Search Results (6,002)

Forests and scrubland comprise a large proportion of terrestrial ecosystems and, due to the long lifespan of trees and shrubs, their capacity to grow and store carbon as lasting woody tissues is particularly sensitive to warming-enhanced drought occurrence. Climate change may trigger a transition from forests to scrubland in many drylands during the coming decades due to the higher resilience of shrubs. However, we lack standardized frameworks to compare the response to drought of woody plants. We present a framework and develop an index to estimate the drought-induced vulnerability (DrVi) of trees and shrubs based on the radial growth trajectory and the response of growth variability to a drought index. We used tree-ring width series of three tree (Pinus halepensis Mill., Juniperus thurifera L., and Acer monspessulanum L.) and three shrub (Juniperus oxycedrus L., Pistacia lentiscus L., and Ephedra nebrodensis Tineo ex Guss.) species from semi-arid areas to test this framework. We compared the DrVi values between species and populations and explored their temporal changes. Across species, the strongest DrVi values were found in declining P. halepensis stands and J. oxycedrus from the same site, while the lowest DrVi values were found in A. monspessulanum, P. lentiscus, and E. nebrodensis. Across populations, J. oxycedrus presented higher vulnerability in one of the dry sites. The P. halepensis declining stand showed a steady increase in DrVi value after the 1980s as the climate shifted toward warmer and drier conditions. We conclude that the DrVi allows comparing species and populations using a standardized general framework. Full article

In the research and practice of integrated scheduling problems, the tree structure of complex products usually presents an asymmetric and complex form. This asymmetry is mainly reflected in the hierarchical relationship between the various components of the product, the degree of dependence, and the sequence of production processes. Existing studies often neglect that leaf nodes with the lowest layer priority can be scheduled at any moment, leading to underutilization of parallelism potential under symmetric structures and exacerbation of critical path delays under asymmetric structures. Aiming at solving this kind of problem, an integrated scheduling algorithm based on the improved Floyd algorithm (ISA-IFA) is proposed. According to the improved Floyd algorithm, the algorithm proposed a path-weighted strategy, which constructs the vertical path value according to the processing time of the process itself. Combined with the proposed process scheduling advantage strategy, the leaf node process is especially emphasized as the priority scheduling object, which makes the connection between the processes more closely, and then significantly reduces the idle time of the equipment. The empirical results show that the ISA-IFA algorithm shortens the completion time of complex products and simultaneously improves the equipment utilization rate to 55.9%, verifying its effectiveness in dynamic scheduling and resource co-optimization. Full article

The study of carbon stocks in organic compounds within terrestrial ecosystems allows us to create a pool of potential carbon farming projects. At present, it is essential to assess the economic viability of natural-based solutions in order to develop strategies to encourage small and medium enterprises (SME) and governments to address climate change through specific measures. This article is devoted to the study of the economic efficiency of afforestation projects. The purpose of this study is to evaluate the economic efficiency of the project and, based on NPV sensitivity analysis, to identify the factors affecting economic efficiency. This will make it possible to formulate directions for stimulating the development of afforestation projects using tools to improve their economic efficiency. Based on data on the number of carbon credits issued, their price, and the costs and other revenue associated with the implementation of the afforestation project, a sensitivity analysis of economic efficiency was conducted, highlighting the most significant factors. Given that different tree species are characterized by variable seedling values, planting costs, and sequestration potentials, an afforestation project with the most carbon efficient tree species was selected as a pilot project. Black alder exhibits the most optimal proportion between the volume of carbon units released and the cost of planting trees. A sensitivity analysis of the project’s net present value was conducted in order to ascertain the factors that have the most significant impact on the project’s economic efficiency. These include the discount rate based on the cost of capital and the cost of tree planting. As a result, this article makes recommendations for improving the economic efficiency of afforestation projects for SME. The government’s role in enhancing the economic efficiency of such initiatives entails reducing the cost of capital through a reduction in the key rate or the provision of subsidies for the interest rate on bank credits. An alternative approach involves the granting of subsidies for the cost of tree planting, since the effects can be seen as a series of public goods, such as the creation of recreational areas and increased biodiversity of the ecosystem. Full article

This study aimed to investigate the impact of local canopy environmental characteristics on the regeneration of common tree species in the understory of broadleaved Korean pine forests, thus deepening the understanding of species coexistence and forest growth cycle mechanisms. This study focused on nine tree species found in the Liangshui National Nature Reserve in Heilongjiang Province, China. We stratified trees by height and simulated the LAI distribution of each class using Voronoi polygons. These layers were overlaid to generate an integrated LAI spatial map. All these procedures were integrated into the self-developed R package Broadleaf.Korean.pine.LAI, which was used to calculate individual-level canopy environment indicators, including average local LAI, local LAI standard deviation, canopy percent, vertical distribution tendency degree, local coniferous LAI, and local broadleaf LAI. These indicators were then compared with the average values of uniformly distributed understory sampling points. A principal component analysis (PCA) was conducted to reduce the dimensionality of the local canopy environmental characteristics for both the uniformly distributed points and regeneration habitats of each tree species, resulting in comprehensive canopy environmental characteristics. Wilcoxon rank-sum tests were applied to assess the significance of differences between the regeneration habitats and the understory average, as well as between the regeneration habitats of seedlings and saplings within the same species. Cliff’s delta effect size was used to evaluate the impact of each environmental factor on the transition of regeneration from seedlings to saplings. The results showed that, based on both individual canopy environmental indicators and composite indices derived from principal component analysis, seedlings tended to regenerate in areas with higher canopy coverage, whereas saplings were more commonly established in relatively open habitats. Clear differences exist between the regeneration habitats of coniferous and broadleaf species, with coniferous species tending to regenerate in areas with higher local broadleaf LAIs compared with broadleaf species. The effect size analysis showed that canopy percent, vertical distribution tendency degree, average local LAI, and local coniferous LAI have greater impacts on the transition from seedlings to saplings, while the effect of local broadleaf LAI is relatively small. These findings suggest that strong shade tolerance allows species to establish seedling banks under canopy patches, while interspecific differences in growth response to microhabitats shape their roles in the forest growth cycle. Future research should explore the physiological responses and trait characteristics of tree regeneration under varying canopy patch environments. Long-term monitoring of regeneration processes—including invasion, growth, and mortality—across different canopy patches will help elucidate the mechanisms shaping understory spatial patterns. Full article

RNA-dependent RNA polymerase (RdRP) represents a critical target for antiviral drug development. We developed a multi-model machine learning framework combining five traditional algorithms (ExtraTreesClassifier, RandomForestClassifier, LGBMClassifier, BernoulliNB, and BaggingClassifier) with a CNN deep learning model to identify potential RdRP inhibitors among FDA-approved drugs. Using the PubChem dataset AID 588519, our ensemble models achieved the highest performance with accuracy, ROC-AUC, and F1 scores higher than 0.70, while the CNN model demonstrated complementary predictive value with a specificity of 0.77 on external validation. Molecular docking studies with the norovirus RdRP (PDB: 4NRT) identified raloxifene as a promising candidate, with a binding affinity (−8.8 kcal/mol) comparable to the positive control (−9.2 kcal/mol). The molecular dynamics simulation confirmed stable binding with RMSD values of 0.12–0.15 nm for the protein–ligand complex and consistent hydrogen bonding patterns. Our findings suggest that raloxifene may possess RdRP inhibitory activity, providing a foundation for its experimental validation as a potential broad-spectrum antiviral agent. Full article

Parkinson’s disease (PD) is a common movement disorder affecting adults. People diagnosed with PD can have a multitude of physical (motor) symptoms, including tremors, and rigidness, and psychological (non-motor) symptoms, including anxiety and depression. These symptoms dramatically affect daily living activities, including dressing oneself, preparing meals, and speaking and writing. Background/Objectives: To determine the symptom similarities and differences among PD patients, a method referred to as cluster analysis can be applied to patient data. This method can separate patients who differ by symptom presence while grouping patients with disease similarities. Previous PD cluster analysis studies provided patient groups that were defined by their age and disease duration—both numerical values—and excluded categorical values, such as patient gender, family history of the disease, and symptom presence. In addition, patient age and disease duration were limited in range in previous studies, providing a patient group that was too similar to divide into distinct clusters. Methods: This study utilized a decision tree cluster analysis method applied to categorical symptom data from PD patients. The applied cluster method automatically determines the number of clusters, reducing estimation errors, as many cluster analysis methods require the end user to estimate the number of clusters prior to applying cluster analysis. A post analysis of additional categorical and numerical variables was conducted, and this provided a means to describe the PD patient clusters in terms of gender, family history of PD, median age, disease duration, and symptom presence. The patient dataset utilized was accessed from the Parkinson’s Progression Markers Initiative (PPMI) website. Results and Conclusions: The cluster analysis results provided a means to describe seven PD patient subtypes based on motor symptom presence, with the largest PD patient cluster containing half of the patient sample, and these individuals had three of the motor symptoms present: bradykinesia, rigidity, and tremors. Full article

This study investigates the hydrothermal gasification (HTG) of apricot tree resin, focusing on the yield and chemical composition of the resulting gas and aqueous phases. K₂CO₃ and KOH were used as catalysts within a temperature range of 300–600 °C, with a constant reaction time of 60 min. The results show that temperature and catalyst choice significantly influence gas yield, liquid composition, and solid residue formation. Higher temperatures increased the gas yield while decreasing aqueous and solid residues. The catalytic effect of K₂CO₃ and KOH enhanced the gaseous product conversion, with KOH achieving the highest gas yield and lowest residue formation at 600 °C. Among the liquid-phase compounds, carboxylic acids and 5-methyl furfural were the most abundant, reaching peak concentrations at 300 °C in the presence of K₂CO₃. The addition of alkali catalysts reduced key acidic intermediates such as glycolic, acetic, and formic acids. The inverse relationship between temperature and liquid/solid product formation underscores the importance of optimizing reaction conditions for efficient biomass conversion. These findings contribute to the growing field of biomass valorization by highlighting the potential of underutilized tree resins in sustainable biofuel production, advancing knowledge in renewable hydrogen production, and supporting the broader development of bio-based energy solutions. Full article

Podocarpus macrophyllus is an evergreen tree with significant ornamental, economic, and medicinal value, widely used in landscape gardening and bonsai production. However, systematic research on the optimal substrate ratios required for its efficient cultivation remains relatively scarce. This study compared the effects of two cultivation substrates (SJ1: 80% native soil + 20% fine sand and SX2: 25% native soil + 25% coarse sand + 25% peat soil + 25% coconut coir) on the growth of P. macrophyllus. Soil physicochemical properties and plant physiological and biochemical indices were measured, and the rhizosphere microbial community structure was analyzed using Illumina MiSeq high-throughput sequencing. The results show that P. macrophyllus grown in the SX2 substrate exhibited significantly greater ground diameter, plant height, chlorophyll content, and soluble protein content than those in the SJ1 substrate. Microbial community analysis indicates that the two different substrates had little impact on alpha diversity. In the bacterial community, the dominant phylum in the SJ1 substrate was Acidobacteriota, whereas in the SX2 substrate, it was Pseudomonadota. In the fungal community, Ascomycota was the dominant phylum in both SJ1 and SX2. Redundancy analysis (RDA) reveals that water content and total porosity were the primary factors influencing the bacterial community structure. Based on physiological indicators and microbial community composition, the SX2 substrate was more conducive to the growth of P. macrophyllus in terms of plant height and ground diameter. Therefore, this study provides valuable insights for substrate selection and optimization in the cultivation of P. macrophyllus. Full article

The exploration of Streptomyces from extreme environments presents a particularly compelling avenue for novel compound discovery. A Gram-positive, pink-pigmented Streptomyces strain designated HC307^T was isolated from a soil sample collected in Xizang (Tibet), China. The exploration of Streptomyces from extreme environments presents a particularly compelling avenue for novel compound discovery. In this study, the 16S rRNA sequence of strain HC307^T exhibited the highest similarity with Streptomyces prasinosporus NRRL B-12431^T (97.5%) and Streptomyces chromofuscus DSM 40273^T (97.3%), which were below 98.7%. The draft genome of the bacteria was 10.0 Mb, with a G+C content of 70.0 mol%. The average nucleotide identity (ANI) values of strain HC307^T and similar type strains ranged from 78.3% to 87.5% (<95%). The digital DNA-DNA hybridization (dDDH) values ranged from 22.6% to 33.9% (<70%), which was consistent with the results obtained from phylogenetic tree analysis. Phenotypically, this bacterium grew within the temperature range of 25–40 °C, at a pH range of 5 to 9, and in NaCl concentrations from 0% to 6% (w/v). The polar lipid profile of strain HC307^T was diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine and unidentified lipids. The analysis of 32 biosynthetic gene clusters (BGCs) indicated the strain’s capacity to synthesize diverse compounds. Phylogenetic and phenotypic analyses demonstrated that strain HC307^T represented a novel species within the genus Streptomyces, and proposed the name Streptomyces flavusporus sp. nov., with strain HC307^T (=DSM 35222^T=CGMCC 32047^T). The strain was deposited in Deutsche Sammlung von Mikroorganismen und Zellkulturen and the China General Microbiological Culture Collection Center for patent procedures under the Budapest Treaty. Full article

Background: Colubridae, known to be one of the most species-rich snake families, remains relatively understudied in termshe context of complete mitochondrial genome research. This study provide the first systematic characterization of the mitochondrial genomes of six colubrid species: Lycodon subcinctus, Lycodon rosozonatus, Lycodon fasciatus, Lycodon gongshan, Lycodon futsingensis, and Lycodon aulicus. Method: In this study, mitochondrial genomes were sequenced using Sanger sequencing. The raw data were subjected to quality- filtered withing using Fastp and subsequently assembled into complete mitochondrial genomes via SPAdes. Gene annotation was performed by Tblastn, Genewise (for CDS coding sequences), MiTFi (for transfer RNAs), and Rfam (for ribosomal RNAs). Sequence analyses were conducted with various tools, including MEGA, tRNAscan-SE, DnaSP, MISA, and REPuter. Finally, phylogenetic trees were reconstructed based on 13 protein-coding genes from 14 species. Results:The mitogenomes of these six species ranged from 17,143 to 17,298 bp in length and con-sisted of 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), 2 ribosomal RNA genes (rRNAs), and 2 control regions. The nucleotide composition of the Colu-bridae mitogenomes was comparable with an A + T composition ranging from 52.1% to 58.8% except for the trnS1 and trnC. All the tRNAs could fold into a stable secondary structure. The Pi and Ka/Ks values suggested that atp8 was the fastest-evolving gene, while cox1 was the most conserved gene. Bayesian inference and maximum likelihood phylogenetic analyses yielded consistent results, with the six sequenced species clus-tering together with their congeneric species. These findings will provide valuable references for further research on the phylogeny of Colubridae. Full article

Background and Objective: Stroke is one of the leading causes of mortality and long-term disability in adults over 18 years of age globally, and its increasing incidence has become a global public health concern. Accurate stroke prediction is highly valuable for early intervention and treatment. There is a scarcity of studies evaluating the prediction value of genetic liability in the prediction of the risk of stroke. Materials and Methods: Our study involved 243,339 participants of European ancestry from the UK Biobank. We created stroke genetic liability using data from MEGASTROKE genome-wide association studies (GWASs). In our study, we built four predictive models with and without stroke genetic liability in the training set, namely a Cox proportional hazard (Coxph) model, gradient boosting model (GBM), decision tree (DT), and random forest (RF), to estimate time-to-event risk for stroke. We then assessed their performances in the testing set. Results: Each unit (standard deviation) increase in genetic liability increases the risk of incident stroke by 7% (HR = 1.07, 95% CI = 1.02, 1.12, p-value = 0.0030). The risk of stroke was greater in the higher genetic liability group, demonstrated by a 14% increased risk (HR = 1.14, 95% CI = 1.02, 1.27, p-value = 0.02) compared with the low genetic liability group. The Coxph model including genetic liability was the best-performing model for stroke prediction achieving an AUC of 69.54 (95% CI = 67.40, 71.68), NRI of 0.202 (95% CI = 0.12, 0.28; p-value = 0.000) and IDI of 1.0 × 10⁻⁴ (95% CI = 0.000, 3.0 × 10⁻⁴; p-value = 0.13) compared with the Cox model without genetic liability. Conclusions: Incorporating genetic liability in prediction models slightly improved prediction models of stroke beyond conventional risk factors. Full article

Island ecosystems are vulnerable, as natural disasters and inappropriate anthropogenic activities can easily disrupt the ecological balance, posing significant challenges to the delivery of ecosystem services. In order to evaluate the ecosystem service functions of the Zhoushan Archipelago, based on the InVEST model, the four services of water conservation, carbon storage, habitat quality, and soil conservation in the Zhoushan Archipelago in 2017, 2020, and 2023 were estimated, and the spatial pattern of comprehensive ecosystem service function was determined by principal component analysis. The results showed the following: (1) the spatial distribution of water conservation, carbon storage, habitat quality, and soil conservation values in 2017, 2020, and 2023 show the same trend, with high values distributed in the central areas of Zhoushan Island, Changtu Island, Taotao Island, and Qushan Island, and low values distributed in the coastal areas of Zhoushan Island, Yangshan Island, and Yushan Island; (2) land use types have a significant effect on four services. Trees, built areas, rangeland, and cropland were the primary contributors to these four ecosystem services; (3) from 2017 to 2023, the highly important areas and extremely important areas showed a decreasing trend. In 2023, the highly important areas and extremely important areas accounted for 17.29% and 2.33% of the total area, which are important for maintaining the virtuous cycle of the ecosystem. This study provides a scientific basis for the sustainable development of the island. Full article

This study quantifies the market values, or implicit prices, of honey quality features (e.g., organic and origin information, package-related features) and floral varieties for supporting beekeepers in differentiating their products to escape from price competition characterizing the Italian honey market. The research employed a sample of sales data, 660 observations collected from the Italian market, and a hedonic price model, estimated via Ordinary Least Squares, to assess the implicit prices of honey characteristics. A high premium price was recorded for honey with added royal jelly and propolis, as well as for “100% Italian” honey. In contrast, moderate price premiums were recorded for Protected Designation of Origin and organic honey. Furthermore, the floral varieties used largely affected the product price: the highest premium prices were estimated for the Manuka, Kanuka, and Tawari floral varieties. Price premiums above +50% were estimated for floral varieties such as Strawberry tree, Pine, Cistus, Tree of Heaven, Sainfoin, Marruca, and Solidago. Results suggest that honey quality features and some floral varieties can effectively differentiate products, supporting beekeepers to achieve higher revenues. This study offers empirical evidence of the extent to which floral varieties and other product characteristics affect the market price of honey using a dataset of secondary data, with the aim to support producers to improve their competitive position in the market. Full article

Accurately monitoring forest canopy height is crucial for sustainable forest management, particularly in southeastern North Carolina, USA, where dense forests and limited accessibility pose substantial challenges. This study presents an explainable machine learning framework that integrates sparse GEDI LiDAR samples with multi-sensor remote sensing data to improve both the accuracy and interpretability of forest canopy height estimation. This framework incorporates multitemporal optical observations from Sentinel-2; C-band backscatter and InSAR coherence from Sentinel-1; quad-polarization L-Band backscatter and polarimetric decompositions from the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR); texture features from the National Agriculture Imagery Program (NAIP) aerial photography; and topographic data derived from an airborne LiDAR-based digital elevation model. We evaluated four machine learning algorithms, K-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and eXtreme gradient boosting (XGB), and found consistent accuracy across all models. Our evaluation highlights our method’s robustness, evidenced by closely matched R² and RMSE values across models: KNN (R² of 0.496, RMSE of 5.13 m), RF (R² of 0.510, RMSE of 5.06 m), SVM (R² of 0.544, RMSE of 4.88 m), and XGB (R² of 0.548, RMSE of 4.85 m). The integration of comprehensive feature sets, as opposed to subsets, yielded better results, underscoring the value of using multisource remotely sensed data. Crucially, SHapley Additive exPlanations (SHAP) revealed the multi-seasonal red-edge spectral bands of Sentinel-2 as dominant predictors across models, while volume scattering from UAVSAR emerged as a key driver in tree-based algorithms. This study underscores the complementary nature of multi-sensor data and highlights the interpretability of our models. By offering spatially continuous, high-quality canopy height estimates, this cost-effective, data-driven approach advances large-scale forest management and environmental monitoring, paving the way for improved decision-making and conservation strategies. Full article

Winch-assisted harvesting has expanded considerably in recent years as it enables ground-based machines to work safely on steep slopes. To analyze operator exposure to whole-body and hand–arm vibration (WBV, HAV) and noise exposure (LA_eq, LC_peak) during winch-assisted harvesting (TW) and harvesting without winch assistance (NTW), a field study using a Ponsse Scorpion King harvester and an Ecoforst T-winch traction winch was conducted. Vibrations were measured at three locations inside the cabin (seat, seat base/floor, control lever), while noise exposure was recorded both inside and outside the cabin. WBV exposure during work time operations was highest in the Y-direction, both on the seat (0.49–0.87 m/s²) and on the floor (0.41–0.84 m/s²). The WBV and HAV exposure levels were highest while driving on the forest and skid road. Exposure during the main productive time was significantly influenced by the harvesting system, diameter at breast height (DBH), and tree species. Noise exposure was higher, while WBV and HAV exposures on the seat, floor and control lever were lower during non-work time than during work time. The daily vibration exposure on the seat exceeded the EU action value, while LC_peak noise exposure surpassed the limit value of 140 dB(C) on all measured days. Noise and vibration exposure were constantly higher during TW than NTW harvesting but differences were small. Compared to other studies, the results show that harvesting on steep terrain increases noise and vibration exposure, while non-work time has the opposite effect on vibration and noise exposure. Full article