Difference between revisions of "EFIMOD"

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[[Category:Forest and ecosystem models]]
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[[Image:EFIMOD_GUI.jpg|300px|thumb|EFIMOD user interface]]
 
[[Image:EFIMOD_GUI.jpg|300px|thumb|EFIMOD user interface]]
  

Revision as of 13:50, 24 January 2010

General System description

Flowchart of EFIMOD-DLES

System name: EFIMOD-Discrete Lattice Ecosystem Simulator

Acronym: EFIMOD-DLES

Brief overview

EFIMOD is a tool to forecast carbon and nitrogen flows in forest ecosystems with strong feedback mechanism between soil and stand. It allows for description and spatial analysis of mixed stand dynamics in boreal and temperate forests at different management and external impacts.
EFIMOD user interface

Scope of the system

The tool provides information to assess forest/soil natural development, forest/land-use management, and different scenarios of external impacts.

System origin

It was developed by a researchers’ team in the Institute of Physico-Chemical and Biological Problems in Soil Science (Pushchino, Russia) and Biological Institute of Sankt-Petersburg State University with support of European Forest Institute (Joensuu, Finland) and Joensuu University (Joensuu, Finland). First prototype was implemented in 1996 being not a commercial product The tool has been applied in Russia, Finland, Sweden, Canada, the Netherlands, Bulgaria, Czech Republic, and in several international projects (three projects in INTAS EU Program, FP5 EU-Programme Project CT98-4124 “Relationships Between Recent Changes of Growth and Nutrition of Norway Spruce, Scots Pine, and European Beech Forests in Europe (RECOGNITION)”, FP6 EU Programme INCO - 013388 “Impacts and risks from anthrpogenic disturbances on soils, carbon dynamics and vegetation in podzolic ecosystems (OMRISK)” and other projects. It has been implemented also for several applications in frame of the National Program of Russian Academy of Sciences “Change of Environment and Climate”.

Application of EFIMOD

Support for specific issues

The system is designed to take into account timber harvest effects, dynamics of ecosystem and forest understorey biodiversivity, climate change effects, landscape analysis methods, nitrogen deposition effects, and fires.

Support for specific thematic areas of a problem type

  • Silvicultural
  • Conservation
  • Restoration
  • Development choices / land use zoning
  • Sustainability impact assessment (SIA)

Capability to support decision making phases

In current version, the GUI helps the user to compare dynamics of ecosystem parameters (e.g. growing stock, stand and soil carbon and nitrogen pools, biodiversity ranks etc.) at different scenarios of forest management and other external impacts.

Related systems

CommonGIS

Data and data models

Typical spatial extent of application

The application can be used on regional, forest-enterprise, and forest stand scale.

Forest data input

The system uses stand-level inputs from forest inventory database, the pools of soil organic matter and nitrogen in different soil layers, and climatic and hydrological data. Detailed list of input parameters you may find at EFIMOD-DLES webpage.

Type of information input from user (via GUI)

User may define the scenario of forest ecosystem development via specifying various management options, such as different types of cuttings, plantings etc.; external impacts, such as fires, climate change, different levels of nitrogen deposition. For biodiversity assessment, regional phytosociological data is required.

Models

Forest models

Flowchart of EFIMOD model

The modelling tool of forest ecosystem EFIMOD [1][2][3] is an individual-based spatially explicit simulator of tree-soil system that calculates parameters of carbon balance and standard forest inventory characteristics: NPP, Rh, soil available nitrogen, tree and stand biomass by tree compartments, soil organic matter (SOM) and N pools, stand density, height, DBH, growing stock and some other parameters. It includes soil model ROMUL as an important component[4] that is driven by soil water, temperature and SOM parameters. The statistical generator of soil climate SCLISS was compiled to run ROMUL. The EFIMOD allows for a calculation the effect of silvicultural operations and forest fires. Now it is linked with a system of plant biodiversity assessment BioCalc.

Soil models

Flowchart of ROMUL model

The ROMUL model[5][6] of soil organic matter (SOM) and nitrogen mineralisation and humification calculates the transformation of litter and SOM compartments, the gross carbon dioxide flow from the soil due to SOM mineralisation and the nitrogen available for plant growth. The rate of litter and SOM mineralisation and humification is dependent on the litter quality, soil temperature and moisture, and on some soil parameters. The model validation and sensitivity analyses had been performed using a set of published laboratory and field experiments[7][8][9].

Climate models

A soil climate generator SCLISS[10] is used in the model for two purposes: (1) as a method of evaluation of soil temperature and moisture using measured standard meteorological long-term data; (2) statistical simulation (generation) of realisations of long-term series of necessary input climate data with known statistical properties. The model uses monthly average data on air, litter and soil temperature, precipitation, litter and mineral soil moisture.

Models of biodiversity

A model BioCalc (BIOdiversity CALCulator) forecasts dynamics of ecosystem and species understorey diversity of each forest unit along the EFIMOD simulation outputs on a base of standard forest inventory data linked with the results of detailed phytosociological research [11].

More detailed description of models you may find at EFIMOD-DLES webpage.

Decision Support

Definition of management interventions

The manager can intervene in the forest: time of harvest, plantations, thinnings, selective cuttings, natural regeneration, converting of forest into agricultural lands and back.

Typical temporal scale of application

The system allows for short-term prognosis (e.g. rotation period) and long-term prognosis (e.g. several generations of tree species) with annual temporal resolution.

Types of decisions supported

  • Management level
    • strategic decisions
    • operating control decisions
  • planning decisions
    • organizing decisions
    • coordination decisions

Decision-making processes and models

  • Logic modeling
  • Heuristic manipulation of simulation models
  • Simulation (with and without stochasticity)

Output

CommonGIS user interface

Types of outputs

Results are reported as tables, maps, graphs, stand-level 3-D visualizations.

Spatial analysis capabilities

The system is linked to CommonGIS.

Abilities to address interdisciplinary, multi-scaled, and political issues

The system produces coordinated results for decision makers operating at different spatial scales, facilitates social negotiation and learning.

System

System requirements

  • Hardware requirements: 1GHz x86 CPU, 256Mb RAM, 50Mb disk space.
  • Operating Systems: Windows 98/2K/XP/Vista.
  • Other software needed: the user does not need to acquire additional software.
  • Development status: completed.

Architecture and major DSS components

Describe the basic architecture of the system in software and hardware. Desktop client-server, web based, as well as the integration with available systems. Basic data flow, focusing on retrieval of required input and propagation and implementations of decisions. Mention its modular and scalability capabilities.

Usage

Research and regional administration level.

Computational limitations

Run time is impacted by the number of management units.

User interface

The system has a standard Windows GUI. Use of the system requires basic forestry and soil science background.

Documentation and support

English version of user manual is now in progress.

Installation

The system is completely portable: no special installation is required.

References

Cited references

  1. ↑ Chertov, O.G. Komarov, A.S., Tsiplianovsky, A.V. 1999. A combined simulation model of Scots pine, Norway spruce and Silver birch ecosystems in European boreal zone. Forest Ecology and Management 116: 189-206.
  2. ↑ Komarov, A., Chertov, O., Zudin, S., Nadporozhskaya, M., Mikhailov, A., Bykhovets, S., Zudina, E., Zoubkova. 2003. EFIMOD 2 - - A model of growth and elements cycling in boreal forest ecosystems. Ecological Modelling 170 (2-3): 373-392.
  3. ↑ Komarov, A.S., Chertov, O.G., Mikhailov, and Autors’ Collective (14 names). 2007. Modelling Dynamics of Organic Matter in Forest Ecosystems [Responsible editor V.N. Kudeyarov]. Nauka, Moscow. 380 p. In Russian with English contents. ISBN 5-02-034053-7.
  4. ↑ Chertov, O.G. Komarov, A.S., Nadporozhskaya, M.A., Bykhovets, S.A., Zudin, S.L. 2001. ROMUL – a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modelling. Ecological Modelling 138 (1-3): 289-308.
  5. ↑ Chertov O.G., Komarov A.S. 1997. SOMM -- a model of soil organic matter dynamics. Ecological Modelling 94(2-3): 177-189.
  6. ↑ Chertov, O.G. Komarov, A.S., Nadporozhskaya, M.A., Bykhovets, S.A., Zudin, S.L. 2001. ROMUL – a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modelling. Ecological Modelling 138 (1-3): 289-308.
  7. ↑ Chertov O.G., Komarov A.S. 1997. SOMM -- a model of soil organic matter dynamics. Ecological Modelling 94(2-3): 177-189.
  8. ↑ Chertov, O.G. Komarov, A.S., Nadporozhskaya, M.A., Bykhovets, S.A., Zudin, S.L. 2001. ROMUL – a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modelling. Ecological Modelling 138 (1-3): 289-308.
  9. ↑ Komarov, A.S., Chertov, O.G., Mikhailov, and Autors’ Collective (14 names). 2007. Modelling Dynamics of Organic Matter in Forest Ecosystems [Responsible editor V.N. Kudeyarov]. Nauka, Moscow. 380 p. In Russian with English contents. ISBN 5-02-034053-7.
  10. ↑ Chertov, O.G. Komarov, A.S., Nadporozhskaya, M.A., Bykhovets, S.A., Zudin, S.L. 2001. ROMUL – a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modelling. Ecological Modelling 138 (1-3): 289-308.
  11. ↑ Khanina, L., Bobrovsky, M., Komarov, A., Mikhajlov, A., 2007. Modelling dynamics of forest ground vegetation diversity under different forest management regimes. For. Ecol. Manage. 248: 80-94

External resources

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