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Eddy covariance - estimating ecosystem fluxes of
carbon and water
Asko Noormets, Jiquan ChenDept. Earth, Ecological and Environmental Sciences
The University of Toledo
Ge Sun, Steve McNultySouthern Global Change Program, USDA FS
Outline
1. Background - brief theory and history
2. What does it look like?
3. Carbon flux in a managed landscape
4. Significance
Principle of operation
• 3-D wind speed and direction
• CO2 and H2O concentrationHow do they co-vary
GEP + R = NEE ?
day day & night
Co-variance
-0.6
-0.3
0
0.3
0.6
12:21:45 12:21:46 12:21:48 12:21:50 12:21:52 12:21:53 12:21:55 12:21:57 12:21:58 12:22:00 12:22:02
u(z)
, m
s-1
583
583.75
584.5
585.25
586
[CO
2], mg m
-3
Theory
History (Baldocchi 2003 GCB)
Theoretical framework - Sir Osborne Reynolds (1895)
First application - Scrase (1930), momentum transfer, analog instruments
Also later, post WW II experiments, mostly focused on measuring the turbulent structure of atmospheric boundary layer rather than CO2 exchange.
First measurements of CO2 flux - Desjardins & Lemon (1974)
First measurements over forests - Baumgartner (1969), Denmead (1969), Jarvis (1976)
First application of open-path IRGA-s and sonic anemometers for CO2 flux
measurements - Anderson et al. (1984), Anderson & Verma (1986), Ohtaki (1984), Desjardins (1985)
First yearlong study - Wofsy et al. (1993), started in 1990
Flux measurement networks - Fluxnet, Ameriflux, CarboEuroflux etc.
Current questions - sources of interannual variation, winter fluxes, separating contribution from layers, separating soil heterotrophic and autotrophic R.
Ecosystem C fluxes
-20
-10
0
10
4/24 6/13 8/2 9/21 11/10 12/30 2/18 4/9
Date
Fc
(g C
O2 m
-2 d
-1)
NEE – net ecosystem exchange of carbonR – ecosystem respirationGEP – gross ecosystem productivity
Seasonal course - NEE, R, GEP
-250
-200
-150
-100
-50
0
50
100
150May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr
NE
E (
g C
m-2
mo
-1)
MHWMRPPBCCYMP
0
50
100
150
200
250
May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr
R (
g C
m-2
mo
-1)
-500
-450
-400
-350
-300
-250
-200
-150
-100
-50
0May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr
GE
P (
g C
m-2
mo
-1)
NEE – net ecosystem exchangeR – ecosystem respirationGEP – gross ecosystem productivity
Decomposing NEE
0
0.5
1
1.5
May Jun Jul Aug Sep
SRR
/R
-1
-0.5
0
0.5
1May Jun Jul Aug Sep
NEE
/GEP
MHWMRPPBCCYMP
-2
-1.5
-1
-0.5
0May Jun Jul Aug Sep
R/G
EP
Age effect on light response of GEP
-12
-6
0
60 20 40 60 80
-12
-6
0
60 20 40 60 80
PAR (mol m-2 d-1)PAR (mol m-2 d-1)
GE
P (
g C
O2 m
-2 d
-1)
Mixed hardwood3 years & 63 years
Red pine8 years & 65 years
Regression of residuals of AQ response
-2
-1
0
1
2
3
0 1 2 3
MHWMRPPBCCYMP
VPD (kPa)Res
id. (
µm
ol C
O2 m
-2 s
-1)
-4
-2
0
2
4
6
8
10
-100 0 100 200 300 400
MHWMRPPBCCYMP
Hs (W m-2 d-1)
Res
id. (
µm
ol C
O2 m
-2 s
-1)
Significance
• Narrows error margins for ecosystem C balance estimates (“missing carbon”).
• Sensitivity analysis of fluxes to environmental drivers. Differences in magnitude and seasonality.
• Due to being a spatially integrative technique (footprint), it can be linked to RS, and used to model exchange in larger scales.
• Quantitation of anthropogenic effects.