The Science of Forestry.

Forestry is a large field with a long history and extensive contents consisting of practical recommendations arrived at by trial and error. In contrast, the science of forestry is a new development relying on reasoning to produce the optimal system of forest management aimed at satisfying human needs and preserving nature at the same time (though not at the same place). The presented overview of this science consists of two parts. The first one develops a theory of tree growth and stand dynamics. The second part applies this theory to optimize forest management and suggest practical recommendations. What unites these two parts is a general method of inquiry. It starts with defining one problem, designs two opposing explanations, and then fuses them into a single solution. Hence, the name: the 1-2-1 method. Unlike material variables of process-based models, the explanations employed by the method are abstractions that outline the boundaries embracing all possible solutions. Each explanation in its turn may be subdivided into two opposites until a solution is reached by bringing the opposites together. The 1-2-1 method accounts for any number of variables by arranging them hierarchically into paired groups. Why exactly two explanations? Because each complex problem has two opposite sides, waiting to be uncovered. We may never know how many factors determine tree growth, yet there is one thing as certain as any mathematical proposition: All these factors are of two kinds—those that facilitate growth and those that restrain it. A factor that does neither is not really a factor. The basic positive process of tree growth is uninhibited cell division. Negative processes include, among others, aging and impediments associated with increasing tree size. When these and several other processes are expressed analytically, we get a meaningful and accurate model of tree growth comprising three pairs of opposites arranged in two levels. The model generalizes empirical equations developed in forestry and exposes biological mechanisms that justify the structure of the equations and explain their success. The resulting growth model describes density-independent growth. The complementary process of competition has inter- and intraspecific components. It is shown that to maximize forest productivity interspecific competition has to be minimized while the intraspecific kind optimized. Uniting the growth model with that describing the effect of intraspecific competition produces the growth-density model that solves many questions of forest management. In particular, the model helps to reconcile two main goals of management: (a) maximizing the financial returns from wood products, and (b) preserving forests with all their biodiversity and invaluable ecosystem services. Still, the thrust of this review is not another growth model or management system. The main point is an attempt to make forestry a science by consistent reasoning from first principles such as discreteness of plant biomass, the inverse relationship between average size and number of trees, and the conflict between the biotic potential and environmental resistance. [ABSTRACT FROM AUTHOR]