Forests and the forest-based sector play important roles in mitigating climate change through carbon sequestration and storage in living biomass and soil. In Europe, the forest sector is the only sector that positively affects atmospheric carbon balance. After the forest harvest, a large share of carbon is removed together with the wood. This wood carbon might be stored for centuries if in the form of long-lived wood products. In 2011, the United Nations decided that countries should account for and report carbon balance not only in forests but also in harvested wood products (HWP), followed by very general guidelines on methods for carbon accounting in HWP. The Intergovernmental Panel on Climate Change (IPCC) proposed three methodological levels called tiers for estimating carbon stock and its changes in HWP. The first reporting period revealed that countries applied different carbon accounting methods (tiers), therefore comparing the carbon budgets of HWP and the effect of climate change mitigation among different countries is difficult. In order to test the differences between carbon accounting methods proposed by the IPCC guidelines, we applied two carbon accounting methods and used different data sources in the case of Lithuania. The methods applied were the IPCC Tier 2 method (data on HWP from statistics or the literature, default half-life values, and default HWP categories) and material flow analysis, which is compatible with the IPCC Tier 3 method (material flow data on HWP, country-specific half-life values, and country-specific HWP categories). Depending on the availability of historical data from different sources for the purpose of this study, three study periods were defined: 1992–2015 Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) data, 1960–1991 data from the literature, and 1940–1991 data from national statistics. The study findings show that carbon stock in HWP significantly differed when different data sources and methods were applied. The highest carbon stock in HWP (19.5 Mt) at the end of the study period was observed when FAOSTAT data from 1992–2015 were used and the Tier 3 method was applied. The lowest carbon stock in HWP (11.2 Mt) at the end of the study period was observed when data from national statistics from 1940–1991 were used and the Tier 2 method was applied. The carbon inflow into the pool of HWP in all cases was estimated to be 40% higher when material flow analysis was applied compared to the IPCC default (Tier 2) method. These findings suggest that in general it is more reasonable to apply the Tier 3 method for carbon accounting of HWP in Lithuania.

Background and Objectives: The aim of this study was to determine the effects of different stand densities on wood density (WD), global modulus of elasticity (MOE), and bending strength (MOR) in 35-year-old Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst) stands, representing the hemiboreal forest zone. Materials and Methods: Scots pine and Norway spruce sites, representing different stand densities of 3000–3100; 2000–2100 and 1000–1100 trees per hectare, were chosen. Visually healthy model pine and spruce trees were selected, and diameter at breast height (DBH) was measured for model trees; the competition index was calculated; the MOE and MOR were evaluated by the Standards EN 408:2006 and EN 384:2016, at 12% moisture content; WD and the knot diameter were measured; and the strength class of wood was determined by the Standard EN 338:2009. To predict wood quality characteristics based on stand and tree characteristics, linear regression models were developed. Results and Conclusions: Higher stand density led to a significant change in the main wood properties of both conifer species. The highest mean WD, MOE, and MOR were obtained at the sites with the highest stand density. The MOE and MOR were highly correlated, but relatively weak correlations were found between MOE and MOR with tree DBH and WD. Despite the lower quality of Scots pine wood, the Norway spruce wood from more dense sites corresponded to the strength class of C16, according the strength grading of softwoods. The linear regression models did not perform well in describing the relationship of wood properties with stand and tree characteristics. The models for MOR accounted for the highest variation of 62–65% for both Scots pine and Norway spruce. These relationships can be expected to change with increased stand age or with the inclusion of specific crown parameters.

Background and Objectives: The aim of this study was to determine the effects of different stand densities and thinning regimes on stem quality parameters, mainly branch characteristics, of Scots pine (Pinus sylvestris L.) trees. The study provides some input to the discussion about Scots pine stem quality responses to different forest management practices in relatively young stands. Materials and Methods: Total tree height, height to the lowest live and dead branch, diameter at breast height (DBH), and diameter of all branches from the whorls located up to 6 m from the ground were measured. The linear regression models to predict branch diameter, as the main parameter for the stem quality assessment, were developed based on stand density and stem parameters. Results and Conclusions: DBH, branch diameter and number of branches up to 6-m stem height were significantly higher in the stands with the lowest density. These stem parameters showed a relatively clear downward trend from the lowest to the highest stand densities. The main identified variables which significantly affected stem quality, were branch diameter and diameter of the thickest branch in the bottom part of the stem, at least up to 3-m stem height. For practical use, the best fitted model was estimated when stand density, DBH, and branch diameter up to 3-m height were included in a single equation. The developed model for branch diameter could be used as a forest management tool for managing stem-wood quality.

Treatment of wood with various physical and chemical factors can change the number of wood parameters, which can also lead to changes in resistance to wood-destroying fungi. This study evaluates the effects of hydrothermal treatments (additives Fe2O3 or FeCl3 with and without commercial tannins, also without additives and fresh wood) on decay and mould fungi resistance of modified wood of Scots pine (Pinus sylvestris), Norway spruce (Picea abies), Douglas fir (Pseudotsuga menziesii), walnut (Juglans regia), and Norway maple (Acer platanoides). For wood samples, the resistance against wood decay fungi Trametes versicolor (white rot) and Coniophora puteana (brown rot) and the resistance against mould fungi Aspergillus niger and Penicillium sp. were assessed. The study findings showed that wood modified with iron compounds could cause a higher resistance to wood-destroying fungi. The weight losses of the modified and control wood, caused by T. versicolor and C. puteana, differed for coniferous and deciduous: the average weight loss of treated pine, spruce, and fir wood caused by C. puteana was higher than that caused by T. versicolor, while these differences on maple and walnut wood were not significant. The wood hydrothermal treatment with Fe2Cl3 with and without tannins significantly reduced the weight loss caused by T. versicolor and C. puteana, and the treatment with Fe2O3 slightly improved the decay resistance. For the wood, hydrothermally modified with FeCl3 and FeCl3 + tannins, the mould area for both tested Aspergillus niger and Penicillium sp. was smallest for the wood of all tested tree species compared to other treatments. A different response was obtained for coniferous and deciduous tree species wood. The spruce wood, followed by fir wood, treated with FeCl3 with and without tannins, was the most resistant against the mould fungi. Relatively low resistance against the mould fungi was fixed for the maple wood treated by various iron compounds, except the treatment with Fe2O3 + tannins, which gave a very positive response against the Penicillium sp.

Strip roads serve to enable silviculture operations, maintain biodiversity, and decrease damages to the soil and environment. At the same time, strip roads decrease the productive area. The aim of this study is to evaluate the influence of strip roads on the productivity of spruce plantations growing in different density regimes. Five trials, each of 0.234 ha area, with different density regimes and two replications in an experimental spruce plantation were used for this study. The permanent plots were established in the plantation of 15 years of age and were remeasured every 4–5 years over 24 years. Differences in tree growth between outer rows bordering strip roads and inner rows, 1.75 and 3.5 m from the strip road, were estimated using t statistics. The gross annual increment of trees in outer rows at age 39 years exceeded the increment of trees in inner rows by up to 60%–78%. Increase of productivity occurred primarily due to the more intensive diameter growth and higher density of trees in the outer rows. In general, the influence of strip roads on the total productivity of plantation depends on the ratio of the growth intensity of trees between outer and inner rows as well as ratio of the width of treed strips to the width of the strip road.

This study examines the performance of 11 tree taper models to predict the diameter of bark at any given height and the total stem volume of eight dominant tree species in the boreal forests of Lithuania. Here, we develop eight new models using stochastic differential equations (SDEs). The symmetrical Vasicek model and asymmetrical Gompertz model are used to describe tree taper evolution, as well as geometric-type diffusion processes. These models are compared with those traditionally used for four tree taper models by using performance statistics and residual analysis. The observed dataset consists of longitudinal measurements of 3703 trees, representing the eight dominant tree species in Lithuania (pine, spruce, oak, ash, birch, black alder, white alder, and aspen). Overall, the best goodness of fit statistics of diameter predictions produced the SDE taper models. All results have been implemented in the Maple computer algebra system using the "Statistics" and "VectorCalculus" packages.

The development of bioenergy markets is beneficial from a climate perspective and helps ensure sustainable forest management both locally and globally. This study aimed to provide an overview of the current state of Lithuanian forest biomass resources with a particular focus on the legal, economic and ecological aspects of forest biomass use for energy and to identify the lessons that should be learned from the history of biomass introduction in the country's energy sector. These experiences and lessons are valuable both nationally and internationally, where good practices and challenges for the introduction and development of forest biomass for energy production are revealed. We examined the question of whether regulatory drivers in the energy sector can increase forest biomass use for energy production and contribute to sustainable development of Lithuania. To answer this question, we described the legal and market instruments regulating forest biomass use for energy production, the forestry sector and renewable energy policy in Lithuania, the current and potential amount of forest biomass available for energy production and ecological considerations relating to forest biomass use for energy. In Lithuania, forest biomass resources are strategically important for the renewable energy sector. The National Energy Strategy of Lithuania aims to increase the share of renewable energy sources, including forest biomass, within the total energy consumption, with targets of 30% in 2020, 45% in 2030 and 80% in 2050. Lithuania successfully achieved the target of EU legislation on renewables in 2015 ahead of the obligation to achieve it in 2020. Renewable energy is mainly used in heating, as well as in the electricity and transport sectors. This has resulted in a significant price reduction for end users due to the increased use of biomass, mainly local forest biomass, for heat energy production and in the emergence of a biofuel exchange, which acts as a system of biomass auctions that to some extent prevent unjustified price increases. Legislation developed for the energy biomass market in Lithuania allows efficient restructuring of the energy sector, especially for heat production. The Lithuanian energy sector has already successfully replaced imported and relatively expensive natural gas with locally available cheaper renewable energy sources (RES). Compliance with formal environmental regulations is required to protect the soil, ground vegetation, understory and biodiversity during commercial tree harvesting. Lithuania has basic guidelines for the use of wood ash as a compensatory fertiliser, with strict requirements for the chemical quality of wood ash.

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.