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TEMPORAL VARIABILITY AND DRIVERS OF NET ECOSYSTEM PRODUCTION OF A TURKEY OAK (QUERCUS CERRIS L.) FOREST IN ITALY UNDER COPPICE MANAGEMENT Luca Belelli.

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Presentation on theme: "TEMPORAL VARIABILITY AND DRIVERS OF NET ECOSYSTEM PRODUCTION OF A TURKEY OAK (QUERCUS CERRIS L.) FOREST IN ITALY UNDER COPPICE MANAGEMENT Luca Belelli."— Presentation transcript:

1 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)

2 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)

3 shoots Stand after coppicing reserve trees ( N; E) ( N ; E) Roccarespampani Coppice forest ~1250ha Mature stand Two eddy covariance sites Sites location and applied management

4 time since forest harvest Rocca 1 ( ), harvested in Dec Rocca 2 ( ), harvested in Dec Chronosequence reconstructed by assembling the dataset of 2 EC stations Standard Carbo-Europe data processing (QA, gapfilling, partitioning) NEE GPP R eco Similar soil features, specific composition, topography, same management 018 EC data set

5 NEE (g C d -1 ) NEE [gC m -2 d -1 ] doy NEE (g C d -1 ) Rocca 1 Rocca 2 Seasonal trend of NEE

6 GPP Soil Water Content (-10 cm) Vapour Pressure Deficit Ecosystem respiration (R eco) NEE Dry period CO 2 fluxes response to air temperature Daily fluxes Gap filling fQC1>=90%

7 Relative importance of “physiological” seasons winter spring dry period fall Growing season doy R1 R2 R1 R2 R1 R2 R1 R2 R1 R2 R1 R2 R1 Duration of seasons

8 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

9 source sink Carbon budget NEE inter-annual variability

10 Decreasing Reco/GPP ratio Trend of Reco consistent with that of soil respiration ( Tedeschi et al., 2006) Reco, GPP inter-annual variability

11 VariablePartial correlationp-level 1Age ** 2Ts mean annual ** 3PPT annual * 4Ta anomaly (JJA) * NEE R=.95 R²=.91 Adjusted R²=.86 F(4,8)= p< Std.Error: VariablePartial correlationp-level 1Age * 2Ta mean GS * 3PPT annual Ta anomaly (JJA) VariablePartial correlationp-level 1Age ** 2PPT anomaly (JJA) Ts mean annual GPP R=.81 R²=.66 Adjusted R²=.53 F(4,10)= p< Std.Error : Reco annual R=.91 R²=.82 Adjusted R²=.76 F(3,9)= p< Std.Error: 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

12 Warming effect of clear cut on forest microclimate * mean values of August cooler soil warmer soil Clear cut effect

13 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

14 Rref Significantly higher in the WS period compared to FW (Wilcoxon test: P=0.013) Decreases with stand age, both in FW ( R , p<0.001); and WS (R 2 =0.48, p<0.01) Rref Q10 difference beween WS and FW (Wilcoxon test p=0.02). Q10 in the WS period significantly varies with age (R 2 =0.41, p<0.05) Q10 Q10 function parameters

15 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.

16 CountrySiteStart of EC records Years in database Vegetation/climate FIHyttiala199613Evergreen/boreal FISodankila20009Evergreen/boreal SENorunda19968Evergreen/boreal SEFlakaliden19967Evergreen/boreal DKSoro199614Deciduous/cool temperate GERTharandt199614Evergreen/cool temperate BEVielsam199614Mixed /cool temperate NLLoobos199614Evergreen/ cool temperate FRLe Bray199613Evergreen/ cool temperate FRHesse199712Deciduous/cool temperate BEBrasschat199711Mixed/ cool temperate ITCollelongo199614Deciduous/ warm temperate ITRoccarespampani Deciduous/ warm temperate ITRoccarespampani Deciduous/ warm temperate ITCastelporziano199710Evergreen/ warm temperate FRPuechabon20009Evergreen/ 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)

17 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. 18 years old stand (simulation) Observed NEE which synthesize the dependence structure of data, regardless of marginal distributions (F x1,F x2,.. ), to produce multivariate probability functions of NEE and climatic drivers and individuate thresholds for different climate domains. X1X1 x2x2 F(x 1,x 2 )/x 3 Example of 3-copula: Joint probability density function of (x 1,x 2 ), given x 3 (from Grimaldi & Serinaldi, 2006) Explore the use of copula (C) functions (Genest & McKay, 1986) (Roccarespampani forest) In particular: Outlook on next activities (2/2)

18 Thank you for your attention! More information: Luca Belelli

19 PPT anomaly (mm) Tair anomaly (°C)


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