1. Fundamental influence of carbon-nitrogen cycle coupling on climate-carbon cycle feedbacks
Peter Thornton
NCAR, CGD/TSS
Collaborators:
Keith Lindsay, Scott Doney, Keith Moore, Natalie Mahowald, Mariana Vertenstein, Forrest Hoffman, Jean-Francois Lamarque, Nan Rosenbloom, Beth Holland, Johannes Feddema

2. Overview Review carbon-nitrogen coupling hypotheses
Summarize results from offline simulations
New results from fully-coupled simulations
Review disturbance history hypotheses
Preliminary results from fully-coupled simulations with landcover change

3. Recent findings from field experiments
Norby et al., Finzi et al., Hungate et al., Gill et al., 2006 (Ecology)
CO2 fertilization shifts N from soil organic matter to vegetation and litter
Some sites show progressive N limitation
Reich et al., 2006 (Nature)
Low availability of N progressively suppresses the positive response of plant biomass to elevated CO2
Perennial grassland: CO2 x N x (sp. diversity)
van Groenigen et al., 2006 (PNAS)
Soil C accumulation under elevated CO2 depends on increased N inputs (fixation or deposition).

4. Brief history of coupled C-N modeling
Pre-1983: Decomposition models
Parton et al., 1983, 1987, 1988, 1989, etc.
CENTURY: soil organic matter and vegetation model, coupled C, N, P, and S dynamics
McGuire et al., 1992
TEM: C, N interactions control net primary production (N.Am.)
Rastetter et al., 1992, 1997
MEL: Effects of CO2, N deposition, and warming on carbon uptake
Schimel et al., 2000
VEMAP: Terrestrial biogeochemistry model intercomparison
Thornton et al., 2002
Biome-BGC: C, N, and disturbance history control net ecosystem carbon exchange (evaluation against eddy flux obs.)
Liu et al., 2005
IBIS: NPP estimates improved when N dynamics added to a C-only model (evaluation against remote sensing NPP est.)

5. Brief history of coupled climate – carbon cycle modeling
Cox et al., 2000
HADCM3 / MOSES / TRIFFID: Strong positive carbon-climate feedback.
Joos et al., 2001
BERN-CC:
Dufresne et al., 2002
LMD5 / SLAVE: Moderate positive carbon-climate feedback
Thompson et al., 2004
CCM3 / IBIS: Strong negative CO2 feedback
Fung et al., Doney et al., 2005
CCM3 / LSM / CASA’: moderate CO2 feedback, weak climate feedback
Friedlingstein et al., 2006
C4MIP Phase 2: Eleven models, wide range of CO2 and climate (temperature) sensitivities.

6. Convergence toward a fully coupled carbon-nitrogen-climate model
CENTURY
MEL
TEM
VEMAP
Biome-BGC
IBIS+N
Convergence toward a fully coupled carbon-nitrogen-climate model
Carbon-Climate
Hadley
IPSL
C4MIP Phase 2
Carbon-Nitrogen-Climate
CCSM/CLM-CN
‘86
‘90
‘88
‘94
‘92
‘96
‘00
‘98
‘04
‘02
‘06

7. litterfall & mortality
Carbon cycle
Nitrogen cycle
Atm CO2
Internal
(fast)
External
(slow)
photosynthesis
denitrification
Plant
N deposition
assimilation
respiration
litterfall & mortality
Litter / CWD
Soil Mineral N
Mention the hypothesis of demand-based competition between plants and heterotrophs
Mention plant stoichiometric constraints
Mention that warming increases PSNS, respiration, and N mineralization – contrast tropics and boreal zone
N fixation
decomposition
Soil Organic Matter
mineralization
N leaching

8. Schematic of terrestrial nitrogen cycle
Image source: US EPA

9. C-N coupling: hypotheses
Smaller CO2 fertilization effect, compared to C-only model
Reduced ecosystem base state
Stoichiometric constraints on new growth
Progressive N-limitation: carbon accumulation in litter and soil leads to increased nitrogen immobilization
Reduced carbon cycle sensitivity to temperature and precipitation variability
Internal N cycling links plant and microbial communities

10. C-N coupling: hypotheses (cont.)
Climate x CO2 response
Expect changes over time in land carbon cycle sensitivity to variability in temperature and precipitation, forced by land carbon cycle response to increasing CO2.
Different fertilization responses for increased CO2 and increased mineral N
CO2: increased storage in vegetation carbon
N: increased storage in vegetation and soil carbon

11. Offline simulation protocol
Drive CLM-CN with 25 years of hourly surface weather from coupled CAM / CLM-CN.
Spinup at pre-industrial CO2, N deposition, landcover
Transient experiments ( )
Increasing CO2
Increasing N deposition
Increasing CO2 and N deposition
Repeat experiments in C-only mode
Supplemental N addition eliminates N-limitation
Test dependence on base state

12. Evaluation of fluxes and states
Thornton and Zimmermann, J. Clim. (in press)

13. Land biosphere sensitivity to increasing atmospheric CO2 (L)
Veg C (Pg C)
GPP (PgC/y)
L (2100)
CLM-C
1014
177
1.44
CLM-C2
771
146
1.25
CLM-CN
653
102
0.35
% change
Veg C
GPP L
CLM-C2
-24%
-18%
-13%
CLM-CN
-35%
-42%
-76%
CN : C2
1.5
2.3
5.8
Difference in beta at 2100 is not primarily due to altered base state
CLM-C
CLM-CN (CO2) 
C4MIP models 
C4MIP mean
CLM-C2
Thornton et al., GBC (in review)

14. Spatial distribution of L
2000
2100
C-N
C-N
Biggest differences in tropics and above 40N. Relationship to base state. Negative beta due to increased fire under higher CO2
C-only
C-only
Thornton et al., GBC (in review)

15. NEE sensitivity to Tair and Prcp (at steady-state)
Tair response not primarily due to altered base state, but prcp response is consistent with altered base state
% change
VegC
GPP
Tair
Prcp
CLM-C2
-24%
-18%
-17%
-32%
CLM-CN
-35%
-42%
-77%
-58%
CN : C2
1.5
2.3
4.5
1.8
Thornton et al., GBC (in review)

16. NEE sensitivity to Tair and Prcp (at steady-state)
C-N
C-N
Strong and potentially cancelling spatial patterns of uptake/release under changes in tair and prcp. Shifting dominance to N.Hem response in both T and P
C-only
C-only
Thornton et al., GBC (in review)

17. NEE sensitivity to Tair and Prcp: effects of rising CO2 and
anthropogenic N deposition
Carbon-only model has increased sensitivity to Tair and Prcp under rising CO2. CLM-CN has decreased sensitivity to both Tair and Prcp, due to increasing N-limitation.
Thornton et al., GBC (in review)

18. Fertilization responses to CO2 and mineral N deposition (period 2000 – 2100)
Tot C (PgC)
% Veg C
% Lit C
% SOM C
C-N: CO2
204 79 13 8
C-N: Ndep 50 56 31
C-only: CO2
843 66 14 20
C-only(2): CO2
740 21
C-N gives qualitative match to observations from field experiments
Changing the base state has negligible effect on partitioning of fertilization response
Important because of order-of-magnitude differences in turnover times for vegetation and SOM pools, regionalization of sink permanence.
Thornton et al., GBC (in review)

19. Summary of offline results
C-N coupling results in large decrease in CO2 fertilization of land ecosystems.
Sensitivities of net carbon flux to temperature and precipitation variation are damped by C-N coupling.
C-N coupling reverses sign of trend in carbon-climate sensitivity under increasing CO2.
Model agrees with experimental studies on contrasting effects of CO2 and N fertilization

20. Fully-coupled climate-carbon-nitrogen simulations
CCSM3 framework: CAM + CICE + POP Doney/Moore/Lindsay ocean ecosystem + CLM-CN
1000-year stable pre-industrial control
Historical + A2 ( ), forced with fossil fuel emissions and nitrogen deposition.
Coupled vs. fixed radiative effects of atmospheric CO2.

22. Land biosphere sensitivity to increasing atmospheric CO2 (L)
Offline results
Results from fully-coupled runs:
Land sensitivity to increasing CO2 is not significantly different between offline and fully-coupled simulations
Negative climate feedback of land carbon cycle

23. Changes in land carbon stocks: 1870-2100
Pool
Change
PgC
% of total
Plant
300
89%
CWD 20 6%
Litter 1
<1%
Soil 17 5%
Total
338
(25%)

24. NEE sensitivity to Tair and Prcp (at steady-state)
CCSM3
Both C-only and C-N have the same sign for global mean response to tair and prcp, but smaller magnitude (buffering)
Land carbon cycle sensitivity to variation in temperature and precipitation is not significantly different between offline and fully-coupled simulations

25. Climate-carbon cycle feedbacks
CO2-induced climate change (warmer and wetter) leads to increased land carbon storage

26. Climate-carbon cycle feedbacks
Vegetation C
CWD C
Climate change feeds back to carbon cycle in part through change in nitrogen availability
Litter C
Soil C

27. Climate-carbon cycle feedbacks
Climate change impact on land carbon uptake closely related to changes in precipitation

28. Climate-carbon cycle feedbacks
Fractions of anthropogenic emissions in land, ocean, and atmosphere pools
CCSM3.1-BGC
C4MIP mean
uncoupled
coupled
Land-borne fraction
0.15
0.18
0.29
0.21
Ocean-borne fraction
0.22
0.25
Airborne fraction
0.63
0.61
0.46
0.54

29. What about disturbance history and landcover change?

30. Results: NEE response to disturbance, changing [CO2]atm, and Ndep shows strong interaction effects

31. Fully-coupled simulations with prescribed landcover changes (prognostic fluxes)
Using subset of data from Johannes Feddema
Annual time slices from , originally on half-degree grid.
Historical data from Ramankutty and Foley (1999), Goldewijk (2001), integration with present-day MODIS landcover.
Landcover change for based on SRES A2 scenario.
New prognostic component in CLM-CN to handle carbon and nitrogen fluxes and mass balance associated with landcover change.
Conversions to/from all plant functional types.
Tracking two wood product pools in each land gridcell (10-yr and 100-yr turnover times).
Fossil-fuel emissions, N deposition, radiatively coupled

32. Influence of landcover change on land carbon flux and global pools
Grass
Tree
+200 ppmv net (by 2100)
Shrub
Agric
+250 ppmv from land
-50 ppmv from ocean

33. GPP falls and then recovers during landcover transition
Plant respiration increases, due to replacement of woody with herbaceous biomass
NPP falls and remains lower (GPP is offset by plant respiration)
Soil respiration rises in response to conversion fluxes, then falls in response to reduced NPP

34. Carbon cycle impacts of landcover change
Transient fluctuations in GPP as new ecosystem is established
Reduced NPP due to increased plant respiration
Depends on tree-to-ag vs. grass-to-ag transition and regional climate (biggest effect for tropical forest conversion)
Increased soil respiration due to more labile litter inputs.
Reduced potential for CO2 fertilization of land ecosystems, due to loss of area of woody vegetation.

35. Changes in vegetation carbon pools due to landcover change

36. Comparison to previous results (preliminary)
IPCC TAR includes estimates of fluxes due to landcover change, for the A2 scenario, which are more than an order of magnitude smaller than those predicted here for the 21st century.
Appear to ignore the mechanism of reduced sink potential.
Gitz and Ciais (2003): EMIC. Landcover flux much larger than IPCC, smaller than CCSM3-BGC.

37. Conclusions
Carbon-nitrogen cycle coupling has a fundamental influence on climate-carbon cycle dynamics
Mechanistic treatment of landcover change suggests this signal will be a major factor influencing future atmospheric CO2 concentrations, and regional patterns of climate change.
Next generation models should explicitly include the factors driving fossil fuel emissions and landcover change.