The SYMFOR framework for modelling the effects of silviculture on the growth and yield of tropical forests
Abstract
SYMFOR is a software framework allowing forest managers and policy makers to simulate the effects of silvicultural treatments on mixed tropical forests. The framework is designed to use Permanent Sample Plot data and house individual-based, spatially explicit models of silvicultural treatments and ecological processes. The framework and models are presented through a Windows-based User Interface with on-line documentation. The framework represents trees on an individual, spatial basis allowing models to represent practical and theoretical forest management explicitly. This is of particular importance for tropical forests where the high biodiversity makes the forest spatially complex.
In many areas of the tropics, new forest management methods are being im-plemented without knowledge of likely outcomes. SYMFOR enables trials to be simulated, permitting comparisons between alternative management regimes, and allowing the examination of the likely effects or outcomes resulting from silvicultural treatments. Predictions of yield, forest structure and composition in both the immediate and the long-term are possible using SYMFOR and are essential for informed forest management decision-making. These estimates can be combined with analysis of likely financial, economic and social outcomes to assess the likely sustainability of forest management regimes.
The core structures of the SYMFOR framework allow modellers to add new processes or models using a simple procedure at design time. The choice of models and their associated parameter values are made or loaded at run-time. The user interface handles data input and output, graphical displays and model selection and definition. The core structures of the SYMFOR framework and an overview of the user interface are presented here.
Citation
Phillips, P.D.; Van Gardingen, P.R. The SYMFOR framework for modelling the effects of silviculture on the growth and yield of tropical forests. In: Rennolls, K. (Ed) Forest Biometry, Modelling and Information Science. Proceedings of IUFRO 4.11 Conference. University of Greenwich, London, UK (2001) 1-12.
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