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The impact of droughts on interannual variability in
terrestrial carbon-13 discrimination
Erik van Schaik
Wageningen University and Research
W. Peters, I. R. van der Velde, M. K. van der Molen, J. B. Miller, P. P. Tans, B.
Vaughn, J. C. White, K. Schaefer
Model estimations of carbon fluxes during the European drought
of 2003
2
TRENDY data from
Sitch et al., 2008
Water – Vegetation coupling
3
Vapour Pressure
Stomatal conductance
Drought
Soil moisture
Mesophyllic conductanceBiochemical capacity
Observed Water Use Efficiency (WUE)
4
y = -0.4491x + 12.221
R
2
= 0.8975
2
3
4
5
16 17 18 19 20 21 22 23
Carbon isotope discrimination (‰)
WUE(gKg-1
)
77
90
88
91
77
9190
85
108
85
88 108
(d)
Dry
Wet
Anyia et al. (2007)
Variations in iWUE at the largest scale from δ¹³C
5
’wet’
’dry’
Van der Velde (2015)
SiBCASA + CO2
+ 13CO2
Variations in iWUE at the largest scale from δ¹³C
6
SiBCASA
SiBCASA + CO2
+ 13CO2
’wet’
’dry’
Van der Velde (2015)
Water – Vegetation coupling
7
Vapour Pressure
Stomatal conductance
gs
Drought
Included
Not included
Soil moisture
Mesophyllic conductance
gm
Biochemical capacity
Vmax, Jmax
SiBCASA
Sellers et al., 1996
Baker et al., 2008
Water – Vegetation coupling
8
Vapour Pressure
Stomatal conductance
Drought
Included
Not included
Soil moisture
Mesophyllic conductanceBiochemical capacity
CLM / JULES
ORCHIDEE
VISIT
Oleson et al., 2010
Anav et al., 2015
Krinner et al., 2005
Ito and Oikawa, 2002
Stomatal conductance
gs
Mesophyllic conductance
gm
Biochemical capacity
Vmax, Jmax
Moisture stress enhances WUE
SiBCASA (and many other
models) do not capture
this response in iWUE.
9
4
3
2
1
0
Dry <- Soil moisture stress [-] -> Wet
0 0.2 0.4 0.6 0.8 1.0
Egea et al. (2011)
Observed
Dry <- Soil moisture stress [-] -> Wet
SiBCASA
RelativeiWUE
Soil moisture
Stomatal
conductance
gs
Biochemical
capacity
Vmax, Jmax
Mesophyllic
conductance
gm
3
2
1
0
0 0.2 0.4 0.6 0.8 1.0
Moisture stress enhances WUE
Soil moisture needs to
be explicitly coupled to
all three processes
10
4
3
2
1
0
Dry <- Soil moisture stress [-] -> Wet
0 0.2 0.4 0.6 0.8 1.0
Egea et al. (2011)
Observed
Dry <- Soil moisture stress [-] -> Wet
SiBCASASiBCASAEgea
RelativeiWUE
Soil moisture
Stomatal
conductance
gs
Mesophyllic
conductance
gm
Biochemical
capacity
Vmax, Jmax
3
2
1
0
0 0.2 0.4 0.6 0.8 1.0
SiBCASA
WUE – Discrimination for Europe (2000-2011)
11
2003
2003
Discrimination during 2003 drought in Europe
12
Months May-June-July
Δ anomaly : -0.21 ‰
NEE anomaly: 0.03 TgC
Discrimination during 2003 drought in Europe
13
Months May-June-July
Δ anomaly : -0.21 ‰ Δ anomaly : -1.04 ‰
NEE anomaly: 0.03 TgC NEE anomaly: -0.06 TgC
Discrimination during 2003 drought in Europe
14
Months May-June-July
Δ anomaly : -0.21 ‰ Δ anomaly : -0.94 ‰ Δ anomaly : -1.04 ‰
NEE anomaly: 0.03 TgC NEE anomaly: -0.24 TgC NEE anomaly: -0.06 TgC
Summary
Measurements of atmospheric δ13C can provide unique insight
in plant functioning on regional to continental scales
Many biosphere models are not able to simulate changes in
iWUE under water-stressed conditions.
iWUE can be a valuable metric to assess the performance of
biosphere models.
15
References
Anav, Alessandro, Pierre Friedlingstein, Christian Beer, Philippe Ciais, Anna Harper, Chris Jones, Guillermo Murray-Tortarolo, et al. 2015.
“Spatiotemporal Patterns of Terrestrial Gross Primary Production: A Review: GPP Spatiotemporal Patterns.” Reviews of Geophysics 53 (3):
785–818. doi:10.1002/2015RG000483.
Anyia, A. O., J. J Slaski, J. M. Nyachiro, D. J. Archambault, and P. Juskiw. 2007. “Relationship of Carbon Isotope Discrimination to Water
Use Efficiency and Productivity of Barley Under Field and Greenhouse Conditions.” Journal of Agronomy and Crop Science 193 (5): 313–23.
doi:10.1111/j.1439-037X.2007.00274.x.
Baker, I. T., L. Prihodko, A. S. Denning, M. Goulden, S. Miller, and H. R. da Rocha. 2008. “Seasonal Drought Stress in the Amazon:
Reconciling Models and Observations.” Journal of Geophysical Research 113 (July). doi:10.1029/2007JG000644.
Egea, Gregorio, Anne Verhoef, and Pier Luigi Vidale. 2011. “Towards an Improved and More Flexible Representation of Water Stress in
Coupled Photosynthesis–stomatal Conductance Models.” Agricultural and Forest Meteorology 151 (10): 1370–84.
doi:10.1016/j.agrformet.2011.05.019.
Ito, Akihiko, and Takehisa Oikawa. 2002. “A Simulation Model of the Carbon Cycle in Land Ecosystems (Sim-CYCLE): A Description Based
on Dry-Matter Production Theory and Plot-Scale Validation.” Ecological Modelling 151 (2-3): 143–76. doi:10.1016/S0304-3800(01)00473-
2.
Krinner, G., Nicolas Viovy, Nathalie de Noblet-Ducoudré, Jérôme Ogée, Jan Polcher, Pierre Friedlingstein, Philippe Ciais, Stephen Sitch, and
I. Colin Prentice. 2005. “A Dynamic Global Vegetation Model for Studies of the Coupled Atmosphere-Biosphere System: DVGM FOR
COUPLED CLIMATE STUDIES.” Global Biogeochemical Cycles 19 (1). doi:10.1029/2003GB002199.
Oleson, Keith, David Lawrence, Gordon Bonan, Mark Flanner, Erik Kluzek, Peter Lawrence, Samuel Levis, et al. 2010. “Technical
Description of Version 4.0 of the Community Land Model (CLM).” doi:10.5065/D6FB50WZ.
Sellers, P.J., D.A. Randall, G.J. Collatz, J.A. Berry, C.B. Field, D.A. Dazlich, C. Zhang, G.D. Collelo, and L. Bounoua. 1996. “A Revised Land
Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation.” Journal of Climate 9 (4): 676–705. doi:10.1175/1520-
0442(1996)009<0676:ARLSPF>2.0.CO;2.
Sitch, S., C. Huntingford, N. Gedney, P. E. Levy, M. Lomas, S. L. Piao, R. Betts, et al. 2008. “Evaluation of the Terrestrial Carbon Cycle,
Future Plant Geography and Climate-Carbon Cycle Feedbacks Using Five Dynamic Global Vegetation Models (DGVMs).” Global Change
Biology 14 (9): 2015–39. doi:10.1111/j.1365-2486.2008.01626.x.
van der Molen, M. K., R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, et al. 2015. “The Effect of
Assimilating Satellite Derived Soil Moisture in SiBCASA on Simulated Carbon Fluxes in Boreal Eurasia.” Hydrology and Earth System
Sciences Discussions 12 (9): 9003–54. doi:10.5194/hessd-12-9003-2015.
van der Velde, I. R. 2015. Studying Biosphere-Atmosphere Exchange of CO2 through Carbon-13 Stable Isotopes. Wageningen:
Wageningen University.
16

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The impact of droughts on interannualvariability in terrestrial carbon-13 discrimination

  • 1. The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University and Research W. Peters, I. R. van der Velde, M. K. van der Molen, J. B. Miller, P. P. Tans, B. Vaughn, J. C. White, K. Schaefer
  • 2. Model estimations of carbon fluxes during the European drought of 2003 2 TRENDY data from Sitch et al., 2008
  • 3. Water – Vegetation coupling 3 Vapour Pressure Stomatal conductance Drought Soil moisture Mesophyllic conductanceBiochemical capacity
  • 4. Observed Water Use Efficiency (WUE) 4 y = -0.4491x + 12.221 R 2 = 0.8975 2 3 4 5 16 17 18 19 20 21 22 23 Carbon isotope discrimination (‰) WUE(gKg-1 ) 77 90 88 91 77 9190 85 108 85 88 108 (d) Dry Wet Anyia et al. (2007)
  • 5. Variations in iWUE at the largest scale from δ¹³C 5 ’wet’ ’dry’ Van der Velde (2015) SiBCASA + CO2 + 13CO2
  • 6. Variations in iWUE at the largest scale from δ¹³C 6 SiBCASA SiBCASA + CO2 + 13CO2 ’wet’ ’dry’ Van der Velde (2015)
  • 7. Water – Vegetation coupling 7 Vapour Pressure Stomatal conductance gs Drought Included Not included Soil moisture Mesophyllic conductance gm Biochemical capacity Vmax, Jmax SiBCASA Sellers et al., 1996 Baker et al., 2008
  • 8. Water – Vegetation coupling 8 Vapour Pressure Stomatal conductance Drought Included Not included Soil moisture Mesophyllic conductanceBiochemical capacity CLM / JULES ORCHIDEE VISIT Oleson et al., 2010 Anav et al., 2015 Krinner et al., 2005 Ito and Oikawa, 2002 Stomatal conductance gs Mesophyllic conductance gm Biochemical capacity Vmax, Jmax
  • 9. Moisture stress enhances WUE SiBCASA (and many other models) do not capture this response in iWUE. 9 4 3 2 1 0 Dry <- Soil moisture stress [-] -> Wet 0 0.2 0.4 0.6 0.8 1.0 Egea et al. (2011) Observed Dry <- Soil moisture stress [-] -> Wet SiBCASA RelativeiWUE Soil moisture Stomatal conductance gs Biochemical capacity Vmax, Jmax Mesophyllic conductance gm 3 2 1 0 0 0.2 0.4 0.6 0.8 1.0
  • 10. Moisture stress enhances WUE Soil moisture needs to be explicitly coupled to all three processes 10 4 3 2 1 0 Dry <- Soil moisture stress [-] -> Wet 0 0.2 0.4 0.6 0.8 1.0 Egea et al. (2011) Observed Dry <- Soil moisture stress [-] -> Wet SiBCASASiBCASAEgea RelativeiWUE Soil moisture Stomatal conductance gs Mesophyllic conductance gm Biochemical capacity Vmax, Jmax 3 2 1 0 0 0.2 0.4 0.6 0.8 1.0 SiBCASA
  • 11. WUE – Discrimination for Europe (2000-2011) 11 2003 2003
  • 12. Discrimination during 2003 drought in Europe 12 Months May-June-July Δ anomaly : -0.21 ‰ NEE anomaly: 0.03 TgC
  • 13. Discrimination during 2003 drought in Europe 13 Months May-June-July Δ anomaly : -0.21 ‰ Δ anomaly : -1.04 ‰ NEE anomaly: 0.03 TgC NEE anomaly: -0.06 TgC
  • 14. Discrimination during 2003 drought in Europe 14 Months May-June-July Δ anomaly : -0.21 ‰ Δ anomaly : -0.94 ‰ Δ anomaly : -1.04 ‰ NEE anomaly: 0.03 TgC NEE anomaly: -0.24 TgC NEE anomaly: -0.06 TgC
  • 15. Summary Measurements of atmospheric δ13C can provide unique insight in plant functioning on regional to continental scales Many biosphere models are not able to simulate changes in iWUE under water-stressed conditions. iWUE can be a valuable metric to assess the performance of biosphere models. 15
  • 16. References Anav, Alessandro, Pierre Friedlingstein, Christian Beer, Philippe Ciais, Anna Harper, Chris Jones, Guillermo Murray-Tortarolo, et al. 2015. “Spatiotemporal Patterns of Terrestrial Gross Primary Production: A Review: GPP Spatiotemporal Patterns.” Reviews of Geophysics 53 (3): 785–818. doi:10.1002/2015RG000483. Anyia, A. O., J. J Slaski, J. M. Nyachiro, D. J. Archambault, and P. Juskiw. 2007. “Relationship of Carbon Isotope Discrimination to Water Use Efficiency and Productivity of Barley Under Field and Greenhouse Conditions.” Journal of Agronomy and Crop Science 193 (5): 313–23. doi:10.1111/j.1439-037X.2007.00274.x. Baker, I. T., L. Prihodko, A. S. Denning, M. Goulden, S. Miller, and H. R. da Rocha. 2008. “Seasonal Drought Stress in the Amazon: Reconciling Models and Observations.” Journal of Geophysical Research 113 (July). doi:10.1029/2007JG000644. Egea, Gregorio, Anne Verhoef, and Pier Luigi Vidale. 2011. “Towards an Improved and More Flexible Representation of Water Stress in Coupled Photosynthesis–stomatal Conductance Models.” Agricultural and Forest Meteorology 151 (10): 1370–84. doi:10.1016/j.agrformet.2011.05.019. Ito, Akihiko, and Takehisa Oikawa. 2002. “A Simulation Model of the Carbon Cycle in Land Ecosystems (Sim-CYCLE): A Description Based on Dry-Matter Production Theory and Plot-Scale Validation.” Ecological Modelling 151 (2-3): 143–76. doi:10.1016/S0304-3800(01)00473- 2. Krinner, G., Nicolas Viovy, Nathalie de Noblet-Ducoudré, Jérôme Ogée, Jan Polcher, Pierre Friedlingstein, Philippe Ciais, Stephen Sitch, and I. Colin Prentice. 2005. “A Dynamic Global Vegetation Model for Studies of the Coupled Atmosphere-Biosphere System: DVGM FOR COUPLED CLIMATE STUDIES.” Global Biogeochemical Cycles 19 (1). doi:10.1029/2003GB002199. Oleson, Keith, David Lawrence, Gordon Bonan, Mark Flanner, Erik Kluzek, Peter Lawrence, Samuel Levis, et al. 2010. “Technical Description of Version 4.0 of the Community Land Model (CLM).” doi:10.5065/D6FB50WZ. Sellers, P.J., D.A. Randall, G.J. Collatz, J.A. Berry, C.B. Field, D.A. Dazlich, C. Zhang, G.D. Collelo, and L. Bounoua. 1996. “A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation.” Journal of Climate 9 (4): 676–705. doi:10.1175/1520- 0442(1996)009<0676:ARLSPF>2.0.CO;2. Sitch, S., C. Huntingford, N. Gedney, P. E. Levy, M. Lomas, S. L. Piao, R. Betts, et al. 2008. “Evaluation of the Terrestrial Carbon Cycle, Future Plant Geography and Climate-Carbon Cycle Feedbacks Using Five Dynamic Global Vegetation Models (DGVMs).” Global Change Biology 14 (9): 2015–39. doi:10.1111/j.1365-2486.2008.01626.x. van der Molen, M. K., R. A. M. de Jeu, W. Wagner, I. R. van der Velde, P. Kolari, J. Kurbatova, A. Varlagin, et al. 2015. “The Effect of Assimilating Satellite Derived Soil Moisture in SiBCASA on Simulated Carbon Fluxes in Boreal Eurasia.” Hydrology and Earth System Sciences Discussions 12 (9): 9003–54. doi:10.5194/hessd-12-9003-2015. van der Velde, I. R. 2015. Studying Biosphere-Atmosphere Exchange of CO2 through Carbon-13 Stable Isotopes. Wageningen: Wageningen University. 16