A review and conceptual framework for a new era of forest management planning: integrating hybrid digital twin systems toward sustainable forest ecosystems

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.