Quercus suber Allometry in the West Mediterranean Basin

The necessity for accurate biomass estimates is greater than ever for the sustainable management of forest resources, which is an increasingly pressing matter due to climate change. The most used method to estimate biomass for operational purposes is through allometric equations. Typically, each country develops their own models to be applied at the local scale because it is more convenient. But, for Quercus suber, a joint regional model can be more beneficial, since the species is distributed across the Mediterranean and is challenging to account for due to felling limitations and the nature of mature cork biomass itself. We found that these characteristics are reflected in the biomass datasets and compatibility was, perhaps, the largest impediment to such a model. The use of dummy variables to differentiate between countries, as well as compromises in the limits of biomass compartments, allowed us to develop two joint models to estimate aboveground biomass in Portugal, Spain and Tunisia. One model as a function of diameter and another as a function of diameter and total tree height. In addition, we developed a separate model for roots (modelling efficiency of fitting = 0.89), since it was not possible to assure additivity of the whole tree. All coefficients were estimated using Seemingly Unrelated Regressions (SUR) and model fitting assured additivity in the aboveground compartments-leaves and woody biomass (modelling efficiency of fitting = 0.89 and 0.93, respectively). This work proves that it is possible to have a biologically sound and efficient model for the three countries, despite differences in the observed allometric patterns.

Automated summary

Accurate estimation of biomass is crucial for the sustainable management of forest resources, especially in the face of climate change. For Quercus suber, a joint regional model would be more beneficial due to its distribution and the nature of its biomass. However, compatibility issues proved to be a major challenge. By using dummy variables and making compromises in biomass compartments, we successfully developed two joint models to estimate aboveground biomass in Portugal, Spain, and Tunisia. We also developed a separate model for roots. All coefficients were estimated using Seemingly Unrelated Regressions (SUR) and model fitting was ensured. This work demonstrates the possibility of establishing a biologically sound and efficient model for these three countries.