USING A GENERALIZED VEGETATION MODEL TO SIMULATE VEGETATION DYNAMICS IN NORTHEASTERN USA

Abstract

Models based on generalized plant physiological theory represent a promising approach for describing vegetation responses to environmental drivers on large scales but must be tested for their ability to reproduce features of real vegetation. We tested the capability of a generalized vegetation model (LPJ-GUESS) to simulate vegetation structural and compositional dynamics under various disturbance regimes at the transition between prairie, northern hardwoods, and boreal forest in the Great Lakes region of the United States. LPJ-GUESS combines detailed representations of population dynamics as commonly used in forest gap models with the same mechanistic representations of plant physiological processes as adopted by a dynamic global vegetation model (the Lund-Potsdam-Jena [LPJ] model), which has been validated from the stand to the global scale. The model does not require site-specific calibration. The required input data are information on climate, atmospheric CO2 concentration, and soil texture class, as well as information on generally recognized species traits (broad-leaved vs. needle-leaved, general climatic range, two fire-resistance classes, shade-tolerance class, and maximum longevity). Model predictions correspond closely to observed patterns of vegetation dynamics and standing biomass at an old-growth eastern hemlock (Tsuga canadensis)/hardwood forest (Sylvania Wilderness, Michigan), an old-growth forest remnant from the “Great Lakes Pines Forest” (Itasca State Park, Minnesota), and a presettlement savanna (Cedar Creek Natural History Area, Minnesota). At all three sites, disturbance (wind or fire) strongly controls species composition and stand biomass. The model could be used to simulate vegetation dynamics on a regional basis or under past or future climates and atmospheric CO2 levels, without a need for reparameterization.