This new, biologically based, nonlinear regression model produces polymorphic site index and height curves as a function of prediction age and a height at any age. The curves are constrained to pass through the origin and appropriate heights at any index age. The model was parametrized on 970 stem-analyzed trees and tested on tree measurements from 147 permanent sample plots. Compared with other lodgepole pine (Pinuscontorta var. latifolia Engelm.) height models in Alberta, this model had fewer parameters, yet showed better accuracy and precision than the other models. Above all, the new model provides compatible site index and height estimates, and it can predict height without prior knowledge of site index.
With two examples of five-parameter, fixed-base-age site index and height growth equations, I demonstrate three methods for deriving dynamic equations that are base-age invariant and use only three parameters. These are initial condition difference equations that compute appropriate heights at all base ages and provide compatible height and site index values from one common equation. Despite having fewer parameters, they can model a broader selection of curves than the original equations. The new equations are applicable for all situations in which the original equations could be applied. Methods demonstrated in this paper can enhance the development of all recursive and otherwise implicitly defined equations used for modeling of height, diameter, basal area, volume, number of trees per hectare, and investment yields.
The field of forestry has employed various computer-assisted optimisation approaches since the early 1960s to address the efficient allocation of resources towards various forest management objectives. These approaches continue to evolve, and in the last 5 years, the research has expanded to demonstrate how complex, non-linear relationships can be recognised and incorporated into planning processes at the tree, stand, forest and landscape levels. In addition to an overview of the use of optimisation in forestry, we provide an examination of work published in the last 5 years from 30 international journals, worldwide, which consistently publish forestry and natural resource management research papers. Through this review, we found that landscape-level optimisation is a relatively new and expanding area of research, most often performed by one large public landowner in regions where the resulting plan of action has an effect on all landowners and resources. We also note that at the forest level, exact methods for optimising systems mainly continue to be used, and at the stand level, optimisation seems to now involve exploration of a variety of analytical methods. A large portion of the recent research in the optimisation of forest management have involved European forests, which is a function of large public ownership of land and the tradition and requirements for management planning, and roughly half of the effort has arisen from researchers located in Nordic countries (Denmark, Finland, Norway and Sweden).
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