Growth and yield models for uneven-aged stands: past, present and future

2000

S. 259-279

1 Abb, 3 Tab., zahlr. Lit. Ang.

Unselbständiges Werk

200067965

Growth and yield modeling has a long history in forestry. Methods of measuring the growth of uneven-aged forest stands have evolved from those developed in France and Switzerland during the last century. Furthermore, uneven-aged growth and yield modeling has progressed rapidly since the first models were pioneered by Moser and Hall (1969) (Moser Jr., J.W., Hall, O.F., 1969, For.Sci. 15, 183-188). Over the years, a variety of models have been developed for predicting the growth and yield of uneven-aged stands using both individual and stand-level approaches. Modeling methodology not only has moved from an empirical approach to a more ecological process-based mechanistic approach, but also has incorporated a variety of techniques, such as, (1) systems of equations, (2) nonlinear stand table projections, (3) Markov chains, (4) matrix models, and (5) artifical neural network models. However, modeling the growth and yield of uneven-aged stands has received much less attention than that of even-aged stands. This paper reviews the current literature regarding growth and yield models for uneven-aged stands, discusses basic types of models and their merits, and reports recent progress in modeling the growth and dynamics of uneven-aged stands. Furthermore, future trends involving integration of new computer technologies (object-oriented programming and user-friendly interfaces), tree visualization techniques, and the spatially explicit application of Geographical Information Systems (GIS) into uneven-aged modeling strategies are discussed.