Search Results (422)

In forests dominated by deciduous tree species, coniferous species are often disproportionately important because of their contrasting functional traits. Eastern white pine (Pinus strobus L.), once a widespread emergent canopy species, co-occurs with deciduous hardwoods in the northern Lake States, but is often uncommon in contemporary hardwood stands. To gain insights into the potential utility of hardwood management strategies for simultaneously regenerating white pine, we leveraged a northern hardwood silvicultural experiment with scattered overstory pine. Seven growing seasons post-harvest, we conducted a complete census of white pine regeneration (height ≥ 30 cm) and mapped their locations and the locations of potential seed trees. Pine regeneration was sparse and strongly spatially aggregated, with most clusters falling within potential seed shadows of overstory pines. New recruits were found to have the highest density in a scarified portion of the study area leeward of potential seed trees. Low regeneration densities within treatment units, strong spatial aggregation, and the spatial arrangement of potential seed trees precluded generalizable inferences regarding the utility of specific treatment combinations. Nevertheless, our results underscore the critical importance of residual overstory pines as seed sources and highlight the challenges associated with realizing their potential in managed northern hardwoods. Full article

The structural analysis of shelterbelts forms the foundation of their planning and management, yet the scientific and effective quantification of shelterbelt structures requires further investigation. This study developed an innovative heterogeneous analytical framework, integrating three key methodologies: the LeWoS algorithm for wood–leaf separation, TreeQSM for structural reconstruction, and 3D alpha-shape spatial quantification, using terrestrial laser scanning (TLS) technology. This framework was applied to three typical farmland shelterbelts in the Ulan Buh Desert oasis, enabling the first precise quantitative characterization of structural components during the leaf-on stage. The results showed the following to be true: (1) The combined three-algorithm method achieved ≥90.774% relative accuracy in extracting structural parameters for all measured traits except leaf surface area. (2) Branch length, diameter, surface area, and volume decreased progressively from first- to fourth-order branches, while branch angles increased with ascending branch order. (3) The trunk, branch, and leaf components exhibited distinct vertical stratification. Trunk volume and surface area decreased linearly with height, while branch and leaf volumes and surface areas followed an inverted U-shaped distribution. (4) Horizontally, both surface area density (Scd) and volume density (Vcd) in each cube unit exhibited pronounced edge effects. Specifically, the Scd and Vcd were greatest between 0.33 and 0.60 times the shelterbelt’s height (H, i.e., mid-canopy). In contrast, the optical porosity (Op) was at a minimum of 0.43 H to 0.67 H, while the volumetric porosity (Vp) was at a minimum at 0.25 H to 0.50 H. (5) The proposed volumetric stratified porosity (Vsp) metric provides a scientific basis for regional farmland shelterbelt management strategies. This three-dimensional structural analytical framework enables precision silviculture, with particular relevance to strengthening ecological barrier efficacy in arid regions. Full article

The rubber plantations in Sankuru province, located in the Democratic Republic of Congo (DRC), have historically been pivotal to the regional economy. However, the absence of suitable silvicultural practices has promoted self-regeneration, resulting in the proliferation of diverse species. This study aims to characterize species richness and plant structure of these plantations. To this end, 80 subplots measuring 0.25 hectares were meticulously established, with a proportionate division between state-owned and farmer plantations. The results obtained from this study indicate that these plantations are home to approximately 105 species, classified into 33 distinct botanical families, with dominant families such as Fabaceae, Meliaceae, Euphorbiaceae, Olacaceae, Clusiaceae, and Moraceae. Despite the similarity between the two types of plantations (Cs = 58%), significant disparities were observed in terms of individuals, 635 ± 84.06 and 828 ± 144.62 (p < 10⁻³); species, 41 ± 7.49 and 28 ± 4.59 (p < 10⁻³); families, 19 ± 3.06 and 16 ± 1.62 (p < 10⁻²); and basal area, 29.88 ± 5.8 and 41.37 ± 7.57 (p < 10⁻²) for state and peasant plantations, respectively. State plantations exhibited greater diversity (H′ = 1.87) and enhanced equity (J’ = 0.43) than peasant plantations. The diametric structure exhibited an inverted J-shaped distribution, indicating constant and regular regeneration of these plantations. The upper canopy dominates the vertical structure in both types of plantations, with a significantly higher proportion in peasant plantations (83.60%) than in state plantations (73.8%), ANOVA (F (2.24 = 21.78), df = 24; p = 4.03 × 10⁻⁶). The findings indicate that the sustainable management of these plantations could incorporate agroecological principles to promote the coexistence of rubber production and biodiversity conservation while contributing to the restoration of degraded ecosystems and the well-being of local communities. Full article

Ungulate browsing represents a contemporary issue for forest development, influencing forest regeneration, composition, and management practices across the world, especially in North America. This review synthesizes findings from 101 studies conducted between 1980 and 2025 to examine patterns of herbivory damage through browsing by moose, elk, white-tailed deer, black-tailed deer, and bison. Despite regional variation, high ungulate density consistently emerges as the primary factor driving browsing intensity and ecological and economic impact, leading to decreased social acceptance of coexistence with ungulates. This review highlights the selective suppression of palatable species such as balsam fir, red oak, and white cedar, leading to shifts toward less-preferred conifers. Preventive and control measures, ranging from fencing and repellents to regulated hunting, are widely implemented but vary in effectiveness and social acceptability. Although predator presence is an evident controlling factor, it was not statistically associated in this review with reduced browsing, nor with behavioral or trophic cascade effects. Ultimately, this study underscores the importance of integrated management strategies that combine silvicultural adaptation, population control, and, where feasible, predator reintroduction to ensure forest resilience and sustainability in the face of increasing pressure from climate change. Full article

Oak–lime–hornbeam forests are among the most biodiverse temperate forests. This study compared older managed stands with a strictly protected old-growth forest in terms of their features. Managed forests at various stages of silvicultural operations were selected: a mature stand where regeneration cuts had not yet begun, as well as stands where such treatments were in the initial or advanced stages. Stand features that may affect the diversity and density of avifauna were analyzed on the basis of 151 sample plots. In four successive breeding seasons, birds in these stands were surveyed. The stands differed significantly in volume, the density of large trees, regeneration, the vertical structure, and the amount of deadwood. The number of bird species was the highest in the initial and advanced gap-cut stands. Group-selection cutting in those stands led to a succession of non-forest bird species and, hence, a greater number of birds building nests on or close to ground as compared to the old-growth forest. The old-growth forest was the most similar to the mature managed stand in terms of bird species composition (Jaccard index = 0.76). The old-growth forest was characterized by the highest bird density (91 pairs per 10 ha), with more than half of the breeding pairs being cavity nesters. In the managed forest, the bird density was from 63 to 72 pairs per 10 ha. Based on the present study, it can be concluded that effective conservation of bird assemblages is possible in managed forests, provided that certain concessions are made. Drawing on the characteristics of old-growth forests, several guidelines can be proposed for forest management. First and foremost, it is essential to maintain a mosaic forest structure. Secondly, it is necessary to retain an adequate number of large, old trees within the stand and to ensure a sufficient volume and diversity of deadwood. Additionally, it is absolutely critical to shift timber harvesting activities outside of the bird breeding season. Full article

Ash dieback (ADB) disease, caused by the devastating fungus Hymenoscyphus fraxineus Baral, Queloz & Hosoya, currently poses a significant threat to forest health by decreasing the ash population across the UK and Europe. In our study, we evaluated how environmental conditions, silvicultural management, and genetic factors influence the spread and severity of ash dieback. We combined these factors in a statistical model for susceptibility. Leaves were collected from twenty-two stands across a large semi-natural woodland in Southern England, encompassing a range of disease symptoms. We conducted gene expression assays of tolerance genes previously identified by Associative Transcriptomics and evaluated how stand structure, tree vigour, and individual tree characteristics affected the disease progression. Our results demonstrated that the severity of symptoms is significantly impacted by tree vitality, genetics, and tree size. We identified a diameter at breast height (DBH) group with the highest explained variation (42%) in the disease susceptibility model, with the tree vitality and genetic markers emerging as key determinants. Our findings highlight that lower susceptibility to ash dieback results from a combination of moderate to high genetic tolerance, good individual tree vitality, and appropriate stand management. Full article

Selection forestry sustains timber production and stand structural complexity via partial harvesting. However, regeneration initiated by harvesting may function as fuel ladders, providing pathways for fire to reach the forest canopy. We sought potential mitigation approaches by simulating stand growth and potential wildfire behavior over a century in stands dominated by coast redwood (Sequoia sempervirens (Lamb. ex. D. Don) Endl.) on California’s north coast. We used the fire and fuels extension to the forest vegetation simulator (FFE-FVS) to compare group selection (GS) to single-tree selection silviculture with either low-density (LD) or high-density (HD) retention on a 20-year harvest return interval. These three approaches were paired with six options involving vegetation management (i.e., hardwood control or pre-commercial thinning (PCT)) with and without fuels treatments (i.e., prescribed fire or pile burning), or no subsequent vegetation or fuel treatment applied after GS, HD, or LD silviculture. Fuel treatment involving prescribed fire reduced hazardous fuel loading but lowered stand density and hence productivity. Hardwood control followed by prescribed fire mitigated potential wildfire behavior and promoted dominance of merchantable conifers. PCT of small young trees regenerating after selection harvests, followed by piling and burning of these cut trees, sustained timber production while reducing potential wildfire behavior by approximately 40% relative to selection silviculture without vegetation/fuel management, which exhibited the worst potential wildfire behavior. Full article

Agriculture and silviculture offer interesting opportunities for food, energy, and construction sectors, but to transform such raw materials into valuable products, multiple engineering works must be carried out within R&D, innovation projects, and programs. The classical official decision to promote or supervise such projects involves many agents and criteria but rarely considers engineering quality, reusability, or other valuable and measurable attributes considered in ISO 25.000 or in value engineering guidelines. Missing them would increase technological, business, and programmatic risks, potentially wasting public money or credibility. Large projects are not free from these risks, and it is not a kind of madness to derive R&D and innovation funds to enable access to such valuable knowledge comprehensively, with models. In this context, communications and services, construction, and renewables play a crucial role in smart rural environments. Model-Based Systems Engineering (MBSE) and generative Artificial Intelligence (AI), combined with Natural Language Processing (NLP), are expected to help Knowledge Management (KM) in engineering and governance to supervise value engineering and their relationship with other metrics. Starting with a motivational and multidisciplinary framework for a smart rural transformation for System of Systems (SoS), the authors conduct specific bibliographic research on MBSE-NLP-AI use for automatizing systems engineering supervision at program governance levels. Full article

Boreal forests have historically been regarded as some of the largest terrestrial carbon (C) sinks. However, increased soil organic matter (SOM) decomposition due to forest harvesting and post-harvest silviculture (e.g., site preparation, planting, and managing for competing vegetation) may exacerbate the effects of climate warming and shift boreal forests from being C sinks to C sources. We used an established stand-scale, fully replicated, experimental study to identify how two levels of forest management (harvesting = Harvest Only, and harvesting with post-harvest silviculture = Harvest Plus) influence SOC dynamics at three boreal forest sites varying in soil texture. Each site was surveyed for forest floor (litter and F/H horizons) and mineral soils pre-harvest (0) and 5, 14, and 20 years post-harvest. We predicted that sites harvested and left to revegetate naturally would have the lowest SOC stocks after 20 years, as sites that were planted and managed for competing vegetation would recover faster and contribute to a larger nutrient pool, and that the sand-dominated site would have the largest SOC losses following harvest due to the inherently lower ability of sand soils to chemically and/or physically protect SOC from decomposition following harvest. Over a 20-year period, both forest management treatments generally resulted in reduced total (litter, F/H, and mineral horizon) SOC stocks compared with the control: the Harvest Only treatment reduced overall SOC stocks by 15% at the silt-dominated site and 31% at the clay-dominated site but increased overall SOC stocks by 4% at the sand-dominated site, whereas the Harvest Plus treatment reduced overall SOC stocks by 32% at the sand- and silt-dominated sites and 5% at the clay-dominated site. This suggests that harvesting and leaving plots to revegetate naturally on sand-dominated sites and harvesting followed by post-harvest silviculture on clay-dominated sites may minimize total SOC losses at similar sites, though a full replicated field experiment is needed to test this hypothesis. Most treatment effects in this study were observed only in the second decade post-harvest (14 and 20 years post-harvest), highlighting the importance of long-term field experiments on the effects of forest harvesting and post-harvest silviculture. This research improves our understanding of the relationship between C dynamics, forest management, and soil texture, which is integral for developing sustainable management strategies that optimize C sequestration and contribute to the resilience of boreal forest ecosystems in the face of climate change. Full article

The precise identification and classification of tree species in young forests during their early development stages are vital for forest management and silvicultural efforts that support their growth and renewal. However, achieving accurate geolocation and species classification through field-based surveys is often a labor-intensive and complicated task. Remote sensing technologies combined with machine learning techniques present an encouraging solution, offering a more efficient alternative to conventional field-based methods. This study aimed to detect and classify young forest tree species using remote sensing imagery and machine learning techniques. The study mainly involved two different objectives: first, tree species detection using the latest version of You Only Look Once (YOLOv12), and second, semantic segmentation (classification) using random forest, Categorical Boosting (CatBoost), and a Convolutional Neural Network (CNN). To the best of our knowledge, this marks the first exploration utilizing YOLOv12 for tree species identification, along with the study that integrates digital aerial photogrammetry with Planet imagery to achieve semantic segmentation in young forests. The study used two remote sensing datasets: RGB imagery from unmanned aerial vehicle (UAV) ortho photography and RGB-NIR from PlanetScope. For YOLOv12-based tree species detection, only RGB from ortho photography was used, while semantic segmentation was performed with three sets of data: (1) Ortho RGB (3 bands), (2) Ortho RGB + canopy height model (CHM) + Planet RGB-NIR (8 bands), and (3) ortho RGB + CHM + Planet RGB-NIR + 12 vegetation indices (20 bands). With three models applied to these datasets, nine machine learning models were trained and tested using 57 images (1024 × 1024 pixels) and their corresponding mask tiles. The YOLOv12 model achieved 79% overall accuracy, with Scots pine performing best (precision: 97%, recall: 92%, mAP50: 97%, mAP75: 80%) and Norway spruce showing slightly lower accuracy (precision: 94%, recall: 82%, mAP50: 90%, mAP75: 71%). For semantic segmentation, the CatBoost model with 20 bands outperformed other models, achieving 85% accuracy, 80% Kappa, and 81% MCC, with CHM, EVI, NIRPlanet, GreenPlanet, NDGI, GNDVI, and NDVI being the most influential variables. These results indicate that a simple boosting model like CatBoost can outperform more complex CNNs for semantic segmentation in young forests. Full article

This study focuses on the production of high-density solid biofuels and high-fixed-carbon biochar from two invasive acacia species harvested in a protected area in Northwestern Spain, thereby contributing to its silviculture management challenge. It is possible to transform the initial biomass into briquettes and pellets reaching high densified values above 1300 kg/m³ and 500 kg/m³, respectively. Using thermochemical conversion processes in a simple double chamber oven, a biochar was obtained with a fixed carbon of 66%. Several parameters were analyzed and compared between the original biomass and the resulting products. The results show that an added value could be achieved without applying a complex system to transform, starting from residual biomass from invasive species. Full article

The goal of this study was to develop a GIS-based Decision Support Model for selecting the best timber harvesting systems on steep terrain. The model combines multiple layers, each representing an important factor in mechanized logging. These layers are used to create a final map that functions as a spatially explicit Decision Support Model that helps decide which machines are best suited for different forest areas. A key idea of this study is to consider not only operational criteria (slope, ruggedness, wetness, and road accessibility), but also a fundamental silvicultural aspect, i.e., the assessment of tree growth classes to enable the integration of silvicultural deliberations into timber harvest planning. The data used for this model come from orthophoto image and a Digital Terrain Model (DTM). The operational factors were analyzed using GIS tools, while the silvicultural aspects were assessed using the deep learning algorithm DeepForest and tree growth equations (allometric functions). The model was tested by comparing its results with field data taken in a Norway Spruce stand in South Tyrol/Italy. The findings show that the model reliably evaluates operational factors. For silvicultural aspects, it tends to underestimate the number of small trees, but provides a good representation of tree size classes within a forest stand. The innovation of this method is that it relies on low-cost, open-source tools instead of expensive 3D scanning devices. Full article

Rapidly evolving surveying and monitoring methods are leading the transition toward more efficient, data-driven forest management practices. Recent research highlights the potential of advanced remote sensing platforms to support “smart” forestry, enabling precise, timely, and cost-effective assessments which inform multi-function management methods and specialized silvicultural practices for each forest type, composition, and structure. We created a digital replica of a marteloscope, which is a forestry tool to practice silvicultural simulations for technicians and students. The selected stand is an official marteloscope included in the Integrate+ Network project coordinated by the European Forest Institute (EFI). We established a framework for data collection and processing to achieve an accurate digital replica, using a mobile laser scanner (MLS) in a European beech (Fagus sylvatica L.) forest stand. We extracted the main structural forest parameters (diameter at breast height (DBH) and total height (TH)), using the 3DFin software and we graphically returned the obtained digital replica with the CloudCompare software. We compared the MLS-derived values of DBH (1087 trees) and TH (50 trees) with those from a traditional field survey and obtained a root mean square deviation (RMSD) of 2.38 cm for DBH and 2.42 m for TH. The digital marteloscope can help to visualize and assess the effects of selective thinning options on forest structure. The implementation of these virtual reality or augmented reality applications is a useful step toward smarter forestry and could be further improved. Full article

Bamboo forest ecosystems are an important component of the Earth’s terrestrial ecosystems and play an important role in addressing the global timber crisis as well as climate change. Bamboo is a typical shallow-rooted, fast-growing clonal plant species whose developed rhizome system and high canopy closure play an important role in soil and water conservation. The function of soil and water conservation services of bamboo forests can intuitively reflect the regional regulation of precipitation, the redistribution function of precipitation, and the function of soil fixation, which is one of the crucial ecological service functions in regional ecosystems. Bamboo forests are divided into monopodial bamboo forests, sympodial bamboo forests, and mixed bamboo forests, which are mainly distributed in tropical and subtropical mountainous areas. The region’s variable climate, abundant precipitation, and high potential risk of soil erosion, in conjunction with the frequent operation of bamboo forests and frequent occurrence of extreme weather events, have the potential to adversely affect the ecosystem function of bamboo forests. Presently, bamboo forests are primarily managed through the cultivation of bamboo, with the objective of enhancing productivity. Extensive research has been conducted on the long-term maintenance of bamboo forest productivity. However, there is a paucity of research on the mechanisms of management measures for ecosystem stability and the development of adaptive management technology systems suitable for soil and water conservation, carbon sequestration and sink enhancement, and biodiversity conservation. This paper is predicated on the biological characteristics of bamboo and, thus, aims to compile the extant research progress on the following subjects: the role of rainfall redistribution in bamboo forest canopies, the role of deadfall interception, and the mechanism of soil fixation mechanics of the root system. It also synthesizes the current status of research on the impact of traditional management measures on the soil and water conservation function of bamboo forests. Finally, it discusses the problems of current research and the direction of future development. Full article

In recent years, the cultivation techniques of large-diameter forests have garnered increasing attention due to their significant ecological and economic values. However, the effects of small-scale latitudinal changes on the species distribution and community composition of large-diameter trees remain poorly understood. This study aims to investigate the effects of narrow latitudinal gradients on the species composition and structure of large-diameter forests. Investigating these impacts provides critical insights for silvicultural species selection and forest structure optimization, particularly in the context of global warming, and is essential for the sustainable development of large-diameter forests. In this study, three forest communities along a small-scale latitudinal gradient in subtropical China were selected to study the community structure of large-diameter trees by analyzing species composition and species diversity. The community structure was also studied by analyzing species rank curves, the diameter structure, PCoA, MRPP, and indicator species. The results revealed that as latitude increased, the proportion of rare species rose from 43.8% in LL (low-latitude) to 63.2% in HL (high-latitude) areas, while the stem density of dominant species and the number of stems per species also increased. Additionally, species composition homogeneity decreased (based on PCoA and MRPP analysis), age-class structures became more complex, and the proportion of tropical genera gradually declined, whereas temperate genera increased. These findings indicate that small-scale latitudinal variation is a key driver of changes in the composition and structure of large-diameter forests. Currently, the northern Guangdong region is suitable for large-diameter forest development, with Fagaceae species (particularly Castanopsis and Lithocarpus) showing high potential. Specifically, Castanopsis eyrei, Castanopsis fissa, and Ternstroemia gymnanthera are well-suited for large-diameter stand cultivation in Guangdong. For mixed large-diameter forests, Machilus chinensis, Cinnamomum porrectum, and Schima superba are recommended as optimal associated species. However, as global warming progresses, the suitability of tree species for afforestation may shift, necessitating adaptive management strategies. Full article