Calibration of the forest vegetation simulator (FVS) model for the main forest species of Ontario, Canada

Abstract

The forest vegetation simulator (FVS) model was calibrated for use in Ontario, Canada, to predict the growth of forest stands. Using data from permanent sample plots originating from different regions of Ontario, new models were derived for dbh growth rate, survival rate, stem height and species group density index for large trees and height and dbh growth rate for small trees. The dataset included black spruce ( Picea mariana (Mill.) B.S.P.) and jack pine ( Pinus banksiana Lamb.) for the boreal region, sugar maple ( Acer saccharum Marsh.), white pine ( Pinus strobus L.), red pine ( Pinus resinosa Ait.) and yellow birch ( Betula alleghaniensis Britton) for the Great Lakes-St. Lawrence region, and balsam fir ( Abies balsamea (L.) Mill.) and trembling aspen ( Populus tremuloides Michx.) for both regions. These new models were validated against an independent dataset that consisted of permanent sample plots located in Quebec. The new models predicted biologically consistent growth patterns whereas some of the original models from the Lake States version of FVS occasionally did not. The new models also fitted the calibration (Ontario) data better than the original FVS models. The validation against independent data from Quebec showed that the new models generally had a lower prediction error than the original FVS models.