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Zusammenfassung:
Forest gap models share a common structure in the way they simulate the population dynamics of forest trees. Many models contain the same ecological factors, but there is a wide variety of formulations used to implement this general structure. The comparison of models incorporating different formulations is important for model validation, for assessing the reliability of model projections obtained under climate change scenarios, and for the development of patch models for global application.
As examples of qualitative model comparisons, the various formulations used for height-diameter relationships, for the maximum growth equation, and for the effects of temperature and drought on tree growth are reviewed. The variety of formulations currently in use has the potential to influence simulation results considerably, but only few quantitative studies on this topic have been performed so far.
Studies of quantitative model comparisons are reviewed. They have yielded the following results: (1) The models are quite sensitive to the formulation of climatic factors under current conditions, and this sensitivity is even more pronounced under a changed climate; (2) Adaptations of forest gap models to specific regions often have required more detailed sub-models of species life history, thus complicating model comparison; (3) Some of the complex models developed for region-specific applications can be simplified without hampering the realism with which they simulate species composition; and (4) Attempts to apply the models without modification beyond the area for which they have been developed have produced controversial results.
It is concluded that the sensitivity of forest gap models to the exact formulation of the ecological factors should be examined in more detail, and that more systematic comparisons of model behaviour at a range of test sites would be desirable. Such studies could be valuable for evaluating the diversity of forest gap models, and they could improve our understanding of forest dynamics considerably.
