20.500.12556/RUL-181960 A review and conceptual framework for a new era of forest management planning Forests deliver a wide array of ecosystem services. They can be sustainably provided across spatial and temporal scales through ecosystem-based multi-objective forest management planning. The growing complexity of ecological dynamics—driven by climate change, natural disturbances, and evolving societal demands—necessitates a shift from static to adaptive, data-driven planning. Such an approach can simultaneously ensure the provision of desired ecosystem services while safeguarding the ecological integrity of forest ecosystems. This paper examines the theoretical foundations and proposes a conceptual framework for forest management planning, integrating emerging technologies such as Digital Twin (DT) systems and recent scientific advancements in ecosystem based forest management planning. At the core of this approach lies the dynamic coupling of real-time, high-resolution data with clearly defined management objectives and conservation targets rooted in ecological reference conditions. The proposed DT-integrated Forest Management Planning (DT-eFMP) framework facilitates continuous monitoring, scenario testing, and participatory decision-making while maintaining alignment with policy frameworks and sustainability goals. Emphasis is placed on the intelligent design of silvicultural regimes that emulate natural disturbance patterns, enhance forest resilience, and optimize the provision of ecosystem services. By incorporating advanced simulation, forecasting, and learning mechanisms, the framework provides a restructured decision support system capable of managing uncertainty and improving long-term planning outcomes. This work contributes an operationally relevant framework for forest managers and policymakers, offering both a scientific foundation and a practical guide for advancing adaptive and resilient forest ecosystem management in the digital era. adaptive forest management ecosystem-based planning digital twins learning process modeling ecosystem services prilagodljivo gospodarjenje z gozdovi ekosistemsko načrtovanje digitalni dvojčki proces učenja modeliranje ekosistemske storitve true false true Angleški jezik Slovenski jezik Članek v reviji 2026-04-21 07:41:44 2026-04-21 07:41:46 2026-04-22 04:28:31 0000-00-00 00:00:00 2026 0 0 20 str. art. 101851 Vol. 79 Jun. 2026 0000-00-00 PostprintKoncna Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 2028-04-19 630*61 2212-0416 10.1016/j.ecoser.2026.101851 275735811 RAZ_Baskent_Emin_Zeki_2026.pdf RAZ_Baskent_Emin_Zeki_2026.pdf 1 BDC35DADD0F2E120B0E1F0DD533C15C3 78d3499a853a37ba27827505dd4f5363285161bf29fed389e4f22c19b93c51fb c41cc5c3-3d44-11f1-b0ab-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=232789 https://www.sciencedirect.com/science/article/pii/S2212041626000392 1 8b63c59c-3d44-11f1-b0ab-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=232788 Biotehniška fakulteta 0 0 0