Environmental Engineering Reference
In-Depth Information
bio-geochemical model, BIOME-BGC. C-Fix is a Monteith type parametric model
(Veroustraete et al.
2002
) which combines satellite-derived estimates of the frac-
tion of Photosynthetically Active Radiation absorbed by forest (fAPAR) with field
based estimates of incoming solar radiation and air temperature to simulate total
photosynthesis. The annual GPP (g C m
−
2
year
−
1
) of a forest can be computed as:
12
GPP
=
ε
Tcor
i
·
Cws
i
·
fAPARi
i
·
Rad
i
(5.1)
i
=
1
where
ʵ
is the maximum radiation use efficiency,
Tcor
i
is a factor accounting for
the dependence of photosynthesis on air temperature,
Cws
i
is the water stress
index,
fAPARi
i
is the fraction of absorbed PAR, and
Rad
i
is the solar incident PAR,
all referred to the
i
-th month.
f
fAPAR can be derived from the top of canopy NDVI
according to the linear equation proposed by Myneni and Williams (
1994
).
Cws
was introduced by Maselli et al. (
2009a
) to optimize the model application in
Mediterranean environments, which are characterized by a long and dry summer
season when vegetation growth is constrained by water availability. This modifica-
tion is completed by the use of the MODIS temperature correction factors and the
maximum radiation use efficiency equal to 1.2 [(g C MJ
−
1
(APAR))] (Chiesi et al.
2011
).
Modified C-Fix was applied to simulate monthly GPP values of all Italian
forests for the past decade (1999-2008) following the multi-step methodology
described in Maselli et al. (
2009a
). In summary, a 1-km
2
dataset of monthly min-
imum and maximum temperatures, precipitation and solar radiation was derived
from the available meteorological maps. These maps were further processed to
compute the temperature and water stress correction factors which are needed to
drive Modified C-Fix. The Spot-VGT ten-day NDVI images of the ten study years
were corrected for residual disturbances, composed over monthly periods and pro-
cessed to obtain
f
fAPAR maps. All these maps were used to apply Modified C-Fix
and yield monthly GPP images over the study years. These images were aggre-
gated to compute an annual average GPP image of Italy, from which average val-
ues were extracted for all forest types and Italian Regions.
The ecosystem respirations needed for the prediction of NPP in the Italian for-
est types were then simulated by BIOME-BGC. This model was developed at the
University of Montana to estimate the storage and fluxes of carbon, nitrogen and
water within terrestrial ecosystems (Running and Hunt
1993
). It requires daily
weather data, general information on the environment (i.e. soil, vegetation and
site conditions) and on parameters describing the ecophysiological characteris-
tics of vegetation. The model works by searching for a quasi-climax equilibrium
(homeostatic condition) with local eco-climatic conditions through the spin-up
phase: this means that the sum of simulated respirations become nearly equivalent
to GPP, which makes annual NPP approach heterotrophic respiration (Rhet) and
NEE tend to zero. Also, such modeling makes the obtained GPP estimates similar
to those produced by C-Fix, which are descriptive of all ecosystem components
(Maselli et al.
2009b
). The version of the model currently used includes complete
