Models are abstractions of reality. In order to be useful, models must include essential elements of the real world system that are to be mimicked to meet some specified modelling objective. The pattern in a data set can often be described with a relatively simple model. Models of forests have been constructed for numerous management and research objectives. To determine an appropriate modelling unit (e.g. cell, organ, tree, stand, landscape), one must define the modelling objective and the forecasting time frame. Often the level of modelling detail possible is dictated by the data available. However, there are guiding principles that can aid in selecting an appropriate level for modelling. These principles include: (i) developing as parsimonious a model as possible; and (ii) adjusting the number of state variables for the forecasting period involved. The application of these principles is discussed within the framework of forest growth and yield models. As an illustration of the relationship between model accuracy and complexity, data from a loblolly pine [Pinus taeda] spacing trial in Virginia, USA, were used to predict stand volume.

We demonstrate the methods and results for broad-scale mapping of forest site productivity for the Canadian province of Alberta. Site index (SI) data were observed for lodgepole pine (Pinus contorta var. latifolia) based on stem analysis (observed height at an index breast height age of 50 years). A total of 2624 trees at nearly 1000 site locations were available for the analysis. Mapping methods were based on ANUSPLIN, Hutchinson's thin-plate smoothing spline in four dimensions (latitude, longitude, elevation, site index). Although this approach is most often used for modelling climatic surfaces, the high density of the site productivity network in Alberta made this an appropriate application of the method. Maps are presented for lodgepole pine, the major forest species of Alberta. Although map patterns were highly complex, predicted SI decreased regularly and continuously as elevation increased from the parklands, through the foothills, to the mountains, conforming to field observations and a shorter growing season. In the high mountains, SI predictions were the lowest (<10 m), again conforming to field observations. Thus, the map correctly represents the inverse relationship between SI and elevation exhibited in the data. Analysis of residuals revealed no bias in the predictions. Furthermore, residuals were homogeneous and had no apparent pattern. The standard deviation of the observed site index values was 3.23 m, and the root mean squared error of the spline surface predictions was 1.16 m.

Generally, modelling the non-linear and complex process of current annual height increment of any timber species is significant both in dendrometric studies and in practical forest exploitation. Using the methods of artificial intelligence based on neural networks, we attempted to extract the non-linear process of height increment from the observed data sets and to generate a prediction as accurately as possible. The first part of the chapter analyses height increment of different provenances of young Douglas-fir (Pseudotsuga menziesii) stands at different sites in Serbia. After that, the corresponding data-based models of height increment were evaluated. The models of suitable sites, standard sites and unsuitable sites for Douglas-fir fast growth and development, as well as the models for superior provenances and inferior provenances, are proposed.

The effects of overstory pine basal area on plant community structure and composition were assessed in uneven-aged stands of loblolly and shortleaf pines (Pinus taedaL. and P. echinata Mill.) in southern Arkansas. Basal area treatments were 40, 60, 80, and 100 ft2/ac for the merchantable pine component (>3.5 in. dbh) and were maintained on a 6 yr cutting cycle using single-tree selection. Assessments of plant communities were made 10 yr after a single hardwood control treatment. The four levels of pine basal area had no effect on percent ground cover of most plants <3 ft tall, but ground cover from graminoids decreased as pine basal area increased. Vertical cover above loft height increased 33% as overstory basal area increased from 40 to 100 ft2/ac, but basal area had no effect on horizontal cover in height zones between 0 and 10ft. It is concluded that uneven-aged stands of loblolly-shortleaf pine with merchantable basal areas of from 40 to 100 ft²/ac may support similar plant species in the understory and consequently probably provide similar habitat requirements for a variety of game and nongame wildlife. South. J. Appl. For. 19(2):84-88.