Stand-level biomass models for predicting C stock for the main Spanish pine species

Abstract Background National and international institutions periodically demand information on forest indicators that are used for global reporting. Among other aspects, the carbon accumulated in biomass of species must be reported. For this purpose, one main sources data is Forest Inventory (NFI), which together with statistical empirical approaches updating procedures can even allow annual estimates requested indicators. Methods Stand level models, relating dry weight stand volume were developed five pine Iberian Peninsula ( Pinus sylvestris , pinea halepensis nigra pinaster ). The dependence model aridity and/or mean tree size was explored, as well importance including form factor to correct bias. Furthermore, capability models estimate stocks, updated a given year, also analysed. Results strong relationship between modulated by size, although effect varied among species. Site humidity, measured using Martonne index, increased cases . Models consider both more accurate less biased than those do not. stocks forests estimated at biases 0.2 Mg?ha ? 1 Conclusions results study reveal considering variables related environmental conditions structure when developing models. described methodology provide precise tool quantifying stored Spanish specific years no field available.