Stefan Petrea

Airborne LiDAR provides a powerful framework for objectively describing forest structure across multiple spatial scales. From LiDAR points to a unit of area, to descriptors of individual trees, to cohorts of trees, to the stand, or at a landscape level, its analytical value can create a hierarchical understanding of drivers affecting the structural variability of trees and their spatial organisation on multiple levels. In this study, we analysed the structure of relatively pure Norway spruce (Picea abies (L.) Karst.) stands in the Ciucaș Mountains (Brașov County, Romania) using airborne LiDAR data. The point cloud was processed in R using an open-source workflow comprising ground classification, terrain modelling, height normalisation, canopy height modelling, treetop detection, and crown delineation. Structural metrics were derived hierarchically, from individual trees to summary statistics for tree cohorts within 500 m² grid cells, and subsequently to stand-level statistics across grid cells within spruce stands. The geospatial dataset consisted of 58,708 grid cells grouped in 147 stands; for inferential analyses, a filtered dataset of 42,015 cells was retained, covering a total area of 2075.6 hectares. We applied a four-part analytical framework: (i) hierarchical mixed-effects models at the cell level, (ii) quantification of within-stand structural heterogeneity, (iii) stand-level structural typology based on principal component analysis and k-means clustering, and (iv) integration of disturbance history using combined Potapov (pre-2001) and Hansen (2001–2022) forest loss layers. The analysis revealed several patterns consistent with ecological expectations: mean canopy height increased with stand age, slope, and topographic position, whereas it decreased significantly with elevation. Canopy cover increased with elevation, slope, and topographic position, whereas the number of LiDAR-detected trees per cell increased with elevation but decreased with age and slope. The null model intraclass correlation coefficients ranged from 0.252 to 0.408, indicating appreciable between-stand variation alongside a larger within-stand residual component. Structural heterogeneity increased strongly with slope and, to a lesser extent, with northness. The stand typology identified five structural types: low-stature dense uniform, mid-height heterogeneous, tall closed uniform, tall open simplified, and very tall closed complex. Mapped tree cover loss occupied a small fraction of the retained forest sample and was associated with lower mean canopy height (approximately 1 m), lower canopy cover (approximately 4 percentage points), smaller mean crown area (approximately 2 m²), and a slightly lower number of LiDAR-detected trees per cell. These associations do not identify the causes of disturbance or its overall historical importance. In the Ciucaș Mountains, LiDAR-derived metrics provide a spatially explicit baseline for characterising spruce stand structure and its associations with stand age, topography, and mapped disturbance history.

The Peleș Park Forest (PPF), a semi-natural peri-urban forest near Sinaia, Romania, is essential in providing ecological benefits and improving human well-being through recreation. As the urban population grows and stress-related health problems increase, green spaces are increasingly recognised for their restorative functions, including air purification, temperature regulation and mental health improvement. This study aims to develop a sustainable management framework that reconciles forest conservation with recreational value use by assessing forest structure, evaluating tourism-related stressors, and proposing adaptive management strategies. We assessed forest structure through tree diameter, height, volume, and crown health measurements, applying principal component analysis (PCA) to identify the main structural drivers. The results revealed a strong correlation between tree diameter and height, modulated by species composition and site conditions. They showed pronounced crown defoliation in the upper canopy layers, particularly among trees of lower wood quality. The findings suggest that uneven-aged stand structures, which support biodiversity and ecological resilience, are subject to tourism-related pressures such as soil compaction and vegetation damage.

Temperate forests are crucial in global carbon dynamics, acting as significant carbon pools through biomass accumulation and soil organic matter storage. This study investigates the dynamics of the forest floor, soil organic matter, and carbon stock estimation on species type, age and forest management. The research focuses on Romania's temperate forests, on broadleaf, coniferous and mixed stands in the Southern Carpathians. The measurements were conducted across a systematic grid network of 450 plots, each combining two circular plots of 500 m² in size. These plots span an altitudinal gradient from 500 to 1650 meters above sea level (ASL), providing a robust dataset for analyzing carbon dynamics. Our research evaluates the contribution of forest floor components - litter, coarse woody debris and fine roots - to total carbon stocks, alongside soil organic matter dynamics at 30 cm depth. The study also integrates tree biomass data for major species such as beech (Fagus sylvatica L.), silver fir (Abies alba Mill. ), and Norway spruce (Picea abies L.), providing a comprehensive assessment of carbon sequestration potential.Our preliminary results reveal significant differences in both forest floor weight and bulk density between management types. Plots in conservation areas had a significantly higher mean forest floor weight (21.1 tonnes/ha) than production plots (17.9 tonnes/ha, p < 0.01), while their mean bulk density was significantly lower (0.84 Mg/m³ vs. 0.96 Mg/m³, p < 0.01). These findings, combined with higher forest floor weight in conservation plots, underline the critical role of management strategies on soil carbon storage. The results also highlight the influence of forest type, stand age, and management practices on carbon storage, emphasizing their importance in climate change mitigation and sustainable forest management. This study provides valuable insights for optimizing forest management strategies to enhance carbon sequestration and improve understanding of carbon fluxes in temperate ecosystems. The findings are particularly relevant for aligning forest policies with national and international climate goals.

Forests mitigate greenhouse gas (GHG) emissions by capturing CO₂ and storing it as carbon in various forms, including living biomass, dead wood, soil, and forest litter. Importantly, when trees are harvested, a portion of the above-ground biomass is converted into harvested wood products (HWPs), which can retain carbon for decades. With approximately 7 million hectares of forest (30% of its land area), Romania significantly contributes to the country’s carbon budget through the HWP pool. Using country-specific data from 1961 to 2022 and an IPCC method, we tracked HWP carbon storage and projected future scenarios to evaluate the category’s significance in achieving the 2050 climate target. During this period, the carbon stored in Romanian HWPs more than doubled from 28.20 TgC to 60.76 TgC, with sawnwood products as major contributors. Fluctuations were influenced by domestic policies, market dynamics, and industry changes, notably after the 1990s. Annual carbon inflow dipped to 0.65 TgC in 1994 and peaked at 2.54 TgC in 2013. By analyzing the scenarios, we demonstrated that a moderate growth trajectory in carbon inflow, combined with a focus on producing long-lived wood products, could double carbon stock changes by 2050 to 4.4 TgC—roughly 4% of the country’s current total emissions excluding the LULUCF sector. Additionally, based on sustainable forest management practices in Romania, this approach would significantly enhance the carbon pool and its importance in achieving the country’s climate policies.

This study examines the impact of silvicultural and land-use management practices on carbon sequestration in peri-urban forest ecosystems, with a particular focus on human-induced carbon dynamics. The study area’s complex profile spans from a compact native forest to varying degrees of fragmentation. This included areas undergoing secondary succession forest without silvicultural interventions (No-SI) alongside sites subjected to high-intensity (High-SI) and low-intensity silvicultural interventions (Low-SI). The research assessed carbon stocks and sequestration in different carbon pools (living biomass, dead organic matter and soil) using field data, allometric equations and laboratory analysis. Findings reveal a significant correlation between the intensity of anthropogenic interventions and variations in carbon stocks. The CASMOFOR model facilitated the reconstruction of carbon stock and carbon-stock change dynamics over four decades (1980–2022), showing disparities in carbon storage capabilities linked to the structural characteristics of the sites. The Low-SI site had the highest carbon stock in all carbon pools (378 tonnes C ha⁻¹), which is more than double compared to High-SI (161 tonnes C ha⁻¹) or No-SI sites (134 tonnes C ha⁻¹). However, the secondary succession forest (No-SI) demonstrated the highest annual carbon stock change (4.4 tonnes C ha⁻¹ year⁻¹), two times higher than the Low-SI mature stand (2.2 tonnes C ha⁻¹ year⁻¹), emphasising the resilience of forest ecosystems to recover and sustain carbon sequestration capacities after harvesting if forest land use remains unchanged. The study underscores the significant importance of anthropogenic interventions on carbon dynamics, especially for living tree biomass, which has consequences in enhancing carbon sequestration and contributing to emission reduction targets.

The European beech (Fagus sylvatica L.) is one of the most common tree species in Romania, with importance both economically and environmentally. Accurate methods of biomass assessment at the tree compartment level (i.e., stump, stem, branches, and leaves) are necessary for carbon stock estimation. Wood density (WD) is an important factor in determining biomass and, ultimately, the tree’s carbon content. The average tree density was found to be 578.6 kg/m³. For this study, WD was evaluated by the weighting method related to tree volume. Also, to investigate a practical approach to determining the weighted wood density (WWD_st), models were run using density at the base of the tree (WD_Base), density at breast height level using discs (WD_DBH), the wood core density (WD_ic), and the diameter at breast height (DBH) as predictors. The biomass assessment was conducted using different model evaluations for WWD_st as well as allometric equations using the destructive method. From the results, it was noted that using the WWD_st, the total biomass was underestimated by −0.7% compared to the biomass measured in the field. For allometric equations that included DBH and tree height as independent variables, the explained variability was around 99.3% for total aboveground biomass (AGB_total), while it was 97.9% for allometric function using just the DBH. Overall, the distribution of biomass across different compartments was as follows: 73.5% in stems, 23.8% in branches, 1.9% in stumps, and 1.3% in leaves. The study findings offer valuable insights into WD, biomass distribution among different components, and biomass allometric quantification in natural beech forest environments in mountainous areas.

With the intensification of the effects of climate change, the urgent need to address their drivers, especially greenhouse gas emissions, has become essential. In this context, forests offer a robust solution, with their potential to store and mitigate carbon emissions. However, striking a balance is critical given the significant economic contribution of the forestry and wood-based industries, which account for about 5% of Romania’s GDP and employ 6% (around 300 thousand) of its active workforce. This study, conducted in the Piatra Craiului National Park located in Romania’s Southern Carpathians, we utilize the EFISCEN application to generate three distinct 50-year forest evolution scenarios based on harvest intensity, namely Business As Usual (BAU), Maximum Intensity (MAX), and No Harvest (MIN), on two historical different managed forests, i.e., conservation and production. The study aims to guide forest owners in decision making with scenario modeling tools, with the objectives of assessing the forest carbon sequestration potential and evaluating the economic feasibility. In the most probable scenario, the BAU scenario, the growing stock increases from 2.6 million m³ to 3.8 million m³ over 50 years, with a more than 40% increase. Comparing the carbon stock change for all tree harvest scenario types indicates that the MIN scenario has the highest carbon sink capacity in the next 50 years; the BAU scenario is a well-balanced option between carbon sink and wood provision and has an optimal EUR 3.7 million in annual revenue. The MAX scenario can boost the growth and increase the annual revenue from wood by 35% but is effective only for a short time and thus has the smallest calculated revenue in time. Achieving a win–win relationship between carbon sequestration and wood supply is imperative, as well as good planning and scenarios to contribute to climate mitigation and also as provisions for local communities and to sustain the local economy.