1. FACE Network * Presented by:Bob Nowak Stan Smith Assistance from:Hormoz BassiriRad Terri Charlet Dave Ellsworth Dave Evans Lynn Fenstermaker Eric Knight Peter Reich Participants of FACE 2000 Conference * aka FACE Universal Network (Norby 2000)

2. F.U.N. Charges 1.How do the various experiments work together as a network? 2.Can we increase the efficiency of CO 2 use? 3.What measurements are being conducted and can they be critically compared? 4.What general ecological principles are being discovered? 5.What is the value-added from the network?

3. Non-agricultural FACE Network Forest Grassland Desert Forest Grassland Chaparral Grassland MEGARICH Grassland MEGARICH BERI MEGARICH BERI MEGARICH BERI Forest Savanna Base map courtesy CDIAC

4. Global Vegetation Types Tundra Taiga Temperate Forest Desert Savanna Tropical Seasonal Forest Tropical Rainforest Grassland Temperate Rainforest

5. FACE Design & Protocols Mini-FACEBNLOther CO 2 fumigation design46%36%18% SeasonalAll year Yearly CO 2 treatment period77%23% Daylight24 hourUnknown Daily CO 2 treatment period36%41%23% CO 2 control point  86% of sites effectively have [CO 2 ] ~550 (± 10%) 90% of these control to set [CO 2 ]; 10% control as +200  9% of sites control to 605  9% of sites have >1 elevated [CO 2 ]

6. Increasing Efficiency of CO 2 Use  Preventative maintenance Keep CO 2 delivery system sealed and fully operational  Potential design enhancements Improve response time of system Increase turbulence mixing

7. Turbulent Mixing: Vortex Generators

8. Variables Measured Yes (%)No / Unk (%) Physiology Leaf gas exchange5446 Root physiology2773 Aboveground production Biomass100-- Litter5941 Carbon pools/fluxes3664 Nitrogen pools/fluxes100-- Belowground production Root5941 Microbial3268 Carbon pools/fluxes4159 Nitrogen pools/fluxes4159 ET / Soil water content5446 Biodiversity Plants919 Herbivores3268

9. Predictions: Leaf physiology  Leaf photosynthesis increases under elevated CO 2, although down- regulation may or may not occur  Stomatal conductance decreases under elevated CO 2  Consequently, water use efficiency at the leaf level increases

10. Dominant species responses to elevated CO 2 : how large is enhancement? Data from: Ellsworth et al. Yellow Bars: compiled from literature and unpublished results WI MN NC NV

11. Enhancement dependence on leaf N Data from: Ellsworth et al.

12. Enhancement dependence on leaf N Data compiled from literature and unpublished sources: Duke, Rhinelander, Oak Ridge, Maricopa, Nevada, Switzerland, Italy

13. Predictions: Productivity After Strain & Bazzazz (1983) Xeric ModerateMesic Drought stress Relative response to CO 2 HighLow Nutrient poor Moderate Nutrient rich Nutrient availability Relative response to CO 2 Low High Hot desert, alluvial Hot desert Alpine Temperate deciduous forest Chaparral Tropical forest Boreal forest Tundra Marsh / Estuary SavannaGrassland Cold desert Temperate coniferous forest

14. Data from BERI, BioCON, FACT-I, FACTS-II, JRGCP, NDFF, NZGraze, ORNL, & Swiss Results: Shoot production

15. Predictions: Root processes  Because of greater carbon assimilation rates, root processes (growth, turnover, or exudation) increase under elevated CO 2  Because of increased plant size (and despite decreased nutrient concentrations per unit tissue weight), whole-plant nutrient uptake increases BUT nutrient uptake per unit root length/biomass may or may not increase

16. Results: Root processes  Some sites have increased root biomass Grasslands (BioCON, JRGC, Swiss) Forests (FACTS-I, ORNL)  Some sites have no change in root biomass Desert (NDFF)

17. Predictions: Water balance  Reduced stomatal conductance under elevated CO 2 reduces leaf water use  If reduced conductance scales to the canopy, then canopy transpiration decreases and soil moisture is conserved under elevated CO 2 BUT increased growth (shoot and root) and increased canopy temperature at least partially offsets this conservation of soil moisture

18. Results: Soil water at NDFF

19. Predictions: Nutrient cycling  Because of increased availability of carbon substrates, microbial activity, including N-fixers and mycorrhizae, increases, and thus alters N cycling BUT effects on N availability could be positive or could be negative

20. Flow diagram from Evans

21. Results: Nutrient Cycling Deciduous forest Conifer forest Grassland Chaparral Desert Data from BassiriRad & Evans

22. Predictions: Biodiversity  Because co-occurring species differ in their response to CO 2, there will be winners and losers … BUT can rarely extrapolate from monoculture studies  Because more diverse species assemblages often produce greater biomass per unit area, elevated CO 2 has greater effects in more diverse communities  Because growth rate, fecundity, and water use efficiency of plants increase under elevated CO 2, invasions occur where water or nitrogen limit recruitment (e.g. invasions of woody plants into grasslands; invasive species)  Perturbations and disturbance (e.g. fire, grazing, pathogens) and concomitant global changes (e.g. warming, altered precipitation, increased UV-B) interact with and alter CO 2 responses

23. Winners & Losers: BioCON Data from Reich

24. Winners & Losers: Observed Responses at Elevated CO 2  Shift to dicots in grasslands Swiss –  legume NZ Graze –  legume MEGARICH –  dicots JRGC –  dicots BioCON –  dicots  Potential for increase of invasives FACTS-I –understory invader ORNL – understory invader NDFF – annual grass

25. Species Richness Production + N, + CO 2 + N, - CO 2 - N, - CO 2 - N, + CO 2 Diversity Increases CO 2 Effect: Hypothetical Response Curves From Reich

26. BioCON –Biomass response (average 1998, 1999) Reich et al. (2001) Nature

27. Results: Increased fire cycle Smith et al. (2000) Nature

28. Elevated CO 2 Current CO 2

29. Elevated CO 2 Current CO 2

30. Community change Photos by T. Huxman & T. Esque Elevated CO 2 Current CO 2

31. Predictions: Evolution  Because of the rapidity of increased CO 2, evolution may have little potential role … BUT evolutionary response likely: in species (e.g. pests) with large population sizes (>10 5 ), short generation times (<1 year), and high intrinsic growth rates where migration and dispersal are limited (e.g. habitat islands)  Evolutionary responses depend on: the extent that phenotypic vs. genotypic processes occur resource availability, including population density level of intraspecific variation, especially compared to interspecific variation Predictions: Plant-animal interactions  Increased C:N ratios of foliage may: lead to increased consumption by insect herbivores but decreased consumption by large ruminants alter growth, development, and reproduction of all herbivores

32. Two contrasting points of view: 1.FACE or OTC experiments mimic future [CO 2 ] so that observations from the experiments represent ecosystem responses to [CO 2 ]. 2.Current experiments exert an ecosystem perturbation – a step- increase in [CO 2 ] – achieved primarily by altering carbon influx. Solutions to step-increase problem: 1.Analyze data from FACE experiments using inverse approach to challenge the structure of existing models and derive parameter values. 2. Collect highly accurate, informative data by improving experimental design and measurement plan for the FACE network. Luo (2001) New Phytol.

33. Need for Data Archives Facilitate cross-site comparisons Compiled results  data means, relative enhancements with SE,  in data base, spreadsheet, or ASCII format New ways to analyze old data Raw data sets  quality checked, quality controlled FACE NETWORK Should some measurements be taken at every site? Can we standardize measurement protocols? How and where to archive the data?

34. Data Availability

35. CDIAC Carbon Dioxide Information Analysis Center FACE Data: Oak Ridge, Tennessee The following data, and summary documentation, from the Oak Ridge, Tennessee, FACE site are now available from CDIAC: weather data CO 2 data - coming soon! tree basal area data - coming soon! leaf production data - coming soon! Relevant publications: Norby, R. J., et al. 2001. Allometric determination of tree growth in a CO 2 -enriched sweetgum stand. New Phytologist 150(2):477-487. Wullschleger, S. D., and R. J. Norby. 2001. Sap velocity and canopy transpiration in a sweetgum stand exposed to free-air CO 2 enrichment (FACE). New Phytologist 150(2):489-498. FACE Home CDIAC Home 10/2001 http://cdiac.esd.ornl.gov/programs/FACE/ornldata/ornldata.html

36. QUALITY-ASSURANCE CHECKS AND DATA-PROCESSING ACTIVITIES PERFORMED BY THE FACE PROJECT AND CDIAC Data is checked and corrected for unrealistic large or small values. Daily statistics are calculated only for those variables with at least 12 good hourly values X-Y scattergrams are used to check for outliers and consistency among the data loggers. Example: Contents and format of the hourly files, r*_wh_*.dat. CDIAC DOCUMENTATION DESCRIPTION and FORMAT OF THE ASCII DATA FILES SAS, FORTRAN, and C CODES TO ACCESS THE DATA Import code for each file type

37. F.U.N. Charges 1.How do the various experiments work together as a network? 2.Can we increase the efficiency of CO 2 use? 3.What measurements are being conducted and can they be critically compared? 4.What general ecological principles are being discovered? 5.What is the value-added from the network?