Environmental Engineering Reference
In-Depth Information
Table 5.1 Average annual GPP and NPP for different forest types according to Corine Land
Cover 20 00 classification
Class
Forest type
GPP average
(ton C ha
NPP average
(ton C ha
1 year
1 )
1
1 )
year
1
Mediterranean shrub land
6.75
3.17
Holm oak and evergreen woods
8.93
4.20
2
Woods mainly planted with Mediterranean pine
trees and/or cypresses
7.83
3.68
3
Hygrophilous forests
6.81
3.20
4
Broad-leaved woods and plantations with non
native species
6.43
3.02
5
Deciduous mixed oaks woods
8.56
4.02
6
Chestnut woods
9.93
4.67
7
8
Beech forests
8.11
3.81
Woods mainly planted with pine-trees in the
sub-alpine and alpine areas (silver fir and red fir
woods)
8.67
4.07
9
10
Black pine and mountain pine woods
7.91
3.72
Conifers woods and plantations of non native
species
8.33
3.92
11
(Reanalysis) and MSG (Meteosat 2nd generation), remotely sensed vegetation
indexes from MOD15A2 LAI-fPAR, soil characteristics from SPADE-2 European
Soil Database and land use-land cover maps from Corine Land Cover 2000.
Model estimates of GPP have been validated against daily measurements from
two Mediterranean Eddy Covariance sites of the CarboItaly Project (Arca di No│-
Le Prigionette (Sardinia) and Castelporziano (Lazio). In particular, model results
show a significant correlation (Fig. 5.3 ) for the Mediterranean sites and a tendency
to overestimate GPP during the summer season.
The map of estimated annual GPP and NPP for Italian forests is shown in
Figs. 5.4 and 5.5 respectively, with maximum values of forest production mainly
distributed in the Apennines sub-alpine areas. In Table 5.1 average annual GPP
and NPP for different forest types according to Corine Land Cover 2000 classifica-
tion is reported, showing the highest values of estimated NPP for chestnut woods,
holm oak and evergreen woods, and more generally for low and middle mountain
forest ecosystems.
5.3 Conclusions
The implementation of hybrid models, based on the integration of different pro-
cess-based and empirical models, represents one of the most important tools for
the understanding of forest ecosystem processes and to estimate forest ecosystem
 
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