GAYA

General System description

System name: GAYA

Brief overview

The first version of GAYA was developed by Prof. Ljusk Ola Eriksson at the Swedish University of Agricultural Sciences. GAYA was "imported" to Norway and transferred to Norwegian conditions by the professors Hans Fredrik Hoen and Tron Eid at the Norwegian University of Life Sciences around 1990. GAYA is a stand simulator and different optimization tools can be connected.

Scope of the system

GAYA is a simulation tool to describe silvicultural regimes. The simulations are based on predefined forest treatments and models describing growth, mortality, prices and costs. Calculations and ”book-keeping” is carried out for up to 20 periods of 5 or 10 years. GAYA is used both for long term forest management planning at forest level based on information for individual forest stands, and for analyses based on sample plot data for the national forest inventory.

System origin

• GAYA was developed for long-term economic analysis of forest production it is used for research and education in Sweden and Norway.

Support for specific issues

It provides support for forest management planning, through harvesting scheduling, economic evaluation, CO₂-flow evaluation, yield prediction, and its optimization.

Support for specific thematic areas of a problem type

• Silvicultural
• Certification
• Conservation
• Development choices / land use zoning
• Policy/intervention alternatives

Related systems

It has a strong resemblance to the Finish MELA model and GAYA is a major part in the SGIS system.

Data and data models

Typical spatial extent of application

GAYA is using stand level growth models.

Forest data input

About 30 state variables are used for defining the forest stand. They are divided between species, biologically, and economically related variables.

• Species is defined by tree number, basal are, height, age and volume.
• Stand is further defined by area, site index, and e.g. earlier treatments in the rotation.
• Economical stand related variables are the terrain transportation distance, several difficulty parameters related to felling operations and a wood quality parameter.

Type of information input from user

The following control variables are examples of variables that can be user-specified when defining potential treatments:

• basal area of the removal as a percentage of total basal area;
• basal area in the remaining stand;
• number of trees in the removal;
• number of trees in the remaining stand;
• diameter ratio between removed trees and remaining stand;
• type of fertilizer;
• intensity of fertilizer.

Models

Forest models

GAYA is the simulator module. It simulates alternative forest management treatment schedules for each calculation unit. Up to three species per stand can be simulated, projecting its development separately. Development is simulated based on regression functions in terms of diameter, basal area, height, spacing and natural mortality. The time dimension of the calculation, the treatment unit, is user controlled, it is a discrete number of time period of uniform length of 5 or 10 years. Cost and revenues for each management unit are also calculated.

Decision Support

Definition of management interventions

Silvicultural treatments, fertilization, regeneration methods, thinnings, harvesting.

Decision-making processes and models

The simulated treatment schedules can be exported to an optimization module to solve the planning problem. The JLP-package and the J-package is commonly used and they both use linear programming.

Output

Types of outputs

Outputs are displayed in tables, showing a number of defined variables for each time period. They are divided in periodic and non-periodic variables.

Periodic variables

Treatment undertaken in the period.

For stand after treatment: total tree number, standing volume by species, basal area, dominant height, age, and NAI (Net Area Increment).

Removal: total tree number, volume for each species., basal area, mean diameter, sawwood and pulpwood proportions, price and cost information (including haulage costs), cash flow, total biomass, and net CO₂ flow.

Non-periodic variables

For the treatment schedule: NPV at time zero, ending inventory value (EIV; NPV at the end of the last period). NPV and EIV of CO₂-flow, total NPV in case CO₂-flow is priced.

Variables for the calculation unit: number of schedules, area, site, vegetation type, altitude, rentability, slope, and a GIS-specified treatment code.

Spatial analysis capabilities

Spatial constraints such as adjacency cannot be taken into account. However, a GIS integration implementation is operative.

System

System requirements

Operating Systems: Windows XP and above.

Usage

Developed for research and educational level. However, GAYA is also used at some Norwegian forest inventory companies as a part of SGIS.

Computational limitations

GAYA is developed using FORTRAN.

User interface

Command line interface and defining potential treatments in a command file are laborious. However, sample command files are available. And graphical user interface developed in MS Excel is also available.

References

Cited references

External resources

• NABUURS G.J. et R. PÄIVINEN (1996): Large Scale Forestry Scenario Models - a compilation and review. European Forest Institute Working Paper No. 10. Joensuu, Finland.