Modelling forest management within a Global Vegetation Model (ORCHIDEE)
Bellassen V
i,Le Maire G
2,Dhote JF
3, Viovy
N1,Ciais P
i1 . Laboratoiredes Sciences du Climatet del'Environnement(CEA-CNRS), 2 . Ecosystèmes de Plantations (CIRAD), 3 . Office National desForêts(ONF)
1 . Why model forest management within a Global Vegetation Model? 3. Structure of forest management module : based on Fagacees (Dhôte, 1999 )
• To improve the predictive power of GVMs
3Explicit representation of forest stand structure allows the comparison of the model to common field dat a from forest inventories
3Shift from the « average tree » representation to the « average stand » will hopefully improve proces s description, especially at early stages of stand growth, and thus the overall predictive powe r
• To improve the understanding of the forest sin k
3In recent years, European forests have been estimated to be a net sink of ~140 TgC/yr -1 (Lindneret al. , 2004). How do « natural » factors (climate change, N deposition) compare to forest management factor s (legacy effect of past management, current practices) in explaining this sink ?
• To study the interactions between climate change and forest managemen t
3What is the impact of future climate change on forest productivity? On the structure of forest stands ? 3Does forest management have an impact on climate change ?
2 . Structure of GVM : ORCHIDEE (Krinneret al., 2005 )
Atmosphere
(prescribed or simulated by a GCM)
Stand volume (ma.ha") Exported volume / Total volume Thinning frequency (years)
Average circumferenc e (m)
Minimal ci rcumference (m)
Maximal ci rcumference (m)
sensible and latent heat fluxes, albedo roughness, surface temperature, CO2 flux...
&Vegetationdistribution (prescribed or calculate by LPJ Dynamic General Vegetation model)
Add-ons:
• ProgressiveincreaseofLAI_maxfor15years afteraclear-cut
• Age-related decline in NPP (LAI_max limited by height and v_max declin
of branches die eac h
rainfall, temperature
solar radiation,CO2
concentration. ..
5 . Validation against European yield table s 4 . Sensitivity analysis
Results of a standard run Standard value of parameters Sensitivi ty of variable
(data source: Teobaldelli M ., Federici S., Bellassen V., Seufert G., Pagliari V. (2008) .The European Yield Tables Database . URL:http://afoludata.jrc.it/data_fs .cfm)
• 2 sets of simulations
Density (ind .há)
Basal area (m2 .m-2)
Variable value at
year 100 Parameter nam e
w
56 pipe_censity N-ma x
28.69 A
604 G
rci_lim 0.49
53
Ti
2.97 b2nch_ratio Diameter-Biomass 0.82 allometry (ciam in cm,bimoassin 4.22 kgMS)
b2nch_tum
0.47 20000 0 a/Dg^ b sgrt(2)/Dg_ini t 0.01*max(0,3.7*d o m_height)-12. 7
0.0 5
Tmax*(0.01+0 .99* ( (circ_lim - circ)/(circ_lim - drr_min)) 0.1 5
B=a*D ^ b 0.000109589 Parameter value
eae: o-ee aamv ea: baei e. a Sfaitl wl: wYme af efmtl mra s°áVp1iasameate~ wmn• /
Th_ea: aaaais RauemY M Uc: a+erege Ualmfaam
aEen: anemm caamre~aw aEam: m•awm ammre~aw oavn abbbu0mm m amimraaae aaea
3« forced » where the forestry module is forced with the productivit y given in yield tables
3« coupled » where the forestry module gets its NPP from ORCHIDE E
• Result s
3The data shows important variability for similar temperature s
3When « forced », the forestry module is globally consistent with data fo r tree density and stand volume, with little systematic bias
3500- 60- 80- 0 .6
70 - ..60 - so - J w F3o
to
Ochidee (stomate) AB (n)
Forest management module
Circ i (tree)
Dg = f(circi+ ócirci ) Rdi = f(Dg, density) Self-thinning :
• Thinning until Rdi = 1
• New values of circi, density, Dg, …
• B(n)= B(n) –thinned tree s
yes
Test:
Rdi > 1?
Human thinning :
• Thinning until Rdi = rdi_go - rdi_li m
• New values of circi, density, Dg, …
• LAI_max = LAI_max – 2, recovered in 3 year s
• B(n)= B(n) –thinned trees
Rdi
Comparison between "measured", "forced"
and "coupled" on a sample of point s
"measured" and "coupled" volume a s a function of temperature
