## 6 Discussion and Conclusions
The rise of ambient CO\({}_{2}\) leads to notable simulated GPP increases (from 23% to 39%), which can be explained by the improved water use efficiency due to reduced stomata conductance and canopy transpiration rates [42, 43]. These reductions improve plant and soil water relations, slowing the rate of soil water loss during droughts [44, 45]. Such an interpretation is supported by the results of [PERSON] and [PERSON] [46], who found that trees exposed to higher CO\({}_{2}\) levels are more tolerant to drought stress. A number of other experimental studies confirm the fertilizing effect of CO\({}_{2}\) on forest production. Most of these studies, however, refer to a concentration of 550 ppm instead of the currently used 670 ppm, and consequently indicate lower GPP increases. For example, [PERSON] _et al._[6] and [PERSON] _et al._[9] reported increases of 18% for _Liquidambar_ at 530 ppm, and of 11% and 22% for poplar at 550 ppm, respectively. Similar effects were found in Tuscany by our research group [47]. Also in that case the GPP increase caused by a CO\({}_{2}\) rise to 550 ppm was lower than that currently found (21% versus 31%). That study also indicated that the GPP increase is maximum for more thermophylous species, due to the positive effect of temperature on CO\({}_{2}\) fertilization. A significant increase in forest production is obtained for all forest types also when the effects of climate changes and increased ambient CO\({}_{2}\) are jointly considered. This implies that, in general, the effects of the CO\({}_{2}\) rise tends to prevail on that of the climate changes. These combined effects, however, are more difficult to evaluate against experimental evidences, because the interaction of the two factors is usually not considered by FACE experiments. Consequently, comparisons can only be made with the results of previous modelling approaches. For instance, the simulation experiment of [PERSON] _et al._[47] indicated a mean production increase of 19% for Tuscany forests (Central Italy) exposed to increased temperatures (+2 \({}^{\circ}\)C) and a CO\({}_{2}\) concentration of 550 ppm. The approach currently applied has some relevant limitations. For example, changes in plant species composition or nutrient soil contents cannot be considered, which can have profound consequences in primary production. Some authors indicated that also changes related to the genetic characteristics of the existing populations should be taken into consideration [48]. Additionally, the use of remotely sensed and ancillary data at 1-km spatial resolution may be not sufficient to accurately reproduce the spatial variability of Italian Mediterranean landscapes, which are extremely heterogeneous and fragmented [24, 49]. In spite of these limitations, the approach has been successful in combining conventional and remote sensing data to simulate the large scale responses of Italian forests to three likely environmental scenarios. The plausibility of the results obtained is supported by their substantial coherency with the findings of previous studies carried out in similar environments. Already in their present form, these results can provide important information on the expected evolution of Italian forest ecosystems. Moreover, the approach can be easily replicated on different spatial and temporal resolutions (e.g., using MODIS data) in order to assess the likely responses of other forest areas.