Forest development forms the foundation for the advancement of sustainable forest management that integrates the knowledge of natural and anthropogenic processes with ecological and biological insights. This study aims to emphasize the role of assisted natural regeneration and balanced forest development phases in fostering closer-to-nature management approaches, contributing to resilient forest ecosystems capable of self-regulation and biodiversity support in the face of anthropogenic and climatic challenges. This study focuses on forest development in Lithuania based on five National Forest Inventories (NFIs) from 2002 to 2022. We examine the tree volume structure of the growing stock by stand type and forest type series from the point of view of stand age and forest development phases. This is performed by applying the standardized methodologies of the Lithuanian National Forest Inventory. Our analysis focuses on broader patterns derived from the selected NFI data rather than stand-level details. Our findings demonstrate that long-term observation of dynamic National Forest Inventories can aid in the development of closer-to-nature forest management methods for different forest type series. In order to implement the European Union’s strategy and policy for closer-to-nature forest management, we call for the use of “assisted succession” methods in commercial forests, promoting the formation of mixed-species forest stands with multi-cohort age profiles, including old-growth all-aged forest patches of >121 years.

Background and Objectives: Significant progress in developing European national forest inventory (NFI) systems could ensure accurate evaluations of gross annual increment (GAI) and its components by employing direct measurements. However, the use of NFI data is insufficient for increasing the efficiency of forest management and the use of wood, as well as for meeting sustainable forestry needs. Specification of forest characteristics, such as GAI and its components, identification of the main factors that impact forest growth, accumulation of wood, and natural losses are among the key elements promoting the productivity of forest stands and possibilities of rational use of wood in large forest areas. The aims of this research were (a) to validate the quality of forest statistics provided by a standwise forest inventory (SFI) and (b) to reveal the potential benefits of rational wood use at the country level through the analysis of forest management results, which are based on GAI, including its components derived from the NFI. Materials and Methods: SFI and NFI data from 1998–2017 were collected from 5600 permanent sample plots and used to evaluate the main forest characteristics. Potential wood use was estimated based on the assumption that 50–70% of the total GAI is accumulated for final forest use. Results: Mean growing stock volume (GSV) is underestimated by 7–14% on average in the course of SFI. Therefore, continuous monitoring of the yield changes in forest stands, detection of factors negatively affecting yield and its accumulation, and regulation of these processes by silviculture measures could increase potential forest use in Lithuania. Conclusions: Implementation of sample-based NFI resulted in an improvement of forest characteristics and led to an increase in GSV and GAI. Continuously gathered data on GAI and its components are a prerequisite for efficient forest management and control of the use of wood.

Carbon stocks in hemiboreal forests are frequently assessed using dominant-species or growing stock metrics, which may obscure ontogenetic and demographic processes governing biomass turnover. This study applied a process-based framework integrating succession theory, forest typology, and ontogenetic strategies to Lithuanian National Forest Inventory data reorganized by forest type-series. Three research expectations were evaluated: whether typology-based classification reveals patterns not visible under dominant-species reporting (H0), whether stand composition converges toward phase-typical configurations (H1), and whether fertile four-phase forests exhibit higher productivity and earlier CO₂ flux reversals than three-phase forests (H2). H0 was rejected: forest type-series reorganization revealed contrasts in species assembly, stand structure, and carbon dynamics not detectable under dominant-species classification. H1 was supported: three-phase forests converged toward colonizer-dominated assemblies, while four-phase forests sustained multi-species, multi-cohort canopies with persistent broadleaved contributions. H2 was supported: four-phase forests exhibited higher gross volume increment and transitioned to negative CO₂ accumulation 40 years earlier (61–80 years) than three-phase forests (101–120 years). Across both pathways, growing stock volume increased while CO₂ accumulation turned negative in older stands, demonstrating divergence between cumulative biomass stock and net annual carbon flux. Forest Inventory data reorganized by forest type-series functioned as a process-based diagnostic tool supporting climate- and biodiversity-oriented management.