslands
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Croplands in the overall carbon balance of Europe
Cropland flux
Main figure from Janssens et al., Science 2003
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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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Methods - methodologies

• Top-down and bottom up (see Ivans talk)
• Flux network
• SOMNET
• Experiments
• IPCC NGGIs
• Models / databases

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CarboEurope IP Building blocks
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The way CarboEurope works
1000 km
10 km
Upscaling Prediction
ha
dm
µm
Downscaling Verification
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Clusters for Ecosystem measurements
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Courtesy of T. Laurila et al.
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Two years of NEE measurements in the peat
soileddy covariance method
Courtesy of T. Laurila et al.
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CO2 exchange measurements with a transparent
ecosystem chamber
Soil respiration chamber
Courtesy of T. Laurila et al.
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Participants in GCTE SOMNET
Europe

86 Experiments
N. America

20 Models
10 Experiments
7 Models
Asia

10 Experiments
1 Model
S. America

3 Experiments
Africa

Australasia

3 Experiments
8 Experiments
3 Models
Totals 120 Experiments, 31 Models
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Long-term experiments in EuroSOMNET
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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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Methods - data

• Climate
• Historical
• Reconstruction for equilibrium / historical
  spin-up relatively straightforward
• Predictive
• Future scenarios (IPCC-SRES), implementation by
  different GCMs (difference as large between GCMs
  as between scenarios)

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Methods - data

• Land-use
• Historical
• Reconstruction difficult.
• Land use history poorly documented.
• RS data from 1980-1990s only.
• Inconsistency of land-based survey systems.
• Net changes are measured how do these reflect
  gross changes?
• How to spatialise statistical data available at
  region only.
• Predictive
• Future scenarios are driven by socio-economics
• Even for regional budgets a global perspective is
  required (land requirements, trade etc.)
• Need to be consistent with climate scenario
  narratives e.g. IPCC-SRES.
• How to implement? with rule based land
  allocation model, other methods should this be
  done regionally or globally?
• How to allow for institutional constraints and
  autonomous adaptation in land-use management
  decisions?

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Methods - data

• Land-management
• Same arguments as for land-use plus activity data
  (i.e. how the land is managed)
• Even more likely to be statistical /
  non-spatially explicit
• Land use / management history (see above)
• Critical for correct dynamics in current C budget
  and future trends

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Data and models used for assessment of soil C
change

• Biological systems models
• Soil carbon dynamics (RothC)
• C returns from increased productivity (Sundial)
• DGVMs for NPP (LPJ)
• Soil geographic database (EU-JRC Pedotransfer
  function model)
• Climate models Climate drivers
• Emission scenarios (IPCC-SRES-IMAGE 2.0)
• General circulation models (GCMs HadCM3, PCM,
  CSIRO2, CGCM2)
• Regional downscaling models (UEA regional GCM
  interpolator)
• Integrated assessment models emissions and land
  demand
• Biospheric processes (IMAGE 2.0)
• Socio-economic drivers (IMAGE 2.0)
• Energy sector GHG emissions (IMAGE 2.0)
• Land-use change models land use and management
• Yield change model
• Human and Physical geography (UCL LUC model)
• Economic decision making (autonomous adaptation)
  - (UCL LUC model)
• Resource base (IMAGE 2.0 and UCL LUC model)

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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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Methods other issues

• Full GHG budgets
• especially important for agriculture (e.g. N2O
  from soils and CH4 from rice paddies / enteric
  fermentation).
• Lots of trade-offs as well as synergies.
• Also for forestry and energy?
• Interactions between regions
• Interaction between sectors
• e.g. biofuels, agroforestry, grass-crop rotations
  etc.
• Incorporating the human dimension

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Importance of non-CO2 GHGs
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Agricultural non-CO2 GHG emissions in Europe
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C mitigation potential with and without trace
gases
Smith et al. (2001)
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Methods other issues

• Full GHG budgets especially important for
  agriculture (e.g. N2O from soils and CH4 from
  rice paddies / enteric fermentation). Lots of
  trade-offs as well as synergies. Also for
  forestry and energy?
• Interactions between regions
• Interaction between sectors
• e.g. biofuels, agroforestry, grass-crop rotations
  etc.
• Incorporating the human dimension

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Outline

• Why croplands?
• Methods
• Methodologies
• Data
• Other issues
• Results and trends

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RothC
co
2
RESIDUE
soil surface
DPM
RPM
BIO
HUM
IOM
-1
-1
-1
k10 y
k0.3 y
k0.66 y
k
-1
0.02 y
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Results

• Climate only

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Climate-only impact on SOC
(effect of different GCMs)
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Climate-only impact on SOC
(effect of different climate scenarios)
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Change in cropland SOC climate only
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Climate data 2080-1990 temperature
Note 2080 and 1990 are 30 year averages of
2051-2080 and 1961-1990 respectively
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Climate data 2080-1990 water balance
Note 2080 and 1990 are 30 year averages of
2051-2080 and 1961-1990 respectively
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What will happen to cropland soil C fluxes in
21st Century?
A1FI
A2
p lt 0.01
p lt 0.01
B1
B2
p lt 0.05
n.s.
Climate only
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Results

• Adding NPP technology

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Comparing climate-only with climate NPP
technology (HadCM3-A2)
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Change in cropland SOC climate only.
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Change in cropland SOC climate, NPP tech.
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Results

• Adding the effects of land-use change

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Effect of changing land-use
Cropland
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Conclusions

• Need a full GHG balance not just carbon
• Need to fully account for human dimension (e.g.
  land manager decisions) via
• Land use
• Land management
• Political, economic, social and institutional
  constraints
• Data is an issue, especially
• Regional differences in predicted climate
• Future land-use change
• Historical land use survey inconsistencies,
  lack of RS before 1980s
• Net rather than gross land-use changes
• Spatialisation of non-spatial data