This study assessed mountain tugai poplar forests in southern and southeastern Kazakhstan by conducting forest inventory analysis and field surveys in Zhongar Alatau, Northern Tien Shan, and Western Tien Shan. The forest inventory identified 1,622.5 hectares of poplar forests, mainly consisting of mature and overmature stands with low density and productivity. Only 47% of these forests were located within protected areas. The primary species, Populus macrocarpa (Schrenk) Pavlov (also known as P. talassica Kom.), was confirmed through molecular genetic analysis using ITS, matK, and rbcL markers. Natural regeneration mainly occured vegetatively, with limited seed reproduction. Recreational activities had a significant impact on stand condition, reducing the proportion of viable trees from 70–85% in protected areas to 50–55% in heavily visited sites. B-INTACT modeling predicted substantial ecosystem degradation with increased recreational infrastructure. Conservation efforts should focus on expanding protected area coverage, controlling invasive species, and implementing systematic long-term monitoring to address these challenges.

Conducting a national urban forest management survey – insights from the 2025 Canadian Urban Forest Census

Drought-induced die-off alters canopy structure and understory microclimatic conditions, but its consequences for tree regeneration remain unclear. We assessed how canopy-driven microclimate filtering and climatic suitability influenced Pinus sylvestris regeneration across developmental stages (seedlings, young saplings, and old saplings) following drought-induced die-off in forests across Catalonia (NE Spain). We analysed recruit densities with linear mixed models incorporating forest condition (die-off vs. control), canopy type (closed, defoliated, and open gaps), survey year (2013, 2017, and 2022), and climatic-niche metrics as fixed effects, while site and plot were considered as random effects. In closed habitats, die-off lowered both young and old saplings relative to controls. Defoliated habitats consistently failed to support regeneration across all stages, even in climatically favourable sites, likely due to impaired propagule supply. Open habitat enhanced seedling and sapling densities in die-off plots. Regarding the position in the climatic niche, old saplings persisted in closed habitats at climatically marginal sites, likely benefiting from canopy-mediated microclimate control. Canopy buffering also protected young saplings in closed habitats during the periods with strong interannual climate fluctuations. In open habitats, young and old saplings were sensitive to climatic position in species’ niche, with their densities declining with increasing distance to the optimum, core niche. Overall, seedlings’ density was higher near the climatic optimum in die-off plots than in controls. Also, nearly a decade after the drought, only young sapling densities increased in die-off plots, likely reflecting disturbance legacies and favourable climatic fluctuations. Our results highlight the silvicultural value of maintaining a mosaic of canopy structures, retaining open habitats in climatically optimal sites to enhance seedling establishment and progression, while preserving closed canopy refugia in marginal climatic sites to buffer climate extremes, thus, favouring saplings survival against increasing drought stress. • Canopy cover-climate niche interactions shape post-drought recruitment. • Drought-driven defoliation suppresses recruitment, even at optimal climates. • Closed habitats buffer old saplings, maintaining survival under suboptimal climates. • Open habitats favour seedling emergence and progression near the climatic optimum. • Adaptive management can enhance forest resilience to drought.

Many studies show that tree diversity promotes forest productivity, and few recent ones suggest that this diversity effect may strengthen under climate warming. Yet this pattern has rarely been tested with observations. Here, we investigated how the species mixture affects forest productivity in response to increasing aridity, relying on 25,838 French forest surveys between 2005 and 2016. We showed that 79.8% of the variation in forest productivity was explained by interactions among tree species richness, baseline and temporal changes in water supply and stand density. Although forest productivity decreased with water deficit (for both baseline conditions and temporal changes), species richness mitigated the magnitude of this productivity reduction. These findings indicate that species mixture stabilizes productivity along a water supply gradient and enhances resistance to increasing aridity. In addition, we found that this species diversity insurance of forest productivity in the face of water supply variation is also dependent on stand density. Our modeling approach evidenced that the positive biodiversity effect, mainly observed in forests where recent climate change has decreased water supply, diminished as tree density increased, and even becoming negative in forests having highest tree density under favorable hydric conditions. Covering a large spectrum of climate conditions, this study reveals how tree species diversity insure forest productivity against climate change over time. Regarding the anticipated acceleration of global warming, forest management should prioritize tree diversity to sustain wood productivity and carbon storage, particularly in water-limited conditions. Additionally, foresters should consider tree density effects in their planning to preserve the beneficial effects of tree diversity on forest productivity.

Canopy Structural Complexity (CSC) is a key structural attribute for evaluating forest ecological functions and health, with accurate canopy extraction serving as the prerequisite for its quantification and the basis for improving metric reliability and elucidating spatiotemporal canopy dynamics. However, existing canopy extraction methods generally rely on large-scale fully labeled point cloud datasets, which are often impractical for large-scale Unmanned Aerial Vehicle (UAV) LiDAR forest surveys. To address this limitation, we propose a weakly supervised canopy extraction strategy that relies on a limited number of labeled plots. By incorporating a pseudo-label generation strategy and a data-augmentation-based consistency self-supervised constraint, the method effectively improves segmentation performance in unlabeled scenarios. Furthermore, we introduce a multi-dimensional joint canopy entropy index that integrates both global and local canopy features, combining projection-based global canopy entropy with graph-based local canopy entropy to provide a more comprehensive CSC quantification. Experiments were conducted using three labeled plots as the training set and a held-out labeled plot for quantitative evaluation, with numerous unlabeled plots used for qualitative generalization analysis. Results showed that on the labeled test plots, the proposed weakly supervised strategy achieved 85.37 % mIoU and 92.64 % OA, surpassing the best-performing fully supervised method. Visual comparisons in real, unlabeled forest scenes demonstrate that the proposed method maintains clear boundaries between canopy and non-canopy regions, even in areas with significant topographic variation, fragmented canopy, or complex structures, while effectively suppressing false positives in ground and low-vegetation areas. The proposed multi-dimensional joint canopy entropy, when applied to the predictions of the weakly supervised canopy extraction strategy, successfully quantified the CSC using large-scale, unlabeled UAV forest LiDAR point clouds. It yielded results consistent with ecological priors and exhibited robustness under varying levels of point cloud sparsification. Based on normalized scores across three evaluation metrics, the proposed index achieved a score of 0.76, outperforming several commonly used CSC quantification indices.

ABSTRACT Forest ecosystems in many low-income tropical countries experience high rates of degradation. Often, remote sensing and forest surveys are used to assess the degradation, neglecting local knowledge in the evaluation and management responses. In this study, we integrate scientific and local knowledge to co-create customized indicators for qualitatively plumb forests and identify suitable management strategies. We used the Drivers-Pressures-Stressors-Condition-Responses framework to guide this collaborative process. Working with 100 farmers in 10 communities, we used in-depth interviews, historical narratives, photography, and geospatial methods to conduct extensive “forest walks” to measure forest quality. Participants described their perception of forest quality based on seven co-created indicators and the impacts of human-environment interactions. We found that co-created indicators of forest quality generally align with indicators used in ecological science, highlighting synergies for collaborative assessment. Perception of forest quality is based mostly on intrinsic value placed on ecosystem services and the degree of human impacts on forest condition. Local knowledge integration and co-creation in forest quality assessment uncovered nuances of the drivers of forest deforestation, which aids in the development of customized co-management strategies for regeneration and conservation. Overall, the study underscores the importance of bottom-up collaboration in bridging the science-policy-practice gap to address forest degradation.

This study conducted a bibliometric review on the subject of floristic surveys of the mixed ombrophilous forest, also known as araucaria Forest, investigating its scientific production and research trends over time. The research utilized the Scopus database (Elsevier). Data were analyzed using the VOSviewer software. A total of 118 documents published between 1981 and 2024 were found, distributed across 46 journals, focusing mainly on the proposed theme. Brazil led in the quantity of documents, followed by Germany and Argentina. The analysis of keywords and institutions revealed predominant themes such as forest fragmentation and natural regeneration, with emphasis on brazilian institutions like the Santa Catarina State University. The results highlight the growing interest in studies on araucaria forests, particularly in Brazil, and the relevance of brazilian institutions in producing this research. Despite the recent decrease in the number of studies, research remains crucial for understanding the biodiversity and conservation of these ecosystems.

Based on the results of a survey of spruce forests in Belarus during 2010–2023, provides data on the area of foci and the incidence of the main pathological factors in spruce forests – bark beetles and root rot. It is noted that the incidence of bark beetle drying increases when moving from the north to the south of the Republic, and root rot – in the opposite direction. Since the 1980s, the epicenter of root rot epiphytosis in spruce forests has moved from the spruce-hornbeam oak grove subzone to the oak-dark coniferous forest subzone. Based on the results of a survey of 7 forestry enterprises in the northwest of the Republic, which was conducted in 2023, using mathematical-statistical methods of analysis, it was found that such forestry and taxation parameters of stands as the average age of the stand, the proportion of spruce in the stand and the indicator of the potential productivity of the stand (bonitet) affect the occurrence of bark beetle and root rot outbreaks in spruce forests. The occurrence of these pathologies increases with the age of the stand, the proportion of spruce in the stand and its productivity. Possible reasons for the influence of forestry factors on the development of bark beetle and root rot outbreaks in stands are described. From a practical point of view, to increase the sustainability of forests, it is advisable to use such forestry techniques as: regulating the age of felling of stands; introducing admixtures of other species into the composition of stands; choosing areas with increased soil moisture for growing spruce forests and regulating their water regime; as well as a combination of several of the above techniques on the same site.

ABSTRACT The Delacour's langur ( Trachypithecus delacouri ) is a Critically Endangered primate, restricted to a small region in northern Vietnam. In view of its very small population and existing threats, frequent population monitoring programs are urgently needed for this species. In this study, we evaluated the utility of handheld thermal imaging devices as a complementary tool to conventional ground‐based visual surveys for primate population monitoring efforts. Based on results of past studies, we conducted field surveys in Kim Bang Protection Forest, Ninh Binh Province, Vietnam, where the second most important population of the Delacour's langur inhabits. While we followed protocols from previous ground‐based visual surveys, we also used thermal monoculars to facilitate langur detections. By integrating thermal handheld devices, we documented at least 18 langur groups with around 116 individuals, an increase of about 11.5% in total population size compared to the most recent extensive study at the same site. When comparing to the 2022 drone survey in Kim Bang, our results also showed that while the drone platform demonstrates superior performance, the integration of thermal imaging devices substantially reduces survey effort relative to conventional ground‐based visual techniques. Given the recent regulations on flying drones in remote areas in Vietnam, our findings suggest that thermal imaging devices offer a viable option to improve the efficacy of ground‐based primate population monitoring surveys. Furthermore, when properly deployed, handheld thermal devices may provide key advantages for certain primate research topics.

Abstract Expanding tree cover outside forests is central to India’s climate and restoration goals, yet the effectiveness of public programs driving these efforts remains uncertain. We examine eight major government schemes aimed at promoting trees on farmlands and other non-forest lands, linking program funding (2013–2019) with observed tree cover change (2017–2023) across three complementary datasets: the Forest Survey of India (FSI), MODIS Vegetation Continuous Fields, and the Brandt et al. (2024) high-resolution individual tree maps. Results reveal that while the Sub-Mission on Agroforestry (SMAF) is consistently associated with gains in tree cover on agricultural lands, several other large programs—including those for afforestation, agricultural development, and compensatory planting—show weak or negative relationships with tree cover outside forests. These patterns suggest that program design and targeting, rather than funding volume alone, determine success. Our findings underscore policy priorities such as better alignment of agricultural and forestry incentives to support on-farm trees, improved transparency in program implementation and monitoring, and greater public access to fine-scale expenditure data to enable evaluation of outcomes. As India and other countries expand tree-planting investments under climate and biodiversity commitments, evidence from this study highlights the need to move from funding inputs to verifying outcomes, ensuring that tree-based interventions contribute effectively to both ecological restoration and rural livelihoods.

Forest ecosystems provide essential ecological functions in the context of accelerating climate change. However, evaluating their conservation values and conditions remains challenging due to conceptual and methodological ambiguities. In particular, ecosystem integrity and ecosystem authenticity are often conflated in vegetation-based assessments, despite representing distinct dimensions of ecosystem condition. This study advances vegetation-based assessments by explicitly decoupling ecosystem integrity from ecosystem authenticity, while integrating spatial completeness, vegetation patterns and quality, and successional–disturbance attributes into a unified operational framework for reserve-level diagnosis and comparison. The resulting indices enable managers to distinguish boundary-driven limitations of landscape integrity from internal vegetation conditions that persist in near-natural states, thus enhancing interpretability for conservation planning in the context of climate change. Using standardized forest resource survey data and spatial analysis, we constructed two composite indices: Forest Ecosystem Integrity (FEI) and Forest Ecosystem Authenticity (FEA). These indices were applied to two adjacent cold-temperate forest nature reserves, Hanma and Huzhong, in the Greater Khingan Mountains of northeastern China, as well as to a merged spatial scenario. The results demonstrate consistently high ecosystem authenticity (>90%) across all study areas, indicating strong naturalness and successional maturity. In contrast, ecosystem integrity remains moderate (63–69%), primarily constrained by the low spatial completeness of conservation units. The spatial integration of the two reserves significantly improved ecosystem integrity without compromising authenticity, highlighting the role of boundary configuration in conservation effectiveness. By operationalizing integrity and authenticity as complementary yet distinct dimensions, this study provides a reproducible framework for evaluating forest ecosystem conditions and offers practical insights for the design of protected area networks and adaptive management in cold-temperate forest regions.

Passive protection is widely assumed to preserve biodiversity and ecological integrity, yet the evidence for long-term vegetation stability in protected temperate forests remains inconclusive. We resurveyed two deciduous forests in SW Poland after 30 years of strict protection to assess temporal changes in their understory vegetation, functional structure, and habitat conditions. Using paired phytosociological relevés (n = 40), collected using the Braun-Blanquet method, we compared baseline (1989–1991) and recent (2022) data with respect to species frequency, Ellenberg indicator values, basic functional traits, and functional diversity. Species composition proved highly stable: only 10% of vascular plant species exhibited significant changes in frequency in particular layers, largely reflecting the vertical redistribution of woody species rather than species turnover. Habitat conditions showed no significant temporal changes. In contrast, the functional structure of the herb layer changed markedly, with significant increases in community-weighted means of seed mass, plant height, and specific leaf area, accompanied by a significant rise in functional diversity. These shifts were partly driven by the increasing abundance of woody species and some opportunistic and invasive species. Our results demonstrate that functional traits may reveal directional ecological changes in passively protected forests even when species composition and habitat indicators remain unchanged, highlighting the importance of trait-based approaches for long-term forest surveys.

The upper Guinean rainforest biome is a poorly studied, yet hyper-biodiverse region facing severe fragmentation due to ongoing habitat transformation. We conducted a herpetological baseline survey in the Dugbe region during 2021 using passive trapping and active searching. Our survey resulted in 1140 herpetofauna observations, representing 72 taxa (39 amphibians and 33 reptiles), with active searching yielding 50% of the total diversity. Nearly half (47.2%) of the documented species are West African endemics. Rarefaction/extrapolation sampling curves indicated incomplete overall sampling of herpetofauna diversity, though amphibian sampling completeness was high. Reptile diversity metrics revealed significant sampling deficiencies, largely explained by the high proportion of singleton observations (60.6% of reptile records). When compared to the IUCN predictive distribution maps, our survey documented 58.5% of the 123 species predicted for the region, with moderate overall Jaccard similarity (47.73%). Taxonomic groups showed varied patterns of congruence: amphibians displayed relatively high Jaccard similarity (55.18%), while reptiles showed lower similarity (40.26%). Notably, our survey documented substantially higher herpetofauna species richness than benchmark surveys from nearby areas, particularly for reptiles (33 species compared to 14 and 5 species in Krahn-Bassa Proposed Protected Area and Grebo National Forest surveys, respectively). Three amphibian species could not be identified to species level using morphological characteristics alone, highlighting the need for further taxonomic research on West African herpetofauna.

ABSTRACTUnderstanding the main factors that influence productivity across stand types is essential for effective management strategies. Chinese fir (Cunninghamia lanceolata) is a key afforestation species in subtropical China. However, comparative studies on productivity differences and the underlying mechanisms among different Chinese fir stand types remain scarce. In the present study, using second‐class forest resource survey data from Ganzhou, southern China, we classified plots dominated by Chinese fir into three stand types: pure Chinese fir (541 plots), Chinese fir–broadleaf mixed (351 plots), and Chinese fir–conifer mixed stands (232 plots). We then assessed productivity differences among stand types and applied the Boruta feature selection and Random Forest modeling to identify the main influencing factors, followed by structural equation modeling (SEM) to evaluate their direct and indirect effects. The results indicated that stand productivity differed significantly among stand types, with stand density, dominant diameter, stand age, Gini coefficient, and mean tree height being the most influential factors. The productivity of pure stands was more sensitive to climatic and site conditions, whereas mixed stands were more strongly influenced by structural heterogeneity. These findings highlight the critical role of stand structure in regulating productivity and suggest that enhancing density regulation in all stands and promoting structural heterogeneity in mixed stands can improve productivity and stability, with mixed‐stand management offering greater potential for long‐term productivity gains and resilience to climate change.

Research on forest growth models is not only crucial for regional ecological security and the optimal allocation of water and carbon resources but is also a key component in the study of carbon cycling in arid regions, holding scientific and practical significance for addressing climate change and promoting green sustainable development. Therefore, this study takes the Manas River Basin in Xinjiang as an example and based on the 2011 forest resource survey data from the Manas River Basin, constructs basic growth models for the diameter at breast height (DBH)-height and age-DBH relationships for five dominant tree types: Spruce, Poplar, Mixed wood, Sand jujube, and Populus euphratica. The optimal basic models for each types are selected. Secondly, climate factors (annual precipitation, Minimum of Daily Maximum Temperature, TXn) and topographic factors (Digital Elevation Model; DEM) are introduced into the optimal models to construct multivariate nonlinear forest growth models. Finally, deep learning is used to optimize the overall accuracy of the models. The results show that the optimal DBH-height models for Spruce, Poplar, Sand jujube, and Populus euphratica are S-curve models, while the optimal DBH-height model for Mixed wood is a logarithmic model. The optimal age-DBH models for Poplar and Populus euphratica are S-curve models, whereas the optimal age-DBH basic models for Spruce, Mixed wood, and Sand jujube are growth model, linear model, and logistics model, respectively. The overall accuracy of the multivariate nonlinear forest growth models is improved, with the highest R2 reaching 0.890 and the average RMSE increasing by 10.590, mainly due to the decrease in model accuracy for some tree types caused by random factors. Lastly, compared to the basic models and multivariate nonlinear forest growth models, the deep learning approach demonstrates the best performance, with the highest correlation coefficient reaching 0.960. Overall, by constructing forest growth models for five main dominant tree types in the Manas River Basin in Xinjiang, the optimal forest management strategies in the region can be determined, which helps to formulate targeted forest management strategies, effectively address the allocation of carbon and water resources, and promote healthy and sustainable forest development.

Background and objective: Vietnam—historically defined by its mountainous and forested landscapes—has long relied on forests as a foundation of its economy, culture, and security. While forest management during the colonial and modern periods has been widely studied, the premodern period remains understudied. This article examines forest conditions and the policies regulating their exploitation, management, and protection under the Nguyen dynasty (1802-1883).Methods: Using an environmental history approach, the study analyzes chronicles compiled by the Nguyen court’s Office of State Historiography (Quoc su quan), chiefly the Dai Nam thuc luc (Veritable Records of the Great South) and the Dai Nam nhat thong chi (Comprehensive Encyclopaedia of the Great South). These sources provide insights into forest resources, administrative measures, and official perceptions of nature. Selected case studies highlight key patterns of governance.Results: Although the Nguyen dynasty lacked systematic forest surveys or a formal forestry code, the royal court issued numerous edicts on timber extraction, taxation, land reclamation, and wildlife control. It also established guard posts in forested regions to suppress banditry and prohibited unauthorized logging near royal tombs and frontier zones. These policies reflect a pragmatic model of environmental governance balancing fiscal, strategic, and ecological concerns.Conclusion: Forest governance under the Nguyen dynasty demonstrates how premodern Vietnamese statecraft linked resource extraction with moral order and administrative authority. Comparison with earlier dynasties and later colonial forestry highlights both continuity and transformation in Vietnam’s long tradition of state-managed nature.

The present study was undertaken to analyze the trend and growth rate performance of forest area as well as geographical area, dense forest,Open Forest, and Total Forest of the Banda district of Bundelkhand region of Uttar Pradesh. The time series data has been collected from the Forest Survey of India, which was published by Dehradun, Uttarakhand. It is under the Ministry of Environment, Forest, and Climate Change, Government of India, from 1991-91 to 2021-22 periods. It was found that the simple and compound growth rates were -4.74 and -4.31, respectively, of the geographical area. The simple and compound growth rates of -15.54 and -13.72, respectively, of the total forest area of the Banda district were negative but significant.

Accurate bird density estimates are essential for conservation planning and understanding ecological dynamics within forest ecosystems. South Africa’s forest avifauna, though limited in range, comprises species of high conservation concern, yet recent, robust population estimates are lacking. We addressed this gap by conducting surveys across key forest biomes in South Africa using both Distance Sampling (DS) and Fixed Radius Counts (FRC), supplemented with a trait-based predictive model. Initial DS surveys in the dense Afrotemperate forests of the Western Cape frequently yielded inflated density estimates because of the challenges of applying DS assumptions in visually obstructed habitats. By incorporating temporal truncation and ecological judgment, we refined these estimates to align with expected species behaviours and ecological plausibility, using the results to create a predictive model. The trait-based model, informed by species’ functional traits and environmental variables, provided a valuable validation method and was extended to assess density estimates for broader forest avifauna, including species of conservation concern. Comparisons between DS, FRC, and model-predicted densities revealed the limitations and strengths of each method, with recommendations for their application in diverse forest environments. This integrated approach offers a pathway to more reliable bird population estimates, essential for effective conservation management in South Africa’s threatened forest biomes. It further allows the estimation of population densities from non-DS surveys. Species density estimates ranged from < 1 to > 100 individuals/km2, with FRC and trait-based predictions generally producing more ecologically plausible values than uncorrected DS, particularly in complex forest habitats.

IntroductionMalaria transmission is highly spatially heterogeneous. Within Southeast Asia, forested landscapes are associated both with increased malaria transmission and reduced healthcare access. Identifying environments with malaria foci is a priority for control and elimination programmes.MethodsHere, we integrate health facility and environmental data to identify optimal surveillance approaches across a forested district in the Philippines. We conducted convenience surveys of health facility attendees utilising tablet-based applications to geolocate participant residences. Malaria infection was assessed using both routine (microscopy and rapid diagnostic test) and molecular methods. Integrating remote-sensing derived data, we assessed how fine-scale environmental factors influence the spatial distributions of malaria infections, diagnostic sensitivity and health-seeking behavior. We evaluated costs and probability of detecting malaria foci for multiple surveillance approaches using different diagnostic methods and target populations defined by landscape data.ResultsWe demonstrate that health facility-based surveys increase the probability of detecting malaria infections by increasing numbers of individuals screened and spatial coverage of surveillance systems. We additionally show sensitivity of routine malaria diagnostics varies spatially, with the decreased sensitivity in forests. By targeting diagnostic methods to high-risk environments, we developed a model approach for how to use landscape data within disease surveillance systems. Risk-based surveillance incorporating forest data is highly cost-effective and increases the probability of detecting malaria foci over three-fold compared to routine surveillance.DiscussionTogether, this illustrates the essential role of environmental data in designing risk-based surveillance to provide an operationally feasible and cost-effective method to characterise malaria transmission.

e paper presents the results of a comparative analysis of the number of trees, stand volume and the position of the height curve within the height overdiameter curves, obtained through a partial survey of high beech forests on different shapes of sample plots: concentric circles used in Montenegro (CC CG), concentric circles used in Serbia (CC RS) and angle count sampling (WZP RS) applied in the Serbian forest inventory. Data processing was conducted in Osnova software and within a GIS environment. Height curves were modelled using the Näslund function, while spatial interpolation of results was performed using the Spline with Barriers method. Regarding the average number of trees and average volume, although the CC CG method produced the lowest values, it is difficult to determine which plot shape is superior. The reason lies in the differing elements of partial survey designs among the tested plot types (number, size, sampling intensity, number of detailed subplots, etc.). However, since the studied stand belongs to selection forests, which represent extremely heterogeneous structural forms, we consider that priority should be given to angle count sampling (WZP RS). This method is based on unequal probabilities of tree selection for measurement, specifically the likelihood of a tree being selected is proportional to its diameter which undoubtedly contributes to a more reliable determination of stand volume under the given conditions. Furthermore, we consider that the method of selecting trees for height measurement in the forest inventory of Montenegro does not ensure a representative sample for accurate modelling of the height curve. As a result, poorer height classes are determined, leading to lower stand volume values. Spatial visualization through raster analysis facilitates planning and decision-making in forest management planning, as it provides a more realistic insight into internal stand variations that are often overlooked in conventional tabular presentations. In this context, GIS software and raster analyses represent efficient tools for the assessment, comparison and visualization of field data results, enabling better decision-making and improvement of forest resource management.