This project leverages the robust capabilities of the GAYA forest simulator, originally developed in Sweden, to create a powerful, AI-enhanced forest planning tool tailored for Lithuanian forests, however, open for adaptation under any other geographic conditions. The integration of Lithuanian forest data and new functionalities will support enhanced decision-making in forest management for both public and private sectors, as well as for the scientific community.

 

Background on GAYA Simulator. GAYA is a versatile and sophisticated forest simulator initially developed by Professor Ljusk Ola Eriksson at the Swedish University of Agricultural Sciences. Designed to support forest management by modeling forest dynamics in response to various silvicultural treatments, GAYA provides a detailed, area-based approach to forecasting forest growth, yield, and other critical factors. The simulator operates at both the stand level (individual forest segments) and the sample plot level, making it ideal for both large-scale and localized analyses. GAYA is capable of simulating how forests evolve over time based on specific management practices. These simulations take into account factors like growth rates, tree mortality, treatment costs, and timber prices, which are essential for making well-informed forest management and optimization decisions.

Project Vision: Expanding GAYA with AI and Lithuanian Data. This project builds on GAYA’s existing capabilities by adapting it to Lithuanian forest conditions and a wide range of input formats, and incorporating AI-driven functionalities that will allow users to conduct even more refined planning and analysis. The integration of AI algorithms will enhance GAYA‘s predictive and optimization features, making it a more powerful tool for forest management to deliver better balanced baskets of multiple ecosystem services. The decision support system is expected to become a central feature of forest sector modeling infrastructure, which will be validated in Lithuania, however, suitable for any international adaptation.

 

Key Project Components
  1. Localization of GAYA with Lithuanian Forest Data. By adapting GAYA’s models to integrate Lithuanian forest data and various input formats, including growth patterns, ecological variations, and other specific factors, the simulator will empower facilitation of precision forestry and produce more accurate predictions tailored to Lithuania’s unique forestry environment.
  2. AI-powered Enhancements for Advanced Planning. AI functionalities will be added to GAYA to support more dynamic and adaptive forest planning. Machine learning algorithms will analyze historical and real-time data to provide predictive insights and offer customized treatment recommendations.
  3. Development of a User Interface. A modern, intuitive user interface will be developed for the new tool, making it accessible and easy to use for forestry professionals, government officials, and scientists. The UI will provide customizable dashboards, scenario planning options, and visualizations of projected forest changes over time.
  4. Addressing the diversity of forest ecosystem services. Gaya will be modernized to incorporate models and methods focused on climate change, biodiversity, and a range of ecosystem services. Key development goals include integrating tools to quantify changes in carbon stocks and to evaluate different aspects of biodiversity across various forest management regimes.

 

The expanded GAYA simulator will provide numerous benefits across sectors:
  • Private Sector: Forestry companies can use the tool to model specific management strategies local, regional and national levels, optimize timber production and delivery of other ecosystem services, contribute to climate change mitigation, optimize timber production, and reduce costs based on AI recommendations.
  • Public Sector: Government agencies will be able to analyze trends and patterns at a national level, facilitating more effective policy-making and resource allocation.
  • Scientific Research: Researchers will gain access to a sophisticated, AI-driven model for conducting in-depth studies on forest dynamics, climate adaptation, and the effects of specific silvicultural practices.
The project’s integration of AI with GAYA will set a new benchmark for forest planning tools, enhancing accuracy and flexibility in forest management. By localizing this tool with Lithuanian data and incorporating predictive AI capabilities, the project will support sustainable forestry practices, economic resilience, and ongoing scientific research.
The advanced GAYA simulator will empower users to make data-driven decisions, preserve natural resources, and contribute to the long-term health and productivity of Lithuania’s forests. This collaboration represents a model for future projects, combining international expertise with cutting-edge technology to address complex, region-specific challenges in sustainable resource management.