TEMPORAL VARIABILITY AND DRIVERS OF NET ECOSYSTEM PRODUCTION OF A TURKEY OAK (QUERCUS CERRIS L.) FOREST

IN ITALY UNDER COPPICE MANAGEMENT

Luca Belelli Marchesini (1), Ana Rey (2), Dario Papale (1), Riccardo Valentini (1)

(1) DISAFRI, University of Tuscia, Viterbo, Italy. (2) EEZA-CSIC, Almería, Spain.

CARBO-Extreme Annual Meeting

13 September 2010, Roskilde (DK)

Activities during the first year of Carbo-Extreme project (WP3):

Analysis of a long-term eddy covariance dataset from Roccarespampani site (coppice forest in central Italy): 15 years of continuous NEE data representative for forest stand age from 0 (post-harvest) to 18 years covering almost the whole rotation period.

Inter-annual and seasonal variability of NEE, GPP, Reco

Climatic drivers (functional relations) of the C cycle and disturbance

induced by coppice management.

Separation of age and climate as factors controlling the temporal trend

of the C balance by Artificial Neural Networks (AANs). (preliminary)

Comparison of NEE with modelled NPP (inventories+ allometric

functions) and assessment of NBP. (not shown here)

shoots

Stand after coppicing

reserve trees

(42.3903 N; 11.9209 E)

(42.4082 N ; 11.9303 E)

Roccarespampani

Coppice forest ~1250ha

Mature stand

Two eddy covariance sites

Sites location and applied management

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

NEE, R

eco, G

PP [

g C m

-2 d

-1]

-15

-10

-5

0

5

10

15

20 stand age

b

2002

2003

2004

2005

2006

2007

2008

2009

-15

-10

-5

0

5

10

15

20

0 1 2 3 4 5 6 7 8

stand age

11 12 13 14 15 16 17

a b

time since forest harvest

Rocca 1 (2000-2008), harvested in Dec. 1999

Rocca 2 (2002-2008), harvested in Dec. 1990

Chronosequence reconstructed by assembling the dataset of 2 EC stations

Standard Carbo-Europe data processing (QA, gapfilling, partitioning)

NEE

GPP

Reco

Similar soil features, specific composition, topography, same management

0 18

EC data set

NE

E (

g C

d-1)

2002

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2003

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2004

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2005

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2006

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2008

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

NEE [

gC

m-2 d

-

1]

doy2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Rain

[m

m]

0

10

20

30

40

50

60

70100

200

300

Air

tem

p [

°C]

0

5

10

15

20

25

30

35

40

45

2005

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2006

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

2008

0 100 200 300

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

NE

E (

g C

d-1)

Rocca 1Rocca 2

Seasonal trend of NEE

Rec

o [g

C m

-2d-

1]

0

1

2

3

4

5

SW

C [

m3 m

-3]

10

15

20

25

30

35

40

45

50

VPD

[hPa

]

0

5

10

15

20

25

30

35

Tair [°C]

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32

GPP

[gC

m-2d-

1]

0

2

4

6

8

10

12

age 0- 8

age 11- 17

Rec

o [g

C m

-2d-

1]

0

1

2

3

4

5

NEE [

gC m

-2d-

1]

- 8

- 6

- 4

- 2

0

2

4

Tair [°C]

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32

GPP

[gC

m-2d-

1]

0

2

4

6

8

10

12

age 0- 8

age 11- 17

GPP

Soil Water Content (-10 cm)

Vapour Pressure Deficit

Ecosystem respiration

(Reco)

NEE

Dry period

CO2 fluxes response to air temperature

Daily fluxes

Gap filling fQC1>=90%

Relative importance of “physiological” seasons

winter

spring

dry period

fall

Gro

win

g se

aso

n

doy

76 61 158 29 41

101 64 56 90 54104 61 56 97 47

100 49 119 50 47105 40 120 59 41

84 79 120 41 4294 83 108 38 43

101 49 126 42 47110 37 129 46 43

96 48 125 46 5096 39 122 49 59

79 86 58 80 62

87 76 94 59 5096 67 94 70 39

0 50 100 150 200 250 300 350

W

S

DP

F

W

2004

2003

2001

2002

2005

2006

2007

2008

R1R2

R1

R1R2

R1R2

R1R2

R1R2

R1R2

R1

Duration of seasons

Growing season GS Reco 0.95 ***

NEE 0.98 ***

GPP 0.93 ***

Spring S Reco 0.77 **

NEE 0.45 n.s

GPP 0.11 n.s

Dry period DP Reco 0.75 **

NEE 0.91 ***

GPP 0.90 ***

Fall F Reco 0.67 **

NEE 0.79 ***

GPP 0.38 n.s

Dormancy NG Reco 0.89 ***

NEE 0.07 n.s

GPP -0.29 n.s

Winter - Spring WS Reco 0.77 **

NEE 0.18 n.s

GPP -0.18 n.s

Fall - Winter FW Reco 0.68 **

NEE 0.74 **

GPP 0.16 n.s

Year

Reco NEE GPP

* P<0.05

** P<0.01

*** P<0.0001

Which period influences mostly the annual C balance?

Correlation analysis (ρ- Spearman):

Annual mean flux

vs

Mean flux of each period

Importance of different seasons on annual NEE

Years after coppicing

0 2 4 6 8 10 12 14 16 18

NEE [

g C m

-2 y

-1]

-1200

-1000

-800

-600

-400

-200

0

200

400

sourcesink

Carbon budget

R2 = 0.66P < 0.001

2008

2008

2003

20032005

2005

2006

2006

20042004 2002

2002

2001

2000

2007

NEE inter-annual variability

R2 = 0.32P=0.02

R2 = 0.41P < 0.01

Years af ter coppicing

0 2 4 6 8 10 12 14 16 18

Rec

o [g

C m

-2 y

-1]

600

800

1000

1200

1400

1600

GPP

[g

C m

-2 y

-1]

1000

1200

1400

1600

1800

2000

stand age (years)

0 5 10 15

Rec

o/G

PP

0.2

0.4

0.6

0.8

1.0

1.2

R2=0.70p<0.0001

Decreasing Reco/GPP ratio2008

20082003

20032005

2005

2006

2006

2004

2004

20022002

2001

2000

2007

2008 2008

2003

20032005

2005

2006

2006

2004

2004

2002

2002

2001

2000

2007

Trend of Reco consistent with that of soil respiration

(Tedeschi et al., 2006)

Reco, GPP inter-annual variability

Variable Partial correlation p-level

1 Age -0.87 0.0021

**

2 Ts mean annual 0.77 0.0079

**

3 PPT annual 0.74 0.0130

*

4 Ta anomaly (JJA)

0.64 0.0457

*

NEER= .95 R²= .91Adjusted R²= .86F(4,8)=20.421 p<.00029 Std.Error: 115.96

Variable Partial correlation p-level

1 Age 0.63 0.0278

*

2 Ta mean GS -0.60 0.0367

*

3 PPT annual -0.47 0.1160

4 Ta anomaly (JJA) -0.41 0.1742Variable Partial correlation p-level

1 Age 0.80 0.0030

**

2 PPT anomaly (JJA) 0.59 0.0528

3 Ts mean annual 0.48 0.1350

GPPR= .81 R²= .66Adjusted R²= .53F(4,10)=5.0438 p<.01736 Std.Error : 197.72

Reco annual R= .91 R²= .82 Adjusted R²= .76F(3,9)=13.993 p<.00098 Std.Error: 89.931

NEE inter-annual variability and climatic factors

Multiple regression (forward step-wise) : Ta, Ts, PPT, Rg (annual-growing season); Ta, PPT anomalies (JJA); PPT anomaly (Jan-May)

Influence of climate on NEE, GPP. Reco inter-annual variability

Warming effect of clear cut on forest microclimate

*mean values of August

Years af ter coppicing

0 5 10 15 20

Tai

r, T

soil

[°C]

-5

0

5

20

25

30Tair

Tsoil

(Ts-Ta)

(T

air

-Tso

il) [

°C]

cooler soil

warmer soil

Clear cut effect

Rocca 1 -FW 2003

T soil [°C]

5 10 15 20

Rec

o [g

C m

-2 d

-1]

0

2

4

6

8

10

R2=0.92 n=97 P<0.001

Rocca 1 -WS 2003

R2=0.82 n=149 P<0.001

10

10

)10(10

T

refeco QRR

Increased soil temperature after coppicing, but same temperature sensitivity?

Analysis of parameters of the Reco-Tsoil curve (Rref, Q10), for the winter-spring (WS) and fall-winter (FW) periods.

Reco- Tsoil dependence

RrefSignificantly higher in the WS period compared to FW(Wilcoxon test: P=0.013)

Decreases with stand age, both in FW (R2 0.61, p<0.001); and WS (R2=0.48, p<0.01)

years af ter coppicing

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Rre

f(10

) [g

C m

-2 d

-1]

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5R ref _FW

Rref _WS Rref

Q10

difference beween WS and FW (Wilcoxon test p=0.02).

Q10 in the WS period significantly varies with age (R2=0.41, p<0.05)

years af ter coppicing

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Rre

f(10

) [g

C m

-2 d

-1]

0

2

4

6

8

Q10 _FW

Q10 _WS Q10

Q10 function parameters

Conclusions

1. Coppice management of Roccarespampani forest associated

to high C sequestration rates and limited duration of net

C release following clear cuts (C budget <0 already after

2years )

2. Sink strenght increases primarily with age, but negatively

impacted by warmer temperatures and droughts.

3. Enhanced ecosystem respiration after coppicing,

independently of the altered microclimate (input of C,N through

biomass residuals/root mortality).

4. Importance of taking into account the role of forest

management on ecosystem carbon dynamics together with

climatic drivers.

Country Site Start of EC records

Years in database

Vegetation/climate

FI Hyttiala 1996 13 Evergreen/boreal

FI Sodankila 2000 9 Evergreen/boreal

SE Norunda 1996 8 Evergreen/boreal

SE Flakaliden 1996 7 Evergreen/boreal

DK Soro 1996 14 Deciduous/cool temperate

GER Tharandt 1996 14 Evergreen/cool temperate

BE Vielsam 1996 14 Mixed /cool temperate

NL Loobos 1996 14 Evergreen/ cool temperate

FR Le Bray 1996 13 Evergreen/ cool temperate

FR Hesse 1997 12 Deciduous/cool temperate

BE Brasschat 1997 11 Mixed/ cool temperate

IT Collelongo 1996 14 Deciduous/ warm temperate

IT Roccarespampani 1 2000 9 Deciduous/ warm temperate

IT Roccarespampani 2 2002 7 Deciduous/ warm temperate

IT Castelporziano 1997 10 Evergreen/ warm temperate

FR Puechabon 2000 9 Evergreen/ warm temperate

Analysis of eddy covariance data from forest sites differing for plant functional type with long time series available:

Outlook on next activities (1/2)

• Use of ANNs to disentangle stand age and climate effects on NEE time series of forest ecosystems and single out main drivers of NEE variability.

-1200

-1000

-800

-600

-400

-200

0

200

400

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

years after coppicing

NEE (

gC m

-2 y

-1)

18 years old stand (simulation)

Observed NEE

which synthesize the dependence structure of data, regardless of marginal distributions (Fx1,Fx2,..), to produce multivariate probability functions of NEE and climatic drivers and individuate thresholds for different climate domains.

X1

x2

F(x

1,x 2

)/x 3

Example of 3-copula:

Joint probability density function of (x1,x2) , given x3

(from Grimaldi & Serinaldi, 2006)

• Explore the use of copula (C) functions (Genest & McKay, 1986)

(Roccarespampani forest)

In particular:

Outlook on next activities (2/2)

Thank you for your attention!

More information: Luca Belelli (belelli@unitus.it)

climate anomalies_ mean Ta, PPT (2000-2008)

-200-150-100

-500

50100150200250300

Jan

-00

Ma

y-0

0

Se

p-0

0

Jan

-01

Ma

y-0

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p-0

1

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-02

Ma

y-0

2

Se

p-0

2

Jan

-03

Ma

y-0

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Se

p-0

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Jan

-04

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y-0

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Se

p-0

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Jan

-05

Ma

y-0

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p-0

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-06

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y-0

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p-0

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-07

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y-0

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Se

p-0

7

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-08

Ma

y-0

8

Se

p-0

8

-5-4-3-2-101234567

PP

T a

nom

aly

(mm

)

Tair

anom

aly

(°C

)