FACE Network *

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 • How do the various experiments work together as a network? • Can we increase the efficiency of CO2 use? • What measurements are being conducted and can they be critically compared? • What general ecological principles are being discovered? • What is the value-added from the network?

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

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

5. FACE Design & Protocols • Mini-FACEBNLOther • CO2 fumigation design 46% 36% 18% • SeasonalAll year • Yearly CO2 treatment period 77% 23% • Daylight24 hourUnknown • Daily CO2 treatment period 36% 41% 23% • CO2 control point • 86% of sites effectively have [CO2] ~550 (± 10%) • 90% of these control to set [CO2]; 10% control as +200 • 9% of sites control to <495; 5% control to >605 • 9% of sites have >1 elevated [CO2]

6. Increasing Efficiency of CO2 Use • Preventative maintenance • Keep CO2 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 exchange 54 46 • Root physiology 27 73 • Aboveground production • Biomass 100 -- • Litter 59 41 • Carbon pools/fluxes 36 64 • Nitrogen pools/fluxes 100 -- • Belowground production • Root 59 41 • Microbial 32 68 • Carbon pools/fluxes 41 59 • Nitrogen pools/fluxes 41 59 • ET / Soil water content 54 46 • Biodiversity • Plants 91 9 • Herbivores 32 68

9. Predictions: Leaf physiology • Leaf photosynthesis increases under elevated CO2, although down-regulation may or may not occur • Stomatal conductance decreases under elevated CO2 • Consequently, water use efficiency at the leaf level increases

10. Dominant species responsesto elevated CO2: how large is enhancement? Yellow Bars: compiled from literature and unpublished results Data from: Ellsworth et al. WI MN NC NV

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

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 Data compiled from literature and unpublished sources: Duke, Rhinelander, Oak Ridge, Maricopa, Nevada, Switzerland, Italy Enhancement dependence on leaf N

13. Hot desert, alluvial Marsh / Estuary Nutrient rich High Temperate deciduous forest Nutrient availability Grassland Savanna Relative response to CO2 Moderate Alpine Cold desert Tropical forest Temperate coniferous forest Chaparral Boreal forest Nutrient poor Hot desert Tundra Low Xeric Moderate Mesic Drought stress High Relative response to CO2 Low Predictions: Productivity After Strain & Bazzazz (1983)

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

15. Predictions: Root processes • Because of greater carbon assimilation rates, root processes (growth, turnover, or exudation) increase under elevated CO2 • 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 CO2 reduces leaf water use • If reduced conductance scales to the canopy, then canopy transpiration decreases and soil moisture is conserved under elevated CO2 • 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 Desert Chaparral Grassland Conifer forest Deciduous forest Data from BassiriRad & Evans

22. Predictions: Biodiversity • Because co-occurring species differ in their response to CO2, 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 CO2 has greater effects in more diverse communities • Because growth rate, fecundity, and water use efficiency of plants increase under elevated CO2, 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 CO2 responses

23. Winners & Losers: BioCON Data from Reich

24. Winners & Losers: Observed Responses at Elevated CO2 • 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. Diversity Increases CO2 Effect: Hypothetical Response Curves + N, + CO2 + N, - CO2 - N, + CO2 Production - N, - CO2 Species Richness 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. Current CO2 Elevated CO2

29. Current CO2 Elevated CO2

30. Current CO2 Elevated CO2 Community change Photos by T. Huxman & T. Esque

31. Predictions: Plant-animal interactions Predictions: Evolution • 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 • Because of the rapidity of increased CO2, evolution may have little potential role … BUT evolutionary response likely: • in species (e.g. pests) with large population sizes (>105), 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

32. Two contrasting points of view: • FACE or OTC experiments mimic future [CO2] so that observations • from the experiments represent ecosystem responses to [CO2]. • Current experiments exert an ecosystem perturbation – a step-increase in [CO2] – achieved primarily by altering carbon influx. • Solutions to step-increase problem: • 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 FACENETWORK 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. CDIAC DOCUMENTATION 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. DESCRIPTION and FORMAT OF THE ASCII DATA FILES Example: Contents and format of the hourly files, r*_wh_*.dat. SAS, FORTRAN, and C CODES TO ACCESS THE DATA Import code for each file type

37. F.U.N. Charges • How do the various experiments work together as a network? • Can we increase the efficiency of CO2 use? • What measurements are being conducted and can they be critically compared? • What general ecological principles are being discovered? • What is the value-added from the network?