Physiology in Forest Models: History and the Future

Empirical models are standard tools in forest management. They provide quantitative information for management and planning that is accurate within the limits of sampling and measurement accuracy, but they are generally site-specific and cannot simulate the results of changing conditions. Mechanistic, or process-based models, based on the physiological processes that govern tree growth can, in principle, provide estimates of the potential productivity of sites for which no mensuration data exist, calculate realized growth and evaluate the effects of actions such as fertilisation or thinning, or the impact of pests and diseases on productivity. It should also be possible to use these models to evaluate the probable effects of climate change on forest growth. However, most process-based models contain too many poorly known parameters and their projections are not as reliable in practice as those of empirical models. In addition they have not, up to now, produced outputs of interest to those concerned with forest management. The reasons for this state of affairs are considered and a brief historical survey of some of the physiological research that, over the last 30 years, has produced the knowledge and information needed to produce useful, practical process-based forest models, is presented. The survey deals with light interception, photosynthesis, stomatal conductance, water relations and nutrition. The evolution of process-based models is outlined, leading to the central thesis of the paper: that hybrid models, combining the advantages of process-based and conventional empirical models will be the management tools of the foreseeable future. The software for these models should be well-designed, robust, ‘user friendly’ and open, in the sense that it is freely available and can be modified by users. Brief comments on mensuration procedures for hybrid models, weather data and the use and values of Geographical Information Systems and remote sensing are provided.