Controls of carbon budgets in terrestrial ecosystems

1. Controls of carbon budgets in terrestrial ecosystems • Does carbon storage in terrestrial ecosystems really depend on temperature? • What factors do we need to consider when we assess vegetation—atmosphere coupling in climate change scenarios? • How well do coupled climate—vegetation models simulate the response of forest CO2 fluxes and carbon sequestration to variations in temperature? • What controls the long-term storage of organic carbon in boreal soils ? [current content: 200—400 ppm of CO2 ; all soils, > 700 ppm ] • Steven C. Wofsy, Harvard University • Presented at: ICDC7 Boulder, CO, 29 Sep 2005

2. 120 100 80 R 60 40 20 0 -20 -10 0 10 20 30 T oC • “Land carbon storage depends on the balance between the input of carbon as Net Primary Productivity (NPP), and the loss of carbon as heterotrophic (soil) respiration (Rh).” • NPP modeled as dependent on light, nutrients, precipitation • Rh modeled as a function of T. Is this right? Daily Mean Ecosystem Respiration (mmole/m2/s) vs T (C) Photosynthesis vs sunlight Harvard Forest Exp fit

3. Modeling long-term Net Ecosystem Carbon Production (NEP)(1st-order): “tree” solar Atmosphere CO2, H2O Leaves (P, R6) H2O, nutrients CO2 Org C Boles (R5) Org C Roots (R4) Soils R1 R2 R3

4. Do climate—ecosystem models capture the temperature dependence of carbon storage? Or the long-term trends in C storage? Example 1: a typical mid-latitude forest (Harvard Forest, Central New England; agricultural use 1750-1850). 60-80 year old mixed deciduous forest, with CO2 fluxes to/from the atmosphere measured every half hour, for 15 years (1991-2005) (S. Wofsy, J. W. Munger, B. Daube, M. Goulden, C. Barford, S. Urbanski, many others), plus a soil warming manipulation (J. Melillo, K. Nadelhofer, P. Studler).

5. Model (IBIS) vs. Observed C balance at a transition deciduous forest. Errors in both seasons are due to T driving respiration emission uptake phenology R vs T: fundamental to climate change—the mean is right, but the model is never right in any month and the CO2 Flux–T feedback is wrong!

6. Modeled and observed respiration at Harvard Forest

7. “Overall, warming treatment did not significantly change soil respiration either with or without clipping.” (Luo et al., 2001)

8. Annual change (%) in soil respiration due to 5o soil warming over a thirteen-year period at Harvard Forest [Melillo, Nadelhofer, Studler, et al. –Marine Biological Laboratory, Woods Hole, MA].

9. Does this extra N increase enhance tree growth? Annual change (%) in N mineralization due to soil warming over a thirteen-year period at Harvard Forest [Melillo, Nadelhofer, Studler, et al. –Marine Biological Laboratory, Woods Hole, MA].

10. Accel. G, R • Accel. NEE • Higher LUE Year 1992 1994 1996 1998 2000 2002 -16 uptake NEElight sat’d 16 R -18 -1x GEE mean NEE PAR 1200-1500 (mmole/sq. m/yr) 14 emission -20 R (tonC/ha/yr) 12 -22 More efficient 1992 1994 1996 1998 2000 2002 10 Year 1992 1994 1996 1998 2000 2002 2004 Year 0 NEE Harvard Forest AmeriFlux Data: 1991--2004 -1 -2 NEE (tonC/ha/yr) -3 AGWB incr. rate net uptake -4 1992 1994 1996 1998 2000 2002 2004 Long-term changes at Harvard Forest J. W. Munger, S. Urbanski, S. C. Wofsy et al.

11. 20 30 50 cm Example 2: Climate and C at a Boreal Forest (NOBS) flux site, Thompson, MB PEAT 45% cover Jan Snow cover Temperature (rapid warming) 1970 2000 1900 2000 Jul

12. a. NEE b. T anomaly c. CMI.3 anomaly Boreal Forest: Comparison of (a) NEE, (b) temperature anomaly, (c) 3-year lagged climate moisture index anomaly (10 years of AmeriFlux Data) Uptake | emission Temperatures warm up, ecosystem switches: sourcesink

13. NEE: C balance at a bog: Jun—Sep Daily respiration, g C m-2 Water table depth, cm    Water Table Water Table Depth (cm) or T (c) T Summer 2002 Summer 2003 Summer 2004 Temper1ature, °C R (gC m-2 day-1)

14. a. NEE b. T anomaly c. CMI.3 anomaly Boreal Forest: Comparison of (a) NEE, (b) temperature anomaly, (c) 3-year lagged climate moisture index anomaly (10 years of AmeriFlux Data) Uptake | emission Water balance & (temperature) explain the transition: sourcesink

15. Positive correlation  warmer-wetter; or cooler-drier Negative correlation  warmer-drier; or cooler-wetter Correlation: {DT, D soil moisture index}CCSM1-Carbon Control Simulation DJF JJA slide courtesy Inez Fung [I. Fung, S. Doney, et al.]]

16. high T, high ppt Low T, low ppt Recent climate variations in central Canada have been [cold:dry] and [warm:wet] …

17. Holdridge Life Zones & potential vegetation: Mean T, Precip, and E/P control vegetation cover: warmer-drier leads to strong degradation in the tropics. .25 125 Data courtesy of D. Skole 1.0 P 1.5 E/P 1500 T 6 8.0 8000 24 Holdridge life zones (Holdridge 1967)

18. Summary•How well do coupled climate—vegetation models simulate the response of forest CO2 fluxes and carbon sequestration to warming? Many models over-estimate the sensitivity of ecosystem C storage to T.•What controls the long-term storage of organic carbon in boreal soils ? [current content: 200—400 ppm of CO2 ; all soils, > 700 ppm equivalent]. Hydrological balance in concert with T dominate; if changed climate has warmer wetter covariance, boreal lands may actually increase C storage in a warmer world.

19. What did we learn?Coupled climate vegetation modeling must carefully and critically examine predictions for climate change and ecosystem response in terms of the key parameters (•regional T •Precipitation •Human impacts (ignition, agriculture, air pollution) and their •covariances .Consider advancing beyond the traditional focus on global mean T. These are all 1st order factors.