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FOR ONLINE PUBLICATION ONLY
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Supplementary material
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FIGURE LEGENDS
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Fig. S1 Seasonal (a, c, e) and interannual variability (b, d, f) in climatic variables
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(PAR, PPT, Ta, Ts, SWC and VPD) from 2003 to 2009 at QYZ. The scaled monthly
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variables were calculated by (Xi - mean)/SD, where Xi is a value of climatic
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variables in a specific month from 2003-2009. The mean and SD (standard
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deviation) were from all the 84 monthly values. The values and error bars on
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panels a, c, e are the means and SDs of scaled monthly variables in equivalent
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months from 2003 to 2009, in which SD represent the interannual variability in
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climate of the specific month. The values of interannual variability on panels b, d, f
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are scaled by annual variables. The monthly PAR, PPT, Ta, Ts, SWC and VPD were
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534±244 μ mol m-2s-1, 95±74 mm mon-1, 18.2±8.0 ℃, 17.8±6.5 ℃, 0.32±0.034,
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and 0.56±0.35 kPa (mean±SD). The annual PAR, PPT, Ta, Ts, SWC and VPD were
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6884±1009 mol m-2 y-1, 1140±186 mm y-1, 18.2±0.30 ℃ , 17.8±0.11 ℃ ,
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0.32±0.016, and 0.57±0.067 kPa.
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Fig. S2 Seasonal (a, c, e) and interannual variability (b, d, f) in climatic variables
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(PAR, PPT, Ta, Ts, SWC and VPD) from 2005 to 2009 at MOZ. Scaled variables
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were calculated by the same method in Figure S1. The monthly PAR, PPT, Ta, Ts,
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SWC and VPD were 347±150 μ mol m-2s-1, 85±62 mm mon-1, 12.9±9.2 ℃,
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13.1±7.3 ℃, 0.35±0.094, and 0.66±0.36 kPa. The annual PAR, PPT, Ta, Ts, SWC
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and VPD were 10972±917 mol m-2 yr-1, 1035±330 mm yr-1, 13.0±0.80 ℃,
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13.2±0.72℃, 0.35±0.078, and 0.67±0.094 kPa.
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Fig. S3 Seasonal (a, c, e) and interannual variability (b, d, f) in climatic variables
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(PAR, PPT, Ta, Ts, SWC and VPD) from 2005 to 2009 at DK1. Scaled variables
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were calculated by the same method in Figure S1. The monthly PAR, PPT, Ta, Ts,
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SWC and VPD were 335±118 μ mol m-2s-1, 84±45 mm mon-1, 15.0±7.5 ℃,
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15.8±7.5 ℃, 0.33±0.11, and 0.61±0.26 kPa. The annual PAR, PPT, Ta, Ts, SWC
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and VPD were 10701±571 mol m-2 yr-1, 1022±191 mm yr-1, 15.1±0.43 ℃,
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16.5±1.2℃, 0.32±0.042, and 0.62±0.11 kPa.
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Fig. S4 Seasonal (a, c, e) and interannual variability (b, d, f) in GPP for the study
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period at QYZ, MOZ and DK1. The scaled GPP was calculated by (Xi - mean)/SD,
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where Xi is GPP in a specific month for the study period. Panels b, d, f represent
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observed and modeled annual GPP. Error bars in modeled values are the range of
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the 95% credible interval predicted by the empirical model. The grey dashed
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horizontal lines are the means of the observed annual GPP.
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Fig. S5 Seasonality (a, c, e) and interannual variability (b, d, f) in RE for the study
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period at QYZ, MOZ and DK1. The calculation of scaled RE and the meaning of
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the error bars are the same as in Figure S4.
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Fig. S6 Comparison of modeled and observed GPP at QYZ (a), MOZ (b) and DK1 (c)
for the study period. The values represent the weekly mean GPP.
Fig. S7 Comparison of modeled and observed RE at QYZ (a), MOZ (b) and DK1 (c)
for the study period. The values represent the weekly mean RE.
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Fig. S8 Daily Am (a) and Q10 (b) from 2005 to 2009 at MOZ. The values were
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obtained from the equations Am = b0 + b1×Ta + b2×Ta2+b3×VPD + b4×VPD2 and
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Q10 = a0 + a1×Ts +a2×SWC using the values of parameters from the
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parameterization of the empirical model.
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Fig. S9 Daily Am (a) and Q10 (b) from 2003 to 2007 at DK1. The values were obtained
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from the equations Am = b0 + b1×Ta + b2×VPD + b3×VPD2 and Q10 = a0 + a1×Ts
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+a2×SWC + a3×Ts×SWC using the values of parameters from the parameterization
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of the empirical model.
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Fig. S10 Contributions of climatic and biotic effects to interannual variability in NEE
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(a-d), GPP (e-h) and RE (i-l) of MOZ at daily, weekly, monthly and seasonal scales.
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The values were derived by partitioning the variance by analysis of variance
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(ANOVA) in crossed model predictions at the specific day (or week, month, season)
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of the year.
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Fig. S11 Contributions of climatic and biotic effects to interannual variability in NEE
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(a-d), GPP (e-h) and RE (i-l) of DK1 at daily, weekly, monthly and seasonal scales.
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The values were derived by partitioning the variance by analysis of variance
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(ANOVA) in crossed model predictions at the specific day (or week, month, season)
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of the year.
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(b)
(a)
PAR
PPT
PAR
PPT
2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
-2
(d)
(c)
Ta
Ts
Ta
Ts
2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
-2
(f)
(e)
SWC
VPD
SWC
VPD
2
2
1
0
0
-1
-2
-2
J
66
M A
M J
J
A
Month
64
65
F
Fig. S1
S
O
N D
2003 2004 2005 2006 2007 2008 2009
Year
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
(a)
PAR
PPT
(b)
PAR
PPT
2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
(c)
Ta
Ts
(d)
Ta
Ts
2
-2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
(e)
SWC
VPD
(f)
SWC
VPD
2
-2
2
1
0
0
-1
-2
-2
J
F M A M
J
J
A
Month
67
68
69
Fig. S2
S O N D
2005
2006
2007
Year
2008
2009
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
(a)
PAR
PPT
(b)
PAR
PPT
2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
(c)
Ta
Ts
(d)
Ta
Ts
2
-2
2
1
0
0
-1
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
-2
(e)
SWC
VPD
(f)
SWC
VPD
2
-2
2
1
0
0
-1
-2
-2
J
F M A M
J
J
Month
70
71
72
Fig. S3
A
S O N D
2003
2004
2005
Year
2006
2007
Anomaly
(dimensionless)
Anomaly
(dimensionless)
4
)
1
Annual GPP ( g C m yr
0
-1
1500
1400
1300
-1
-2
(c) MOZ
1200
1400
1
)
(d) MOZ
2
Annual GPP ( g C m yr
Index
1
0
1000
-2
-1
1200
-1
-2
800
1600
(f) DK1
1
)
(e) DK1
1400
2
1
0
-1
1200
1000
-1
-2
800
F M A M
J
J
A S O N D 2003
2004
2005 2006
2007
Index
Fig. S4
-2
Annual GPP ( g C m yr
Index
Annual GPP ( g Cm yr )
2
Annual GPP ( g Cm yr )
2
73
75
1600
Observed
Modeled
2
1
J
74
(b) QYZ
-2
Scaled GPP (dimensionless)
GPP anomaly Scaled GPP (dimensionless)
GPP anomaly Scaled GPP (dimensionless)
GPP anomaly
(a) QYZ
Annual GPP ( g Cm yr )
2
2008 2009
)
1
Annual RE ( g C m yr
1150
2
-1
1100
1050
1000
-2
950
800
)
(d) MOZ
0
-1
600
500
-1
-2
3
400
1500
(f) DK1
)
(e) DK1
1400
1
Index
2
1
0
1200
1100
-2
-1
1300
900
M A M J
J
A S
O N D
2003
2004
2005 2006
Index
Fig. S5
2007
2008 2009
-1
1000
-2
F
Annual RE ( g Cm yr )
2
700
2
1
-2
Annual RE ( g C m yr
1
Index
Annual RE ( g Cm yr )
2
(c) MOZ
Annual RE ( g C m yr
Scaled RE (dimensionless)
RE anomaly
Observed
Modeled
-1
Scaled RE (dimensionless)
RE anomaly
0
76
78
(b) QYZ
-2
Scaled RE (dimensionless)
RE anomaly
1
J
77
1200
(a) QYZ
Annual RE ( g Cm yr )
2
0.08
0.04
0.02
c(rep(NA, 104), GPP.mod.w$MOZ[1:260])
2
1
GPP ( g C m yr )
Modeled
Observed
0.06
0.00
0.15
(b) MOZ
Index
0.10
0.05
0.00
0.15
(c) DK1
Index
GPP.mod.w$DK1
2
1
GPP ( g C m yr )
(a) QYZ
GPP.mod.w$QYZ
2
1
GPP ( g C m yr )
0.10
0.10
0.05
0.00
2003
2004
2005
2006
Year
Index
79
80
81
Fig. S6
2007
2008
2009
(a) QYZ
0.06
0.04
0.02
c(rep(NA, 104), RE.mod.w$MOZ[1:260])
2
1
RE ( g C m yr )
0.00
0.08
(b) MOZ
Index
0.06
0.04
0.02
0.00
0.16
(c) DK1
Index
0.12
RE.mod.w$DK1
2
1
RE ( g C m yr )
Modeled
Observed
RE.mod.w$QYZ
2
1
RE ( g C m yr )
0.08
0.08
0.04
0.00
2003
2004
2005
2006
Year
Index
82
83
84
Fig. S7
2007
2008
2009
(a)
2
Am ( mg C m s
1
)
0.8
0.6
0.4
0.2
0.0
5
(b)
Q10
4
3
2
1
0
2005
2006
2007
Year
85
86
87
Fig. S8
2008
2009
2
Am ( mg C m s
1
)
0.4
(a)
0.3
0.2
0.1
0.0
5
(b)
Q10
4
3
2
1
2003
2004
2005
Year
88
89
90
Fig. S9
2006
2007
Contribution to IAV
in NEE
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)
(k)
(l)
1.0
Climatic effect
Biotic effect
0.8
0.6
0.4
0.2
Contribution to IAV
in GPP
0.0
1.0
0.8
0.6
0.4
0.2
Contribution to IAV
in RE
0.0
1.0
0.8
0.6
0.4
0.2
0.0
0
100
200
Day of year
91
92
93
Fig. S10
300
0
10
20
30
Week
40
50
Feb Apr Jun Aug Oct
Month
Spring
Summer
Autumn
Season
Winter
Contribution to IAV
in NEE
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)
(k)
(l)
1.0
Climatic effect
Biotic effect
0.8
0.6
0.4
0.2
Contribution to IAV
in GPP
0.0
1.0
0.8
0.6
0.4
0.2
Contribution to IAV
in RE
0.0
1.0
0.8
0.6
0.4
0.2
0.0
0
100
200
Day of year
94
95
96
Fig. S11
300
0
10
20
30
Week
40
50
Feb Apr Jun Aug Oct
Month
Spring
Summer
Autumn
Season
Winter