Welcome

This web site is the home for a research project involving the Forest Vegetation Simulator (FVS) in the Great Lakes region of the US upper midwest and the Canadian province of Ontario.  FVS is a forest modelling framework that has been used extensively in the United States and more recently in Canada.  FVS is most appropriately called a simulation framework rather than a model, because many variants have been created that use different growth engines in a similar larger structure.  For example, all FVS variants have growth and mortality components, many have regeneration components, and all variants simulate trees individually and aspatially and summarize from the individual to the stand level to generate composite outputs.

The original FVS variant is the Prognosis Model for Stand Development (Prognosis – Wykoff et al. 1982), developed by the USDA Forest Service for the northern Rocky Mountain region of Idaho and western Montana, USA.  In the US Great Lakes region, FVS uses a growth engine adapted from the TWIGS model developed by the USDA Forest Service in the 1980s (Miner et al. 1988). The British Columbia Ministry of Forests has adapted the Prognosis growth engine for the Province and developed a new FVS software implementation (called PrognosisBC) in metric units.  Recently, the PrognosisBC software and the TWIGS FVS growth engine have been adapted for many Ontario forest conditions (called FVS^Ontario).

As implemented in FVS, Prognosis and TWIGS have important similarities and differences.  Both growth engines are aspatial, single-tree, diameter-driven simulators with prediction equations empirically calibrated using regression techniques.  They both divide trees into two groups, based on diameter, that are simulated separately. For example, in TWIGS a breakpoint of 7.62-15.24 cm (3-6 in.) dbh is used, depending on species, to distinguish between “large” and “small” trees.  They differ in how site quality is represented; in TWIGS site index (SI) is the only proxy for site effects, while Prognosis eschews SI and uses instead a number of variables including slope, aspect, elevation, geographic location and habitat type, the latter an ecological classification system.  Also, the TWIGS model uses a “potential times modifier” (POTMOD) approach to predicting diameter increment, where the prediction is a composite of two parts, one representing the potential increment of a tree with little competition from neighbours, and the other the fraction of the potential that is achieved by a given tree.  In contrast, Prognosis uses a single curvilinear equation that describes increment as a continuous function of tree size, site and competition effects.

Problem Statement

The Prognosis and TWIGS growth engines were developed independently, in different geographic regions and in response to differently perceived needs.  This at least partially explains their differences and similarities.  That they were incorporated and not substituted by one or the other in the larger FVS framework is also not surprising, because of the substantial investment in and user acceptance of each in their respective regions.  Nevertheless, a thorough examination of the strengths, weaknesses and costs or benefits of selecting one approach over the other has not been made.  Furthermore, recent research has suggested further refinement of how site quality effects are included in the prediction equations should be undertaken.  A calibration of portions of the TWIGS engine for FVS^Ontario produced increment equations for many species where SI was not statistically useful (Lacerte et al. 2004), which is a counterintuitive result.  Other studies have suggested improvements in accuracy or flexibility may be obtained if spatially imputed values of climate, soils or other variables are used to augment or replace traditional site quality predictors (e.g., Froese 2003; Gustafson et al. 2003).