1. General Model Information

Name: Grassland Ecosystem Model

Acronym: GEM_1


Main medium: air+terrestrial
Main subject: biogeochemistry
Organization level:
Type of model: not specified
Main application:
Keywords: grassland, agroecosystem, CO2, temperature changes, precipitation changes, nutrient cycling, climate change, elevated CO2, nutrient limitation, Agropyron cristatum, Bouteloua gracilis

Contact:

H. William Hunt
Natural Resources Ecology Lab
Colorado State University
Fort Collins, CO 80523Phone: 970 491-1985
Fax : 970 491-1965
email: billh@eleocharis.nrel.colostate.edu

Author(s):

H. William Hunt

Abstract:

GEM (Grassland Ecosystem Model) is a grassland and agroecosystem simulation, as well as a process and predictive model used to explore the interactions of elevated CO2, elevated temperature and precipitation changes on grassland production, decomposition rates and nutrient cycling. It is one of several large models that derive its origin from the ELM model.

GEM differs from other ELM-related models in that it has refined photosynthesis components, and the ability to model two species that differ in their photosynthetic pathways (Hunt et al., 1991).

The model has been validated by executing it under different scenarios. Outputs from these executions were examined to determine whether trends were likely to occur and whether short-term predictions agreed with experiments on physiological processes.

The model contains water, plant and decomposition components. The driving variables include daily precipitation, weekly maximum and minimum air temperature, wind speeds, relative humidity and monthly soil temperature. State variables include soil inorganic ammonium and nitrate levels. Several parameters (e.g. growth parameters) are also required for proper model execution.

Author of the abstract:

CIESIN (CONSORTIUM FOR INTERN SCIENCE INFORMATION NETWORK) :

A Model Data Needs Assessment Report CIESIN


II. Technical Information

II.1 Executables:

Operating System(s): UNIX Computer Requirements: Sun SPARC 1, runs in 2-3 minutes for 2-3 year increments. Threeinput files (initial values, initial PH, initial dv). Output file (svout, a large binary output file, and asummary file)

II.2 Source-code:

Programming Language(s): FORTRAN 77 (6600 lines of code)

II.3 Manuals:



II.4 Data:



III. Mathematical Information


III.1 Mathematics


III.2 Quantities

Driving variables: daily precipitation., weekly max/ min air

III.2.1 Input

Driving variables: daily precipitation., weekly max/ min airtemperatures, wind speed, relative humidity, monthly mean soil temperature. State variables: soiland inorganic ammonium, nitrate data. Other data requirements for other situations: e.g. growthparameters.

III.2.2 Output


IV. References

Hunt, H.W., M.J. Trlica, E.F. Redente, J.C. Moore, J.K. Detling,T.G.F. Kittel, D.E. Walter, M.C. Fowler, D.A. Klein and E.T.Elliot. 1991. Simulation model for the effects of climate changeon temperate grassland ecosystems. Ecol. Mod. 53: 205-246.

V. Further information in the World-Wide-Web



VI. Additional remarks

Global change implications: This model has been used for globalchange research to predict grassland ecosystem dynamics as they could be affected by expected changes in temperature, elevated CO2 concentrations andchanges in precipitation (Hunt et al., 1991). Potential responses of grasslands to several climate change scenarios were examined using 40-year projections. This research showed that changes in precipitation had a greater effect on grassland productivity than did elevated temperature or elevated carbon dioxide. Elevated CO2 also led to increased amounts of carbon storage in grassland ecosystems.


Last review of this document by: T. Gabele : 17. Sep 1997
-
Status of the document:
last modified by Tobias Gabele Wed Aug 21 21:44:43 CEST 2002

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