FACE Network*

Presented by: Bob NowakStan Smith

Assistance from: Hormoz BassiriRadTerri CharletDave EllsworthDave EvansLynn FenstermakerEric KnightPeter ReichParticipants of FACE 2000 Conference

* aka FACE Universal Network (Norby 2000)

F.U.N. Charges

1. How do the various experiments work together as a network?

2. Can we increase the efficiency of CO2 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?

Non-agricultural FACE Network

ForestGrassland

Desert

Forest

Forest

Grassland

Chaparral

Grassland

Grassland

MEGARICH

Grassland

MEGARICH

BERI

BERI

MEGARICH

MEGARICH

BERI

MEGARICH

BERIBERI

ForestSavanna

Base map courtesy CDIAC

Global Vegetation Types

Tundra

Taiga

TemperateForest

Desert

Savanna

TropicalSeasonal Forest

TropicalRainforest

Grassland

TemperateRainforest

FACE Design & Protocols

Mini-FACE BNL OtherCO2 fumigation design 46% 36% 18%

Seasonal All yearYearly CO2 treatment period 77% 23%

Daylight 24 hour UnknownDaily 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]

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

Turbulent Mixing: Vortex Generators

Variables Measured

Yes (%) No / Unk (%)Physiology

Leaf gas exchange 54 46Root physiology 27 73

Aboveground productionBiomass 100 --Litter 59 41Carbon pools/fluxes 36 64Nitrogen pools/fluxes 100 --

Belowground productionRoot 59 41Microbial 32 68Carbon pools/fluxes 41 59Nitrogen pools/fluxes 41 59

ET / Soil water content 54 46Biodiversity

Plants 91 9Herbivores 32 68

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

Bet

ula

Pop

ulus

Ace

rB

rom

usA

grop

yron

Sol

idag

oP

inus

Liqu

idam

bar

Larr

eaA

mbr

osia

Sw

eetg

umC

otto

n

Rye

Pop

lar

Enh

ance

men

t of A

net b

y C

O2

(Ele

v/A

mb)

0.0

0.6

0.8

1.0

1.2

1.4

1.6

1.8

Dominant species responses

to elevated CO2: how large is enhancement? Data from:Ellsworth et al.

Yellow Bars:compiled from literatureand unpublished results

WI MN NC NV

Elev Na/Amb Na

0.6 0.8 1.0 1.2 1.4

Enh

ance

men

t,E

lev

A/A

mb

A

0.8

1.0

1.2

1.4

1.6

1.8BromusPoaLupinus

Achillea

Solidago

Anemone

Agropyron

Oenothera

Betula

Populus

Acer

Pinus

Liquidambar

Larrea

Ambrosia

Expected

Enhancement dependence on leaf N

Data from:Ellsworth et al.

Elev N / Amb N

0.6 0.8 1.0 1.2 1.4

Enc

hanc

emen

t,E

lev

A /

Am

b A

0.8

1.0

1.2

1.4

1.6

1.8

Woody Species

Herbaceous SpeciesExpected

Enhancement dependence on leaf NData compiled from literature and unpublished sources:Duke, Rhinelander, Oak Ridge, Maricopa, Nevada, Switzerland, Italy

Predictions: Productivity

After Strain & Bazzazz (1983)

Xeric Moderate MesicDrought stress

Relative response to CO2High Low

Nut

rien

t po

orM

oder

ate

Nut

rien

t ri

ch

Nut

rien

t av

aila

bilit

y

Rel

ativ

e re

spon

se to

C

O2

Lo

wH

igh

Hot desert, alluvial

Hot desert

Alpine

Temperate deciduous

forest

Chaparral

Tropical forest

Boreal forest

Tundra

Marsh / Estuary

SavannaGrassland

Cold desert

Temperate coniferous

forest

Data from BERI, BioCON, FACT-I, FACTS-II,JRGCP, NDFF, NZGraze, ORNL, & Swiss

Annual precipitation (mm)

0 1000 2000 Bog

CO

2 en

hanc

emen

t of

sho

ot p

rodu

ctio

n

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Results: Shoot production

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

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)

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

##&& ## & ##

Soil depth: 0 - 0.5 m

Oct Feb Jun Oct Feb Jun Oct Feb Jun Oct Feb Jun

Soi

l moi

stur

e co

nten

t (m

m)

0

20

40

60

80

100Ambient CO2

Elevated CO2Non-ring control

1997 1998 1999 2000 2001

Treatment: NSTreatment X Date: <0.001

& = Ambient > Elevated # = Non-ring > Amb/Elev

Results: Soil water at NDFF

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

Soil Microbes

So

ilO

rga

nic

Ma

tter

LabilePool

RecalcitrantPool

Available N

Gaseous Loss

PlantsLitter

CO2CNN

Mycorrhizae

Flow diagram from Evans

Results: Nutrient Cycling

15 N

elv

- 1

5 Nam

b (o / oo

)

-3

-2

-1

0

1

2

3

Deciduous forest

Conifer forest

Grassland

Chaparral

Desert

Data from BassiriRad & Evans

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

response to CO2%

cha

nge

in

tota

l pla

nt b

iom

ass

-10

0

10

20

30

response to N

c4 g

rass

es

c3 g

rass

esfo

rbs

legum

es

c4 g

rass

es

c3 g

rass

esfo

rbs

legum

es

% c

hang

e in

tota

l pla

nt N

poo

ls

0

10

20

30

40

a b

c d

Winners & Losers: BioCON

Data from Reich

Winners & Losers: Observed Responses at Elevated CO2

Shift to dicots in grasslandsSwiss – 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

Species Richness

Pro

du

ctio

n+ N, + CO2

+ N, - CO2

- N, - CO2

- N, + CO2

Diversity Increases CO2 Effect: Hypothetical Response Curves

From Reich

Number of species

Cha

nge

in b

iom

ass

(g/m

2 )[r

espo

nse

to e

leva

ted

CO

2 an

d/or

N]

com

pare

d to

am

bien

t CO

2 an

d am

bien

t N

0

50

100

150

200

250

300

350

400

1 4 9 16 1 4 9 16 1 4 9 16

elevatedCO2 effect

(ambient N)

N additioneffect

(ambient CO2)

combined elevated CO2

and N addition effect

+18

%

+7%

+10

%+

18% +

22%

+2%

+11

%

+17

%+

15%

+34

%+

36%

+25

%

BioCON –Biomass response (average 1998, 1999)

Reich et al. (2001) Nature

Results: Increased fire cycle

Smith et al. (2000) Nature

Elevated CO2Current CO2

Elevated CO2Current CO2

Community change

Photos by T. Huxman & T. Esque

Elevated CO2Current CO2

Predictions: Evolution

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

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

Two contrasting points of view:

1. FACE or OTC experiments mimic future [CO2] so that observations from the experiments represent ecosystem responses to [CO2].

2. Current experiments exert an ecosystem perturbation – a step-increase in [CO2] – 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.

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?

Data Availability

CO2

WeatherGas ExchangeGrowthSpecies ListsDocumentation

CO2

WeatherDocumentation

CO2

WeatherGrowthDocumentationGas ExchangeGrowthRoot DynamicsSoilsNPP

DATA TYPE BE

RI

Eu

rop

e,

5 si

tes

OR

NL

Ne

w Z

ea

lan

d

ME

GA

RIC

H

PO

PF

AC

E (

Ita

ly)

Sw

iss

As

pe

n F

AC

E

Oa

k R

idg

e,

TN

Du

ke

FA

CT

S I

, N

C

Ma

ric

op

aA

rizo

na

Ce

ntr

al

CA

Sk

y O

ak

sS

ou

the

rn C

A

ND

FF

SO

UR

CE

Ne

vad

a

Eu

rop

e,

6 si

tes

Bio

CO

NC

ed

ar

Ck,

MN

Ja

sp

er

Rid

ge

Rh

ine

lan

de

r,W

I

NZ

Gra

ze

+/-- +/--

+ ++ + +

++

+ + +

HO

ME

PA

GE

W

EB

SIT

E

++

CD

IAC

+

+

Gie

ss

en

Ge

rma

ny

OZ

FA

CE

Au

stra

lia

+

BN

L + +++ +

+ ++ +

Co

mp

iled

Oth

er,

R

el.

Re

sp

on

se

s +++

+ + + + + ++ + + + + + + ++ + + + + ++ + + +

+ + +

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

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

Variable Variable

type Variable width

Starting column

Ending column

Units Definition and comments

PAR2m Real 10 54 63 umol/m2/s Mean incident photosynthetically active radiation,measured at 2m above the ground

SAS, FORTRAN, and C CODES TO ACCESS THE DATAImport code for each file type

F.U.N. Charges

1. How do the various experiments work together as a network?

2. Can we increase the efficiency of CO2 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?