Background Maritime pine (Pinus pinaster Ait.) is a common conifer species in Portugal that contributes significantly to the national economy. Accurate classification
of forest productivity based on site index and height growth dynamics is the main basis for sustainable forest management of this species.
Objectives The main objective of this study was to develop a new dynamic site-dependent height–age model for the maritime pine in Portugal, using the generalized algebraic difference approach (GADA) methodology, and to explore possible improvements of the model´s performance by expanding its parameters as sub-functions of soil and climate variables.
Methods We tested for this purpose several dynamic equations, including anamorphic, polymorphic with common asymptote, and polymorphic with multiple asymptotes equations. The candidate models were fitted to a large set of stem analysis data, and tested on independent data from permanent sample plots.
Results The two best models with multiple asymptotes, one anamorphic and one polymorphic, showed similar performance; however, upon expanding the parameters as
sub-functions of the climate and soil variables, the polymorphic model outperformed the anamorphic model, as well as other models previously used for the management of this species in Portugal. The results of this study also demonstrated that the maritime pine model, developed with stem analysis data, can accurately predict the dominant height growth measured on permanent sample plot data.
