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Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
CarboZALF - the carbon dynamics of arable landscapes in North-East Germany
Jürgen Augustin
Olomouc October 21th 2010
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
atmospheric CO2
ocean
land
fossil fuel emissions
deforestation
7.7
1.4
4.13.0
2000-2008PgC
CO2 f
lux
(PgC
y-1)
Sink
Sour
ce
Time (y) 0.3 Residual
2.3
Global Carbon Project 2009; Le Quéré et al. 2009, Nature Geoscience
Role of terrestrial biosphere in the anthropogenic carbon cycle is unclear (reduced sink efficiency?)
0.4 - 4.7 PgC
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Erosion – mean reason for uncertainties?
SINK SOURCE
NEUTRAL+1.5 Pg/yr -1.5 Pg/yr
0
→ Lal, 2004→ Stallard, 1998→ Jacinthe, 2001→ Berhe, 2007→ Smith, 2001→ Van Oost, 2007→ Ito, 2007
(Van Ost 2009)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Particularly unclear: Significance of agricultural landscapes for C sequestration and climate impact
• Influence of land management on soil and carbon dynamics (controversial discussion, e.g. in case of energy crop cultivation)?
Creation of the project „CarboZALF“
Photo: R.J. Michel
Transfer: DOC, DIC, SOCsolid
CO2 exchange
Sink?CO2 exchange
Source?
CO2 exchange
steady state
• Significance of agricultural landscape elements and/or landscape pattern on soil and carbon dynamics
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
CarboZALF – target results
• Multi-scale and multidisciplinary approach for the investigation of the C dynamics (process analysis + modeling)
• Procedure for the assessment of land use and climate change impact at the complete landscape C dynamics
Methodical
• Effect of current land use systems, sites, and climate at the exchange of greenhouse gases and the C sequestration in agricultural landscapes
• Landscape use systems with reduced climate impact und long-term preservation of the C sequestration potential
Answers
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Approach: Coupling of process analysis and the development of multi-scale models
Development of landscape based indicators (structure-process coupled), inclusively of lateral processes
model
Quantification of C balance elements on site scalemodel +
experiment,site
Clearing up processes (mechanism) on micro scale experiment,lab
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
First step: Establishing of a multidisciplinary field experiment as a „seed crystal“ (CarboZALF-D)
ObjectiveClearing up the influence of the energy crop cultivation and erosion on soil functions, greenhouse gas exchange, C dynamics, and the climate impact of the north-east German glacial landscape
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
experimental site
• Site selection based on landscape reference and process relevance (Uckermark - north-east German glacial landscape: hummocky moraines, peaty lowlands)
• All relevant C fluxes are included (gaseous, solid, liquid)
• Manipulation experiments for the erosion
• Long term field trial (> 10a)
What is new at CarboZALF-D?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Crop rotationRotation 1winter rye/silage maize (monoculture)Rotation 2winter rye/silage maize– winter rye/food millet– winter triticale/perennial ryegrass
Fertilization only mineral fertilizer50 % mineral fertilizer and 50 % biogas slurry (related to N)100 % biogas slurry (related to N)
Soilsorthic luvisoleroded orthic luvisol eroded orthic luvisol, manipulated calcaric regosol colluviumcolluvium, manipulated
Experimental design and test factors
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Work packages
• Long term measurements of soil parameter and erosion
• Long term measurements gas fluxes and global warming potential (Net CO2, N2O, CH4)
• Crop production aspects of C dynamics
• Development/test of a C dynamics model of agricultural sites
• Characterization of soil organic matter fractions
• Influence of soil microbiological activities on C turnover
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
C balance approach (C gas fluxes, C export/import)
Slurry Harv
SOCpin SOCpout
DOC/DICin
DOC/DICout
∆ SOC = NEE + (slurry – harvest) + (SOCpin – SOCpout) + (DOCin + DICin) – (DOCout + DICout)
GPP Reco
NEE (Net CO2 exchange) = GPP - Reco
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Greenhouse gas exchange and global warming potential: chamber measurements
Manual chambers Big automated chambers: 2.5 m
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Monitoring of water and matter dynamics in soils
Soil water potential
Soil moisture (FDR)
leachate (suction cups):DOC, DIC, others
Eh potentials
CarboZALF-D installations
9
1011
12
1314 15
7
65
43
2
1
Manual chambers
Automated chambers
Erosion manipulation
plots
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Chamber test I: Maize 08.14.2008
20
22
24
26
28
30
32
34
36
38
40
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
0C
min after closing
Temp 40 cm outsideTemp 40 cm insideTemp 200 cm insideELU mV
0
5
10
15
20
25
30
35
40
45
50
0
50
100
150
200
250
300
350
400
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49
H2O
pp
t
CO 2p
pm
min after closing
CO2_Licor_M ppm
ELU mV
H2O_Li ppt
H2O and CO2 concentration after closing
Air temperature inside and outside after closing
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
0
50
100
150
200
250
300
350
400
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
pp
m C
O2
min after closing
CO2_Licor_M ppm
CO2_Licor_U ppm
CO2_Licor_D ppm
ELU mV
0
50
100
150
200
250
300
350
400
1 2 3 4 5 6 7 8 9 10111213141516171819202122232425262728293031323334353637383940414243444546474849
pp
m C
O2
min after closing
CO2_Licor_M ppm
CO2_Licor_U ppm
CO2_Licor_D ppm
ELU mV
Chamber test II: Maize 08.14.2008
Vetilators turned off
Ventilators switched on
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Chamber performance I: influence of herbicide application on NEE
Maize, June 11th 2009
- 50 till -40 ppm
-5 till +5 ppm
Herbicide application
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Chamber performance II: CO2 uptake influneced by crop and time
Maize 09.02.2009
max. -150 ppm
Winter rye 10.30.2009
max. -10 ppm
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
> 95% of German peatlands
drained/rewetted
Succow 1988
Up to 5000 t C and 120 t N per ha
Stronly increased net climate impact (N2O, net CO2)
Very uncertain estimates
Already integrated: GHG exchange and C dynamics of fen peatlands (minerotrophic mires)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Changed situation Fen restoration
(rewetting and reflooding)
UnclearIs a strong reduction of net climate impact (net
CO2 sink, weak CH4 source) feasible
again?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Approach: Long term gas flux measurements by enclosure and eddy technique (net CO2, CH4, N2O)
Cropland + grassland
Alder swamp forest Rewetted + flooded fen grassland
Willow swamp forest
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
What is the effect of fen rewetting on trace gas exchange and global warming potential?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Zarnekow – a former fen grassland in the Peene river valley
geoportal-mv.de
A8.2NEU Advisory Group
Stakeholders
WP 8NEU Management
Coordinator
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
A10.4ESF N Assessment &
UNEP - INIErisman, ECN, NL
A10.3 COST Atmos-Biosphere& multiple N strategies
Domburg, NL
A10.5Input to EC,
FCCC & CLRTAPSeufert, JRC, I.
A10.2IGBP - iLEAPS
Nemitz, UK / Vesala FI
Figure 3. NitroEurope IP: Science and management structure
A8.4General AssemblyAll NEU Partners
A8.5Review & Assessment
SSC +AG
A8.3Financial
ManagementCoordinator + partners
A10.1 Innovation Highlights
& NEU PortalCEH, Sutton, UK
A8.1Science Management
Scientific Steering Committee
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 10 NEU Dissemination
IP Secretariat
WP 7NEU Standards and Data Management
IP Secretariat
A9.1Summer Schools
Zechmeister, A/ Rees, UK
A7.3NEU Data Centres & TF Data ManagementBADC, de Rudder, UK
A.7.1 TF Common
measurement protocolsBeier, DK
A7.2TF Common
modelling protocolsde Vries, NL
WP 9NEU Training
IP Secretariat
A9.2Executive Training
Erisman/Domburg NL
RTD & Innovation Activities
Work Package Activity
Training Activities
Management Activities
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
A8.2NEU Advisory Group
Stakeholders
WP 8NEU Management
Coordinator
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
A10.4ESF N Assessment &
UNEP - INIErisman, ECN, NL
A10.3 COST Atmos-Biosphere& multiple N strategies
Domburg, NL
A10.5Input to EC,
FCCC & CLRTAPSeufert, JRC, I.
A10.2IGBP - iLEAPS
Nemitz, UK / Vesala FI
Figure 3. NitroEurope IP: Science and management structure
A8.4General AssemblyAll NEU Partners
A8.5Review & Assessment
SSC +AG
A8.3Financial
ManagementCoordinator + partners
A10.1 Innovation Highlights
& NEU PortalCEH, Sutton, UK
A8.1Science Management
Scientific Steering Committee
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 10 NEU Dissemination
IP Secretariat
WP 7NEU Standards and Data Management
IP Secretariat
A9.1Summer Schools
Zechmeister, A/ Rees, UK
A7.3NEU Data Centres & TF Data ManagementBADC, de Rudder, UK
A.7.1 TF Common
measurement protocolsBeier, DK
A7.2TF Common
modelling protocolsde Vries, NL
WP 9NEU Training
IP Secretariat
A9.2Executive Training
Erisman/Domburg NL
RTD & Innovation Activities
Work Package Activity
Training Activities
Management Activities
Work Package Activity
Training Activities
Management Activities
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Control (flooded in winter) Control (drained from spring till autumn)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Reflooded (06/2006)Reflooded (11/2005)Reflooded (7/2005)Reflooded (04/2005)Reflooded in future (2004)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
07/201009/200902/200810/2007
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Surprise: Much more CH4 than expected!
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Methane emission 2005-2008: weak reduction on the reflooded site
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
20.01.
19.04.
06.06.
13.07.
22.08.
26.10.
09.04.
15.05.
19.06.
24.07.
28.08.
01.10.
06.11.
18.12.
12.03.
22.04.
29.05.
02.07.
06.08.
10.09.
15.10.
19.11.
27.12.
21.01.
28.02.
31.03.
05.05.
16.06.
18.08.
20.10.
30.12.
04.05.
13.07.
24.09.
23.11.
Date
µg
CH
4-C
m-2
h-1
fluctuating wt flooded
2005 2006 2007 2008 2009
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
20.01.19.04.06.06.13.07.22.08.26.10.
09.04.15.05.19.06.24.07.28.08.01.10.06.11.18.12.12.03.22.04.29.05.02.07.06.08.10.09.15.10.19.11.27.12.21.01.28.02.31.03.05.05.16.06.18.08.20.10.30.12.04.05.13.07.24.09.23.11.
Date
µg C
H4-C
m-2
h-1
fluctuating wt flooded
2005 2006 2007 2008 2009
Methane emission 2005-2009: No reduction on the reflooded site!
temporarily dry
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
05/200706/200809/2009
-600
-500
-400
-300
-200
-100
0
100
2005 2006 2007 2008 2009
CO
2-C
(g
m-2
a-1
)
Net CO2 exchange after flooding: sink function is suspended
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
GWP-J ahresbilanzen
938
2861
13671242
3389
11 55256
462
20
500
1000
1500
2000
2500
3000
3500
4000
2005 2006 2007 2008 2009
GW
P1
00
CO 2
-C e
qu
. (g
m-2
a-1
)
Z-flood Z-wet
GHG balance: flooded site is much worse than control site to this day
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Arising discussion: Does flooding make sense at all?
Is increased methane emission after reflooding like a snapshot!
Short-term measurements of only a site do not permit any generalization capable statements, especially about long term effects!
Is the global warming potential permanently more negative than on the site with fluctuating water table?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
litter of reed canary grass?
Which substrate is responsible for the methane formation?
old peat +/- roots?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Gas exchange measurements from substrate colums in lab incubation studies*
*together with M. Hahn-Schöfl, A. Freibauer, D. Zak, M. Minke
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Main CO2 and CH4 source: reed canary grass litter (OM)
OM = Organic mud (Reed canary grass litter)
WT = old peat + rootsAT = old peat
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Flooding of degraded and eutrophic fens: temporarily increase of climate impact
Intermediate conclusion
How can I avoid increased climate impact after restoration?- Water table only up to the peat surface- Promotion of helophyte development
Reason: permanent high CH4 emission, caused by flooding in combination with a high C pool of easily decomposable plant litter
The spreading of helophytes might cause a diminution of the climate impact in the long-term (net CO2 uptake, reduced CH4 emissions as a result of the shunt effect)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
In many cases restoration of drained peatlands is limited by water shortage and socio-economic reasons
Problem
QuestionCan a reduction of the climate impact be reached also with an adapted land use?
Rhin-Havelluch - a drained fen area with different land use variants near Berlin
TG 3
Field research station Paulinenaue
A8.2NEU Advisory Group
Stakeholders
WP 8NEU Management
Coordinator
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
A10.4ESF N Assessment &
UNEP - INIErisman, ECN, NL
A10.3 COST Atmos-Biosphere& multiple N strategies
Domburg, NL
A10.5Input to EC,
FCCC & CLRTAPSeufert, JRC, I.
A10.2IGBP - iLEAPS
Nemitz, UK / Vesala FI
Figure 3. NitroEurope IP: Science and management structure
A8.4General AssemblyAll NEU Partners
A8.5Review & Assessment
SSC +AG
A8.3Financial
ManagementCoordinator + partners
A10.1 Innovation Highlights
& NEU PortalCEH, Sutton, UK
A8.1Science Management
Scientific Steering Committee
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 10 NEU Dissemination
IP Secretariat
WP 7NEU Standards and Data Management
IP Secretariat
A9.1Summer Schools
Zechmeister, A/ Rees, UK
A7.3NEU Data Centres & TF Data ManagementBADC, de Rudder, UK
A.7.1 TF Common
measurement protocolsBeier, DK
A7.2TF Common
modelling protocolsde Vries, NL
WP 9NEU Training
IP Secretariat
A9.2Executive Training
Erisman/Domburg NL
RTD & Innovation Activities
Work Package Activity
Training Activities
Management Activities
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
A8.2NEU Advisory Group
Stakeholders
WP 8NEU Management
Coordinator
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 1 NEU
Flux NetworkSutton, UK
A1.3 NEU Advanced Network:Fluxes, pools & budgets
Campbell, UK
A1.1 Advanced N flux
measurement methods Nemitz, UK
A1.2 Long-term N flux
methods & applicationPilegaard, DK
A.1.4 Plant & soil pools,
processes & interactionsCotrufo, I
A.1.5 Inferential N fluxes and C interactions
Sutton, UK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
WP 2 NEU Ecosystem
ManipulationBeier, DK
A2.1 Forest change
(inc. afforestation)Gundersen, DK
A2.2 Shrubland change
(& natural wetlands)Beier, DK
A2.4 Arable change
(inc. drainage effects)Rees, UK
A2.3 Grassland change
(inc grazing interactions)Soussana, FR
A2.5 Manipulation Synthesis
Beier, DK
A10.4ESF N Assessment &
UNEP - INIErisman, ECN, NL
A10.3 COST Atmos-Biosphere& multiple N strategies
Domburg, NL
A10.5Input to EC,
FCCC & CLRTAPSeufert, JRC, I.
A10.2IGBP - iLEAPS
Nemitz, UK / Vesala FI
Figure 3. NitroEurope IP: Science and management structure
A8.4General AssemblyAll NEU Partners
A8.5Review & Assessment
SSC +AG
A8.3Financial
ManagementCoordinator + partners
A10.1 Innovation Highlights
& NEU PortalCEH, Sutton, UK
A8.1Science Management
Scientific Steering Committee
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 5 NEU European
Integrationde Vries, NL
A5.1 GIS-based assembly
of input dataSeufert, JRC, I
A5.2 Deriving past, present
& future scenariosObersteiner, IIASA, A
A5.3 Developmt. of integratedmulti-component model
de Vries, NL
A5.4 Application of European-scale ecosystem models
P. Smith, UK
A5.5 Application of the multi-
component modelKros, NL
WP 10 NEU Dissemination
IP Secretariat
WP 7NEU Standards and Data Management
IP Secretariat
A9.1Summer Schools
Zechmeister, A/ Rees, UK
A7.3NEU Data Centres & TF Data ManagementBADC, de Rudder, UK
A.7.1 TF Common
measurement protocolsBeier, DK
A7.2TF Common
modelling protocolsde Vries, NL
WP 9NEU Training
IP Secretariat
A9.2Executive Training
Erisman/Domburg NL
RTD & Innovation Activities
Work Package Activity
Training Activities
Management Activities
Work Package Activity
Training Activities
Management Activities
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 3 NEU Plot Scale
ModellingButterbach-Bahl, D
A3.1 Assessment of models & uncertainty analysis
van Oijen, UK
A3.2 Development of
core modelsButterbach-Bahl, D
A3.3 Interpretn. & simulation
of flux measurementsCalanca, CH
A3.4 Effect of past & present management decisions & adaptation strategies
P. Smith, UK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 4NEU Landscape
AnalysisCellier, FR
A4.1 Landscape Inventories
Cellier, FR
A4.3Landscape validation
measurementsTheobald, UK
A4.2Development & applic’n
of landscape modelCellier, FR
A4.4Whole-farm and
landscape decisionsOlesen, DK
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
WP 6 NEU Verification
Erisman, NL
A6.1 Verification & uncertnty:bottom-up NEU models
van Oijen, UK
A6.4 Improvement of IPCC methods & inventories
van Amstel, NL
A6.3 Verification of official UNFCCC inventories
Erisman, NL
A6.2 Independent inverse-
modelling of European N2O & CH4 emissions
Bergamaschi, JRC, I
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
Experimental Variants
• Meadow extensive (1 cut)
• Meadow middle (reed canary grass, 3 cuts)
• Pasture (extensive, middle, intensive, partly simulated)
• cattle tracks
• cropland (maize?)
(the same spectrum parallel on histosols with lower C content)
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
„Drained“ fen site 2007: flooded, flooded, flooded…
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
2008 – strongly swaying groundwater table
September
January
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
Annual CH4-C fluxes: influenced very strongly by the groundwater
Threshold
Mean groundwater table (cm)
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
Annual net CO2-C losses: In the dry year 2008 much higher than in the wet year 2007
0
200
400
600
800
1000
1200
1400
g CO
2-C m
-2 a
-1
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
Pasture extens 2007
Pasture mid 2007
Meadow mid 2007
Pasture intens 2007
Meadow extens 2007Meadow mid 2008
Pasture mid 2008
Pasture extens 2008
Meadow extens 2008
Maize 2008
Pasture intens 2008
0
200
400
600
800
1000
1200
1400
1600
1800
2000
-70 -60 -50 -40 -30 -20 -10 0 10 20
mean groundwater table (cm below floor)
g C
O2-C
-Äqu
ival
m-2
a -1
CH4 dominatesN2O and CO2 dominate
N2O contri. 26-44%
GHG balances are influenced by ground water level, weather and land use at the same time
Meadow extens 2007
Pasture intens 2007
Meadow mid 2007
Pasture mid 2007
Pasture extens 2007
0
200
400
600
800
1000
1200
1400
1600
1800
2000
-70 -60 -50 -40 -30 -20 -10 0 10 20
mean groundwater table (cm below floor)
g C
O2-C
-Äqu
ival
m-2
a -1
CH4 dominates
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
-3000
-2000
-1000
0
1000
2000
3000
extensive meadow middle meadow (reed canary grass)
g C
O2-C
m-2
a-1
Ecosystem respiration (Reco) Gross primary production (GPP)CO2 balance (NEE) CO2 balance + C export
Reed canary grass has lower CO2 losses (more favourable climate impact) than extensive meadow: higher GPP at the same Reco
Leibniz-Zentrum für Agrarlandschaftsforschung (ZALF) e. V.
Negative climate impact (and heavy C losses) can be caused by quite different factor constellations
Gas exchange, GHG and C balance are influenced by groundwater table, land use, and weather simultaneously
Adapted land use (reed canary grass cultivation) could contribute to the reduction of the climate impact. However, this presupposes further check and well-considered procedure.
This drained fen site shows very high climate impact (and strong C losses)
Intermediate conclusion
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Summary fen peatlands
Gas fluxes and GWP are influenced by ground-water level, land use, and weather at the same time
A reduction of the climate effect seems possible; however, requires sound knowledge
How can this be guaranteed?
Expanding of sites, long-term flux measurements, Upscaling model studies for understanding and controlling
reflooding process
Drained and newly reflooded fens can be strong sources for greenhouse gases
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Photo: M. Sommer
Next step: Clearing up the role of small waters for the carbon dynamics of agricultural landscapes (“CarboAqua”)
Hot spots of C/N dynamics and gas fluxes in agricultural landscapes?
?
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Outlook: from “CarboZALF” to “Carbo-Landscape”
• Separation and dynamics of the assimilate fluxes in the plant soil system
(isotope studies)
• Modeling of the interactions between a lateral matter transfer and soil C
dynamics (different scales, erosion specialists etc.)
• Including other landscape compartments: grassland, forest)
• Development of a landscape and regional model (+ urban rural relations)
• General: fund raising, integration into research networks
Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V.
Thank you for attention!
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