## 2 Forest biophysical Properties
### Forest Productivity  
The biochemical construction of new organic material over a specified time interval--known as net primary production (NPP)--of tropical forests and its partitioning between long-lived carbon pools(wood) and shorter-lived pools (leaves, fine roots) is of considerable importance in the global carbon cycle [4]. It has been suggested that the NPP as well as the nitrogen and phosphorus content, all scale allometrically with phytomass across diverse plant communities, from tropical forest to arctic tundra [57]. The quantification of NPP is still very uncertain but considerable work has been done on the assessment of the above-ground components of NPP (leaf, flower, fruit and wood production) for different ecosystems. On the other hand, below-ground NPP, the partitioning between above- and below-ground components and the main environmental drivers of these patterns are still poorly understood. Data on both below- and above-ground NPP are especially limited in Amazonia due to elevated costs and challenging logistics involved in setting up and monitoring measurement sites. There are different approaches to evaluate and quantify the below- and above- ground primary production. Field measurements for assessing the above-ground component should include litterfall, branch production, coarse woody biomass production, aboveground biomass losses to consumers, and the emission of volatile organic carbon compounds and aboveground losses of leached organic compounds [58, 59, 60, 61, 62]. For the below-ground component, data on coarse and fine root productivity, dead coarse and fine roots, losses to consumers, and the carbon loss through exudates and mycorrhizae are necessary [63, 61]. The second option for evaluating the above-ground component (mainly canopy process) relies on the use of remote sensing data and modeling [64, 65, 66, 67], although field measurements are important for validation purposes. Looking at the above-ground coarse wood carbon productivity in stems and branches, [PERSON] _et al._[60] demonstrated that wood production varies by up to a factor of three across Amazonian forests. Lower wood production, according to that study, is found on poor oxisols in lowland eastern Amazonia and higher production occurs in more fertile soils in western Amazonia. In relation to the canopy NPP (leaves, twigs, flowers and fruits), [PERSON] _et al._[62] suggested that soil is not a major determinant of litterfall patterns, however infertile white sandy soils have significantly lower litterfall than other soil types, and more fertile soils exhibit higher canopy production [61]. Below-ground allocation declines with increasing clay content and more fertile soils tend to have higher fine root production [61]. Overall, soil phosphorus is likely to be more important than nitrogen in the determination of the total NPP across the Amazon [16]. It has also been suggested that forests in infertile soils, such as eastern Amazonia, have low carbon use efficiency, in comparison with recently disturbed forests or forests in fertile soils [69]. Remote sensing and modeling studies suggest or assume that temperature followed by solar radiation primarily determine variation in NPP in Amazonia, which is especially sensitive to large ENSO events [70, 71] although soil depths significantly affect the gross primary production (GPP, the sum of net primary production (NPP) and autotrophic respiration) [68, 72]. While temperature appears to exert a strong influence on NPP in some models [64], other models suggest that radiation increases carbon fluxes in Amazonian [65, 73]. This is also suggested by remote sensing observations, which showed increases in leaf area index (LAI) and Enhanced Vegetation Indices (EVI) during the dry-season [66, 74]. It is important to mention that not only remote sensing data but also modeling studies have limitations when applied to evergreen canopies such as the tropical forests, due to saturation in the data in the first case and lack of information in the latter.