Search Results (50)

In this work, we evaluated the silvicultural and ecological parameters of Populus bolleana Lauche trees growing in conditions of anthropogenic pollution, using the example of one of the largest megacities of the Donetsk ridge, the city of Donetsk. The objectives of this study included determining the level of anthropogenic load of the territory; conducting dendrological studies to assess morphometric and allometric parameters, age structure, and condition of P. bolleana stands under the influence of environmental factors; as well as completing biomechanical studies to assess and predict the mechanical stability of stands. A total of 1109 plants growing in areas with increased anthropogenic load and in the control areas were studied. The model territories of the study were located in the city of Donetsk on Fallen Communards Avenue (length of field routes: 2.6 km) and Ilyicha Avenue (length of field routes: 9.7 km). Control plantings grew on the territory of the Donetsk botanical garden and residential (dormitory) districts of the city. The age structure of P. bolleana plantations remained uniform throughout the city for 50–55 years due to the fact that the landscaping was under a single state program. In the steppe zone in the south of the East European Plain, with a high level of anthropogenic load and severe natural climatic factors, the critical age of P. bolleana (55 years) was determined. The condition of plantations and their morphometric indices correlate with the level of anthropogenic load of the city (H, Dbase, DBH). Under control conditions, the plants are in good condition with signs of weakening (2 points). Under conditions of increased anthropogenic load, the plants are in a severely weakened condition (3 points). A total of 25% of the plants in the sample are in critical condition (4–5 points). The main damages to the crowns and trunks of plants include core rot, mechanical damage to bark and tissues, the development of core rot through the affected skeletal branch, crown thinning, and drying. P. bolleana trees are valued for their crown area and ability to retain dust particles from the air. The analysis of experimentally obtained data on the crown area showed that in the initial phases of ontogenesis, the average deviation in the crown area of plants does not depend on the place of growth. Due to artificial narrowing and sanitary pruning of the crown, as well as skeletal branches dying along the busiest highways, the values do not exceed 22–23 m² on average, with an allometric coefficient of 0.35–0.37. When comparing this coefficient in the control areas, the crown area in areas with a high level of anthropogenic load is 36 ± 11% lower. For trees growing under the conditions of the anthropogenic load of an industrial city and having reached the critical age, mechanical resistance varied depending on the study area and load level. At sites with a high level of pollution of the territory, a significant decrease in indicators was revealed in comparison with the control (mcr—71%, EI—75%, RRB—43%). Having analyzed all the obtained data, we can conclude that, until the age of 50–55 years, P. bolleana retains good viability, mechanical resistance, and general allometric ratios, upon which the stability of the whole plant depends. Even with modern approaches and tendencies toward landscaping with exotic introductions, it is necessary to keep P. bolleana as the main species in dendrobanocenoses. Full article

The stem taper function is essential in predicting diameter outside bark (DOB) variations along the tree height, contributing to volume estimation, harvest planning, and precision forestry. Traditional taper models, such as the Kozak function, offer interpretability but often fail to capture nonlinear growth dynamics and regional variability, particularly in the upper stem segments. This study aimed to evaluate and compare the prediction accuracy of conventional and machine learning-based taper models using Pinus densiflora, a representative conifer species in Korea. Field data from two ecologically distinct regions (Gangwon and Central Korea) were used to build and test four models: the Kozak taper function, random forest, extreme gradient boosting, and an artificial neural network (ANN). Model performance was assessed using the RMSE, R², and MAE, along with stem profile visualizations for representative trees. The results showed that the ANN consistently achieved the highest prediction accuracy across both regions, particularly at an upper crown zone relative height (RH) > 0.8, while maintaining smooth and stable taper curves. In contrast, the Kozak model tended to underestimate the diameter of the upper stem. This study demonstrates that machine learning models, particularly ANNs, can effectively enhance the taper prediction precision and serve as practical tools for data-driven forest management and the implementation of precision forestry in Korea. Full article

Tree growth potential is crucial for maintaining forest health and sustainable development. Traditional expert-based assessments of growth potential are inherently subjective. To address this subjectivity and improve accuracy, this study proposed a method of using Backpropagation Neural network (BPNN) to classify tree growth potential. 60 Pinus tabulaeformis (Carr.) and 60 Platycladus orientalis (Linn.) were selected as experimental trees in the Miyun Reservoir Water Conservation Forest Demonstration Zone in Beijing, and 95 Pinus massoniana (Lamb.) and 60 Cunninghamia lanceolate (Linn.) were selected as experimental trees in the Jigongshan Nature Reserve. The average annual ring width of the outermost 2 cm xylem of the experimental trees were measured by discs or increment cores, and the wood volume increment of each experimental trees in recent years were calculated. According to wood volume increment, the growth potential of experimental trees was divided into three levels: strong, medium, and weak. Using tree height, breast height diameter, average crown width as input variables, using growth potential level as output variables, four sub models for each tree species were established; Using tree species, tree height, breast height diameter, average crown width as input variables, using growth potential level as output variables, a generalized model was established for these four tree species. The test results showed that the accuracy of the sub models for Pinus tabulaeformis, Platycladus orientalis, Pinus massoniana, and Cunninghamia lanceolate were 68.42%, 77.78%, 86.21%, and 78.95%, respectively, and the accuracy of the generalized model was 71.19%. These findings suggested that employing BPNN is a viable approach for accurately estimating tree growth potential. Full article

This study investigates the effect of the spatial distribution of soil water and nutrients on cork oak (Quercus suber) architecture. Fertirrigation is being tested in cork oak plantations to accelerate tree growth up to the production stage. To assess the impact of wet bulb location on tree development, six trees (three subjected to subsurface drip irrigation and three controls) were fully excavated at a sandy soil site, along with a seventh tree subjected to surface drip irrigation at a sandy loam soil site. The aerial parts of the trees were digitized using a Polhemus Fastrak magnetic digitizer and segmented into orders starting from the main trunk. Roots with diameters greater than 0.5 cm were digitized during excavation and segmented by size and order from the root collar. For each segment, length, orientation, and spatial location were calculated. General linear models were then applied to compare total root length across orientation and quadrant classes. Crown architecture was influenced by factors such as light competition. Irrigation treatments did not significantly affect root architecture when wet bulb formation was constrained. However, tree no. 7 had 50% of its total root length located within the wet bulb quadrant. These findings suggest that differences in soil type and irrigation method influence wet bulb formation, potentially reducing the impact of fertirrigation on root architecture. Strategies to minimize tree dependence on wet bulb zones are crucial for enabling future irrigation suppression. Full article

Azadirachta indica was designated the “Tree of the 21st century” by the United Nations, as it is believed to be the largest natural depository of bioactive phytochemicals. This study investigates genetic variability among 152 Candidate Plus Trees (CPTs) of A. indica selected from three agro-climatic zones (ACZs) in eastern India: the Lower Gangetic Plains (ACZ III), Middle Gangetic Plains (ACZ IV), and the Eastern Plateau and Hills region (ACZ VII). Phenotypic characters, fruit and seed morphology, kernel oil content (KOC), and Azadirachtin concentration (AC) were assessed to characterize the genetic diversity. Significant variation was observed across all parameters among individual CPTs. Girth at breast height ranged from 0.9 to 2.8 m, tree height from 6 to 16 m, and crown volume from 146.95 to 2339.86 m³. Fruit length varied from 13.55 to 21.55 mm and seed length from 9.21 to 17.37 mm. KOC ranged from 36.51 to 58.86%, with a mean of 47.22% (±0.4), while AC showed extreme variability (19.46–1823.45 μg/g seed). KOC exhibited strong positive correlations with crown diameter (R = 0.57, p ≤ 0.001) and crown volume (R = 0.45, p ≤ 0.001). Interestingly, AC did not correlate significantly with any studied parameter. Analysis of variance revealed significant differences (p < 0.05) between ACZs, but only for some traits. All of the parameters demonstrated high heritability and moderate to high genetic advance. Cluster analysis using Ward’s minimum variance criterion based on Euclidean square (D²) distances performed in RStudio grouped the CPTs into five clusters as per pooled effects of all parameters. The highest inter-cluster distance was observed between Clusters III and V (7.703), indicating a potential for heterosis in hybridization between these groups. Each cluster contained CPTs from all three ACZs, suggesting uniformly distributed variation across the study area rather than zone-specific patterns. This study provides valuable insights for improvement programs of the species and emphasizes the need for further research, including progeny trials, to comprehensively understand the genetic variability of A. indica in eastern India. Full article

In May 2008, Chaitén volcano entered an eruptive process, leading to one of the world’s largest eruptions in recent decades. The magnitude of tephra ejected by the eruption left different types of disturbances and caused diverse forms of environmental damage that were heterogeneously distributed across the surrounding area. We went to the field to assess the early vegetation responses a year after the eruption in September 2009. We evaluated the lateral-blast disturbance zone. We distributed a set of plots in three disturbed sites and one in an undisturbed site. In each of these sites, in a rectangular plot of 1000 m², we marked all standing trees, recording whether they were alive, resprouting, or dead. Additionally, in each site of 80 small plots (~4 m²), we tallied the regenerated plants, their coverage, and the log volume. We described whether the plant regeneration was occurring on a mineral or organic substrate (i.e., ash or leaf litter, respectively). In the blast zone, the eruption created a gradient of disturbance. Close to the crater, we found high levels of devastation marked by no surviving species, scarcely standing-dead trees and logs, and no tree regeneration. At the other extreme end of the disturbance zone, the trees with damaged crowns were resprouting, small plants were regrowing, and seedlings were more dispersed. The main form of regeneration was the resprouting of trunks or buried roots; additionally, a few seedlings were observed in the small plots and elsewhere in disturbed areas. The results suggest that the early stages of succession are shaped by life history traits like dispersion syndrome and regeneration strategy (i.e., vegetative), as was found after other volcanic eruptions. Likewise, the distribution of biological legacies, which is related to disturbance intensity, can cause certain species traits to thrive. For instance, in the blow-down zone, surviving species were chiefly those dispersed by the wind, while in the standing-dead zone, survivors were those dispersed by frugivorous birds. Additionally, we suggest that disturbance intensity variations are related to the elevation gradient. The varying intensities of disturbance further contribute to these ecological dynamics. The early succession in the blast zone of Chaitén volcano is influenced by the interaction between species-specific life history, altitudinal gradient, and biological legacies. Further studies are required to observe the current successional patterns that occur directly in the blast zone and compare these results with those obtained following other volcanic disturbances. Full article

Sustainable forestry for the management of forest resources is more important today than ever before because keeping forests healthy has an impact on human health. Recent advances in Unmanned Aerial Vehicles (UAVs), computer vision, and Deep Learning (DL) models make remote sensing for Forest Insect Pest and Disease (FIPD) possible. In this work, a UAV-based remote sensing process, computer vision, and a Deep Learning framework are used to automatically and efficiently detect and map areas damaged by bark beetles in a Mexican forest located in the Hidalgo State. First, the image dataset of the region of interest (ROI) is acquired by a UAV open hardware platform. To determine healthy trees, we use the tree crown detection prebuilt Deepforest model, and the trees diseased by pests are recognized using YOLOv5. To map the area of the damaged region, we propose a method based on morphological image operations. The system generates a comprehensive report detailing the location of affected zones, the total area of the damaged regions, GPS co-ordinates, and both healthy and damaged tree locations. The overall accuracy rates were 88% and 90%, respectively. The results obtained from a total area of 8.2743 ha revealed that 16.8% of the surface was affected and, of the 455 trees evaluated, 34.95% were damaged. These findings provide evidence of a fast and reliable tool for the early evaluation of bark beetle impact, which could be expanded to other tree and insect species. Full article

Mapping the distribution of living and dead trees in forests, particularly in ecologically fragile areas where forests serve as crucial ecological environments, is essential for assessing forest health, carbon storage capacity, and biodiversity. Convolutional neural networks, including Mask R-CNN, can assist in rapid and accurate forest monitoring. In this study, Mask R-CNN was employed to detect the crowns of Casuarina equisetifolia and to distinguish between live and dead trees in the Pingtan Comprehensive Pilot Zone, Fujian, China. High-resolution images of five plots were obtained using a multispectral Unmanned Aerial Vehicle. Six band combinations and derivatives, RGB, RGB-digital surface model (DSM), Multispectral, Multispectral-DSM, Vegetation Index, and Vegetation-Index-DSM, were used for tree crown detection and classification of live and dead trees. Five-fold cross-validation was employed to divide the manually annotated dataset of 21,800 live trees and 7157 dead trees into training and validation sets, which were used for training and validating the Mask R-CNN models. The results demonstrate that the RGB band combination achieved the most effective detection performance for live trees (average F1 score = 74.75%, IoU = 70.85%). The RGB–DSM combination exhibited the highest accuracy for dead trees (average F1 score = 71.16%, IoU = 68.28%). The detection performance for dead trees was lower than for live trees, which may be due to the similar spectral features across the images and the similarity of dead trees to the background, resulting in false identification. For the simultaneous detection of living and dead trees, the RGB combination produced the most promising results (average F1 score = 74.18%, IoU = 69.8%). It demonstrates that the Mask R-CNN model can achieve promising results for the detection of live and dead trees. Our study could provide forest managers with detailed information on the forest condition, which has the potential to improve forest management. Full article

The circumpolar Taiga–Tundra Ecotone significantly influences the feedback mechanism of global climate change. Achieving large-scale individual tree crown (ITC) extraction in the transition zone is crucial for estimating vegetation biomass in the transition zone and studying plants’ response to climate change. This study employed aerial images and airborne LiDAR data covering several typical transitional zone regions in northern Finland to explore the ITC delineation method based on deep learning. First, this study developed an improved multi-scale ITC delineation method to enable the semi-automatic assembly of the ITC sample collection. This approach led to the creation of an individual tree dataset containing over 20,000 trees in the transitional zone. Then, this study explored the ITC delineation method using the Mask R-CNN model. The accuracies of the Mask R-CNN model were compared with two traditional ITC delineation methods: the improved multi-scale ITC delineation method and the local maxima clustering method based on point cloud distribution. For trees with a height greater than 1.3 m, the Mask R-CNN model achieved an overall recall rate ($A_r$) of 96.60%. Compared to the two conventional ITC delineation methods, the $A_r$ of Mask R-CNN showed an increase of 1.99 and 5.52 points in percentage, respectively, indicating that the Mask R-CNN model can significantly improve the accuracy of ITC delineation. These results highlight the potential of Mask R-CNN in extracting low trees with relatively small crowns in transitional zones using high-resolution aerial imagery and low-density airborne point cloud data for the first time. Full article

Epiphytes represent a key component in tropical forests. They are affected by anthropogenic and natural disturbances suffered by forests, since they depend on their hosts and the microclimatic conditions they generate. We analyzed differences in abundance, species richness, and vertical distributions of epiphytic bromeliads in primary and disturbed forests. We found a higher abundance (5316 individuals) and species richness (8 species) of bromeliads in disturbed forest than in primary forest (1360 individuals and 4 species, respectively). Most bromeliads (97%) were found on Taxodium mucronatum, a dominant tree with rough bark in the disturbed forest (gallery forest). Bromeliads were more abundant in the middle of the tree and diminished towards the trunk base and the upper crown. Tillandsia baileyi was the most abundant bromeliad, and the size categories of this species differentially colonize trees in gallery forest according to Johansson zones; seedlings of T. baileyi abundantly colonize the upper canopy, and juveniles colonize the middle canopy or secondary branches. Gallery forest represents an important reservoir for epiphytic bromeliads. Hence, it is important to extend this kind of study to wetland sites to understand the role they play as a habitat for epiphytes, as well as the dynamics and ecological processes that occur in such habitats. Full article

Sweet cherry grown under sustainable management produces highly valuable fruits, whose quality shows important biochemical and morphological changes during ripening. Research was carried out in Iasi (Romania), with the aim to assess the quality characteristics of the sweet cherry fruits of three cultivars (Van, Andreiaș, Margonia), grown in an inner or outer position inside the tree crown, at the pre-ripening or full ripeness phase. In 2022, the colour component a* showed higher values in cv. Van and Andreias red fruits and in an inner position, whereas the components L* and b* at the full ripeness phase were highest in cv. Margonia. The dry matter and total soluble solids contents increased from the pre-ripening to the full ripeness phase and were highest in cv. Van sweet cherry fruits; the DM of fruit from the outer part of crown was higher than that of fruit from the inner part at the pre-ripening phase. The content of phenolics was the highest in cv. Margonia fruits at the pre-ripening stage and in cv. Van at the full ripeness phase and higher in the inner tree crown zones. The cultivar Margonia generally showed the highest vitamin C content in both years and development phases. The yellow fruit cv. Margonia mostly showed the highest values of chlorophyll a and b. The fruit’s content of carotene, lycopene, and anthocyanins was generally the highest in the red fruits of cv. Andreias. The examined sweet cherry cultivars showed a high variability in fruit nutritional quality and proved to be a rich source of bioactive compounds with antioxidant potential. Full article

The Hotan River, the sole river traversing the Taklimakan Desert in northwest China, sustains a critical desert riparian ecosystem dominated by Populus euphratica. This riparian habitat is integral to biodiversity maintenance. However, global climate change and anthropogenic disturbances have profoundly impacted the Taklimakan desert landscape, leading to fragmentation and reduced environmental heterogeneity. Consequently, there has been a notable decline in P. euphratica populations. This study aimed to assess the physiological resilience of P. euphratica under harsh conditions and analyze the vegetation distribution patterns along the desert riparian zone. Laboratory tests were employed to determine the physiological indexes including Relative Water Content (RWC), Chlorophyll (Chl), Soluble Sugar (SS), Free Proline (Pro), and Peroxidase Activity (POD) of P. euphratica, providing insights into its capacity to endure challenging environmental conditions. Quadrat surveys were conducted at varying distances from the riverbed to examine vegetation distribution patterns. Plant growth indexes were analyzed to unveil the resistance of the desert riparian forest to drought. The study identified 45 shrubs and herbs belonging to 17 families in the Hotan River understory, with P. euphratica exhibiting the highest abundance. In river flats, annual herbs dominated due to favorable water conditions, while shrub grasslands displayed a relatively complete community structure with trees, crowns, and grasses. As the distance increased from the river channel, more perennial herb and shrub species prevailed, leading to a decline in overall species richness as annual herbs diminished. Physiological assessments revealed that P. euphratica in a medium growth grade (VS3) exhibited the highest physiological indexes, indicating its adaptability to environmental changes. The findings underscore the significance of water conditions in the growth and development of vegetation in desert riparian forests, particularly highlighted by the physiological indexes of P. euphratica. This research contributes valuable insights that can inform the preservation and restoration of desert riparian forests, providing a scientific basis and technical guidance for conservation efforts. Full article

Silver birch (Betula pendula Roth) is one of the fast-growing tree species that often colonize abandoned agricultural lands in Europe and the European part of Russia. The purpose of this article is to analyze the spatiotemporal dynamics of Betula pendula crown cover on abandoned arable lands in a zone of broad-leaved forests of the Bashkir Cis-Ural (Russia, Republic of Bashkortostan). The assessment of current and retrospective values of crown cover was carried out using a regression model of the dependence of crown cover on the values of red channel brightness in early-spring images from Landsat 5–8 and Sentinel-2 satellites from 2012–2022. To estimate the number and height of trees, a survey was carried out using a LiDAR camera mounted on a UAV. After calculating the crown cover in grid squares and their distance from the seed source in QGIS, variance analysis was carried out to assess the influence of the factor of distance from the seed source on the crown cover. The influence of the factor of distance from the seed source on the crown cover was higher at earlier stages of overgrowth of abandoned agricultural lands. An exception to this dependence was only one sample plot where the prevailing wind direction was opposite to the direction of seed dispersal. The leading factors affecting the distribution of birch on abandoned agricultural lands were wind direction, height of seed trees, and grazing. In the parts of the sample plots that were furthest away from seed sources, the trees were 1–3 years younger or the same age, and stand density was lower than in sites located closer to the seed trees. In general, the results of the present study indicate two opposite relationships between seedling survival and distance to seed trees: (1) seed fall and seedling density decrease with increasing distance from the seed tree, and (2) the probability of seed/seedling survival increases due to decreased competition. Full article

In this study, carbon and nitrogen contents in the undisturbed terrestrial ecosystems in the northern taiga zone of Russia’s Murmansk region were estimated. The goal of this study was to examine the carbon and nitrogen dynamics in atmospheric precipitation, assimilating organs of coniferous trees (Picea obovata and Pinus sylvestris), needle litter, soils, and soil water. The objects of our research were the most common dwarf shrub-green moss spruce forests and lichen-dwarf shrub pine forests of the boreal zone. The study was carried out on permanent plots between 1999 and 2020. The long-term dynamics of carbon concentrations in snow demonstrated a trend towards increasing carbon concentrations in forested and treeless areas of the Murmansk region. It was shown that in representative spruce and pine forests, the concentrations and atmospheric precipitation of carbon compounds and carbon leaching with soil water were higher below the tree crowns, compared to between the crowns. In soil water, a decrease was found in carbon concentration with the soil profile depth. For soils, the highest carbon concentrations were found in the organic and illuvial soil horizons. The main soil sinks of carbon and nitrogen in northern taiga forests were found to be located in the organic soil horizon below the crowns. In northern taiga forests, the carbon content of living Picea obovata and Pinus sylvestris needles and Pinus sylvestris needle litter had minor variability; no significant interbiogeocoenotic and age differences were found. We found that the nitrogen content in brown needles and needle litter was significantly lower compared to photosynthetically active needles, probably due to retranslocation processes (withdrawal before needle abscission), corroborating the literature in the results session. The largest stocks of carbon and nitrogen in northern taiga forests are concentrated in the soil organic horizon, and the removal of these elements with soil water is insignificant. Carbon and nitrogen stocks in living and fallen needles are lower than in soil. The least amount of carbon and nitrogen is contained in atmospheric precipitation. Full article

As an integral part of urban forests, urban parks play a vital role in mitigating urban heat islands (UHI) and providing residents with comfortable outdoor recreational plots. For high-quality use of the trees in regulating the thermal comfort of urban parks, previous studies primarily focused on the microclimate variations caused by tree coverage and morphological features separately. However, there is still a lack of systematic understanding of how tree canopy coverage (TCC) and its morphological elements, including leaf area index (LAI), trunk height (TH), and crown diameter (CD), combined affect the thermal comfort in the urban park. This study employed an orthogonal experiment design and ENVI-met software to simulate the microclimate of various multi-factor combination models in the case of a typical urban park in a temperate continental climate zone in China, analyzing the simulated result through physiological equivalent temperature (PET). Results show that the contribution ratio of various elements to the thermal environment vary over time. In studied elements, the contribution ratio of TCC to PET is consistently higher than 50% during the morning, midday, and evening periods, reaching a peak of 67% in the evening. The maximum contribution ratios for CD, TH, and LAI occur during midday, morning, and midday, respectively, with corresponding contribution ratios of approximately 22%, 10%, and 9%, respectively. The ranking of elements affecting thermal comfort in the urban park generally is TCC, CD, LAI, TH throughout the day, apart from the morning, when the influence of TH is greater than LAI. The optimal combination of elements is 85% TCC, 4m TH, 3.9 LAI, and 7m CD, and thirteen combinations of element cases meet the thermal comfort requirements during summer. The research findings highlight the significance of optimizing the configuration of trees in creating a more comfortable and inviting space for human activities. Full article