Search Results (1,245)

Post-fire soil and vegetation changes can intensify erosion and sediment yield by altering the factors controlling the runoff–infiltration balance. Erosion barriers (EBs) are widely used in hydrological and forest restoration to mitigate erosion, reduce sediment transport, and promote vegetation recovery. However, precise spatial assessments of their effectiveness remain scarce, requiring validation through operational methodologies. This study evaluates the impact of EB on post-fire vegetation recovery at two temporal and spatial scales: (1) Remotely Piloted Aircraft System (RPAS) imagery, acquired at high spatial resolution but limited to a single acquisition date coinciding with the field flight. These data were captured using a MicaSense RedEdge-MX multispectral camera and an RGB optical sensor (SODA), from which NDVI and vegetation height were derived through aerial photogrammetry and digital surface models (DSMs). (2) Sentinel-2 satellite imagery, offering coarser spatial resolution but enabling multi-temporal analysis, through NDVI time series spanning four consecutive years. The study was conducted in the area of the Luna Fire (northern Spain), which burned in July 2015. A paired sampling design compared upstream and downstream areas of burned wood stacks and control sites using NDVI values and vegetation height. Results showed slightly higher NDVI values (0.45) upstream of the EB (p < 0.05), while vegetation height was, on average, ~8 cm lower than in control sites (p > 0.05). Sentinel-2 analysis revealed significant differences in NDVI distributions between treatments (p < 0.05), although mean values were similar (~0.32), both showing positive trends over four years. This study offers indirect insight into the functioning and effectiveness of EB in post-fire recovery. The findings highlight the need for continued monitoring of treated areas to better understand environmental responses over time and to inform more effective land management strategies. Full article

The restoration of “Heitutan” degraded grasslands on the Qinghai-Tibetan Plateau was hindered by suboptimal grass species mixtures, leading to low vegetation productivity, impaired soil nutrient cycling, and microbial functional degradation. Based on a 22-year controlled field experiment, this study systematically elucidated the regulatory mechanisms of different artificial grass mixtures on vegetation community characteristics, soil physicochemical properties, and bacterial community structure and function. The results demonstrated that mixed-sowing treatments significantly improved soil conditions and enhanced aboveground biomass. The HC treatment (Elymus nutans Griseb. + Poa crymophila Keng ex L. Liu cv. ‘Qinghai’ + Festuca sinensis Keng ex S. L. Lu cv. ‘Qinghai’) achieved aboveground biomass of 1580.0 and 1645.0 g·m⁻², representing 66.14% and 60.91% increases, respectively, compared to the HA monoculture (E. nutans). Concurrently, this treatment increased soil organic matter content by 52.3% and 48.4%, total nitrogen by 59.4% and 69.2%, while reducing electrical conductivity by 48.99% and 51.72%, with optimal pH stabilization (7.34–7.38). These findings confirmed that optimized grass mixtures effectively enhance soil physicochemical properties and carbon–nitrogen retention. Microbiome analysis revealed that the HE treatment (E. nutans + P. crymophila + F. sinensis + Poa poophagorum Bor. + Festuca kryloviana Reverd. cv. ‘Huanhu’) exhibited superior α-diversity indices (OTU, Shannon, Ace, Chao1, Pielou) with increases of 9.36%, 4.20%, 15.0%, 1.76%, and 13.4%, respectively, over HA, accompanied by optimal community evenness (lowest Simpson index). Core bacterial phyla included Pseudomonadota (22.7–29.9%), Acidobacteriota (21.5–23.6%), and Actinomycetota (13.6–16.0%), with significant suppression of pathogenic bacteria. Co-occurrence network analysis identified specialized functional modules, with HC and HD treatments (E. nutans + P. crymophila + F. sinensis + P. poophagorum) forming a “nitrogen transformation–antibiotic secretion” network (57.3% positive connections). Structural equation modeling (SEM) revealed that mixed sowing had the strongest direct effect on bacterial diversity (β = 0.76), surpassing indirect effects via soil (β = 0.37) and vegetation (β = 0.11). Redundancy analysis (RDA) identified vegetation cover (24.7% explained variance) and soil pH (20.0%) as key drivers of bacterial community assembly. Principal component analysis (PCA) confirmed HC and HD treatments as the most effective restoration strategies. This study elucidated a tripartite “vegetation–soil–microorganism” restoration mechanism, demonstrating that intermediate-diversity mixtures (3–4 species) optimize ecosystem recovery through niche complementarity, pathogen suppression, and enhanced nutrient cycling. These findings provided a scientific basis for species selection in alpine grassland restoration. Full article

Large-scale vegetation loss induced by surface coal mining constitutes a critical driver of regional ecological degradation. However, the applicability of existing change detection methodologies based on remote sensing within complex mining areas under diverse climatic conditions remains systematically unverified. To address this gap and reveal nationwide disturbance patterns, this study systematically evaluates the performance of two algorithms—Continuous Change Detection and Classification (CCDC) and Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr)—in identifying vegetation loss across three major climatic zones of China (the humid, semi-humid, and semi-arid zones). Based on the optimal algorithm, the vegetation loss year and loss magnitude across all of China’s surface coal mining areas from 1990 to 2020 were accurately identified, enabling the reconstruction of the comprehensive, nationwide spatio-temporal pattern of mining-induced vegetation loss over the past 30 years. The results show that: (1) CCDC demonstrated superior stability and significantly higher accuracy (OA = 0.82) than LandTrendr (OA = 0.31) in identifying loss years across all zones. (2) The cumulative vegetation loss area reached 1429.68 km², with semi-arid zones accounting for 86.76%. Temporal analysis revealed a continuous expansion of the loss area from 2003 to 2013, followed by a distinct inflection point and decline during 2014–2016 attributable to policy-driven regulations. (3) Further analysis revealed significant variations in the average magnitude of loss across different climatic zones, namely semi-arid (0.11), semi-humid (0.21), and humid (0.25). These findings underscore the imperative for region-specific restoration strategies to ensure effective conservation outcomes. This study provides a systematic quantification and analysis of long-term, nationwide evolution patterns and regional differentiation characteristics of vegetation loss induced by surface coal mining in China, offering critical support for sustainable development decision-making in balancing energy development and ecological conservation. Full article

The rapid expansion of photovoltaic installations in arid and semi-arid regions has altered regional water–heat regimes, triggering complex responses in vegetation recovery and soil processes. However, systematic assessments of ecological restoration under varying operational durations and microenvironmental interactions remain insufficient. Therefore, this study examines photovoltaic power stations operating for 1, 7, and 13 years within China’s temperate desert regions, alongside undeveloped control areas, to compare differences across four microenvironments: the front eave of photovoltaic panels (FP), underneath photovoltaic panels (UP), back eave of photovoltaic panels (BP), and interval between photovoltaic panels (IP). Combining analysis of variance, correlation analysis, variance partitioning analysis (VPA), and generalised additive models (GAMs), the study evaluates the coupling mechanisms between vegetation and soil. The results indicate that operational duration significantly enhances vegetation cover, biomass, and species diversity, with the 13 year operational zone demonstrating optimal restoration outcomes. Microenvironmental variations were pronounced, with vegetation and soil quality in the front eave zone surpassing other areas, while the inter-panel zone exhibited the weakest recovery. Key soil factors shifted with recovery stages: early-stage vegetation showed heightened sensitivity to soil water content (SWC), whereas later stages relied more heavily on soil organic matter (SOM) and nutrient supply. Variation Partial Analysis (VPA) revealed that soil factors in the 13 year operational zone accounted for 71.9% of the variation in vegetation cover. The operational lifespan of photovoltaic power stations, microenvironmental variations, and key soil factors collectively drive the restoration of thermophilic desert vegetation. This research reveals phased regulatory mechanisms during the restoration process, providing scientific grounds for optimising photovoltaic layouts and enhancing desert ecosystem stability. Full article

We here delve into the intricate and evolving concepts of brain death and consciousness, particularly at the end of life. We examine the historical and technological advancements that have influenced our understanding of death, such as mechanical ventilation and resuscitation techniques. These developments have challenged traditional definitions of death, leading to the concept of brain death, defined as the irreversible loss of all brain functions, including the brainstem. We emphasize that consciousness exists on a continuum, ranging from full alertness to deep coma and complete cessation of brain activity. It explores various disorders of consciousness, including coma, vegetative state, minimally conscious state, and locked-in syndrome, each with distinct characteristics and levels of awareness. Neuroimaging techniques, such as EEG, fMRI, and DTI, are highlighted for their crucial role in diagnosing and understanding disorders of consciousness. These techniques help to detect covert consciousness, assess brain activity, and predict recovery potential. The phenomenon of the “wave of death,” which includes a paradoxical surge in brain activity at the point of death, is also discussed. We address the challenges in defining and understanding both death and consciousness, calling for biologically grounded, ethically defensible, and culturally sensitive definitions. We advocate for standardized neuroimaging protocols, longitudinal studies, and the integration of artificial intelligence to improve diagnosis and treatment. In conclusion, the document underscores the importance of an integrated, evidence-based approach to understanding the gray zones between life and death, recognizing that consciousness and death are dynamic processes with both biological and experiential dimensions. Full article

The main aim of this study was to analyze the excessive biomass of invasive alien aquatic plants reducing the water quality of a lake which was restored in the past. This study was conducted on Długie Lake (26.8 ha, 17.3 m, Masurian Lake District, northeastern Poland), which was completely degraded by raw wastewater inflow. After the long-term restoration (1987–2003) and recovery of submerged macrophyte meadows, the invasion of Elodea nuttallii—an invasive alien aquatic plant (IAAP)—was observed due to the increasing water temperature in recent years, impairing the functioning, biodiversity, and ecosystem services of this urban lake, as well as causing the deterioration of lake water quality. Therefore, an excessive biomass of E. nuttallii has been removed from the lake since 2022. The analysis of physico-chemical water quality parameters showed that consecutive excessive biomass macrophyte gradual removal (three times during the growing season) helps to limit the excessive growth of E. nuttallii and also removes nutrient loads from the ecosystem. Removing excess aquatic vegetation also helps maintain the lake’s aesthetic and recreational value. Currently, the total phosphorus concentration in lake water did not exceed 0.3 mg P/L and total nitrogen did not exceed 2.0 mg N/L. Chlorophyll a contents oscillated in the range of 5 to 9 µg/L, and Secchi disk visibility exceeded 3 m. Full article

Complex matrix of vegetable severely interferes with enzyme-linked immunosorbent assay (ELISA) accuracy, limiting its application in parathion residue detection. This study investigated the interference mechanism of vegetable matrix, including chlorophyll, perilla protein, glucose, fructose, and sucrose, on ELISA. Furthermore, we validated the vegetable matrix interference on parathion residue ELISA by comparing the matrix interference index (I_m) and recovery rate of vegetable samples before and after acetic acid-treatment. The results demonstrate that the addition of vegetable matrix significantly interferes with ELISA, with the antibody–IgG-HRP binding being subject to the most pronounced interference. Compared to the I_m (16–26%) of non-acetic acid treatment, the I_m (10–13%) was significantly reduced after the acetic acid treatment. Concomitantly, spiked recovery experiments of acid-treated samples yielded satisfactory average recovery rate (80–113%) as the matrix interference was minimized. The findings of this study provide valuable insights into the mechanism of vegetable matrix interference on ELISA. Full article

Leaching mining of ion-adsorption rare earths degrades soil organic matter and hampers vegetation recovery. High-resolution UAV remote sensing enables large-scale monitoring of reclamation, yet vegetation detection accuracy is constrained by key challenges. Conventional three-channel detection struggles with terrain complexity, illumination variation, and shadow effects. Fixed UAV altitude and missing topographic data further cause resolution inconsistencies, posing major challenges for accurate vegetation detection in reclaimed land. To enhance multi-spectral vegetation detection, the model input is expanded from the traditional three channels to six channels, enabling full utilization of multi-spectral information. Furthermore, the Channel Attention and Global Pooling SPPF (CAGP-SPPF) module is introduced for multi-scale feature extraction, integrating global pooling and channel attention to capture multi-channel semantic information. In addition, the C2f_DynamicConv module replaces conventional convolutions in the neck network to strengthen high-dimensional feature transmission and reduce information loss, thereby improving detection accuracy. On the self-constructed reclaimed vegetation dataset, MRV-YOLO outperformed YOLOv8, with mAP@0.5 and mAP@0.5:0.95 increasing by 4.6% and 10.8%, respectively. Compared with RT-DETR, YOLOv3, YOLOv5, YOLOv6, YOLOv7, yolov7-tiny, YOLOv8-AS, YOLOv10, and YOLOv11, mAP@0.5 improved by 6.8%, 9.7%, 5.3%, 6.5%, 6.4%, 8.9%, 4.6%, 2.1%, and 5.4%, respectively. The results demonstrate that multichannel inputs incorporating near-infrared and dual red-edge bands significantly enhance detection accuracy for reclaimed vegetation in rare earth mining areas, providing technical support for ecological restoration monitoring. Full article

High-intensity functional training (HIFT) has grown in popularity in the past several decades, yet previous research has largely focused on the dietary habits and body composition of elite HIFT athletes and utilized only quantitative study designs, potentially limiting our understanding of typical HIFT athletes. This study aimed to comprehensively describe the common dietary habits and body composition of HIFT athletes. Data were only analyzed descriptively. Among 62 HIFT athletes (age: 36 ± 11.7 years), we estimated body fat percentage (BF%) using a Siri 3-compartment model, and we assessed dietary habits, dietary supplement (DS) use, and open-response rationales for DS use/disuse via an online questionnaire. Qualitative data from open-response questions were coded and grouped via inductive thematic analysis. Body composition varied among both male (n = 36, BF% = 6.5–27.6%) and female participants (n = 26, BF% = 10.6–37.6%). Most participants reported regular consumption of lean meats and home-cooked meals, yet few participants (~20%) regularly consumed the recommended twice daily servings of dairy, fruits, vegetables, and whole grains. Most (77.4%) HIFT athletes reported DS use, with the average HIFT athlete using approximately six DS; dairy protein, creatine, caffeine, and electrolyte drinks were the most reported DS. Improving health, recovery, and nutrient intake were common reasons for using DS, whereas a lack of noticeable results was the most common reason for discontinuation. Some HIFT athletes may rely on DS to address nutrient gaps rather than whole foods. Full article

Sprayers for vineyards with solution recovery represent an important innovation, offering several advantages, the most important being the efficient use of pesticides and environmental protection. This paper presents the experimental equipment designed to study the treatment process of grapevine foliage, the applied research methods, and the results of optimizing key technological parameters (hydraulic pressure p of the working solution, speed V of the airflow at the nozzle outlet) and design parameters (surface area S of the central orifice of the diffuser) in different growth stages of grapevines with varying foliar density ρ, the response function being the recovery rate of the working solution. The construction of the SVE 1500 (Experimental model, manufactured at the Institute of Agricultural Technology “Mecagro”, Chisinau, Republic of Moldova) vineyard sprayer with solution recovery is presented, along with test results obtained in field conditions, which demonstrated that the experimental model of our machine ensures a 38% reduction in working solution consumption during the active vegetation phase while maintaining treatment quality in compliance with agrotechnical requirements. The SVE 1500 machine can be towed with a sufficient turning radius for use in modern vineyard plantations. Construction documentation has been developed for the production and delivery of the experimental batch of SVE 1500 machines to agricultural enterprises. Full article

Land degradation in Iraq’s Mesopotamian plain threatens food security and rural livelihoods, yet the relative roles of climatic water deficits versus anthropogenic pressures remain poorly attributed in space. We test the hypothesis that multi-timescale climatic water deficits (SPEI-03/-06/-12) exert a stronger effect on vegetation degradation risk than anthropogenic pressures, conditional on hydrological connectivity and irrigation. Using Babil and Al-Qadisiyah (2000–2023) as a case, we implement a four-part pipeline: (i) Fractional Vegetation Cover with Mann–Kendall/Sen’s slope to quantify greening/browning trends; (ii) LandTrendr to extract disturbance timing and magnitude; (iii) annual LULC maps from a Random Forest classifier to resolve transitions; and (iv) an XGBoost classifier to map degradation risk and attribute climate vs. anthropogenic influence via drop-group permutation (ΔAUC), grouped SHAP shares, and leave-group-out ablation, all under spatial block cross-validation. Driver attribution shows mid-term and short-term drought (SPEI-06, SPEI-03) as the strongest predictors, and conditional permutation yields a larger average AUC loss for the climate block than for the anthropogenic block, while grouped SHAP shares are comparable between the two, and ablation suggests a neutral to weak anthropogenic edge. The XGBoost model attains AUC = 0.884 (test) and maps 9.7% of the area as high risk (>0.70), concentrated away from perennial water bodies. Over 2000–2023, LULC change indicates CA +515 km², HO +129 km², UL +70 km², BL −697 km², WB −16.7 km². Trend analysis shows recovery across 51.5% of the landscape (+29.6% dec⁻¹ median) and severe decline over 2.5% (−22.0% dec⁻¹). The integrated design couples trend mapping with driver attribution, clarifying how compounded climatic stress and intensive land use shape contemporary desertification risk and providing spatial priorities for restoration and adaptive water management. Full article

The Bełchatów Lignite Mine (BLM) in central Poland, one of Europe’s largest Neogene lignite deposits, provides key insights into palaeofloral evolution. Located in the Kleszczów Graben, the BLM consists of four distinct lithological units: subcoal, coal, clayey-coal, and clayey-sandy units. The study presents a palynological investigation of 31 samples from all units, identifying 78 sporomorph taxa, including 10 plant spores, 15 gymnosperm pollen, and 53 angiosperm pollen taxa. Pollen grains from angiosperms and gymnosperms were consistently observed in all samples, while plant spores were scarce. The analysis reveals three distinct palynological zones, reflecting shifts in vegetation. The first zone is characterized by swamp, riparian, and mixed mesophilous forests, dominated by Taxodium/Glyptostrobus, Ulmus, Carya, Engelhardia, Pterocarya, and Quercus. In the second zone, slightly cooler climatic conditions led to the decline of Taxodium/Glyptostrobus and Alnus, indicating a deterioration of swamp forests. The third zone marks a subsequent recovery of these forests. Palaeoclimatic interpretations indicate three phases: a subtropical-humid climate during the Early Miocene, fluctuating humidity in the late Early Miocene, and a transition to a warm-temperate and humid climate in the Late Miocene. Full article

The REPowerEU plan is aimed at a target of 35 bcm of biomethane annually by 2030, up from 4 bcm in 2023, requiring about EUR 37 billion in investment. Food waste is identified as a key feedstock, characterized by discrete homogeneity, although its availability may vary seasonally. In Italy, the Emilia-Romagna region generates approximately 450 kt/y of industrial waste from the food and beverage sector, primarily originating from meat processing (NACE 10.1), fruit and vegetable processing (NACE 10.3), and the manufacture of vegetable and animal oils and fats (NACE 10.4). Of this amount, food and beverage processing waste (EWC 02) accounts for about 302 kt from NACE 10 (food, year 2019) and 14 kt from NACE 11 (beverage, year 2019). This study provides a comprehensive screening of waste streams generated by the local food and beverage industry in Emilia-Romagna, evaluating the number of enterprises, their value added, and recorded waste production. The screening led to the identification of suitable streams for further valorization strategies: a total of ~93 kt/y was selected for the preliminary conceptual design of an integrated process combining anaerobic digestion with hydrothermal treatment, aimed at supporting national biomethane production targets while maximizing material recovery through hydrochar production. Preliminary estimations indicate that the proposed process may achieve a biochemical methane potential of approximately 0.23 Nm³/kg_VS, along with a hydrochar yield of about 130 kg/t_waste. Full article

Forest density is a key parameter in forestry research, and its variation can significantly impact ecosystems. Saihanba, as a focal site for afforestation and restoration, offers an ideal case for monitoring these dynamics. In this study, we compared three machine learning algorithms—Random Forest, Support Vector Regression, and XGBoost—using Landsat surface reflectance data together with the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI), and reference tree densities derived from LiDAR individual tree segmentation. The best-performing algorithm, XGBoost (R² = 0.65, RMSE = 174 trees ha⁻¹), was then applied to generate a long-term forest density dataset for Saihanba at five-year intervals, covering the period from 1988 to 2023. Results revealed distinct differences among tree species, with larch achieving the highest accuracy (R² = 0.65, RMSE = 161 trees ha⁻¹), whereas spruce had larger prediction errors (RMSE = 201 trees ha⁻¹) despite a relatively high R² (0.70). Incorporating 30 m slope data revealed that moderate slopes (5–30°) favored faster forest recovery. From 1988 to 2023, average forest density rose from 521 to 628 trees ha⁻¹—a 20.6% increase—demonstrating the effectiveness of restoration and providing a transferable framework for large-scale ecological monitoring. Full article

This study developed a gas chromatography–tandem mass spectrometry (GC-MS/MS) method for detecting dinotefuran residues in fruits and vegetables. The modified extraction procedure employed solvent conversion for GC-MS/MS compatibility, achieving a linear range of 0.001–2.0 mg/kg (r² > 0.999), a LOD of 0.003 mg/kg, and a LOQ of 0.01 mg/kg. Recovery rates ranged from 88.2% to 104.5% (RSD: 3.5–5.8%). The analysis of 18 commercial samples from Weifang, China, revealed the highest residues in nectarines (0.12 mg/kg) and lowest residues in cucumbers (0.02 mg/kg), with the dietary exposure risk assessment indicating hazard quotients well below safety thresholds. The literature review showed that dinotefuran has a shorter soil half-life (10–30 days) than most neonicotinoids, a low adsorption coefficient (Koc 30–50), high leaching potential, and significant toxicity to pollinators (LD₅₀ = 0.023 μg/bee). The validated method provides reliable detection across diverse matrices, while the environmental behavior analysis highlights the need for the careful management of dinotefuran applications to minimize ecological impacts despite its favorable degradation profile compared to other neonicotinoids. Full article