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Zusammenfassung:
This study investigates the performances of different optical indices to estimate gross primary production (GPP) of herbaceous stratum in a Mediterranean savanna
with different nitrogen (N) and phosphorous (P) availability.
Sun-induced chlorophyll fluorescence yield computed
at 760 nm (Fy760), scaled photochemical reflectance index
(sPRI), MERIS terrestrial-chlorophyll index (MTCI) and
normalized difference vegetation index (NDVI) were computed
from near-surface field spectroscopy measurements
collected using high spectral resolution spectrometers covering
the visible near-infrared regions. GPP was measured
using canopy chambers on the same locations sampled by
the spectrometers. We tested whether light-use efficiency
(LUE) models driven by remote-sensing quantities (RSMs)
can better track changes in GPP caused by nutrient supplies
compared to those driven exclusively by meteorological data
(MM). Particularly, we compared the performances of different
RSM formulations – relying on the use of Fy760 or sPRI
as a proxy for LUE and NDVI or MTCI as a fraction of absorbed photosynthetically active radiation (f APAR) – with those of classical MM. Results showed higher GPP in the N-fertilized experimental
plots during the growing period. These differences in GPP
disappeared in the drying period when senescence effects
masked out potential differences due to plant N content. Consequently,
although MTCI was closely related to the mean
of plant N content across treatments (r2 D 0:86, p < 0:01),
it was poorly related to GPP (r2 D 0:45, p < 0:05). On the
contrary sPRI and Fy760 correlated well with GPP during
the whole measurement period. Results revealed that the
relationship between GPP and Fy760 is not unique across
treatments, but it is affected by N availability. Results from
a cross-validation analysis showed that MM (AICcv D 127,
MEcv D 0:879) outperformed RSM (AICcv D 140, MEcv D
0:8737) when soil moisture was used to constrain the seasonal
dynamic of LUE. However, residual analyses demonstrated
that GPP predictions with MM are inaccurate whenever
no climatic variable explicitly reveals nutrient-related
changes in the LUE parameter. These results suggest that
RSM is a valuable means to diagnose nutrient-induced effects on the photosynthetic activity.
