Search Results (47)

Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate the effect of forest management regimes on bird communities in the Italian Peninsula during 2022 through audio recordings. We studied the structure, composition, and specialization of the breeding bird community in four managed beech stands (three even-aged beech stands aged 20, 60, and 100 years old, managed by a uniform shelterwood system; one uneven-aged stand, managed by a single-tree selection system) and one uneven-aged, unmanaged beech stand in the northern Apennines (Tuscany region, Italy). Between April and June 2022, data were collected through four 1-hour audio recording sessions per site, analyzing 5 min sequences. The unmanaged stand hosted a richer (a higher number of species, p < 0.001) and more specialized (a higher number of cavity-nesting species, p < 0.001; higher Woodland Bird Community Index (WBCI) values, p < 0.001; and eight characteristic species, including at least four highly specialized ones) bird community, compared to all the managed forests; moreover, the latter were homogeneous (similar to each other). Our study suggests that the unmanaged beech forests should be a priority option for conservation, while in terms of the managed beech forests, greater attention should be paid to defining the thresholds for snags, deadwood, and large trees to be retained to enhance their biodiversity value. Studies in additional sites, conducted over more years and including multi-taxon communities, are recommended for a deeper understanding and generalizable results. Full article

Tree height and vertical forest structure are important attributes in forestry, but their traditional measurement or assessment in the field is expensive, time-consuming, and often inaccurate. One of the main advantages of using remote sensing data to estimate vertical forest structure is the ability to obtain accurate data for larger areas in a more time- and cost-efficient manner. Temporal changes are also important for estimating and analysing tree heights, and in many countries, national airborne laser scanning (ALS) surveys have been conducted either only once or at specific, longer intervals, whereas aerial surveys are more often arranged in cycles with shorter intervals. In this study, we reviewed all freely available national airborne remote sensing data describing three-dimensional forest structures in Slovenia and compared them with traditional field measurements in an area dominated by uneven-aged forests. The comparison of ALS and digital aerial photogrammetry (DAP) data revealed that freely available national ALS data provide better estimates of dominant forest heights, vertical structural diversity, and their changes compared to cyclic DAP data, but they are still useful due to their temporally dense data. Up-to-date data are very important for forest management and the study of forest resilience and resistance to disturbance. Based on field measurements (2013 and 2023) and all remote sensing data, dominant and maximum heights are statistically significantly higher in uneven-aged forests than in mature, even-aged forests. Canopy height diversity (CHD) information, derived from lidar ALS and DAP data, has also proven to be suitable for distinguishing between even-aged and uneven-aged forests. The CHD_ALS 2023 was 1.64, and the CHD_CAS 2022 was 1.38 in uneven-aged stands, which were statistically significantly higher than in even-aged forest stands. Full article

The role of forest community configurations in multiple ecosystem functions remains poorly understood due to the absence of quantifiable metrics for evaluating these configurations. This limitation hinders our ability to use forests to enhance urban well-being effectively. This study integrates both observation and experimentation to elucidate the effects of community configurations on the multifunctionality of forests. We examine seven ecosystem functions in Changchun’s urban forests: carbon sequestration, rainwater interception, temperature reduction, humidity increase, particulate matter reduction, noise reduction, and water conservation. Assortment indices, derived from traditional diversity metrics and relative importance values, reveal a negative correlation with multifunctionality. This suggests that improving forest multifunctionality requires a strategically planned species composition rather than simply increasing diversity. Furthermore, the creation of comprehensive configuration indices for evaluating intraspecific configurations has confirmed their beneficial impact on multifunctionality. Our results highlight the significance of intraspecific structural configurations and advocate for using mixed-species plantings in urban forestry practices. We propose practical management strategies to enhance urban forest multifunctionality, including selecting tree species for their functional benefits, implementing uneven-aged plantings, and integrating both shade-tolerant and sun-loving species. Together, our findings underscore the essential role of community configuration in sustaining multifunctionality and strongly support the management of urban forests. Full article

Canopy gaps and their associated processes play an important role in shaping forest structure and dynamics. Understanding the information about canopy gaps allows forest managers to assess the potential for regeneration and plan interventions to enhance regeneration success. Traditional field surveys for canopy gaps are time consuming and often inaccurate. In this study, canopy gaps were detected using unmanned aerial vehicle (UAV) imagery of two sub-compartments of an uneven-aged mixed forest in northern Japan. We compared the performance of U-Net and ResU-Net (U-Net combined with ResNet101) deep learning models using RGB, canopy height model (CHM), and fused RGB-CHM data from UAV imagery. Our results showed that the ResU-Net model, particularly when pre-trained on ImageNet (ResU-Net_2), achieved the highest F1-scores—0.77 in Sub-compartment 42B and 0.79 in Sub-compartment 16AB—outperforming the U-Net model (0.52 and 0.63) and the non-pre-trained ResU-Net model (ResU-Net_1) (0.70 and 0.72). ResU-Net_2 also achieved superior overall accuracy values of 0.96 and 0.97, outperforming previous methods that used UAV datasets with varying methodologies for canopy gap detection. These findings underscore the effectiveness of the ResU-Net_2 model in detecting canopy gaps in uneven-aged mixed forests. Furthermore, when these trained models were applied as transfer models to detect gaps specifically caused by selection harvesting using pre- and post-UAV imagery, they showed considerable potential, achieving moderate F1-scores of 0.54 and 0.56, even with a limited training dataset. Overall, our study demonstrates that combining UAV imagery with deep learning techniques, particularly pre-trained models, significantly improves canopy gap detection accuracy and provides valuable insights for forest management and future research. Full article

Climate change increases the vulnerability of relict forests. To address this problem, regional Forest Services require silvicultural and conservation actions to designate specific forest management alternatives. In this context, the main objective of this study was to develop a methodology to map complex Abies pinsapo forest typologies using multispectral and low-density airborne LiDAR data and machine learning. Stand density, species composition and cover were used to identify seven forest typologies. Random forest resulted as the more accurate model (OA = 0.62; Kappa = 0.43) to classify those types based on multispectral and LiDAR data, although showing a moderate model performance. Classification performance showed great differences between forest types with better results for the uneven-aged stands compared to the even-aged and two-aged stands. The developed typology was applied to supply local forest managers with more accurate forest maps that can be used to improve forest management plans. The typology proposed is easy to apply in forest management practices since it only uses as input the diameter at breast height, tree density and specific composition. The study demonstrated the potential of low-density LiDAR data combined with spectral information from high-resolution orthophotos to predict the structural characteristics of complex forest typologies. Full article

In uneven-aged forests, trees of different diameters, heights, and ages are located in a small area, which is due to the felling of individual trees or groups of trees, as well as small-scale natural disturbances. In this article, we present an objective method for classifying forest stands into even- and uneven-aged stands based on freely available low-resolution (with an average recording density of 5 points/m²) national lidar data. The canopy closure, dominant height, and canopy height diversity from the canopy height model and the voxels derived from lidar data were used to classify the forest stands. Both approaches for determining forest structural diversity (canopy height diversity—CHD_CHM and CHD_V) yielded similar results, namely two clusters of even- and uneven-aged stands, although the differences in vertical diversity between even- and uneven-aged stands were greater when using CHM. The first analysis, using CHM for the CHD assessment, estimated the uneven-aged forest area as 49.3%, whereas the second analysis using voxels estimated it as 34.3%. We concluded that in areas with low laser scanner density, CHM analysis is a more appropriate method for assessing forest stand height heterogeneity. The advantage of detecting uneven-aged structures with voxels is that we were able to detect shade-tolerant species of varying age classes beneath a dense canopy of mature, dominant trees. The CHD_CHM values were estimated to be 1.83 and 1.86 for uneven-aged forests, whereas they were 1.57 and 1.58 for mature even-aged forests. The CHD_V values were estimated as 1.50 and 1.62 for uneven-aged forests, while they were 1.33 and 1.48 for mature even-aged forests. The classification of stands based on lidar data was validated with data from measurements on permanent sample plots. Statistically significantly lower average values of the homogeneity index and higher values of the Shannon–Wiener index from field measurements confirm the success of the classification of stands based on lidar data as uneven-aged forests. Full article

To maintain the ecosystem resilience to large-scale disturbances in managed forests, it is essential to adhere to the principles of close-to-nature silviculture, adapt practices to the traits of natural forest types, and utilize natural processes, including natural regeneration. This study examines the natural regeneration patterns in silver fir (Abies alba Mill.)-dominated forests, analyzing how the stand structure—tree size diversity, species composition, and stand density—affects the regeneration. We analyze the data from four sites in Poland, Germany, and Italy, employing generalized linear and zero-inflated models to evaluate the impact of the management strategies (even- vs. uneven-aged) and forester-controlled stand characteristics (structural diversity, broadleaf species admixture, and stand density) on the probability of regeneration, its density, and the developmental stages (seedling, small sapling, and tall sapling) across a climatic gradient. Our results indicate a significantly higher probability of regeneration in uneven-aged stands, particularly in areas with lower temperatures and lower overall regeneration density. The tree size diversity in the uneven-aged stands favors advancement from juveniles to more developed stages (seedling to sapling) in places with higher aridity. A denser stand layer (higher stand total basal area) leads to a lower density of natural regeneration for all the present species, except silver fir if considered separately, signifying that, by regulating the stand growing stock, we can selectively promote silver fir. A higher admixture of broadleaf species generally decreases the regeneration density across all the species, except in a water-rich site in the Bavarian Alps, where it had a strong positive impact. These findings underscore the complex interactions of forest ecosystems and provide a better understanding required for promoting silver fir regeneration, which is essential for a close-to-nature silviculture under climate change. Full article

In this paper, uneven-aged stands from two important Romanian mountain areas—the Southern Carpathians and Banat Mountains—are compared with the purpose of studying the stationary conditions of uneven-aged forest stands in order to determine which management strategies are best suited to these forests and other Romanian forests with a similar structure. The study is based on silvicultural practices and natural growth conditions related to uneven-aged forest stands. The analysed surface represents 20% of Romania’s forests and includes all uneven-aged forest stands in the Southern Carpathians and half of the Romanian Western Carpathians. It has been concluded that the Southern Carpathians and Banat Mountains contain a relatively reduced percentage of uneven-aged stands compared with the total number of stands due to their composition and less favourable stationary conditions of the stands. This section highlights the novelty of the work carried out in this study on uneven-aged forest stands from two landscape reliefs in Romania. Full article

There is increasing interest in optimizing stand structure through forest management. The forest structure influences growth and maintains the structure, promoting sustainability. Structure-based forest management (SBFM), which is based on the spatial relationships between a reference tree and its four nearest neighbors, considers the best spatial structure for the stand and promotes the development towards a healthy and stable state by selectively thinning specific trees. This management method is a scientific approach for sustainable forest management, and appropriate harvesting is the core principle of uneven-aged forest management. However, the application of this approach in the management of uneven-aged mixed stands is a challenge because their dynamics are more difficult to elucidate than those of planted or pure stands. This study presented a stand spatial structure optimization model with a transition matrix growth model for selecting suitable timber harvest during uneven-aged mixed-forest management optimization. The model was developed using three neighborhood-based structural indices (species mingling, diametric differentiation, and horizontal spatial pattern) and diameter diversity indices. The approach was applied to four broadleaf stands in the Maoershan Forest Farm of the Heilongjiang Province. The results demonstrate that optimizing the stand spatial structure with a transition matrix growth model improved the objective function values (F-index) by 23.8%, 12.8%, 14.6%, and 28.3%, and the optimal removal of trees from the stands ranged from 24.3% to 25.5%. The stand structure in the next cycle (after 5 years) was closer to the uneven-mixed state. The main conclusion of this study is that optimizing the stand spatial structure with a transition matrix growth model can improve the speed and accuracy of tree selection for harvesting in unevenly mixed forests, thus helping regulate stable and diverse forest growth. Full article

The age, size and morphology of trees, including crown dimensions, can influence crown defoliation. In Croatia, the selection management of silver fir (Abies alba Mill.) forests involves pure or mixed stands, either of which can be affected by various disturbances, resulting in unbalanced stand structures. The aim of this study was to estimate the probability of trees transitioning from one defoliation class to the next, examine the influence of tree attributes on that process and analyze the changes in survival over time. The study was conducted over a 18-year period (1990–2007) on two sites with contrasting stand structures: a uniform stand with a dominant share of silver fir (Site A) and an uneven-aged mixed beech–fir stand (Site B). Logistic regression was used to model tree transitions between defoliation classes. Uniform stand structure increased the likelihood of silver fir trees transitioning to a higher defoliation class, with limited dependence on the tree crown position. In contrast, suppressed and central trees in uneven-aged stands were more likely to transition to a higher defoliation due to greater competition between them. Diameter at breast height (DBH) was found to be a significant predictor of tree transition to higher defoliation classes, with a linear trend of increasing probability with increasing DBH. Crown position and crown length were also found to be significant predictors of changing defoliation class, with observed differences between sites occurring due to differences in stand structure. To ensure a balanced stand structure and enhance tree vitality, careful consideration of easily measurable tree elements such as DBH, crown length, and tree crown position is imperative when selecting trees for felling. Full article

Bird–forestry relationships have been the subject of research and conservation initiatives for decades, but there are few reviews of resulting recommendations for use by forest managers. We define “bird-friendly forestry” as forest management that applies recommendations from research seeking to reconcile logging with bird conservation in natural forests used for timber production. We reviewed relevant studies to synthesize 10 principles of bird-friendly forestry: (1) protect and enhance vertical structure through uneven-aged silviculture; (2) leave abundant dead wood in different decay stages; (3) maintain residual large green trees; (4) create and maintain sufficient amounts of uncut reserves and corridors; (5) maximize forest interior by retaining large contiguous forest tracts in landscapes with sufficient functional connectivity; (6) maintain buffers along streams, rivers, and wetlands cultural and urban landscapes; (7) maintain horizontal stand structure and enhance vegetation diversity by creating canopy gaps; (8) extend the temporal scale of logging cycles; (9) minimize post-logging disturbance to forests, particularly during the bird breeding season; and (10) manage for focal species and guilds. These principles may serve as guidelines in developing bird-friendly management plans customized for regional priority species, with a clearly articulated vision and quantitative objectives through which success can be measured. Full article

In order to solve the problem in that the classical forest land expectation value method ignores the actual forest stock volume when assessing the income at the end of the current production cycle in the forest, and fill the research gap in this area, the technical system of the forest land asset evaluation was enriched. The forest land returns were divided into two parts, i.e., the segmented forest land return price from the growth of the actual forest stand to the end of the growth cycle (B_u1), and the segmented forest land return price for an infinite number of growth cycles after the growth of the actual forest stand to the end of the growth cycle (B_u2). Through structure, the forest land gain price expansion model was obtained, and the stand quality including the average diameter at breast height, average height, stock volume, and outturn of stand as dummy variables were used to construct the growth harvest model related to asset evaluation. Taking Cunninghamia lanceolata forest land as an example, the traditional asset evaluation methods were comparatively analyzed. The residual standard deviation (RSD) of the growth model was less than 10%, the total relative error (TRE) and mean system error (MSE) were within ±10%, the mean prediction errors (MPE) were less than 5%, and the mean percentage standard errors (MPSE) were less than 10%, respectively. Combining the forest land net present value expansion model with the traditional evaluation method, the evaluation value of the forest land assets was subsequently calculated, and accordingly, the forest land asset evaluation prime stand factors were predicated. It was found that the valuation results of the forest land net present value expansion model were consistent with the actual situation. The forest land net present value expansion model can therefore be used for asset evaluation of tree forest land (including natural uneven-aged forest land), bamboo forest land, shrub forest land, and economic forest land, and provide new technical support for forest land asset evaluation. Full article

Accurate above-ground biomass (AGB) estimation across multiple spatial and temporal scales is essential for mitigating climate change and optimizing forest management strategies. The aim of the present study was to investigate the potential of Sentinel optical and Synthetic Aperture Radar (SAR) data in reliably estimating the plot-level total stem biomass (TSB), which constitutes the dominant material among the different tree components of AGB (stem, branches, and leaves). The study area was located in a dense coniferous forest characterized by an uneven-aged structure and intense topography. A random forest (RF) regression analysis was performed to develop TSB predictive models using Sentinel-1 and -2 images in an individual and combined manner. Consequently, three RF models were produced and evaluated for their predictive performance through the k-fold cross-validation (CV) method. The results showcased that the individual use of Sentinel-1 contributed to the production of the most accurate plot-level TSB estimates (i.e., coefficient of determination-R² = 0.74, relative mean square error (RMSE) = 1.76 Mg/1000 m², mean absolute error (MAE) = 1.48 Mg/1000 m²), compared to the use of Sentinel-2 data individually and the Sentinel-1 and -2 combination. In fact, the synergistic use of optical and SAR data led to the generation of an RF model that only marginally underperformed the SAR model (R² = 0.73 and R² = 0.72, respectively). Full article

Modelling is essential in forest management as it enables the prediction of productions and yields, and to develop and test alternative models of silviculture. The allometry of trees depends on a set of factors, which include species, stand structure, density and site. Several mathematical methods and techniques can be used to model the individual tree allometry. The variability of tree allometry results in a wide range of functions to predict diameter at breast height, total height and volume. The first functions were developed for pure even-aged stands from crown closure up to the end of the production cycle. However, those models originated biased predictions when used in mixed, uneven-aged, young or older stands and in different sites. Additionally, some modelling methods attain better performances than others. This review highlights the importance of species, stand structure and modelling methods and techniques in the accuracy and precision of the predictions of diameter at breast height, total height and volume. Full article

The aim of this study was to identify changes in the concentrations of elements in fir assimilation organs over the past 30 years in order to assess fir reactions as a bioindicator of changes in the functioning of Central European fir forest ecosystems under conditions of reduced anthropogenic emissions. In particular, we selected the example of the Świętokrzyskie Mountains (Świętokrzyski National Park located in the northern range of Abies alba Mill.). The research was carried out in the “Łysica-Święty Krzyż” area under strict protection, including multi-species and uneven-aged tree stands with a complex structure, dominance of beech and fir, and numerous admixtures of other tree species. A decrease in the concentrations of pollutants in fir needles indicates a significant reduction in pressure on the environment and an improvement in the conditions of ecosystems in 2018 compared with those in 1986. In the period of more than 30 years between the sets of research, the concentrations of lead in fir needles decreased threefold and those of sulfur decreased twofold. A significant increase in the concentrations of cadmium, copper, manganese, and zinc in the three-year-old needles showed that they are a good indicator of environmental pollution with trace elements and may be used in biomonitoring. Full article