Modelling forest ecosystems: state of the art, challenges, and future directions

Abstract

Forest models should in future combine the predictive power and flexibility of process-based models with the empirical information and descriptive accuracy of conventional mensuration-based models. Progress is likely to be rapid if model developers identify the potential users of their models and the needs of those users. Users include operational forest managers, planners, bureaucrats, politicians, community and environmental groups, scientists, and academics. Extant models that could be used immediately or could be adapted for use by these groups are reviewed. Currently available process-based models can provide good estimates of growth and biomass productivity at various scales; combined with conventional models they can provide information of the type required by managers and planners. Climate-driven models can provide good estimates of potential plantation productivity, while detailed process models contribute to our understanding of the way systems function and are essential for future progress. Technical challenges for the future include continued research on carbon-allocation processes, nutrient availability in soils, and nutrient uptake by trees. It is important that we have models that can be used to predict and analyze the effects of technologies such as clonal forestry and possible genetic manipulation, as well as intensive management in relation to nutrition, weed control, and disease control. Large-scale analysis of forest productivity is already possible using models driven by remote sensing; inclusion of nutrition should be a goal in this area. Moves towards active collaboration and the implementation of mixed models in operational systems, as well as improving communication between model developers and users, should ensure that practical problems are identified and fed back to modellers, which should lead to rapid progress.