Speaker
Description
Resilient forest value chains depend on the adaptive capacity of forest managers at all scales. Small-scale forest owners, who manage a substantial share of Europe’s forest area, play a critical role in ensuring sustainable timber supply, safeguarding biodiversity, and maintaining multifunctional landscapes. However, their decision-making environment is becoming increasingly complex and uncertain. Climate change intensifies disturbance risks such as drought, storms, and pest outbreaks; timber markets are volatile and globally interconnected; and regulatory as well as societal expectations regarding ecosystem services, carbon sequestration, and habitat protection continue to grow. At the same time, many small-scale forest owners operate with limited access to specialized advisory services or advanced analytical tools. While innovation in harvesting technology, digital monitoring, and smart operations has advanced considerably, decision support solutions tailored specifically to the realities, constraints, and objectives of small-scale forestry remain underdeveloped.
A prototype AI-based decision support system designed to strengthen adaptive forest management at the holding level will be presented. The system builds on a systematic review of recent advances in generative and agentic artificial intelligence and translates these developments into a practical forestry context. Functioning as an interactive and context-aware assistant, the AI supports decision-making in complex and dynamic environments. By integrating stand-level data, owner-defined objectives, risk considerations, and regulatory constraints, the system generates context-sensitive management options aligned with multifunctional forest management and biodiversity goals. It structures trade-offs between economic performance, ecological resilience, and long-term sustainability, thereby enhancing transparency in strategic planning.
The study is showcasing how agentic AI can translate complex data, expert knowledge, and scenario assumptions into actionable guidance for decentralized forest managers. By empowering small-scale forest owners with adaptive, user-oriented digital tools, this approach contributes to strengthening resilience and sustainability across the whole forest value chain.
| Keywords | "Agentic-AI; Innovation; Decisionmaking; Digitalization" |
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