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Abstract: A methodology for improving the application of Biome‐BGC in peninsular Spain was developed focusing on the optimization of the rooting depth (zroot), which is not available for the study area on a spatially distributed basis. The optimal zroot was identified by comparing daily gross primary production (GPP) simulations with varying zroot to GPP estimations from a production efficiency model previously optimized for and validated in the study area. The methodology was first tested in four eddy covariance (EC) sites representative of Mediterranean ecosystems and next applied at a regional scale to the whole study area. As a result, daily GPP simulated maps for the 2005–2012 period and an optimal zroot map were obtained. Optimal zroot in the four EC sites was shallower than the default one (100 cm) and led to better simulation results. Realistic, spatially distributed GPP estimates were obtained at regional scale. Withal, some discrepancies appeared both at local and regional scale emphasizing the difficulty to adequately simulate the site's water budget and the need for proper setting of inputs, including zroot for the correct functioning of Biome‐BGC. The performed optimization opens the door for using Biome‐BGC to simulate other main vegetation processes, such as net carbon fluxes, in the study area. [ABSTRACT FROM AUTHOR]

The availability of daily meteorological data over extended wide areas is a common requirement to model ecosystem processes on a regional scale. The meteorological dataset E-OBS (European Observations) has been downscaled in 2012 to a 1 km spatial resolution in Italy. The assessment of this dataset against ground measurements revealed a marked under-estimation of rainfall, which is a major driving factor for vegetation growth in water-limited Mediterranean environments. The objective of the present study is to correct the downscaled rainfall dataset through the use of additional ground meteorological data collected over a 30 year period (1981-2010). The corrected dataset was evaluated using the ecosystem process model BIOME-BGC (BioGeochemical Cycles). After identifying the most under-estimated areas, seven sites that were representative of different forest ecosystems were selected; for each of these sites, gross primary production ( GPP) was simulated using the E- OBS original and corrected rainfall datasets. The test was completed for one site in central Italy ( IT-Ro2), assessing the outputs of the BIOME-BGC data versus the daily GPP data obtained by the eddy correlation technique. In all cases, the use of the corrected dataset produced more realistic GPP simulations; for IT-Ro2, the mean bias error was 0.18 instead of 2.33 g C m−2 day−1. The beneficial effect of the correction depended on the aridity of the examined site, that is, it was the maximum in the driest Mediterranean ecosystems and almost null in the most humid environments. It can therefore be concluded that the corrected dataset is suitable to drive the long-term simulation of forest ecosystem processes in all Italian eco-climatic conditions. [ABSTRACT FROM AUTHOR]

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. 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). 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 × 1-km NOAA AVHRR Normalized Difference Vegetation Index data were used to improve the adaptation of the model to local forest conditions. 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 ( R2 = 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. 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. [ABSTRACT FROM AUTHOR]