Model Name: FORCLIM (FORests in a changing CLIMate)
FOREL (spatially-explicit landscape model with climate response functions similar to FORCLIM)
Authors/Developers: H. Bugmann (ETHZ Zurich), A.M. Solomon (USEPA Corvallis, now USFS
Washington Office), R.T. Busing (USGS Corvallis)
Model Category (related to what types of ecosystem services): Forest community and
ecosystem dynamics model
Ecosystem types (e.g., forest, aquatic): Forests
Time Step: Annual
Maximum run length: Multiple Centuries
Spatial Scale/representation: Sites, watersheds, landscapes/grid-based, spatially interactive
model (FOREL, Busing 2007) is also available for landscape dynamics
Language: MODULA 2, C, C# (FORCLIM), and FORTRAN (FOREL) versions are available
Computing Environment (UNIX, PC, LINUX): UNIX or PC
Equations mainly statistical or process-based? Process-based
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc)
FORCLIM simulates the dynamics of multiple tree species populations and ages on patches of
land. It tracks the establishment, growth and mortality of each tree in response to temperature
extremes, growing degree days, drought, light availability and nutrient availability. Mortality can
also be affected by disturbances of varying severity. For example, fire effects can be simulated
with the PNW version developed ca. 2005.
Forcing/Driving variables: Site temperature, precipitation, soil water holding capacity, soil depth, soil
fertility, population responses of tree species
Output variables: Forest composition, forest structure, density, basal area, biomass, detritus
mass, LAI
Availability/Source (e.g., freeware, website, need to contact authors)
FORCLIM: contact Harald Bugmann
FOREL (spatially-explicit model): contact Rick Busing (rtbusing@aol.com)
Key Publications
Bugmann (1996) ECOLOGY 77:2055-2074
Bugmann & Solomon (2000) ECOLOGICAL APPLICATIONS 10:95-114
Busing et al. (2007) ECOLOGICAL APPLICATIONS (in press)
Busing (2007) USGS SIR 2007-5040
URL Links
pubs.er.usgs.gov (search author: busing)
LTER6 user contact: Tom Spies, Rick Busing (rtbusing@aol.com)
Bob McKane (mckane.bob@epa.gov)
1
Model Name: GTHM-MEL
(Georgia Tech Hydrology Model coupled with the Multiple Element Limitation model)
Authors/Developers: GTHM: Marc Stieglitz & Feifei Pan, Georgia Institute of Technology,
Atlanta, GA; MEL: Ed Rastetter, Marine Biological Laboratory, Woods Hole, MA
Model Category (related to what types of ecosystem services)
Eco-hydrology model, linking hydrologic and biogeochemical processes in a spatially explicit
framework
Ecosystem types (e.g., forest, aquatic): Forests, grasslands, agricultural, tundra…
Time Step: Daily
Maximum run length: Centuries
Spatial Scale/representation: Hillslopes, watersheds, landscapes/grid-based
Language: Mathematica/Delphi
Computing Environment (UNIX, PC, LINX): PC
Equations mainly statistical or process-based? Process-based
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc)
The coupled GTHM-MEL eco-hydrology model simulates the cycling and transport of
water and nutrients (C, N, P) within hillslopes and watersheds.
GTHM is a spatially-distributed representation of land-surface hydrology, including ET,
infiltration, and surface and subsurface runoff within multiple soil layers. The approach is based
on individual soil column models, each of which simulates ET and the vertical movement of water
within the soil. Soil columns may be variable in depth and surface area (delineated by user
based on soils and LULC maps). Downslope lateral flow from one column to another, or from a
column to the stream, is based on flow routing information.
MEL simulates the interaction of carbon, nitrogen and water cycles in terrestrial
vegetation and soils. MEL is based on a novel resource-optimization algorithm that simulates
how plants and microbes allocate their internal assets (biomass, proteins, carbohydrate...) to
acquire multiple resources from the environment (CO2, NH4, NO3, water, light...). For example,
as the availabilities of different resources change during succession, vegetation in MEL
acclimates by reallocating biomass and other internal assets to maintain a balanced uptake for all
resources. This ensures that all resources in the environment equally limit production, thereby
preventing too many assets from being expended for acquiring a non-limiting resource. The
intent is to provide a more realistic approach for simulating biogeochemical responses to
environmental disturbances.
Forcing/Driving variables: Topography (DEM); atmospheric CO2; daily Tmin, Tmax, precipitation,
irradiance and N deposition.
Output variables: Eco-hydrology: vertical and lateral transport of water, NH4, NO3, DON, DOC
within multiple soil layers, and discharge to surface waters.
Biogeochemistry: gross photosynthesis, autotrophic and heterotrophic respiration, nutrient uptake by
plants and microbes, vegetation growth and detritus production, formation of soil organic matter, N fixation,
denitrification, production & leaching of NH4, NO3, DON, DOC.
Availability/Source (e.g., freeware, website, need to contact authors)
GTHM: contact Marc Stieglitz (marc.stieglitz@ce.gatech.edu) and Feifei Pan (feifei.pan@ce.gatech.edu)
2
MEL: contact Ed Rastetter (erastett@mbl.edu)
Key Publications
MEL: see URL links http://ecosystems.mbl.edu/Research/Models/mel/welcome.html
GTHM: in prep
URL Links
MEL: http://ecosystems.mbl.edu/Research/Models/mel/welcome.html
HJA LTER6 user contact: Bob McKane (mckane.bob@epa.gov)
3
Model Name: LANDCARB
Authors/Developers: Harmon, Domingo, Smithwick
Model Category (related to what types of ecosystem services) Carbon, Timber Harvest
Ecosystem types (e.g., forest, aquatic):forest
Time Step : annual for most processes, but monthly for climatic indices
Maximum run length: decades to hundreds of years
Spatial Scale/representation: the grain is 0.2 to 1 ha. The extent is thousands to millions of
ha/grid-based
Language: C++
Computing Environment (UNIX, PC, LINX): PC
Equations mainly statistical or process-based? Process based
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc)
Community/population processes- colonization, establishment, mortality, competition, succession
Hydrological processes-interception, evaporation, transpiration, throughfall, run-off
Physiological processes- light absorption, transpiration, allocation, autotrophic respiration, heartrot
Ecosystem processes-growth/primary production, mortality, decomposition, formation of “stable”
organic matter
Disturbance processes- regular mortality (gap formation), fire, harvest, (all of these are spatially
explict)
Forcing/Driving variables: solar radiation, minimum, maximum, and mean air temperature,
precipitation, soil characteristics (depth, coarse fraction, texture), topography (slope steepness
and aspect), disturbance regime, management system
Output variables: the major pools predicted are: live, dead, stable, and total carbon pools, the
volume and density of trees, and the amount of harvest. For the major pools there are subpools
(i.e., live contains foliage, branches, fine roots, coarse roots, sapwood, heartwood and heart-rot).
Other output variables can be requested for information about climatic indices, and processes
rates.
Availability/Source (e.g., freeware, website, need to contact authors): Need to contact
authors as the model is being significantly revamped in the next year.
4
Key Publications
Cohen, W. B., M. E. Harmon, D. O. Wallin, and M. Fiorella. 1996. Two decades of
carbon flux from forests of the Pacific Northwest. Bioscience 46:836-844.
Smithwick, E. A. H., M. E. Harmon, and J. B. Domingo. 2007. Changing temporal
patterns of forest carbon stores and net ecosystem carbon balance: The stand to landscape
transformation. Landscape Ecology 22:77-94.
URL Links:
not available
HJA LTER6 user contact: Mark Harmon
5
Model Name: LPJ-GUESS (Generalized Ecosystem Simulator)
Authors/Developers: Ben Smith (Lund Univ.), I. Colin Prentice (Univ. Bristol), Martin Sykes
(Lund Univ.), Stephen Sitch (UK MetOffice, Wallingford, UK)
Model Category (related to what types of ecosystem services)
Plant biodiversity, production, carbon sequestration
Ecosystem types (e.g., forest, aquatic): Terrestrial
plant species, plant functional types
(PFTs, e.g., grass, needleleaf evergreen trees), biomes (e.g., grassland, boreal forest,
desert)
Time Step: Daily
Maximum run length: Centuries or longer
Spatial Scale: Landscapes (approx. 30-second grid cell resolution) to global
Language: C++
Computing Environment (UNIX, PC, LINX): PC.
Equations mainly statistical or process-based? Process-based
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc):
Carbon and nutrient dynamics: photosynthesis, respiration, and carbon allocation for individual
plants; soil and litter decomposition
Biodiversity: taxa and PFT distributions, mortality, establishment, and resource competition for
light and water among individual plants; fire disturbance
Hydrology: interception, evaporation, percolation, surface and subsurface runoff, snowmelt,
transpiration.
Forcing/Driving variables:
Daily or monthly temperature, precipitation, and sunshine, annual atmospheric CO 2
concentration, soil variables (e.g., water-holding capacity)
Output variables:
Taxa or PFT-specific variables describing vegetation types, plant productivity (e.g., NPP, leaf
area index, respiration), soil-hydrology (e.g., evapotranspiration, available soil-water), soil organic
matter, litter, fire regime dynamics, etc.
Availability/Source (e.g., freeware, website, need to contact authors)
Model code may be requested from Ben Smith (Lund Univ.)
Key Publications
Sitch, S., B. Smith, I. C. Prentice, A. Arneth, A. Bondeau, W. Cramer, J. O. Kaplan, S. Levis, W.
Lucht, M. T. Sykes, K. Thonicke, and S. Venevsky. 2003. Evaluation of ecosystem
dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global
vegetation model. Global Change Biology 9:161-185.
Smith, B., I. C. Prentice, M. T. Sykes. 2001. Representation of vegetation dynamics in the
modelling of terrestrial ecosystems: comparing two contrasting approaches within
European climate space. Global Ecology & Biogeography 10:621-637.
6
URL Links
http://www.nateko.lu.se/embers/
http://www.pik-potsdam.de/members/erbrecht/lpjweb/
HJA LTER6 user contact: Sarah
Shafer (sshafer@usgs.gov)
7
Model Name: LPJ (Lund-Potsdam-Jena)
Authors/Developers :I. Colin Prentice (Univ. Bristol), Wolfgang Cramer (Potsdam Institute for
Climate Impacts Research), Martin Sykes (Lund Univ.), Stephen Sitch (UK MetOffice,
Wallingford, UK), Ben Smith (Lund Univ.) and the LPJ consortium members
Model Category (related to what types of ecosystem services):
Dynamic global vegetation model (DGVM)
Ecosystem types (e.g., forest, aquatic):
Terrestrial plant functional types (PFTs, e.g., grass, needleleaf evergreen trees), biomes (e.g.,
grassland, boreal forest, desert)
Time Step: Daily
Maximum run length: Centuries or longer
Spatial Scale: Landscapes (approx. 30-second grid cell resolution) to global
Language: FORTAN77, FORTRAN90, C, C++ (Different versions of the model are written in
different languages)
Computing Environment (UNIX, PC, LINX):
PC windows or PC-LINX.
Equations mainly statistical or process-based? Process-based
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc):
Carbon and nutrient dynamics: photosynthesis, respiration, carbon allocation, soil and litter
decomposition
Biodiversity: PFT and biome distributions, mortality, establishment, and resource competition for
light and water, fire disturbance
Hydrology: interception, evaporation, percolation, surface and subsurface runoff, snowmelt,
transpiration
Forcing/Driving variables:
Daily or monthly temperature, precipitation, and sunshine, mean annual atmospheric CO2
concentration, soil variables (e.g., water-holding capacity)
Output variables:
PFT-specific variables describing vegetation types, plant productivity (e.g., NPP, leaf area index,
respiration), hydrology (e.g., evapotranspiration, available soil-water), soil organic matter, litter,
fire regime dynamics, etc.
Availability/Source (e.g., freeware, website, need to contact authors):
Older versions of the model are available via the LPJ project website (http://www.pikpotsdam.de/members/erbrecht/lpjweb/), newer versions of the model may be requested from the
authors.
Key Publications
Gerten, D., S. Schaphoff, U. Haberlandt, W. Lucht, S. Sitch. 2004. Terrestrial vegetation and
water balance—hydrological evaluation of a dynamic global vegetation model. Journal of
Hydrology 286:249-279.
8
Sitch, S., B. Smith, I. C. Prentice, A. Arneth, A. Bondeau, W. Cramer, J. O. Kaplan, S. Levis, W.
Lucht, M. T. Sykes, K. Thonicke, and S. Venevsky. 2003. Evaluation of ecosystem
dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global
vegetation model. Global Change Biology 9:161-185.
URL Links:http://www.pik-potsdam.de/members/erbrecht/lpjweb/
HJA LTER6 user contact: Sarah
Shafer (sshafer@usgs.gov)
9
Model Name: Stream Ecosystem Model
Authors/Developers: McIntire and Colby
Model Category (related to what types of ecosystem services): aquatic
Ecosystem types (e.g., forest, aquatic): Aquatic and riparian
Time Step: mostly daily but riparian and primary production hourly
Maximum run length: 1year
Spatial Scale/representation: reach or point
Language: fortran
Computing Environment (UNIX, PC, LINX): PC
Equations mainly statistical or process-based? Process
Processes represented (please list in general terms; e.g., evaporation, transpiration,
allocation, etc) The M & C Stream Model has a hierarchical structure that represents biological processes that
are usually active in most lotic ecosystems. From this perspective, stream ecosystems are
conceptualized as two coupled subsystems, the processes of primary consumption and
predation. Primary Consumption represents all processes associated with the direct consumption
and decomposition of both autotrophic organisms and detritus, including that of autochthonous
production dynamics of the autotrophic organisms collectively. Predation includes processes
related to the transfer of energy among primary, secondary, and tertiary macroconsumers. The
subsystems of Predation are the processes of invertebrate and vertebrate predation, whereas
Primary Consumption is represented by the processes of herbivory and detritivory. Herbivory
consists of all processes associeated with the production and consumption of autotrophic
organisms within the system, whereas Detritivory includes the consumption and decomposition of
detrital inputs. The corresponding subsystems of Herbivory are Primary Production and Grazing,
and those of Detritivory include Shredding, Collecting, and Microbial Decomposition.
Forcing/Driving variables: physical chemical
Output variables: standing stocks of functional feeding groups,
Availability/Source (e.g., freeware, website, need to contact authors)
Freeware on hja web page.
Key Publications
McIntire, C. David; Colby, Jonathon A. 1978. A hierarchical model of lotic ecosystems. Ecological
Monographs. 48(1): 167-190
McIntire, C. David; Gregory, Stanley V.; Steinman, Alan D.; Lamberti, Gary A. 1996. Modeling
benthic algal communities: an example from stream ecology. In: Stevenson, R. J.;
Bothwell, M.; Lowe, R. L., eds. Benthic algal ecology in freshwater ecosystems (Algal
Ecology). Academic Press, Inc.: 669-704.
McIntire, C. David; Colby, Jonathon A.; Hall, James D. 1975. The dynamics of small lotic
ecosystems: a modeling approach. Verhandlungen International Verein Limnologie. 19:
1599-1609.
URL Links
10
http://www.fsl.orst.edu/lter/data/tools/models/strmeco.cfm?topnav=148
HJA LTER6 user contact: Sherri Johnson
11