factors influencing co 2 exchange in northern ecosystems - a synthesis (kind of) anders lindroth...
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Factors influencing CO2 exchange innorthern ecosystems - a synthesis (kind of)
Anders LindrothLund University
Geobiosphere Science CentrePhysical Geography and Ecosystems Analysis
Sölvegatan 12, 223 62 Lund, [email protected]
Part of synthesis work within the Nordic Centre for Ecosystem Carbon Exchange and Its Interactions With the Climate System, NECC (and partly from LUSTRA1)23 papers to appear in two coming issues of Tellus B
Co- authors:
Mika Aurela, Brynhildur Bjarnadottir, Torben Röjle Christensen,Ebba Dellwik, Achim Grelle, Andreas Ibrom, Torbjörn Johansson, Leif Klemedtsson, Fredrik Lagergren,Harry Lankreijer, Ola Langvall,Samuli Launiainen, Tuomas Laurila, Magnus Lund, Eero Nikinmma,Mats Nilsson, Kim Pilegaard, Janne Rinne, Jörgen Sagerfors,Bjarni Sigurdsson, Lena Ström, Juha-Pekka Tuovinen, Timo Vesalaand Per Weslien
1 LUSTRA; A swedish research programme on developing land-use strategies for reducing emissions in forestry
• Part A1 - understanding differences in CO2 exchange between forests of different species, age, climate and soils
• Part B2 - Productivity and respiration in the forest of similar species but growing in different climates
• Part C3 - Factors controling CO2 exchange in peatlands
1Lindroth, A., Lagergren, F., Aurela, M., Bjarnadottir, B., Christensen, T., Dellwik, E., Grelle, A., Ibrom, A., Johansson, T., Lankreijer, H., Launiainen, S., Laurila, T., Mölder, T., Nikinmaa, T., Pilegaard, K., Sigurdsson B. and Vesala, T. 2007. Leaf area index is primary scaling parameter for both gross photosynthesis and ecosystem respiration of Northern deciduous and coniferous forests. Tellus B (accepted)
2Lindroth, A., Klemedtsson, L., Grelle, A., Weslien, P. and Langvall, O. 2007. Net ecosystem exchange, productivity and respiration in three spruce forests in Sweden. Biogeochemistry (in press).
3Lindroth, A., Lund, M., Nilsson, M., Aurela, M., Christensen, T.R., Laurila, T., Rinne, J., Sagerfors, J., Ström, L., Tuovinen, P. and Vesla, T. 2007. Environmental controls on CO2 exchange of boreal mires in northern Europe. Tellus B doi: 10.1111/j.1600-0889.2007.00310.x
Part A - Eight different forests
T = 8.3°CP = 730 mmBeech
T = 5.5°CP = 527 mmPine/Spruce
T = 3.0°CP = 700 mmPine
T = -1.0°CP = 429 mmPine
T = 1.2°CP = 523 mmSpruce
T = -0.9°CP = 305 mmBirch
T = 3.4°CP = 738 mmLarch
Method:
• Day and night separately• One ’normal’ year from all sites• Fco2 only for u*>threshold• Two-week means
Light response curve
Q (mol m-2 s-1)
0 500 1000 1500 2000 2500 3000
Fc
(m
ol m
-2 s
-1)
-15
-10
-5
0
5
ddsatc
dsatcc RRFQ
RFF
exp1
= initial slope of line
Rd
Fcsat
GPP
Daytime analysis
13.227
1
02.56
1308.56
10 e Tnight RNEE
Nighttime analysis
(Lloyd & Taylor, 1994)
Half-month no.
0 2 4 6 8 10 12 14 16 18 20 22 24
NE
En
igh
t ( m
ol m
-2s-1
)
0
2
4
6
8
10
NorundaSkyttorpFlakalidenAbiskoHyytiäläSoroeSodankyläVallanes
Lloyd & Taylor equation
Mean nighttime air temperature (°C)
-15 -10 -5 0 5 10 15 20
NE
Eni
ght (
mol
m-2
s-1)
0
2
4
6
8
10
NorundaSkyttorpFlakalidenAbiskoHyytiäläSoroeSodankyläVallanes
Mean nighttime air temperature (°C)
-20 -15 -10 -5 0 5 10 15 20
Res
idua
l
-2
-1
0
1
2
r2 = 0.75
-20 -15 -10 -5 0 5 10 15 20
0.0
0.5
1.0
1.5
2.0
2.5
NorundaSkyttorpFlakalidenAbiskoHyytiäläSoroeSodankyläVallanes
NE
En
igh
t rel
ativ
e to
the
resp
irat
ion
rate
at
10 °
C
0 2 4 6 8 10 12 14 16 18 20 22 24
Fcs
at (
mol
m-2
s-1)
0
5
10
15
20
25NorundaSkyttorpFlakalidenAbiskoHyytiäläSoroeSodankyläVallanes
0 2 4 6 8 10 12 14 16 18 20 22 24
(
mm
ol
mol
-1)
-40
-20
0
20
40
60
80
100
120
Half-month no.
0 2 4 6 8 10 12 14 16 18 20 22 24
Rd
(m
ol m
-2s-1
)
-2
0
2
4
6
8
10
12
Two-week means ofparameter values
• air temperature• PAR• VPD• Soil water content• Leaf area index• Species• Age• (Latitude)
LAI
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
GP
Pm
ax
(m
ol m
-2s-1
)
0
5
10
15
20
25
30
y= 0.588 + 4.326xr ² = 0.807
LAI
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
Fcs
at ( m
ol m
-2s-1
)
0
5
10
15
20
25
y= -1.607 + 3.840xr ² = 0.769
LAI
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
m
mol
m
ol-1
)
10
20
30
40
50
60
y = 15.728 + 6.669xr2 = 0.69
LAI
1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5
Rd
(m
ol m
-2s-1
)
1
2
3
4
5
6
7
8
9
Y = 0.826 + 1.204xr ² = 0.861
54 56 58 60 62 64 66 68 70
Fcs
at (
mol
m-2
s-1)
468
10121416182022
54 56 58 60 62 64 66 68 70G
PP
max
( m
ol m
-2s-1
)
468
10121416182022
Latitude
54 56 58 60 62 64 66 68 70
(
mol
mol
-1)
20
25
30
35
40
45
50
55
60
54 56 58 60 62 64 66 68 70
Rd
(m
ol m
-2s-1
)
2
3
4
5
6
7
8
54 56 58 60 62 64 66 68 70
Nor
m G
PP
max
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m F
csat
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m R
d
0.4
0.6
0.8
1.0
1.2
1.4
r2 = 0.932 r2 = 0.932
r2 = 0.002r2 = 0.058
r2 = 0.054r2 = 0.046
r2 = 0.814r2 = 0.814
.and after normalizing for LAI-dependence
What about correlation with latitude?(reminding about Valentini et al., 2000)
54 56 58 60 62 64 66 68 70
Fcs
at (
mol
m-2
s-1)
468
10121416182022
54 56 58 60 62 64 66 68 70G
PP
max
( m
ol m
-2s-1
)
468
10121416182022
Latitude
54 56 58 60 62 64 66 68 70
(
mol
mol
-1)
20
25
30
35
40
45
50
55
60
54 56 58 60 62 64 66 68 70
Rd
(m
ol m
-2s-1
)
2
3
4
5
6
7
8
54 56 58 60 62 64 66 68 70
Nor
m G
PP
max
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m F
csat
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m R
d
0.4
0.6
0.8
1.0
1.2
1.4
r2 = 0.932 r2 = 0.932
r2 = 0.002r2 = 0.058
r2 = 0.054r2 = 0.046
r2 = 0.814r2 = 0.814
.and after normalizing for LAI-dependence
54 56 58 60 62 64 66 68 70
Fcs
at (
mol
m-2
s-1)
468
10121416182022
54 56 58 60 62 64 66 68 70G
PP
max
( m
ol m
-2s-1
)
468
10121416182022
Latitude
54 56 58 60 62 64 66 68 70
(
mol
mol
-1)
20
25
30
35
40
45
50
55
60
54 56 58 60 62 64 66 68 70
Rd
(m
ol m
-2s-1
)
2
3
4
5
6
7
8
54 56 58 60 62 64 66 68 70
Nor
m G
PP
max
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m F
csat
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m
0.4
0.6
0.8
1.0
1.2
1.4
54 56 58 60 62 64 66 68 70
Nor
m R
d
0.4
0.6
0.8
1.0
1.2
1.4
r2 = 0.932 r2 = 0.932
r2 = 0.002r2 = 0.058
r2 = 0.054r2 = 0.046
r2 = 0.814r2 = 0.814
After normalization for the LAI-dependency - no correlation
with latitude!
Stand age (yrs)
0 20 40 60 80 100 120
Nor
mal
ized
Rd
0.8
0.9
1.0
1.1
1.2
1.3
y = 0.877 + 0.002214xr ² = 0.700
..but stand age does matter
Conclusions:
• Ecosystem respiration is well determined by the Lloyd & Taylor equation with only one fitting parameter, the respiration rate at 10°C.
• Leaf area index is the parameter that best explaines between stand variations in parametes controling respiration as well as gross photosynthesis
• After correction for leaf area, stand respiration shows a weak dependency on stand age
Part B - Three similar forests(all are ca. 40 yrs old spruce stands)
T = 5.5°C; P = 688 mmGley podzolSoil0-100 C = 23 kg m-2
Basal area = 32.3 m2 ha-1
T = 3.4°C; P = 613 mmPodzolSoil0-100 C = 5.9 kg m-2
Basal area = 14.7 m2 ha-1
T = 1.2°C; P = 523 mmPodzolSoil0-100 C = 7.2 kg m-2
Basal area = 20.7 m2 ha-1
Method:• Grouping into bi-weekly periods• Filled when u*<threshold- light response fkn for daytime- exp fkn for nighttime• Components separation: Pg = Fcmeas- modelled Reco
• Biomass increment from empirical functions within foot- print area• Litterfall & fine root turnover measured in nearby plots
Pn a constant fraction of Pg?
Pg(g C m-2yr-1)
700 800 900 1000 1100 1200 1300 1400
Pn
(g C
m-2
yr.1
)
100
200
300
400
500
600
y = 0.358 x(0.43 - 0.31)
Conclusions:
• Norunda is not unique in being a ’looser’!
• Pn is probably not a constant fraction of Pg but varies in the range 30-45%.
• Unexpected very large losses of soil carbon
• Large difference in NEP between forests of the same species and age
Part C - Factors controling CO2 exchange in peatlands
T = 6.2°C; P = 700 mmTemperate ombrotrophic bog
T = 3.0°C; P = 713 mmBoreal oligotrophic fen
T = 1.2°C; P = 523 mmBoreal oligotrophicminerotrophic mire
T = -1.1°C; P = 474 mmSub-arctic mesotrophic fen
Fäje myrThe source area is dominated by a mosaic of
hummocks, lawns and carpets
SiikanevaThe source area is dominated by sedges and moss carpet
Degerö Stormyr The source area is dominated by a lawn
plant community
KaamanenThe source area is dominated by the hummock-
hollow microstructure
Questions asked:
• Similarities/differences in seasonal dynamics of NEE, GPP & Reco • Similarities/differences in responses of respiration and photosynthesis to enviromental parameters among different types of Nordic peatlands?
• What are the major controls of CO2 exchanges?
Methods
• De-trending of seasonal effects were made using dummy variable
• Total ecosystem respiration during daytime was estimated as the difference between measured NEE and estimated GPP
• GPP was estimated using fitted bi-weekly light-response functions
• Datasets were further divided into 14-days periods for parameter estimations
• One year of data separated into DAYTIME and NIGHTTIME periods
• The same method was used at all sites (i.e., Euroflux methodology)
• Half hourly fluxes of CO2 net exchange between peatland surface and atmosphere measured by eddy covariance under well-mixed conditions (u*>0.1)
Eddy Covariance Method
F
'' cwF
-1.00.01.0
0 5 10 15 20
w
348350352
0 5 10 15 20
CO
2
-1.5
0.0
1.5
0 5 10 15 20
w'C
O2'
w
CO2
'' 2COw
w'C'1
N(w w)(C C)i
i 1
N
i
Weather during growing season
Apr May Jun Jul Aug Sep Oct Nov
Q ( m
ol m
-2s-1
)
0
200
400
600
800
1000
FäjeDegeröKaamanenSiikaneva
Apr May Jun Jul Aug Sep Oct Nov
Ta
da
y (°
C)
0
5
10
15
20
25
Apr May Jun Jul Aug Sep Oct Nov
VP
D (
hPa)
0
2
4
6
8
10
Apr May Jun Jul Aug Sep Oct Nov
WT
D (
cm)
-30
-20
-10
0
10
20
30
May
Hour2 4 6 8 10 12 14 16 18 20 22 24
NE
E (
mg
m-2
s-1)
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15June
Hour2 4 6 8 10 12 14 16 18 20 22 24
NE
E (
mg
m-2
s-1)
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
July
Hour2 4 6 8 10 12 14 16 18 20 22 24
NE
E (
mg
m-2
s-1)
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
August
Hour2 4 6 8 10 12 14 16 18 20 22 24
NE
E (
mg
m-2
s-1)
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
September
Hour2 4 6 8 10 12 14 16 18 20 22 24
NE
E (
mg
m-2
s-1)
-0.20
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
FäjeDegeröKaamanenSiikaneva
Mean diurnalvariation in NEE during summer
Seasonal variationof components
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
NE
E (
g m-2
)
-100
-80
-60
-40
-20
0
20
FäjeDegeröKaamanenSiikaneva
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecG
PP
(g
m-2)
-225
-200
-175
-150
-125
-100
-75
-50
-25
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Re
co (
g m
-2)
0
25
50
75
100
125
150
175
Seasonal variationof components
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
NE
E (
g m-2
)
-100
-80
-60
-40
-20
0
20
FäjeDegeröKaamanenSiikaneva
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecG
PP
(g
m-2)
-225
-200
-175
-150
-125
-100
-75
-50
-25
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Re
co (
g m
-2)
0
25
50
75
100
125
150
175
Seasonal variationof components
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
NE
E (
g m-2
)
-100
-80
-60
-40
-20
0
20
FäjeDegeröKaamanenSiikaneva
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecG
PP
(g
m-2)
-225
-200
-175
-150
-125
-100
-75
-50
-25
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Re
co (
g m
-2)
0
25
50
75
100
125
150
175
Relationship between GPP, Reco and environmental variables
Independent variables:
- GPP- Reco- GPP_res- Reco_res- GPP_res_norm- Reco_res_norm
Dependent variables:
- Air temperature- Photon flux density (PPFD)- Vapour pressure deficit (VPD)- Water table depth WTDa (whole season) WTDb (period of decreasing WTD)
GP
P (
g C
m-2
)
-250
-200
-150
-100
-50
0
Period
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
GP
P_r
es (
g C
m-2
)
-80
-40
0
40
80
120
New de-trended GPP variable
GPP dummy
Measured GPP
De-trending for seasonal effects
Normalizing for temperature dependencies
Temperature
6 8 10 12 14 16 18 20 22 24
GP
P_r
es
(g C
m-2
)
-80
-60
-40
-20
0
20
40
60
80
100
y = 105.32 - 6.55*T
New seasonally de-trended and temperature normalized variable:
GPP_res_norm = GPP_res/f(T)
Fäje
-5 0 5 10 15 20 25
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
Kaamanen
-15 -10 -5 0 5 10 15
0.00
0.02
0.04
0.06
0.08
0.10
Siikaneva
-15 -10 -5 0 5 10 15 20
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
Degerö
-20 -15 -10 -5 0 5 10 15 20
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
Reco = f(Tan)
Tannight eRNEE 0
Fäje Degerö Kaamanen Siikaneva All sites
r2 0.9454 0.9518 0.9324 0.9507 0.8601
R0 0.0262 0.0124 0.0151 0.0097 0.0223
0.0849 0.1860 0.1343 0.1646 0.0980
• differences in base respiration and temperature sensitivity due to litter quality?
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
GPP GPP_res GPP_res_norm Reco Reco_res Reco_res_norm
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
Ta PPFD VPD WTDa WTDb GPP Reco
De
term
ina
tio
n c
oe
ffic
ien
t (-
)
0.0
0.2
0.4
0.6
0.8
1.0
Fäje myr
Degerö
Kaamanen
Siikaneva
Regression analysis
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
GPP GPP_res GPP_res_norm Reco Reco_res Reco_res_norm
Ta PPFD VPD WTDa WTDb GPP Reco
0.0
0.2
0.4
0.6
0.8
1.0
Ta PPFD VPD WTDa WTDb GPP Reco
De
term
ina
tio
n c
oe
ffic
ien
t (-
)
0.0
0.2
0.4
0.6
0.8
1.0
Fäje myr
Degerö
Kaamanen
Siikaneva
GPP (g C m-2)
-200 -150 -100 -50 0
Rec
o (g
C m
-2)
0
50
100
150
200
y = 15.39 - 0.756xr ² = 0.9653
Fäje Degerö
-200 -150 -100 -50 0
0
50
100
150
200
y = 8.44 - 0.643xr ² = 0.9270
GPP (g C m-2)
Rec
o (g
C m
-2)
Kaamanen
-200 -150 -100 -50 0
0
50
100
150
200
y = 12.67 - 0.458xr ² = 0.8934
Rec
o (g
C m
-2)
GPP (g C m-2)
Siikaneva
-200 -150 -100 -50 0
0
50
100
150
200
y = 10.72 - 0.555xr ² = 0.9098
Rec
o (g
C m
-2)
GPP (g C m-2)
Today Reco is 50 - 80% of GPP - how sustainable is this relationship?
Fäje
Siikaneva
Degerö
Kaamanen
-120
-100
-80
-60
-40
-20
0
-10 -5 0 5 10 15Ta (° C)
NE
E (
g C
O2
m-2
)
R2 = 0.41
NE
E (
g C
m-2)
What about other peatlandsin northern hemisphere?
Conclusions
• Apart from a high correlation between the two main components themselves, i.e., respiration and photosynthesis, temperature was the single most important variable in explaining the variation in the component fluxes
• Surprisingly, gross primary productivity was, also after de-trending the inherent seasonal variation, found to be more sensitive to temperature than respiration for the actual sites
• Water table depth explained variations in respiration and photsynthesis only during consistent drying up phases
• Wetlands seems to be small but consistent sinks
Thanks for your attention!