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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

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Page 1: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

The impact of droughts on interannual variability in terrestrial carbon-13 discrimination

Erik van SchaikWageningen 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

Page 2: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Model estimations of carbon fluxes during the European drought

of 2003

2

TRENDY data from Sitch et al., 2008

Page 3: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Water – Vegetation coupling

3

Vapour Pressure

Stomatal conductance

Drought

Soil moisture

Mesophyllic conductanceBiochemical capacity

Page 4: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Observed Water Use Efficiency (WUE)

4

y = -0.4491x + 12.221

R2 = 0.8975

2

3

4

5

16 17 18 19 20 21 22 23

Carbon isotope discrimination (‰)

WU

E (

g K

g-1) 7790

88

91

77

9190

85

108

85

88 108

(d)

Dry

Wet

Anyia et al. (2007)

Page 5: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Variations in iWUE at the largest scale from δ¹³C

5

’wet’

’dry’

Van der Velde (2015)

SiBCASA + CO2+ 13CO2

Page 6: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Variations in iWUE at the largest scale from δ¹³C

6

SiBCASA

SiBCASA + CO2+ 13CO2

’wet’

’dry’

Van der Velde (2015)

Page 7: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Water – Vegetation coupling

7

Vapour Pressure

Stomatal conductancegs

Drought

IncludedNot included

Soil moisture

Mesophyllic conductancegm

Biochemical capacityVmax, Jmax

SiBCASASellers et al., 1996Baker et al., 2008

Page 8: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Water – Vegetation coupling

8

Vapour Pressure

Stomatal conductance

Drought

IncludedNot included

Soil moisture

Mesophyllic conductanceBiochemical capacity

CLM / JULES ORCHIDEE VISIT

Oleson et al., 2010Anav et al., 2015Krinner et al., 2005Ito and Oikawa, 2002

Stomatal conductancegs

Mesophyllic conductancegm

Biochemical capacityVmax, Jmax

Page 9: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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 [-] -> Wet0 0.2 0.4 0.6 0.8 1.0

Egea et al. (2011)

Observed

Dry <- Soil moisture stress [-] -> Wet

SiBCASA

Rel

ativ

e iW

UE

Soil moisture

Stomatal conductance

gs

Biochemical capacityVmax, Jmax

Mesophyllicconductance

gm

3

2

1

00 0.2 0.4 0.6 0.8 1.0

Page 10: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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 [-] -> Wet0 0.2 0.4 0.6 0.8 1.0

Egea et al. (2011)

Observed

Dry <- Soil moisture stress [-] -> Wet

SiBCASASiBCASAEgea

Rel

ativ

e iW

UE

Soil moisture

Stomatal conductance

gs

Mesophyllicconductance

gm

Biochemical capacityVmax, Jmax

3

2

1

0

0 0.2 0.4 0.6 0.8 1.0

SiBCASA

Page 11: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

WUE – Discrimination for Europe (2000-2011)

11

2003

2003

Page 12: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

Discrimination during 2003 drought in Europe

12

Months May-June-July

Δ anomaly : -0.21 ‰NEE anomaly: 0.03 TgC

Page 13: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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

Page 14: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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

Page 15: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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.

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Page 16: The impact of droughts on interannual variability in ... · The impact of droughts on interannual variability in terrestrial carbon-13 discrimination Erik van Schaik Wageningen University

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.

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