Estimation of Mediterranean forest transpiration and photosynthesis through the use of an ecosystem simulation model driven by remotely sensed data

Abstract

Aim This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the main ecophysiological processes (transpiration and photosynthesis) of Mediterranean coastal forest areas using remotely sensed data. Location Model testing was carried out at two protected forest sites in central Italy, one of which was covered by Turkey oak (Circeo National Park) and the other by holm-oak (Castelporziano Estate). Methods At both sites, transpiration and photosynthesis measurements were collected in the field during the growing seasons over a four-year period (1999 and 2001 for the Turkey oak; 1997, 1999 and 2000 for the holm-oak). Calibration of the model was obtained through combining information derived from ground measurements and remotely sensed data. In particular, remote sensing estimates of the Leaf Area Index derived from 1 x 1-km NOAA AVHRR Normalized Difference Vegetation Index data were used to improve the adaptation of the model to local forest conditions. Results The results indicated different strategies regarding water use efficiency, 'water spending' for Turkey oak and 'water saving' for holm-oak. The water use efficiency for the holm-oak was consistently higher than that for the Turkey oak and the relationship between VPD and WUE for the holm-oak showed a higher coefficient of determination (R-2 = 0.9238). Comparisons made between the field measurements of transpiration and photosynthesis and the model estimates showed that the integration procedure used for the deciduous oak forest was effective, but that there is a need for further studies regarding the sclerophyllous evergreen forest. In particular, for Turkey oak the simulations of transpiration yielded very good results, with errors lower than 0.3 mm H2O/day, while the simulation accuracy for photosynthesis was lower. In the case of holm-oak, transpiration was markedly overestimated for all days considered, while the simulations of photosynthesis were very accurate. Main conclusions Overall, the approach offers interesting operational possibilities for the monitoring of Mediterranean forest ecosystems, particularly in view of the availability of new satellite sensors with a higher spatial and temporal resolution, which have been launched in recent years

Changes of the potential distribution area of French Mediterranean forests under global warming

“…1). Some previous works succeeded in such modeling using remote sensing (LAI) calibration (Anselmi et al, 2004). Our approach is, in a way, different and original, as we have calibrated a complex ecophysiological model, using dendrochronological time series .…”

“…Some of them have focused either on ecophysiological processes (Anselmi et al, 2004) or on spatial patterns by the use of statistical relationships (Luoto et al, 2005;Thuiller et al, 2004). We intend here to simultaneously investigate both issues.…”

Comparing two approaches for parsimonious vegetation modelling in semiarid regions using satellite data

“…NDVI can and NDVI back may be retrieved from the NDVI images (Anselmi et al, 2004). The parameters used in this study were NDVI can = 0.9915; NDVI back = 0.0549 and k = 0.212 (Anselmi et al, 2004).…”

The contribution of remote sensing to the assessment of drought effects in forest ecosystems

“…Numerous studies address the problem of the coupling of these process models with remote sensing data (see [3]) and their spatial parameterisation. The assimilation of thermal infrared response into the MuSICA model of Ogée et al [75] is currently being tested over maritime pine stands, and a reduction of errors in the water budget due to the directional and instantaneous measurement of the surface temperature is particularly expected.…”

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