Phenology and Carbon Exchange of Ecosystems

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Phenology Modulates Carbon and
Water Exchange of Ecosystems
Dennis Baldocchi
Siyan Ma
Ecosystem Sciences Div/ESPM
University of California, Berkeley
AGU 2006
B19, Land Surface Phenology, Seasonality and Water Cycle
Objectives
• Phenology and Vegetation-Atmosphere Interactions
• Role of Phenology on Carbon and Water Fluxes
–
–
–
–
–
Leaf Area Index, LAI
Photosynthetic Capacity, Vcmax
Annual Carbon Fluxes
Annual Evaporation
PBL Dynamics
• New Assessment of Phenology
– Temperature Deciduous Forest
• When Soil Temperature Exceeds Mean Annual Air Temperature
– Annual Grassland
• Amount of Rainfall in the Spring
Hopkins Law of Phenology
• Phenology differs by four days for every degree
of latitude, .every 5 degrees of latitude and every
400 feet of altitude
Andrew Delmar Hopkins
Schwartz, M. D., 1997.
Spring Index Models: An Approach to
Connecting Satellite and Surface Phenology.
In Phenology of Seasonal Climates
Phenology Affects Evaporation, which affects Atmospheric
Demand, and Vice Versa
14
vapor pressure (mb)
12
data of Schwartz and Karl (1990)
10
8
6
4
2
-60
-40
-20
0
20
Days before/after lilac leaf out
40
60
Phenology, a Measure of Global Change
Mean annual growing season in Europe increases by 10.8 days from 1981 to 1991.
Menzel and Fabian, Nature 1999
Spring Temperature Affects
Phenology and the Seasonality of
CO2 Exchange: case 1,
Deciduous Forests
Temperate Broadleaved
Deciduous Forest
5
4
3
-1
-2
-3
-4
)
-2
x
ma
-1
g
rin
sp
now
no s -)
(
T soil
(- )
R eco
g
rin
sp
rly
ea
NEE (gC m d )
e
lat
0
Vc
AI,
f( L
P=
GP
2
1
LAI=0
GPP=0;
Litterfall (+)
Reco=f(litterfall)(+)
:
snow )
+
(
(+)
T soil
; R eco
0
=
P
GP
Drought:
(-)
GPP(-); Re(-)
-5
Clouds:
PAR(-)
GPP=f(PAR)(+)
-6
-7
0
50
100
150
200
Day
250
300
350
Phenology Modulates Source-Sink via LAI
Walker Branch Watershed, TN
6
5
1995
1996
1997
1998
Leaf Area Index
4
3
2
1
0
0
50
100
150
200
250
300
350
Day
•Interannual Variability in Length of Growing Season > 30 days
•Latitudinal Variation in Length of Growing Season > 30 days
Spatial Gradients:
NEE and Length of Growing Season
Michigan, USA
Massachusetts, USA
Prince Albert, CANADA
Indiana, USA
Tennessee, USA
Denmark
Belgium
Ontario
Italy
Japan
100
Broad-Leaved Forests
0
NEE (gC m-2 yr-1)
-100
-200
-300
-400
-500
-600
-700
-800
100
150
200
Length of Growing Season
Baldocchi et al, 2001, BAMS
250
Year to Year differences in NEE across sites is due to
differences in Growing Season Length
Temperate Deciduous Forests
0
-100
NEE (g C m-2 year-1)
-200
-300
-400
-500
-600
CANOAK, Oak Ridge, TN
Published Measurements, r2=0.89
-700
-800
120
140
160
180
200
Days with NEE < 0
Baldocchi et al, 2001 Ecol Modelling
220
240
Caveat Emptor
• Growing Season Length has More
Explanatory Power across a Latitudinal
Gradient than at an Individual Site
• Additional factors explaining annual NEE
at a Single Site include:
– Absence/presence winter snow
– Occurrence of Summer Drought
– Extent of cloudiness
The Duration of Winter/Spring Rain affects
Phenology and the Seasonality of CO2
Exchange: case 2, Annual Grasslands
Grasslands
4
snow covered
dormant grass
GPP=0, Reco > 0
Autumn Rains:
T(-),  (++)
GPP(+), Reco(-)
ra
in
s
0
-2
L
GP ate
P( spr
+) in
g
-2
-1
NEE (gC m d )
2
Spring/Summer Drought
(-)
GPP(-); Reco(-)
Rain Pulse
Reco(++)
GPP=0
GPP > 0;
AM Frost:
GPP(-)
Tmin > 0 oC
GPP =f(LAI) (+)
-4
-6
0
50
100
150
200
250
300
Day
Mediterranean Grassland
Temperate C4 grassland
Data sources: Valentini et al. 1996; Baldocchi + Xu, unpublished; Verma +Suyker
350
Length of Rain Period affects Phenology of Annual Grassland
Annual Grassland, Ione, CA
0.5
2001
2002
2003
2004
Soil Moisture at 20 cm
0.4
0.3
0.2
0.1
0.0
0
50
100
150
200
250
300
350
Day
Interannual variation of Wet season can vary by > 50 days
Annual Grassland, Vaira Ranch
3.0
2001-2002
2002-2003
2003-2004
2004-2005
Leaf Area Index
2.5
2.0
1.5
1.0
0.5
0.0
-100
-50
0
50
100
150
200
Day of Year
Timing of Rainfall Can Force Substantial Interannual Variability in LAI
Remote Sensing Can be Used to study Phenology of Carbon Fluxes
Land Surface Water Index LSWI = (ρ860 - ρ1640)/(ρ860 + ρ1640)
0.0
0
-0.2
4
0
120
240
-4
PRI
14 day NEE
PRI
-0.06
-2
0
-0.08
2
PRI = (r531 - r570) / (r531 + r570)
-0.10
gC day
-120
-1
-4
gC day
0.2
MODIS - LSWI
Daily NEE
-1
LSWI
0.4
4
6
-120
-60
0
60
DOY after 1/1/2005
120
180
PRI and NEE
Falk, Baldocchi, Ma, in preparation
Humidity Deficits and Phenology:
Annual grassland near Ione California
o
Mean annual air temp 16.3 C
50
Tair (oC)
40
2001
2000
Max
30
20
10
Min
0
10
VPD (kPa)
8
6
4
2
0
300
100
200
DOY
Xu and Baldocchi, 2003 AgForMet
300
Amount of Rain During the Wet Season Affects NEE of
Annual CA Grassland and Savanna Woodland
Open Grassland
Savanna
Annual Flux (gC m-2)
1200
1000
800
GPP
Reco
NEE
600
400
200
0
-200
0
50
100
150
200
250
PPT3-6 (mm)
Ma, Baldocchi, Xu and Hehn, submitted, AgForMet
300 0
50
100
150
200
PPT3-6 (mm)
250
300
Seasonality of Model Parameters:
e.g. Photosynthetic Capacity
Quercus alba (Wilson et al)
Quercus douglasii (Xu and Baldocchi)
Live Fast, Die Young
In Stressed Environments
140
120
Vcmax
100
80
60
40
20
0
100
150
200
DOY
250
300
350
Annual and Spatial Variation in Photosynthetic Capacity,
Vcmax, for Deciduous Forests in North America (HV, WB) and
Europe (HE)
-2
-1
vx,25 (mol m s )
35
30
HE
HV
WB
25
20
15
10
5
0
-5
0
2
4
6
Month
Wang et al, 2006 GCB
8
10
12
6
5
4
3
2
1
0
80
60
40
20
0
0
10
20
Year
Wang et al, 2006 GCB
30
40
Canopy LAI
-2
-1
)
s
vx,25 (mol m
Interannual Variation in Ps Capacity
Seasonality of Vcmax is needed to simulate LE, H and NEE
-2
Modelled Fe (W m )
Latent heat (Fe)
120
80
40
0
-40
0
5
10
15
20
25
140
120
100
80
60
40
20
0
-20
-20 0 20 40 60 80 100120 140
-2
200
-2
Modelled Fh (W m )
Sensible heat (Fh)
Observed Fe (W m )
100
0
-100
0
5
10
15
20
25
120
100
80
60
40
20
0
-20
-40
-40 -20 0 20 40 60 80 100 120
-2
0
-1
-2
-3
-4
-5
0
Modelled NEE
NEE (Fc)
Observed Fh (W m )
-2
-3
-4
-5
0
5
10
15
Month
Wang et al, 2006 GCB
-1
20
25
-5
-4
-3
-2
-1
0
-2
-1
Observed NEE (mol m s )
Growing Season Length and ET, Field Data
Oak Ridge, TN
5
6
5
4
4
Leaf Area Index
E (mm d-1)
1996: 492 mm
1997: 519 mm
1996, Starts d121
1997, Starts d108
3
2
3
2
1
1
0
0
50
100
150
200
250
300
350
0
0
50
100
150
Day
200
Day
Year with Longer Growing Season (13 days)
Evaporated More (27 mm).
Other Climate Factors could have confounded results,
but Rg (5.43 vs 5.41 GJ m-2) and Tair (14.5 vs 14.9 C)
were similar and rainfall was ample (1682 vs 1435 mm)
Wilson and Baldocchi, 2000, AgForMet
250
300
350
Effect of Timing of Leaf-Out on Evaporation, Theory
Temperate Deciduous Forest
Oak Ridge, TN
7
Leaf out: D90
D100
D110
D120
D130
6
ET (mm d-1)
5
4
3
2
1
0
0
50
100
150
200
Day
250
300
350
Year to Year differences in LE is partly due to differences in Growing Season Length
CANOAK
700
690
Slope: -1.68 mm/day
-1
ET (mm y )
680
670
660
650
640
630
620
80
90
100
110
120
130
140
Date of Leaf-Out
Field data show that ET decreases by 2.07 mm for each day the
start of the growing season is delayed
Caveat Emptor
• Early Spring can be followed by Summer
Drought
– ‘Net spring CO2 uptake increased from 1994-2002,
whereas net growing season uptake did not... We
have shown that these opposing trends in summer
and spring are probably related to a drought-induced
reduction in summer photosynthesis…Thus warming
does not necessarily lead to higher CO2 uptake’
• Angert et al, 2005, PNAS
Phenology and PBL Growth
Walker Branch
Data of Davis + Baldocchi
3000
2500
PBL (m)
2000
1500
1000
500
0
0
50
100
150
200
250
300
350
Days
Deeper PBL Growth occurred after Leaf Out
Predicting Phenology
•
•
•
•
•
Growing Degree Days
Chill Degree Days
Chill Hours
Chill Degree Hours
Heat Degree Days
Tmax  Tmin
GDD   (
 Tref )
2
Critical Heat Units Need Calibration and are not Universal
Using the Onset of Photosynthesis as indicator of Phenology
Oak Ridge, TN 1996
4
3
1
-2
-1
NEE (gC m d )
2
0
-1
Coefficients:
b[0] 21.6
b[1] -0.183
r ² 0.696
-2
-3
-4
100
105
110
115
120
Day of Year
Baldocchi et al., 2005, Int J Biomet
125
130
135
Soil Temperature:
An Objective Indicator of Phenology??
Soroe, Denmark
Beech Forest
1997
20
NEE, gC m-2 d-1
Tair, recursive filter, oC
Tsoil, oC
15
10
5
0
-5
-10
0
50
100
150
200
day
Data of Pilegaard et al.
250
300
350
Soil Temperature:
An Objective Measure of Phenology, part 2
Temperate Deciduous Forests
160
150
140
Day NEE=0
130
Denmark
Tennessee
Indiana
Michigan
Ontario
California
France
Massachusetts
Germany
Italy
Japan
120
110
100
90
80
70
70
80
90
100
110
120
130
140
150
160
Day, Tsoil >Tair
Data of: Baldocchi, Wofsy, Pilegaard, Curtis, Black, Fuentes, Valentini, Knohl, Yamamoto. Granier, Schmid
Baldocchi et al. Int J. Biomet, 2005
Onset of Spring is Delayed ~ 5 days with each
degree reduction in mean temperature
160
Day of NEE = 0
140
120
100
Coefficients:
b[0]: 169.3
b[1]: -4.84
r ²: 0.691
80
60
4
6
8
10
12
Mean Air Temperature, C
Baldocchi et al. Int J. Biomet, 2005
14
16
18
When Transformed onto a Climate Map, We observe a
General Correspondence with N-S gradient Obtained from
the denser Phenology Network
d140
d90
Summary and Conclusions
• The Length of the Growing Season has significant effects on annual
Carbon and Water exchange
– As long as Warmer Springs are not followed by Summer Drought
• The correspondence between soil temperature and mean annual air
temperature has a strong correlation with Spring Leaf-out
– The metric does not need tuning/calibration and works across a wide
latitudinal range.
• Processes derived from Networks of Flux Measurement Sites can
be Transformed onto Climate Space to produce Phenology Maps
• New Technologies for monitoring Phenology
– Eddy Flux, $$$$
– Digital Camera, $$
– LED, NDVI/PRI Sensor, $
Acknowledgements
• Funding
– DOE/TCP, NIGEC/WESTGEC, CalAgExpt
Station
• Collaborators
– YingPing Wang
– Matthias Falk
– Liukang Xu
– Kell Wilson
– AmeriFlux/Fluxnet Colleagues
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