FACE Network

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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)
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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?

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Non-agricultural FACE Network
Base map courtesy CDIAC
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Global Vegetation Types
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FACE Design Protocols

• Mini-FACE BNL Other
• CO2 fumigation design 46 36 18
• Seasonal All year
• Yearly CO2 treatment period 77 23
• Daylight 24 hour Unknown
• 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 605
• 9 of sites have 1 elevated CO2

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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

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Turbulent Mixing Vortex Generators
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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 -- Be
lowground production Root 59 41 Microbial 32 68 Ca
rbon pools/fluxes 41 59 Nitrogen
pools/fluxes 41 59 ET / Soil water
content 54 46 Biodiversity Plants 91 9 Herbivores
32 68
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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

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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
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Enhancement dependence on leaf N
Data from Ellsworth et al.
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Enhancement dependence on leaf N
Data compiled from literature and unpublished
sources Duke, Rhinelander, Oak Ridge, Maricopa,
Nevada, Switzerland, Italy
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Predictions Productivity
After Strain Bazzazz (1983)
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Results Shoot production
Data from BERI, BioCON, FACT-I, FACTS-II, JRGCP,
NDFF, NZGraze, ORNL, Swiss
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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

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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)

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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

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Results Soil water at NDFF
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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

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Flow diagram from Evans
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Results Nutrient Cycling
Desert
Chaparral
Grassland
Conifer forest
Deciduous forest
Data from BassiriRad Evans
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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

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Winners Losers BioCON
Data from Reich
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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

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Diversity Increases CO2 Effect Hypothetical
Response Curves
N, CO2
N, - CO2
- N, CO2
Production
- N, - CO2
Species Richness
From Reich
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BioCON Biomass response (average 1998, 1999)
Reich et al. (2001) Nature
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Results Increased fire cycle
Smith et al. (2000) Nature
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Community change
Photos by T. Huxman T. Esque
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Predictions Evolution
Predictions Plant-animal interactions

• Increased CN 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 (
  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

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• 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.
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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?

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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)4
77-487. 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/o
rnldata.html
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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
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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?