Carbon – Nitrogen – Climate Coupling Peter Thornton NCAR, CGD/TSS June 2006

The global carbon cycle: fluxes and storage

The global C cycle: changes over time

The global nitrogen cycle: fluxes and storage

The global N cycle: changes over time

Atm CO 2 Plant Litter / CWD Soil Organic Matter Carbon cycle Soil Mineral N N dep N fix nit/denit N leaching Nitrogen cycle Respiration Internal (fast) External (slow)

Elements of design Establish design goals Persistence in the pursuit of quality Probe, test, explore… …build prototypes, and be prepared to abandon them Build to last, and archive your efforts

C-N coupling: hypotheses N-limitation reduces land ecosystem response to increasing CO 2 concentration –Reduced base state –Stoichiometric constraints, internal N cycling –Progressive N-limitation due to biomass accumulation N-limitation damps carbon cycle sensitivity to temperature and precipitation variability –Reduced base state –Persistence due to internal N cycling

C-N coupling: hypotheses (cont.) Climate x CO 2 response –Changes over time in land carbon cycle sensitivity to variability in temperature and precipitation, forced by land carbon cycle response to increasing CO 2.

Simulation protocol 1.Spinup at pre-industrial CO 2 and N deposition ~700 yrs, following Thornton and Rosenbloom (2005) 2.Drive CLM-CN with 25 years of hourly surface weather from coupled CAM / CLM-CN. 3.Transient experiments ( ) Increasing CO 2 Increasing N deposition Increasing CO 2 and N deposition 4.Repeat experiments in C-only mode supplemental N addition, following Thornton and Zimmermann (in review)

offline CLM-CN (CAM drivers) coupled (CAM – CLM-CN) transient, control(transient-control) GPP (CO 2 +Ndep)

CLM-C CLM-CN (CO2,Nfix,dep) CLM-CN (CO2,Nfix) CLM-CN (CO2)  C4MIP models  C4MIP mean Land biosphere sensitivity to increasing atmospheric CO 2 (  L ) Results from offline CLM-CN, driven with CAM climate, in carbon-only (CLM-C) and carbon-nitrogen (CLM-CN) mode, from present to Using SRES A2 scenario assumed CO 2 concentrations.

Spatial distribution of  L C-N C-only

NEE sensitivity to Tair and Prcp (at steady-state) Coupling C-N cycles buffers the interannual variability of NEE due to variation in temperature and precipitation (global means, control simulations).

NEE sensitivity to Tair and Prcp (at steady-state) C-N C-only TairPrcp

FIRE HR NPP NEE Components of NEE temperature response NPP dominates NEE response to temperature in most regions. Exceptions include Pacific Northwest, Scandanavia.

Dissection of NPP temperature response GPP Soil ice BtranNPP Warmer temperatures lead to drying in warm soils (increased evaporative demand), and wetting in cold soils (less soil water held as ice).

FIRE HR NPP NEE Components of NEE precipitation response NPP dominates NEE response to precipitation in tropics, midlatitudes, HR dominates in arctic and coldest climates.

Dissection of HR precipitation response Snow depth NEE HR Tsoil Higher Precip in arctic/cold climate produces deeper snowpack, warmer soils, increased HR.

NEE sensitivity to Tair and Prcp: effects of rising CO 2 and anthropogenic N deposition Carbon-only model has increased sensitivity to Tair and Prcp under rising CO 2. CLM-CN has decreased sensitivity to both Tair and Prcp, due to increasing N-limitation.

Conclusions (1) C-N coupling significantly reduces  L –not primarily the result of altered base state –strongest in the tropics and above 40N

Conclusions (2) C-N coupling significantly reduces NEE sensitivity to interannual variation in Tair and Prcp at steady-state –Tair effect is not primarily due to altered base state –Prcp effect consistent with alteration to base state –Tair: NPP dominates, with warming leading to drying in warm soils, wetting in cold soils. –Prcp: NPP dominates in tropics/temperate, but HR dominates in cold climates, with wetting leading to deeper snow, warmer soil, increased HR. –Tair and Prcp responses likely in tension for warmer- wetter future climate.

Conclusions (3) Increasing CO 2 amplifies the sensitivity of land carbon cycle to Tair and Prcp in C-only model, but damps these sensitivities in C-N model –This difference is not primarily due to a difference in base state. –Tair response is consistent with increasing N limitation under increasing CO 2

The role of disturbance in C-N- climate coupling Wildfire

The role of disturbance in C-N- climate coupling Wind damage

The role of disturbance in C-N- climate coupling Insects

The role of disturbance in C-N- climate coupling Forest harvest

Simulated disturbance effects: Duke Forest, NC Harvest loss: gC m -2 Thornton, in prep.