Search Results (4,588)

Anthropogenic disturbances interact with wildfire, altering successional dynamics across North America’s boreal forest. Linear disturbances, including seismic lines used for oil and gas exploration, dissect forests, while wildfire is a fundamental agent of forest succession. However, little is known about early succession dynamics after both seismic line creation and wildfire, especially across transitions from uplands to peatlands. To address this, we characterized and compared regeneration and recruitment after individual and successive disturbances in peatland, transitional, and mesic upland forests across the oil sands region of Alberta, Canada. We used non-metric multidimensional scaling to compare composition and mixed-effects generalized linear models to compare densities of trees and tall shrubs 10 to 24 years after disturbance. Compositionally, regeneration was similar within forest types and between transitional and peatland forests, while patterns in recruitment were more influenced by past disturbances. Overall, we found evidence of dominant, additive, and interactive effects on early successional patterns within linear disturbances in boreal forests. In transitional and peatland forests, disturbances influenced tree and tall shrub regeneration and recruitment in complex ways. Early successional dynamics after disturbance influence forest structure and composition and are vital to understanding recovery in boreal forests, especially across boreal forest transitions. Full article

Accurate classification of individual tree types is a key component in forest inventory, biodiversity monitoring, and ecological modeling. This study evaluates and compares multiple Machine Learning (ML) and Deep Learning (DL) approaches for tree type classification based on Airborne Laser Scanning (ALS) data. A mixed-species forest in southeastern Austria, Europe, served as the test site, with spruce, pine, and a grouped class of broadleaf species as target categories. To examine the impact of data representation, ALS point clouds were transformed into four distinct structures: 1D feature vectors, 2D raster profiles, 3D voxel grids, and unstructured 3D point clouds. A comprehensive dataset, combining field measurements and manually annotated aerial data, was used to train and validate 45 ML and DL models. Results show that DL models based on 3D point clouds achieved the highest overall accuracy (up to 88.1%), followed by multi-view 2D raster and voxel-based methods. Traditional ML models performed well on 1D data but struggled with high-dimensional inputs. Spruce trees were classified most reliably, while confusion between pine and broadleaf species remained challenging across methods. The study highlights the importance of selecting suitable data structures and model types for operational tree classification and outlines potential directions for improving accuracy through multimodal and temporal data fusion. Full article

In order to precisely improve the quality of major tree species in northern China, near-natural differentiated management has been gradually introduced into forestry practice, aiming to optimize forest structure, enhance forest quality, and promote nutrient cycling and water conservation. As an essential element of forest ecosystems, soil microbes contribute to biodiversity preservation and nutrient turnover in soils. This study selected three typical forest types (Quercus acutissima forest, Pinus tabulaeformis forest, and Pinus tabulaeformis × Quercus mixed forest) that have been managed with target trees on Zhongtiao Mountain. Using 16S/ITS rRNA high-throughput sequencing, this study systematically assessed the influences of forest type and soil depth (0–60 cm) on the soil properties and microbial communities. The results showed that the fungal alpha diversity indices were the highest in Pinus tabulaeformis forest, which decreased with soil depth. Actinobacteriota exhibited the greatest relative abundance in mixed forest, whereas Ascomycota predominated in the Pinus tabulaeformis forest. The microbial co-occurrence network exhibited greater complexity compared to the pure forest. Microbial carbon and nitrogen cycling functions showed strong correlation with soil pH and nutrient levels. Symbiotrophs dominated the fungal community, and ectomycorrhizae were significantly abundant in mixed forests. pH is the dominant factor driving changes in microbial communities. In summary, the mixed forest improved soil nutrients, enhanced the complexity of microbial networks, and supported higher ectomycorrhizal abundance. These findings provide practical guidance for improving soil health and stability of forest ecosystems through near-natural management. Full article

This study investigates the deterioration of skid resistance and surface macrotexture following preventive maintenance using micro-milling techniques. Field data were collected from 31 asphalt pavement sections located across four climatic zones in Texas. The data encompasses a variety of surface types, milling depths, operational speeds, and drum configurations. A standardized data collection protocol was followed, with measurements taken before milling, immediately after treatment, and at 3, 6, 12, and 18 months post-treatment. Skid number and Mean Profile Depth (MPD) were used to evaluate surface friction and texture characteristics. The dataset was reformatted into a time-series structure with 930 observations, including contextual variables such as climatic zone, treatment parameters, and baseline surface condition. A comparative modeling framework was applied to predict the deterioration trends of both skid resistance and macrotexture over time. Eight regression models, including linear, tree-based, and ensemble methods, were evaluated alongside a time series Transformer model. The results show that the Transformer model achieved the highest prediction accuracy for skid resistance (R² = 0.981), while Random Forest performed best for macrotexture prediction (R² = 0.838). The findings indicate that the degradation of surface characteristics after preventive maintenance is non-linear and influenced by a combination of environmental and operational factors. This study demonstrates the effectiveness of data-driven modeling in supporting transportation agencies with pavement performance forecasting and maintenance planning. Full article

Human activities are increasing the occurrence of megafires that alter ecological dynamics in forest ecosystems. The objective of this study was to understand the impacts of a 610 km² megafire on patterns of tree regeneration and herbivory across three forest types (aspen/fir, oak/maple, and pinyon/juniper). Seventeen transect pairs in adjacent burned/unburned forest stands (6 aspen/fir, 5 oak/maple, and 6 pinyon/juniper) were measured. Sapling density, meristem removal, and height were measured across the transect network over a three-year period from 2019 to 2021. Tree species able to resprout from surviving roots (oak and aspen) generally responded positively to fire while species that typically regenerate by seeding showed little post-fire regeneration. Browse pressure was concentrated on deciduous tree species and was greater in burned areas but the effect diminished over the three-year study period. Meristem removal by herbivores was below the critical threshold, resulting in vertical growth over time. Our results indicate that forest regeneration within the megafire scar was generally positive and experienced sustainable levels of ungulate browsing that were likely to result in forest recruitment success. Full article

The widespread availability and spatial coverage of land surface temperature (LST) estimates from space often result in LST being used as a proxy for near-surface air temperature in order to characterize the urban heat island (UHI) effect. High-spatial-resolution satellite-based LST estimates from sensors such as Landsat-8 provide the spatial and thematic details necessary to understand the potential effects of urban greening measures to mitigate the increased frequency and intensity of heatwaves that are projected to occur as a result of human-induced climate change. Here, we investigate the influence of land cover on Surface Urban Heat Island (SUHI) observations of LST using a technique to reduce the spatial spread of the per-pixel temperature observation. Additionally, using land cover-based linear mixture models, we downscale the surface temperature to a 2 m spatial resolution. We find a mean difference in LST, compared to the city average, of +8.94 °C (+/−1.87 °C at 95% CI) for built-up cover type, compared to a difference of −7.42 °C (+/−0.8 °C) for broadleaf trees. This highlights the potential benefits of creating urban green spaces for mitigating the UHI amplification of extreme heatwaves. Furthermore, we highlight the need for improved observations of night-time temperatures, e.g., from forthcoming missions such as TRISHNA, in order to fully capture the diurnal variability of land surface temperature and energy fluxes. Full article

Under cool and moist climates, timely implementation of ditch network maintenance (DNM) is crucial for sustaining productivity of drained forests, thus reducing operational costs, while mitigating environmental risks. This underscores the need to understand tree growth responses to DNM. This study evaluated the effects of DNM on tree radial increment in sites with both organic and mineral drained soils, focusing on regionally commercially important species: Scots pine (Pinus sylvestris), Norway spruce (Picea abies), and silver birch (Betula pendula). Responses of relative growth changes over eight years post-DNM to site and tree characteristics were assessed using a linear mixed-effects model. Species- and site-specific growth responses to DNM were indicated by significant interactions between tree species, site type, and distance from the drainage ditch. While growth responses were generally neutral (non-significant), variability among sites and species suggests that both organic and mineral soils might be prone to site-level moisture depletion near drainage infrastructure in the post-DNM period. The effect of stand age and density suggested higher responsiveness of older and less dense stands, hence positive effects of thinning to resilience of stands to DNM. These findings highlight the importance of adapting DNM strategies to local site conditions and stand characteristics to minimize drought-related growth limitations. Full article

This study focused on the response mechanism of plants in karst ecosystems under rock stress, and explored the influence of aboveground rocks on the root phenotype and leaf water potential of plants. By quantifying the root characteristics of a total of 9 plant species in 3 types of vegetation areas, this study found: (1) The root biomass of grassland plants (Heteropogon contortus, Bidens pilosa, and Imperata cylindrical) in the near-rock area was on average 17.2% higher than that in the far-rock area. The lateral extension of roots was 27.8% lower, the vertical extension was on average 16.9% higher, and the total root bifurcation ratio (Rb) was on average 11.5% higher, respectively, compared to the far-rock area. (2) The root biomass of shrubland plants (Rubus mesogaeus, Spiraea martini, and Pyracantha fortuneana) in the near-rock area was on average 14.5% higher than the far-rock area. The average lateral extension of the root system was on average 17.5% lower, while there was no significant difference in the vertical extension. The Rb was on average 10.5% higher. (3) The root characteristics of forestland trees (Pistacia weinmanniifolia, Pinus yunnensis, and Carpinus turczaninowii) were significantly different from those of grassland and shrubland (p < 0.001), but the differences between the near-rock area and the far-rock area were not significant. The predawn and midday leaf water potential data showed that the plants in near-rock area of the grassland were 0.07 ± 0.03 (mean ± SD) MPa and 0.16 ± 0.07 MPa higher than those in the far-rock area, respectively, and the shrubland area was 0.12 ± 0.06 MPa and 0.20 ± 0.08 MPa higher, while there was no significant difference in the forestland. This study confirmed that aboveground rocks significantly enhanced the leaf water status of plants in arid environments by influencing root biomass, extension, and bifurcation ratio. This discovery provides a new perspective for understanding the survival mechanism of plants in karst areas. Full article

The Pinus yunnanensis forest of southwestern China represents a unique and ecologically critical vegetation type, historically shaped by fire disturbances. To mitigate catastrophic wildfire risks, prescribed burning has been widely implemented as a management tool in these ecosystems. However, its effects on plant community structure and biodiversity remain insufficiently quantified. To investigate the specific changes in plant community characteristics caused by prescribed burning, this study was conducted in the Pinus yunnanensis forest in Zhaobi Hill, Xinping county. Our results revealed that prescribed burning induced differential effects on understory communities while exerting negligible effects on canopy tree composition. In the shrub layer, the number of shrub species decreased from 26 to 20, accompanied by a complete extirpation of arboreal saplings. Dominance hierarchies shifted markedly, transitioning from Lithocarpus mairei and Pinus yunnanensis regeneration cohorts in unburned plots to fire-adapted species Duhaldea cappa and Craibiodendron stellatum. Concomitantly, the average height of shrubs had a significant reduction in burning plots. Contrastingly, the number of herb species increased from 30 to 37 in burning plots, with non-significant alterations in abundance, height, and importance values. Prescribed burning significantly decreases the α species diversity of shrubs, but only has minimal effects on the α species diversity indices of herbs. Overall, prescribed burning appears to be the primary factor affecting the species diversity index of shrubs, while altitude, forest structure, and soil nutrient content exert greater influences on the species diversity index of the herbaceous layer. Prescribed burning was the dominant factor shaping the community structure and species diversity of the shrub layer, and the missing saplings of trees in the shrub layer might influence future forest succession in the long term. Full article

Tomicus yunnanensis, a notorious forest pest in southwest China, primarily employs infochemicals to coordinate mass attacks that overcome host tree defenses. However, secondary visual cues, particularly detection of host color changes, also aid host location. This study characterized the compound eye structure and vision of T. yunnanensis using electron microscopy and phototaxis tests. The apposition eye contains 224–266 ommatidia, with asymmetry between left and right. Quadrilateral facets occupy the dorsal third, while hexagonal facets dominate elsewhere. Each ommatidium comprises a large corneal lens, an acone-type crystalline cone from four cone cells, and an open-type rhabdom formed by eight retinular cells (R7–R8 centrally, R1–R6 peripherally), surrounded by two primary and at least seventeen secondary pigment cells. Dark/light adaptation alters cone size/shape and rhabdom cross-sectional area/outline (without pigment granule movement) to regulate light reaching the photoreceptors. Behavioral observations showed peak flight activity occurs between 7:00–11:00 AM, with no nighttime activity. Phototaxis tests revealed females are highly sensitive to 360 nm, 380 nm, and 700 nm wavelengths, while males exhibit high sensitivity to 360 nm and 400 nm. This work enhances knowledge on the integration of visual and olfactory sensory information in beetles for host location and non-host avoidance. Full article

A strictly anaerobic bacterium denoted as strain NIT-TF6 of the genus Desulfitobacterium was isolated from a trichloroethene-dechlorinating culture with formate. Cells were straight rods of 1.6–6 µm long and 0.25–0.5 µm in diameter and used H₂, lactate, pyruvate, and malate as electron donors and thiosulfate and Fe (III)-citrate as electron acceptors. The genome of strain NIT-TF6 was 4.8 Mbp in size and included nine 16S rRNA genes. Phylogenetic analysis based on 16S rRNA sequences showed that NIT-TF6 shared the highest sequence similarity (96.39%) with Desulfitobacterium hafniense DCB-2ᵀ, forming an independent clade in the phylogenetic tree. Digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) values between strain NIT-TF6 and other Desulfitobacterium species ranged from 15.9 to 16.9% and from 71.68 to 72.51%, respectively. These are well below the thresholds for species delineation. A distinguishing feature of strain NIT-TF6 was its possession of both L-lactate dehydrogenase (L-LDH) and D-lactate dehydrogenase (D-LDH), in contrast to other Desulfitobacterium strains that exclusively express D-LDH. Based on the dDDH and ANI results, combined with physiological, phylogenetic, morphological, biochemical, genomic, and metabolic iron-related characteristics, strain NIT-TF6 has been proposed as a novel species within the genus Desulfitobacterium. The name Desulfitobacterium elongatum sp. nov. has been proposed for this strain, with NIT-TF6ᵀ designated as the type strain. Full article

A quantitative study of the complicated three-dimensional structures of artificial atoms in the field of intense matter physics requires a collaborative method that combines a statistical analysis of unusual graph features related to atom topology. Simplified circuits can also be produced by using similar transformations to streamline complex circuits that need laborious mathematical calculations during analysis. These modifications can also be used to determine the number of spanning trees required for specific graph families. The explicit derivation of formulas to determine the number of spanning trees for novel pyramid graph types based on the Fritsch graph, which is one of only six graphs in which every neighborhood is a 4- or 5-vertex cycle, is the focus of our study. We conduct this by utilizing our understanding of difference equations, weighted generating function rules, and the strength of analogous transformations found in electrical circuits. Full article

The urban heat island (UHI) effect has emerged as a growing ecological challenge in compact urban environments. Although urban vegetation plays a vital role in mitigating thermal extremes, its cooling performance varies depending on vegetation type and urban morphological context. This study explores the extent to which compact urban development—quantified using the Mixed-use and Intensive Development (MIXD) index—modulates the cooling responses of different vegetation types in Nanjing, China. A combination of landscape metrics, regression-based interaction models, and XGBoost with SHAP analysis is employed to uncover vegetation-specific and structure-sensitive cooling effects. The results indicate that densely planted trees exhibit reduced cooling effectiveness in compact areas, where spatial clustering and fragmentation tend to intensify UHI effects, particularly during nighttime. In contrast, scattered trees are found to maintain more stable cooling performance across varying degrees of urban compactness, while low-lying vegetation demonstrates limited thermal regulation capacity. Critical thresholds of MIXD (approximately 28 for UHI area and 37 for UHI intensity) are identified, indicating a nonlinear modulation of green space performance. These findings underscore the importance of vegetation structure and spatial configuration in shaping urban microclimates and offer mechanistic insights into plant–environment interactions under conditions of increasing urban density. Full article

Swietenia macrophylla King, commonly known as Brazilian mahogany, is a high-value neotropical tree species currently threatened due to intensive logging in previous decades. Technologies aimed at clonal production are essential for this species’ conservation and sustainable use at times of climate change and increasing demand for ecological restoration. The aim of the present study is to develop a low-cost protocol for mahogany clonal propagation through mini-cutting by assessing clonal mini-hedge nutrition, vegetative propagule type and indole-3-butyric acid (IBA) application effects on rooting and early clone growth. The experiment was conducted in nursery under controlled conditions based on using basal and apical mini-cuttings rooted in a low-cost mini-greenhouse subjected to three nutrient solution concentrations (50%, 100%, and 200%) and five IBA doses (0–8000 ppm). The mini-cutting technique proved efficient and led to over 90% survival after the hardening phase. The 200% nutrient solution concentration allowed balanced performance between cutting types and optimized clonal yield. IBA concentration at 4000 ppm accounted for higher root percentages at the bottom of the tube and the trend towards higher dry biomass production at 160 days. The results highlighted mini-cutting’s potential as a viable mahogany conservation and sustainable production technique. It also supported tropical forestry sector adaptation to challenges posed by climate change. Full article

The sustainable utilization of saline water resources represents an effective strategy for alleviating water scarcity in arid regions. However, the mechanisms by which prolonged saline water irrigation influences soil salinization and dryland crop growth are not yet fully understood. This study examined the effects of six irrigation water salinity levels (CK: 0.87 g·L⁻¹, S1: 2 g·L⁻¹, S2: 4 g·L⁻¹, S3: 6 g·L⁻¹, S4: 8 g·L⁻¹, S5: 10 g·L⁻¹) on soil salinization dynamics and jujube growth during a three-year field experiment (2020–2022). The results showed that soil salinity within the 0–1 m profile significantly increased with rising irrigation water salinity and prolonged irrigation duration, with the 0–0.4 m layer accounting for 50.27–74.95% of the total salt accumulation. A distinct unimodal salt distribution was observed in the 0.3–0.6 m soil zone, with the salinity peak shifting downward from 0.4 to 0.5 m over time. Meanwhile, soil pH and sodium adsorption ratio (SAR) increased steadily over the study period. The dominant hydrochemical type shifted from SO₄²⁻-Ca²⁺·Mg²⁺ to Cl⁻-Na⁺·Mg²⁺. Crop performance exhibited a nonlinear response to irrigation salinity levels. Low salinity (2 g·L⁻¹) significantly enhanced plant height, stem diameter, leaf area index (LAI), vitamin C content, and yield, with improvements of up to 12.11%, 3.96%, 16.67%, 16.24%, and 16.52% in the early years. However, prolonged exposure to saline irrigation led to significant declines in both plant growth and water productivity (WP) by 2022. Under high-salinity conditions (S5), yield decreased by 16.75%, while WP declined by more than 30%. To comprehensively evaluate the trade-off between economic effects and soil environment, the entropy weight TOPSIS method was employed to identify S1 as the optimal irrigation treatment for the 2020–2021 period and control (CK) as the optimal treatment for 2022. Through fitting analysis, the optimal irrigation water salinity levels over 3 years were determined to be 2.75 g·L⁻¹, 2.49 g·L⁻¹, and 0.87 g·L⁻¹, respectively. These findings suggest that short-term irrigation of jujube trees with saline water at concentrations ≤ 3 g·L⁻¹ is agronomically feasible. Full article