Allometric equations for predicting mineralomass in high-forest chestnut stands in Portugal
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The evaluation of nutrients in biomass tree-components is a process time consuming and
expensive, often involving tree felling, not always possible or desirable. Thus, mineralomass
prediction equations are an important tool for the quantification of the nutrients exported in
management and harvesting activities towards to its replacement and sustainable management
as well as to evaluate the effect of other disturbances in the balance of ecosystems. Thus, given
the importance of the relationship of biomass and nutrients (mineralomass) for dynamic and
sustainable management of chestnut woodlands, aboveground mineralomass was studied in sweet
chestnut (Castanea sativa Mill.) high forest stands located in Northern Portugal. Nutrient specific
prediction equations that allow estimating the mineralomass (N, P, K, Ca, Mg, S, B and C) above
the ground, total and by components: stem-wood, stem-bark, branches, leaves and flowers, based
on tree dendrometric variables, DBH (diameter breast height) and total height, were developed.
Linear and non-linear regression estimation methods were used. Data analysis is based on
information collected in destructive analysis of thirty-four felled trees, distributed by the existing
diameter classes (10-65 cm) in three adult chestnut stands. Several linear and nonlinear equations
were fitted by the least squares method to select models. A simultaneous fit by SUR method using
iterative seemingly unrelated regression (ITSUR) was used for the final selected models. The best fitting
models are presented.
