Search Results (110)

Forest-inventory precision depends jointly on plot size and sample size. Using 42 stem-mapped 1000 m² plots in an uneven-aged hybrid fir (Abies × borisii-regis Mattf.) forest in Pertouli, Greece, we reconstructed 100–1000 m² concentric plots at the same centers. RSE was calculated using a simple-random-sampling variance working approximation. At $n=42$, 300 m² was the minimum acceptable plot size under an adopted ±10% practical agreement criterion relative to the 1000 m² reference; the minimum remained 300 m² at ±7.5% but increased to 400 m² for basal area and 700 m² for tree density at ±5%. Under a 5% RSE target, basal area met the target from 500 m², whereas tree density met it at no acceptable size; both attributes met a 10% target from 300 m². Controlled resampling and compartment-group analysis placed 95%–100% of group-by-size RSEs within same-sample-size resampling intervals. Pareto-efficient designs showed the sample-size–sampled-area trade-off. Holding total sampled area constant, more small plots reduced median RSE by 13%–23%. Designs requiring $n>42$ remain projections. Case-study plot-size values should not be transferred directly to other forest structures; the procedure provides a transferable way to define an acceptable plot-size range and evaluate sample-size and sampled-area trade-offs for a selected attribute and precision target. Full article

Old-growth forests are recognized as key reference systems for biodiversity conservation and sustainable forest management, yet they remain rare and highly fragmented ecosystems across Europe. In this study, we developed and applied a quantitative, measurement-based framework to assess candidate old-growth beech stands by comparing their structural attributes with reference old-growth forests and with a broader set of beech forests from the National Forest Inventory (NFI). Specifically, we compared the structural attributes of two candidate old-growth (COG) beech stands to assess their degree of naturalness and their similarity to three reference old-growth (ROG) beech forests in the central Apennines. The approach integrated field-based structural measurements, deadwood quantification, dendrochronological assessment of dominant trees and diachronic aerial imagery evaluation, comparing COG stands with both ROG and other beech forests from the NFI database. The two COG stands differ clearly from common beech forests, exhibiting lower stem density, larger size variability, higher occurrence of large trees and of standing wood biomass. Stem diameter distributions followed a reverse J-shaped pattern, typical of uneven-aged and scarcely managed forests. Some very old trees were also found, especially at one of the two COG sites. These characteristics are largely comparable to the ROG beech forests, except for deadwood volumes, lower at the two COG forests. In addition, historical aerial imagery and tree-ring analysis suggested that these forests are intermediate stages along an old-growth gradient. Our findings demonstrate that a prolonged forest management abandonment of over 70 years can induce the development of old-growth attributes in Mediterranean mountain beech forests, even in stands previously coppiced or pastured for a long time. This study provides a replicable measurement-based approach for identifying and validating candidate old-growth forests, under current Italian regulations and contributes to conservation targets consistent with the EU Biodiversity Strategy for 2030. Full article

Comparing the economic performance of continuous cover forestry (CCF) in the broader context of uneven-aged management (UEA) and rotation forest management (RFM) representing conventional even-aged forest management (EA) has been a long-standing question in forest economics. In this review, we present a literature search of 134 scientific papers published between 1994 and June 2026, combining one keyword set related to economic terms and a second keyword set related to forest management. The search was restricted to temperate and boreal forests in the Northern hemisphere. Within the searched papers, different categories were identified according to their main focus, methodology, and the nature of their results. Of the 134 studies, 64 analyzed economic data covering the entire forest production cycle, but only 31 of them included relevant data to calculate an economic criterion for a correct comparison between CCF and RFM, by using net present value (NPV), or land expectation value (LEV). Regarding timber production, results show that neither CCF nor RFM is economically better overall. Advancements of one alternative over the other depend on site conditions, tree species, initial state of the forest, and interest rate. In contrast, studies have consistently proven that CCF is a better alternative for sustainability in a broader context as it decreases risks, mitigates climate change impacts, and provides non-productive ecosystem services. Full article

Sustainable forest management depends on reliable compartment-level growing stock volume (GSV) estimates, which inform the prescribed cut. At the University Forest of Pertouli (Greece), four management-plan inventories (1989–2028) span a methodological transition from full-callipering in 1988 and 1997 to a systematic-sample-plot inventory with empirical compartment-level upscaling in 2008 and 2018. We distinguish methodological discontinuity (a change in method) from methodological inconsistency (variation in empirical sample-plot weighting between sample-based inventories) and develop a four-hypothesis diagnostic framework. Hypothesis 1 tests temporal change via a linear mixed model on 149 compartments. Hypotheses 2–4 use non-parametric bootstrap on 231 common sample plots under three nested resampling schemes, which bound a documented plot-center relocation. The 2008 compartment-level estimator underestimated the sample-plot benchmark by 19% (deviation $B_{2008}$ = +54.9 m³ ha⁻¹, 95% confidence interval (CI) +39.6 to +70.8); in 2018 the two converged ($B_{2018}$ = −2.2 m³ ha⁻¹). The implied decadal changes differ by difference-in-differences DID = +57.0 m³ ha⁻¹ (robust across three schemes), with ~96% attributable to baseline-year underestimation; the 2008 underestimation was confirmed in all nine orographic units. The framework provides a retrospective consistency assessment for inventory time series crossing methodological transitions. The 19% deviation documented here is invisible without it; its identification restores estimation reliability to compartment-level estimates. Full article

The COVID-19 pandemic triggered an unprecedented expansion of telehealth within the Medicare program, raising the question of whether this surge represented a temporary crisis response or a durable shift in care delivery. This study applied supervised machine learning and explainable artificial intelligence methods to national Medicare Telehealth Trends data to model nonlinear adoption dynamics and evaluate differential stabilization across demographic and geographic groups. Using state by quarter by demographic group observations from 2020 through 2025, random forest and gradient boosting models with temporally aware validation were implemented to characterize surge magnitude, peak timing, and post-surge equilibrium levels. Differential saturation was assessed using model predicted plateau estimates across age, race, dual eligibility status, and state. The results revealed a rapid and synchronous surge across demographic strata followed by stabilization into persistent but heterogeneous equilibrium levels. Age and dual eligibility status were associated with substantial divergence in plateau magnitude, while racial differences were comparatively modest after accounting for temporal and geographic factors. Geographic heterogeneity exceeded demographic variation, indicating that state level structural environments exert the strongest influence on long-term telehealth equilibrium. These findings suggest that telehealth has transitioned from emergency expansion to partial institutional embedding within Medicare preventive care delivery. However, uneven stabilization across states highlights structural disparities that may influence continuity of chronic disease management, behavioral health access, and routine preventive services. Strengthening digital infrastructure and policy alignment may therefore be necessary to ensure that telehealth functions as an equitable and durable component of preventive medicine beyond the pandemic period. Full article

Sustainable forest management requires current, territory-wide data, which is difficult to obtain in vast regions like Quebec, Canada. To complement ground inventories and photo-interpretation, the province developed an airborne laser scanning (ALS)-based model that performs well in coniferous stands, but its accuracy in hardwood stands remains untested. This study aims to evaluate the accuracy of the ALS-based prediction of stand basal area and then test new approaches to increase its performance. Airborne LiDAR data from 2011 to 2020 and 12,506 validation plots from sample plots were used. The ALS model accuracy was initially compared across the stand types, revealing lower accuracy in shade-tolerant deciduous stands. Three inputs were found to increase prediction accuracy: proportion of each species basal area in the stand, geographical coordinates, and meteorological data associated with location. Parametric and auto machine learning (AutoML) methods were employed using those inputs to improve accuracy, with AutoML achieving the highest improvement with initial R² of 0.27, 0.47 and 0.54 and after correction R² of 0.31, 0.56 and 0.67, respectively, for shade-tolerant deciduous, shade-intolerant deciduous, and coniferous stand. Even with the advancements made, further improvements will be necessary to consider using an ALS-based model for shade-tolerant deciduous species. Full article

This investigation examines diffusion processes for predicting whole-stand volume, incorporating the variability and uncertainty inherent in regional, operational, and environmental factors. The distribution and spatial organization of trees within a specified forest region, alongside dynamic fluctuations and intricate uncertainties, are modeled by a set of nonsymmetric stochastic differential equations of a sigmoidal nature. The study introduces a three-dimensional system of stochastic differential equations (SDEs) with mixed-effect parameters, designed to quantify the dynamics of the three-dimensional distribution of tree-size components—namely diameter (diameter at breast height), potentially occupied area, and height—with respect to the age of a tree. This research significantly contributes by translating the analysis of tree size variables, specifically height, occupied area, and diameter, into stochastic processes. This transformation facilitates the representation of stand volume changes over time. Crucially, the estimation of model parameters is based exclusively on measurements of tree diameter, occupied area, and height, avoiding the need for direct tree volume assessments. The newly developed model has proven capable of accurately predicting, tracking, and elucidating the dynamics of stand volume yield and growth as trees mature. An empirical dataset composed of mixed-species, uneven-aged permanent experimental plots in Lithuania serves to substantiate the theoretical findings. According to the dataset under examination, the model-based estimates of stand volume per hectare in this region exhibited satisfactory goodness-of-fit statistics. Specifically, the root mean square error (and corresponding relative root mean square error) for the living trees of mixed, pine, spruce, and birch tree species were 68.814 m³ (20.4%), 20.778 m³ (7.8%), 32.776 m³ (37.3%), and 4.825 m³ (26.3%), respectively. The model is executed within Maple, a symbolic algebra system. Full article

Forest measurements are essential for monitoring stand dynamics and long-term trends. Errors in tree measurement can seriously affect the outcomes of a forest inventory. This study investigates measurement errors from successive measurements on permanent concentric circular plots based on data from 74 plots in Dinaric uneven-aged mixed fir–beech stands. Tree data errors were detected and corrected. Diameter increment was calculated as a difference in DBH from two successive inventories, and linear regression models were developed based on original and corrected data. Measurement errors were identified in 2.57% of trees, some having a substantial impact on tree volume. Volume discrepancies between original and corrected data were generally minor, where 93.2% of plots in the first and 70.3% in the second inventory required no corrections and volume differences in the overall levels were negligible and statistically non-significant: 0.30 m³/ha in the first inventory (p = 0.550) and 0.05 m³/ha in the second (p = 0.974). Although diameter increment models with original and corrected data differed significantly, model choice resulted in minimal impact on volume increment. Since omitting erroneous measurement data would lead to volume underestimation, data correction is preferable. However, when modeling tree increment, excluding incorrect or doubtful data remains a practical and acceptable approach. Full article

The diversity of forest tree life strategies is fundamental to species coexistence in mixed stands. Growth rate is one of the most important elements of a species’ life strategy. This aspect has been relatively well recognised in even-aged stands. However, the situation is different in uneven-aged stands, particularly in multi-species stands comprising species with different light demands. In this study, we aimed to compare stem basal area increment (BAI) in regard to five species forming multi-species, uneven-aged deciduous forests in Central Europe as an important element of their growth strategy. Particular attention was paid to the relationship between this feature and tree height and competitive status. These relationships were analysed using a linear mixed model. The BAI was positively correlated with tree height, while a negative correlation was observed between BAI and increasing competitive level. However, the observed variations in the trends of these relationships were not associated with the light demands of the compared species. In general, the majority of the studied species demonstrated similar growth dynamics. This may suggest that the role of this trait in shaping species coexistence is modulated by other life-history strategy components and by specific growth conditions. An exception to this is the most light-demanding species, black alder (Alnus glutinosa (L.) Gaertner), which, contrary to expectations, exhibits a lower basal area increment under uneven-aged conditions. Full article

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

This study presents a model for estimating forest productivity based on a sample of 2048 permanent field plots covering a wide range of growing sites in Mexico. Our state-space approach assumes that the growth behavior of any stand over time can be estimated on the basis of its current state, defined by the dominant height (H), number of trees per hectare (N), and stand basal area (BA). We used transition functions to estimate the change in states as a function of the current state. We also present transition functions for the change in stand volume (V) and total above-ground biomass (AGB). The first transition function relates dominant height to dominant diameter by using the guide-curve method to estimate site form. The transition function for N consists of two models, one for estimating natural mortality and the other for estimating recruitment. These models were developed in two steps: in the first step, the logistic regression and maximum likelihood approach were used to estimate the probability of the occurrence of mortality or recruitment, and in the second step, the rate of change associated with each event was modeled when mortality or recruitment was assumed to have occurred as a result of the first step. The remaining three transition functions (BA, V, and AGB) were fitted simultaneously to account for possible correlations between errors. The model estimating total above-ground biomass (AGB), which can be considered a state variable that summarizes the performance of the whole model, explained more than 97% of the observed variability, with a root mean square error value of 10.57 Mg/ha. Full article

Forests in Croatia are characterized by higher levels of biodiversity in species composition. Three significant events occurred in Croatian forests over the past ten years, all of which have a common denominator—sanitary felling. The challenge in the sustainable development of forests started with the ice storm of 2014 that amounted to damage and raised costs in forest stands to EUR 231,180,921. The second challenge was in 2017 when the bark beetle outbreak occurred in the Gorski Kotar region. In December 2017, a windstorm in the same area caused damage to approximately 500,000 m³ of wood stock. The third climate extreme was in the summer of 2023 when three storms with strong winds and heavy rain damaged even-aged forests of common beech and pedunculated oak. The damage was substantial: 3,954,181 m³ of timber was mostly broken and destroyed across 21,888.61 ha of area, and the most damage was in the pedunculate oak forests of Slavonia, i.e., Quercus robur subsp. Slavonica, at 1,939,175 m³. For the main meteorological stations in lowland Croatia, data on precipitation amounts (mm) and wind speeds (m/s) were collected for the period 1981–2023, and the results of our analysis for the last decade are presented. Meteorological drought was analyzed using the rain anomaly index RAI. Data regarding open space fires in the Mediterranean karst area of Croatia were collected from the Croatian Firefighting Association, and the calculation of the burned area index (BAI) was determined. Throughout the entire area of Gorski Kotar County, a sample of permanent plots was set and used to assess the extent of forest damage from the ice storm in 2014 and for the establishment of permanent monitoring of the recovery of trees and forests damaged by the ice storm. The monitoring of bark beetles in the Gorski Kotar region started in 1995 and is still in progress. The aftermath of bark beetle outbreaks in two uneven-aged silver fir stands was studied after a bark beetle outbreak and a sanitary felling of 4655.34 m³. In the area of lowland Croatia, a statistically significant and positive correlation was found between sanitary fellings, maximum wind speeds, and rain anomaly indices in even-aged forests. In conclusion, sustainable development will be at risk due to difficult recovery, rising costs, and overall climate change in the years to come. 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