# Remote Sensing and Bio-Geochemical Modeling of Forest Carbon Storage in Spain
## 6 Discussion
### NPP in Future Condition  
Some tests were firstly performed using the scenarios from AdapteCCa ([[https://www.adaptecca.es](https://www.adaptecca.es)]([https://www.adaptecca.es](https://www.adaptecca.es))) data as inputs in Biome-BGC for some sites where station-level AdapteCCa data obtained with the same model were available. Daily GPP and respirations were simulated for 2006-2100. However, unexpected extreme (i.e., both very high and very low) carbon fluxes values were obtained. This, together with the abundance of different models that provide different climate projections and their high uncertainty, led to the decision of generating a simplified dataset of possible future changes in meteorological variables trying to cover most of the climatic projections (both from different models and for different scenarios). This simplified dataset was elaborated by applying variations to a reference dataset that was previously used in the simulation of GPP by both the production efficiency model and Biome-BGC [19], the daily precipitation and maximum and minimum air temperature for the 2005-2012 period, so different sets of 8-year periods were produced instead of a long time series as in the case of AdapteCCa. Thus, the results presented in Section 5.2 might approximately correspond to different 8-year periods over the present century depending on whether any actions are taken to mitigate climate change and how intense their application is. Still, the generation of the abovementioned 8-year datasets presents some important limitations. First, there are some limitations regarding the direction of the modifications applied to the reference period. Both global and regional climatic models predict increment in air temperature in the study area for the different emission scenarios. Therefore, only increments in temperature were considered. Whereas in the case of precipitation, an increase is also expected globally, but regional models predict reductions in annual precipitation over the study area. Therefore, only reductions in precipitation were considered. Second, there are limitations regarding the temporal variation of the applied modifications. While climatic models usually provide, for example, different variations for winter and summer within the same year, the datasets generated in the present study were produced by applying the same modification to each value in the series, that is, a regular variation. Regarding the spatial variation, which is especially relevant in the case of precipitation, it is provided by the spatial variation of the reference series itself. Other limitations of the current approach are due to the use of a bio-geochemical model, which can be suboptimal for the simulation of future climatic conditions. Biome-BGC respirations are actually simulated using a Q10 function of air temperature [50], which however does not account for the possible response and adaptation of vegetation to high air temperature [51]. The consideration of stable GSV for driving the NPP modeling strategy in future condition is also disputable but can be justified by the unpredictable dependence of this forest attribute on human activities (tree cutting and thinning operations, wildfires of arson origin, etc.). When comparing the annual forest NPP shown in Figure 4b (reference period 2005-2012) and Figure 4c (\(\Delta T=+2~{}^{\circ}\)C and 8 PRE = -20%), it can be appreciated how NPP is greater in Figure 4c in the regions where it was already great in Figure 4b and smaller in Figure 4c in the regions where it was already small in Figure 4b, that is, it presents a more extreme variation in Figure 4c. This is supported by the statistics reported in Tables 5 and 6: maxima and standard deviations of NPP are greater in Table 6 (corresponding to Figure 4c, \(\Delta T=+2\)\({}^{\circ}\)C, and \(\delta\)PRE = -20%). The increment of NPP in already very productive regions (mostly the north of the study area) may be caused by the increment in air temperature and the water not being a limiting factor.