PROCESS-BASED FOREST PRODUCTIVITY MODELS AND THEIR APPLICATION IN FOREST MANAGEMENT

Few process-based forest productivity models have become incorporated into forest management systems. The prevalent perception is that proce ss-based models are suited only for research applications and that man agement questions will be solved only by using descriptive empirical m odels. This is despite the fact that the latter can neither deal satis factorily with changing environmental and management conditions nor an swer all questions currently asked by managers. This paper develops th e proposition that the end-use specifies the design and scale of fores t simulation models, and that given the range of questions now asked i n forest management a range of models is required. The spatial and tem poral resolution, and the input and output data required to address ty pical forest management questions is examined. A survey of recent lite rature examines in which areas, and by whom, existing forest productiv ity models are being applied. It is concluded that many current manage ment questions can be adequately answered using models in which a phen omenological approach is applied to predict annual forest growth at th e stand-scale. Lumped-parameter process-based models and hybrid models provide the most immediate means through which our understanding of t he biological processes underlying forest growth can be included in fo rest management systems. However, more detailed process-based models c an Flay an important role in validating simpler models, in the develop ment of generalizations applicable over long time scales and for testi ng hypotheses about the way trees function and respond to interacting stresses. Guidelines are also given on model structures appropriate fo r different classes of management questions. (C) 1998 Elsevier Science B.V.