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Using a generalized vegetation model to simulate vegetation dynamics in northeastern USA

Hickler, Thomas LU ; Smith, Benjamin LU ; Sykes, Martin LU ; Davis, MB; Sugita, S and Walker, K (2004) In Ecology 85(2). p.519-530
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... (More)
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 CO, levels, without a need for reparameterization. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Itasca State Park, North America, Great Lakes region, forest gap models, disturbance, fire, USA, Minnesota, Cedar Creek Natural History Area, ecosystem model, LPJ-GUESS, old-growth forest, savanna, Sylvania Wilderness, Michigan, vegetation dynamics
in
Ecology
volume
85
issue
2
pages
519 - 530
publisher
Ecological Society of America
external identifiers
  • wos:000220108700021
  • scopus:1542289069
ISSN
0012-9658
DOI
10.1890/02-0344
language
English
LU publication?
yes
id
df8d9326-89cb-4b60-9166-4dd623c8379a (old id 285566)
date added to LUP
2007-10-30 11:58:30
date last changed
2017-10-22 04:35:29
@article{df8d9326-89cb-4b60-9166-4dd623c8379a,
  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 CO, levels, without a need for reparameterization.},
  author       = {Hickler, Thomas and Smith, Benjamin and Sykes, Martin and Davis, MB and Sugita, S and Walker, K},
  issn         = {0012-9658},
  keyword      = {Itasca State Park,North America,Great Lakes region,forest gap models,disturbance,fire,USA,Minnesota,Cedar Creek Natural History Area,ecosystem model,LPJ-GUESS,old-growth forest,savanna,Sylvania Wilderness,Michigan,vegetation dynamics},
  language     = {eng},
  number       = {2},
  pages        = {519--530},
  publisher    = {Ecological Society of America},
  series       = {Ecology},
  title        = {Using a generalized vegetation model to simulate vegetation dynamics in northeastern USA},
  url          = {http://dx.doi.org/10.1890/02-0344},
  volume       = {85},
  year         = {2004},
}