Difference between revisions of "The Forest Time Machine"
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== General System description == | == General System description == | ||
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Spatial data is used for estimating the amount and species composition of natural regeneration, which depend on the age and species composition of neighbouring stands. | Spatial data is used for estimating the amount and species composition of natural regeneration, which depend on the age and species composition of neighbouring stands. | ||
− | In order to the evaluation of nutrient balances a model for nutrient cycling is used. It is called PROFILE | + | In order to the evaluation of nutrient balances a model for nutrient cycling is used. It is called PROFILE<ref>SVERDRUP, H., A. HAGEN-THORN, J. HOLMQVIST, P. WALLMAN, P. WARFVINGE, C. WALSE et M. ALVETEG (2002): Bio-geochemical processes and mechanisms. In: SVERDRUP, H. et I. STJERNQUIST (Eds.): ''Developing Principals and Models for Sustainable Forestry in Sweden''. Kluwer Academic Publishers, pp. 91–196.</ref>. |
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===Cited references=== | ===Cited references=== | ||
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===External resources=== | ===External resources=== | ||
* ANDERSSON, M., B. DAHLIN et M. MOSSBERG (2005): The Forest Time Machine — a multi-purpose forest management decision-support system. ''Computers and Electronics in Agriculture'', 49, 114–128. | * ANDERSSON, M., B. DAHLIN et M. MOSSBERG (2005): The Forest Time Machine — a multi-purpose forest management decision-support system. ''Computers and Electronics in Agriculture'', 49, 114–128. |
Revision as of 08:51, 1 December 2010
General System description
System name: The Forest Time Machine
Acronym: FTM
Brief overview
The Forest Time Machine is a Swedish DSS whose goal is to study several issues in an integrated way, having a multi-objective approach.
Contents
Scope of the system
The Forest Time Machine was originally constructed for integrated strategy analyses, enabling the simulation of different treatment schedules at a forest level and providing data enough to evaluate this schedules from economic, biodiversity and nutrient balances point of view.
System origin
- The FTM DSS was developed within the SUFOR (Sustainable Forestry in Southern Sweden) research programme.
- The Forest Time Machine started as a simple spreadsheet model (combined with a (GIS)) in the beginning of the 1990s, but has evolved into an object oriented program with modular components and a modern user interface.
- Main use in research, at least three PhD theses have used The Forest Time Machine for different types of analyses.
Support for specific issues
Economical evaluation, based in costs and benefits from from forest operations. Game or recreation utilities, that would generate costs and benefits, are not considered.
Biodiversity evaluation, through indirect variables such as amount of dead wood, or areas of old forest and of broad-leaf forest.
Nutrient balances evaluation, analysing the differences between nutrients provided by weathering and deposition and nutrients removed in harvesting and loss from leaching.
Support for specific thematic areas of a problem type
- Silvicultural
- Certification
- Conservation
- Restoration
- Development choices / land use zoning
- Policy/intervention alternatives
Data and data models
Typical spatial extent of application
It was designed to deal with forest level management problems, by gathering the forest stands' features of the forest studied. It is suitable for analyses of landscapes of up to 25,000 ha.
Forest data input
The minimum data input required to run the FTM is an ordinary (for Swedish conditions) stand database. Location and altitude have to be known for the whole area. For each stand, area, site index, age, volume, and species composition must be entered. Variables that are optional, but give more precise estimates when included are: tree height, stem number, basal area, average diameter at breast height, soil moisture, slope, and ground structure. Some analyses, like those for determining nutrient balances, require additional data (average temperature, annual precipitation and run-off, and deposition of nutrients as well as soil moisture, texture and mineralogy).
In order to enable spatial analyses a digital map of the area with stand division is required.
Type of information input from user (via GUI)
Number of years to the simulation to be run, and interest rate have to be specified. Furthermore, in order to create a treatment schedule, the user has to choose some regeneration, thinning, and harvesting parameters, such as species, point in time for each treatment, weight,... And, after the creation of the stand management regime set, each stand has to be assigned to any regime, or even the assignment of three consecutive regimes to each stand is possible. This can be done either using a built-in query within the FTM or using the GIS externally.
Models
Forest models
The FTM decision-support system is not one model, but a complex of interacting stand based models. This models can analyise the following issues:
- tree growth, including regeneration and mortality
- forest operations
- economy
- biodiversity
- nutrient balances
Spatial data is used for estimating the amount and species composition of natural regeneration, which depend on the age and species composition of neighbouring stands.
In order to the evaluation of nutrient balances a model for nutrient cycling is used. It is called PROFILE[1].
Decision Support
Typical temporal scale of application
The time step is 5 years, i.e. all operations are carried out at the start of each 5-year-period, before growth for the period takes place. All stands development is projected before the initiation of the next 5-year-period, so a step-wise approach, taking into account the results for each period in order to make decisions for the next one, is possible.
Number of periods, management time horizon, is specified by the user via GUI. Anyway, the system was developed to deal with strategic analyses, normally the specified time is up to 100 years.
Types of decisions supported
In the FTM, the user can create the stand management regimes he wants to use in the different strategies that are to be evaluated. Within this regimes, the user can handle five types of treatments: regeneration, pre-commercial thinning, commercial thinning, final felling, and seed-tree or shelter-tree felling.
Decision-making processes and models
The present version of The Forest Time Machine is only a simulation tool, i.e. it does not offer possibilities for optimising management.
Output
Types of outputs
Stand results can be displayed in a spatially explicit fashion.
Spatial analysis capabilities
The Forest Time Machine system does not have a GIS on his own, or an integrated one. Thus, to manage geographic data any GIS that can handle a database format compatible with FTM is required (common packages such as ArcView, ArcInfo and MapInfo have been tried succesfully). Within the GIS, the stand data and results are linked to the polygons representing the stands, enabling spatial analyses and results visualization.
System
System requirements
- Operating Systems: Microsoft Windows OS
- Other software needed: In order to make spatial analyses (it is not mandatory) any GIS software that can handle a database format compatible with FTM is required.
- Development status: many future developments are foreseen.
Usage
It has been used for research.
Computational limitations
Landscapes up to ca. 25,000 ha are not suitable, because of the programme running will take too much long, even though there are no area limitations in the current version. However, with the development of faster computers this limit is expected to increase.
References
Cited references
- ↑ SVERDRUP, H., A. HAGEN-THORN, J. HOLMQVIST, P. WALLMAN, P. WARFVINGE, C. WALSE et M. ALVETEG (2002): Bio-geochemical processes and mechanisms. In: SVERDRUP, H. et I. STJERNQUIST (Eds.): Developing Principals and Models for Sustainable Forestry in Sweden. Kluwer Academic Publishers, pp. 91–196.
External resources
- ANDERSSON, M., B. DAHLIN et M. MOSSBERG (2005): The Forest Time Machine — a multi-purpose forest management decision-support system. Computers and Electronics in Agriculture, 49, 114–128.