1. Continental Scale Carbon Synthesis Pedro L. Silva Dias Institute of Astronomy, Geophysics and Atmospheric Sciences University of São Paulo

2. From local measurements to basin wide: tower to biometric measurements to satellite based estimates Inverse techniques Can we constrain the regional C balance in the Amazon? - BARCA Are our models good enough for modeling the climate control on the biosphere and feedbacks? Fire Some ideas for discussion this afternoon

3. Ecotone (forest-Cerrado transition) – seasonally flooded Tannus (2004) Cerrado s. s. Bananal ~ 5 m Cerradão Bananal ~ 18 mWet season Cerrado sensu stricto Negrón-Juarez (2004) Rocha et al (2002) Miranda et al (1996) Vourlitis et al (2001, 2004) Tropical rain forest Goulden et al (2004) Rocha et al (2004) Saleska et al (2003) Araujo et al (2001) Von Randow et al (2004) Santarém km83 Dry season Tower 67m

4. CO2 flux (NEE) daily mean (kg C ha -1 day -1 ), over Cerrado s.s (Gleba Pé de Gigante, from October 2000 to November 2001. Source: Rocha et al. (2002). Cerrados sensu strictu (woodland savanna) : strong seasonality Leaves senesceny, grass dormency during the winter Grows in the wet season Looses C in the dry season

5. Tropical forest (Santarém km83, km67) Saleska et al. (2003) (Science), Goulden et al. (2004) (Ecol App) Seasonality GEE (photosynthesis), tree growth : increases in the wet season Soil Resp (Soil CO2 eflux) : increases in the wet season Net CO2 ecosystem flux – shows the opposite: absorbs in the dry season

6. Amazon Basin : wetlands sum ~17% (Mellack et al. 2004) 1.C functionality in land biota - ecotone (wetlands) in Bananal Island

7. Dry season pattern drives the seasonal tropical rain forests productivity Contr.: H. Rocha

8. EXAMPLE: Remote sensing Data (MODIS Enhanced Vegetation Index, EVI) shows that broad areas of Amazon forest “green up” in the dry season: Green-up region Brown-down region Source: Huete, Shimabukuro et al., (in review) Eddy flux tower site

9. Caxiuana São Gabriel Cachoeira Sinop Scaling Carbon Fluxes with models and remote sensing Eddy flux data from a dozen towers spans: 1.5 – 3.5 m annual precip from 0  - 21  S from primary wet forest to Cerrado, including pasture and agricuture sites Goals for Data Cross-site comparisons of ecosystem properties parameterize and test models data-grounded extrapolations with remote sensing

10. CO2 flux variability over tropical forests in Amazonia (t C / ha / yr) (1) Phillips (1998); (2) Meir (1996), Trumbore (1998), Davidson (2000) (3) Trumbore (2000); (4) Grace (1995), Malhi (1998), Miller (2002) (5) Houghton (2000); (6) Richey (2002) Above ground biomass increment  ( 1 – 3 ) (1) Net ecosystem productivity  ( + 2 to – 6) (3) Soil C increment  0,5 (isotope studies) (4) CO2 outgassing  1 (6) TOC exported to ocean  ( 0,05 ) (6)

11. However, we have a very limited sample of the carbon balance....

12. Marengo, 2003 Variabilidade interanual e interdecadal das chuvas na Amazônia – Marengo, 2003

13. Parcel studies with tree growth monitoring - show positive trends all across Amazonia - is larger in western Amazonia partly to the shortest dry season + fertile soils Malhi et al (2004) (Global change biology)

14. How about models?

15. Model Output from: TEM (Tian et al, 1998, 2000) & IBIS (Botta & Foley, 2002) models (8 years, colored lines) Data from Tapajos Forest eddy flux sites (black line is moving average monthly NEE  SD, points are average weekly NEE) Mean seasonal NEE and precipitation (  SD of interannual variation) in the Flona Tapajós, Para Slide and analysis provided by Scott Saleska, Harvard University What’s missing in the models? Vertical resolution of respiration- relevant moisture? Diagnosis of moisture levels of litter and CWD? Moisture dependence of surface soil respiration?

16. And how about the future based on interactive biosphere models? Is the Amazon Dieback hypothesis solid?

17. The first two GCM climate projections to include an interactive carbon cycle showed a positive climate- carbon cycle feedback mostly due to the negative impacts of climate change on land carbon storage (Cox et al. 2000; Friedlingstein et al. 2001); Interactive CO 2 and dynamic vegetation 2090s - 1990s Haddley Center

19. However, the magnitude of the feedback varied markedly between the models (Friedlingstein et al. 2003). Other recent coupled simulations: Thompson et al. 2004, Matthews et al. 2004, Zeng et al. 2004, Brovkin et al. 2004), as part of the Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP). Dufresne et al. (2002) presented results with a fully coupled version of the IPSL where by 2100 the atmospheric CO2 would be 18% higher due to inclusion of carbon cycle feedbacks than without. This positive feedback from the carbon cycle is about 1/3 that reported in Cox et al. Preliminary fully coupled simulations with the Earth Simulator in Japan yield results similar to those of Cox et al. (Kawamiya, pers. comm.).

20. Carbon-Climate Futures Coupled climate — vegetation models project dramatically different futures (CO 2, vegetation, T) using different ecosystem models. ~ 2º K in 2100  T=5  T=3 Coupled simulations of climate and the carbon cycle Slide: A.S. Denning  CO 2 => 700 => 500

21. SummaryHow well do coupled climate—vegetation models simulate the response of forest CO 2 fluxes and carbon sequestration to warming? Most models seem to over-estimate the sensitivity of ecosystem C storage to T: they use T responses from short-term studies (“zero-order” or “first-order” models), conflate seasonal changes in ecosystem structure with a response to T, and neglect short term/long-term decoupling (e.g. soil warming) What are the strongest determinants of vegetation transitions (forest—non-forest) ? [current content of forests (as wood): 350 ppm CO 2 equivalent] Precipitation and T together, in concert with sources of ignition, appear to dominate in the tropics, at least under current climate. What do coupled climate—vegetation models tell us about covariance among climate change parameters and drivers? Basic model climate sensitivity is critical  non-linearity of Carbon – Climate coupling. Warmer—wetter may be likely at mid– and high—latitudes and warmer—dryer in the tropics, implying less positive vegetation—climate feedback and damage to tropical ecosystems. Contr: Steve Wofsy

22. Conclusions ● Seasonal water stress is a major determinant of seasonal carbon exchange in tropical forests in the Amazon region ● Overestimation of drought stress may lead to severe climate simulation errors in coupled models ● Correct coupled climate simulation requires resolution of vertical gradients of soil moisture, and probably also of soil respiration Contr.: Scott Denning

23. Another problem in the models: “SAVANIZATION”

24. Contribution: Jon Lloyd

25. Modeling needs ● Better understanding of determinants between savanna and forest globally ● Better representation of savanna diversity ● (In one often used global data base there are 16 types of temperate/boreal forest and one type of savanna!) Jon Lloyd contribution

26. CONCLUSIONS In order to reduce the significant uncertainties in climate-carbon cycle projections it is critically important that carbon cycle models are more completely constrained by observational data. In order to do this the models need to be more complete so that they are more obviously comparable to the real world. In the case of the land carbon cycle current limitations include the lack of consistent modelling of the effects of land-use change and regrowth (Sitch et al., 2005), and the neglect of carbon- nitrogen interactions.

27. C fluxes in tropical amazonian rain forests depend strongly on - the dry season pattern and soil type Some places loose and some absorb C on the 1 km2 scale Net primary productivity shows positive trend in parcel studies Flooded areas are single biomes in the Amazon, where the flood pulse control the emission and sink. They respond for a substantial fraction of the Amazon basin Understanding the C cycle mechanisms is a remarkable contribution to the vegetation-climate couple models (a nice tool to assess environmental sustainability over the next decades) The C in Amazonia can substantially strengthen the greenhouse effect, given the current IPCC scenarios and deforestation.

28. Need for BARCA!!! (answer some questions but...others....) Strategy: Lagrangian regional experiments: diurnal airborne measurements of CO 2, CO, and H 2 O within and above the Planetary Boundary Layer (PBL). Eulerian experiments: vertical profiles at different times of the day over selected locations Large-scale surveys: sampling of large-scale CO 2 distribution along the synoptic flow pattern, combined with knowledge of diurnal variations from the Eulerian experiments, gives Basin- scale flux constraints to promote simultaneous observation activities in and around the Amazon Basin as a basis for the budgets of heat, water, carbon. conduct the regular surface measurements in towers and operational networks with high quality during a full year starting in August 2004 Activities: