Abstract

AbstractIn Komatiland Forests (South Africa) the objectives of growth and yield research are to develop a range of empirical stand-level growth and yield models for thinned pine stands. The models are used for resource description, growth and yield predictions for the purpose of management planning and for the development of optimum stand-level management regimes. The growth and yield research programme consists of four main components, namely a field programme, long term data management, growth modelling and the development of simulation systems. For each of these components, a strategy has been developed. In the field, programme data are collected for each of the target model components from a number of sources, such as spacing trials, permanent sample plots (PSPs), silvicultural response trials, plantation inventories and destructive sampling for volume and taper data. The modelling strategy is to develop multi-component model architectures for modelling stand-level growth, namely dominant height, unthinned basal area and survival. For thinned stands, additional functions for the modelling of the basal area thinning ratio and the basal area response after thinning are required. Depending on the data, both the Chapman-Richards-type and the Schumacher-type functions are used for modelling unthinned stand-level basal area. Various methods are used for modelling basal area response after thinning, e.g. the index of suppression or the age-adjustment method. A major challenge in growth modelling is to develop models for thinned stands based on PSP data only, while conforming to the hypothesis of thinned stand growth. Stand structure is modelled using the Weibull function in conjunction with the method of moments approach for recovering the relevant Weibull parameters. Finally, the models are built into simulation systems for stand-level scenario analysis, e.g. the development of rule-based thinning and pruning systems, and also forestry scenario analysis. However, the main function of stand-level growth and yield models is still to provide for more accurate company planning systems.

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