Search Results (10,218)

Cacti thrive in arid and coastal environments partly through associations with beneficial endophytic and rhizosphere bacteria; however, current knowledge remains limited. This study aimed to assess the diversity of cultivable bacteria associated with Opuntia dillenii and evaluate their potential as Plant Growth-Promoting (PGP) agents. Endophytic bacteria were isolated from cladodes and roots, while rhizobacteria were recovered from rhizosphere soil. Bacterial isolates were identified using morphological characteristics and 16S rRNA/gyrB sequencing, followed by screening for PGP traits, pH and temperature tolerance. A total of 31 isolates were obtained, including 23 endophytes and 8 rhizobacteria, mainly affiliated with Firmicutes, Actinobacteria, and Proteobacteria. Bacillus (35.48%) and Priestia (32.25%) predominated, with Priestia flexa as the most prevalent species. The most frequent PGP traits were phosphate solubilization (80.65%), proteolytic activity (70.97%), siderophore production (67.74%), and nitrogenase activity (64.52%). The highest phosphate solubilization indices were observed for strain R3 (3.41), R6 (3.39) and S6 (3.21), whilst the highest indole-3-acetic acid yields were recorded for C9 (172.88 µg/mL), R11 (96.22 µg/mL) and C3 (90.94 µg/mL), and the strongest siderophore production for C3 (30.37 mm), C7 (27.96 mm) and S7 (27.88 mm). These findings highlight O. dilleniid-associated coastal bacteria as promising resources for plant growth and plant stress resilience. Full article

Earthworms possess a highly developed innate immune system based on the coordinated activity of coelomocytes and humoral factors present in the coelomic fluid. These immune components play a central role in host defence against pathogens, maintenance of physiological homeostasis, and adaptation to environmental stressors. Coelomocytes exhibit remarkable functional and morphological diversity, including participation in phagocytosis, encapsulation, extracellular trap formation, cytotoxic responses, wound healing, and regulation of oxidative and osmotic stress. In addition, coelomic fluid contains numerous biologically active molecules, such as lysenin, coelomic cytolytic factor 1, perforin, serine proteases, lysozyme, antimicrobial peptides, and pattern recognition receptors, which contribute to cellular and humoral immune responses. Recent studies have demonstrated that earthworm coelomocytes are highly sensitive to environmental pollutants, including heavy metals, pesticides, nanomaterials, and microplastics, highlighting their importance in ecotoxicological research and soil biomonitoring. Furthermore, antifungal, antimicrobial, anti-inflammatory, antipyretic, and cytotoxic activities associated with coelomocytes and coelomic fluid suggest promising applications in agriculture, biotechnology, and pharmaceutical research. This review summarises current knowledge regarding the classification, characteristics, immune functions, toxicological responses, and applied significance of earthworm coelomocytes and coelomic fluid, with particular emphasis on their role in environmental monitoring and potential biomedical applications. Full article

Wildfires are a major ecological disturbance in Mediterranean ecosystems, affecting vegetation dynamics and landscape resilience. However, the relative importance of environmental factors controlling post-fire vegetation recovery remains insufficiently quantified at regional scales. This study investigates the drivers of vegetation regeneration following 45 large wildfires (>1000 ha) that occurred across Greece between 2017 and 2023. Vegetation recovery was assessed using Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series, while environmental predictors included burn severity metrics, soil moisture at four depth layers derived from the European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land (ERA5-Land) climate reanalysis dataset, terrain characteristics (slope and aspect), land cover, and time since fire. All variables were harmonized at the fire-perimeter scale and analyzed using two complementary modeling approaches: multiple linear regression and artificial neural network (ANN) modeling. The linear regression model explained approximately 38% of the variability in vegetation recovery (R² = 0.38), while the ANN showed improved predictive performance, indicating the presence of complex relationships among predictors. Across the applied modeling approaches, burn severity, topographic conditions, and soil moisture emerged as important drivers of post-fire vegetation recovery. In particular, Soil Moisture Layer 1 (SM₁) showed the strongest positive association with NDVI recovery, followed by Soil Moisture Layer 4 (SM₄), highlighting the importance of water availability for vegetation regeneration under post-fire conditions. Overall, the results confirm that vegetation recovery is strongly controlled by environmental conditions rather than time alone. The findings contribute to a better understanding of post-fire ecosystem dynamics in Mediterranean landscapes and provide a useful framework for supporting wildfire management and restoration planning. Full article

Accurate assessment of carbon storage dynamics and their driving factors is important for ecological sustainability and land management on the Loess Plateau under China’s dual carbon goals. In this study, the InVEST and PLUS models were integrated to evaluate carbon storage changes from 2000 to 2020 and simulate future carbon storage patterns for 2030 under four development scenarios, including natural development (ND), rapid development (RD), cropland protection (CP), and ecological protection (EP). In addition, the XGBoost-SHAP framework was employed to identify the dominant drivers and nonlinear response relationships controlling spatial variation in carbon storage. During 2000–2020, ecosystem carbon storage across the Loess Plateau generally increased, rising from 5.780 Pg to 5.893 Pg. Spatially, carbon storage displayed a pronounced pattern characterized by higher levels in the southeast and lower levels in the northwest, aligning with forest–grassland restoration belts. Scenario simulations showed that EP produced the largest carbon storage gain, with total carbon storage projected to reach 5.962 Pg in 2030. In contrast, RD reduced carbon storage to 5.858 Pg because of intensive construction land expansion. XGBoost-SHAP results identified net primary productivity (NPP) as the most influential factor controlling spatial variation in carbon storage, accounting for 57.3% of the total explanatory importance, whereas soil erosion (SE) exhibited a strong negative effect on carbon storage. Population density (POPD) also exerted a negative effect, whereas gross domestic product (GDP) showed positive contributions in economically developed counties. These findings enhance understanding of the spatial response characteristics of carbon storage under environmental gradients and human disturbance across the Loess Plateau. They further provide scientific support for differentiated ecological management and regionally adapted carbon mitigation planning. Full article

Phosphorus (P) accumulation in intensively agricultural soils represents a growing environmental concern due to its potential mobilization and contribution to eutrophication. This study investigated the mechanisms controlling P availability and redistribution in agricultural soils from the Elota–Piaxtla Irrigation District (northwestern Mexico) during cropping and non-cropping periods. Soil P fractions were determined using the Hedley sequential extraction method and related to soil physicochemical properties through a correlation analysis. During the cropping period, P in Fe/Al hydroxides dominated (45–67% of total P), indicating strong adsorption and fixation in fine-textured soils. In contrast, the non-cropping period showed a significant increase in organic P in humic substances (up to 55%), suggesting enhanced biological transformation and residue recycling. Labile P fractions decreased from 60% to 44% of total P between sampling periods, while moderately labile fractions increased, indicating seasonal redistribution of P pools. Statistical analysis revealed that P dynamics were primarily governed by mineralogical characteristics and organic matter transformations rather than by individual soil properties. The accumulation of moderately labile and organic P fractions during fallow periods highlights a latent environmental risk, particularly in irrigated systems prone to runoff and erosion. These findings emphasize the need for fraction-based nutrient management strategies that integrate both agronomic efficiency and environmental protection in intensive agricultural soil. Full article

With the occurrence of global climate change and the depletion of agricultural water resources, there is a growing need to develop rapid, non-destructive, and autonomous plant health monitoring systems. As an economically valuable crop, Ocimum basilicum L. (basil) is sensitive to changes in water availability and may exhibit stress-related morphological variations under drought and over-irrigation conditions. However, due to the visual similarity of leaf symptoms under drought stress, waterlogging stress, and optimal irrigation conditions, accurately distinguishing these conditions remains challenging in practical applications. To address this challenge, this paper presents an attention-based dual-branch deep learning framework designed to extract both subtle leaf details and channel-related features from high-resolution plant images. By combining the Convolutional Block Attention Module (CBAM) and Squeeze-and-Excitation (SE) mechanism in a parallel structure, the proposed network improves the analysis of high-resolution images with an input size of 720 × 720 pixels. Under controlled environmental conditions, with ground-truth labels obtained using soil moisture sensor measurements, the proposed model was compared with eight deep learning architectures, including DenseNet121, InceptionV3, and VGG16. The proposed model achieved a hold-out evaluation accuracy of 99.54%, outperforming the second-best model, DenseNet121, which achieved 96.43%. In addition, the proposed model reached a class-specific precision value of 100% for the Drought Stress category and achieved an area under the receiver operating characteristic curve of 1.00 under the controlled experimental setting. Taylor Diagram analysis also indicated that the model closely preserved the variability pattern of the reference data. These results suggest that the proposed application-specific framework may support non-destructive basil water-stress detection under controlled conditions. After further validation with larger datasets, different cultivars, variable environmental conditions, and real-world agricultural scenarios, the proposed approach may contribute to precision irrigation management and sustainable agricultural production. The contribution of this study should be interpreted as an application-specific implementation and evaluation of complementary attention mechanisms for controlled-environment basil water-stress classification, rather than as the introduction of a fundamentally new deep learning methodology. Full article

Soil erosion poses a severe threat to agricultural productivity and ecological security on the Loess Plateau. However, previous studies have rarely integrated physical modeling, elasticity coefficients, and spillover effects into a unified framework at the county level. To address this gap, this study coupled the Revised Universal Soil Loss Equation (RUSLE) with the Spatial Durbin Model (SDM) to systematically investigate the spatiotemporal dynamics, factor elasticity characteristics, and spatial dependence mechanisms of soil erosion on the Loess Plateau from 1990 to 2024. Results show that the annual average erosion rate decreased by 15.5%, with a highly volatile phase before 2001 and a stabilized, low-erosion phase thereafter. The driving factors exhibited marked heterogeneity in direction and strength. The land cover and management factor (C) was the strongest erosion-reducing factor, whereas annual precipitation (PRE) was the primary natural erosion-enhancing factor. County-level erosion also displayed significant positive spatial dependence. PRE had a stable positive indirect effect, whereas C and the support practice factor (P) mainly contained erosion within local jurisdictions. These findings of a unified RUSLE–SDM framework reveal a joint driving mechanism of localized human interventions and climate-driven cross-regional spillovers, providing quantitative support for differentiated soil and water conservation strategies on the Loess Plateau. Full article

Grain for Green, as an important ecological restoration method, profoundly affects soil nitrogen (N) cycling by altering the soil physicochemical properties and microbial community. Soil nitrogen mineralization is a key process in the terrestrial N cycle. However, the dynamics and underlying driving mechanisms of soil N mineralization rate (Rmin) that respond to afforestation remain unclear. In this study, we selected a typical afforestation sequence in Northeast China, including farmland (F), 21-year-old larch plantation (L21), 42-year-old larch plantation (L42), and natural larch forest (NL). The soil Rmin, associated soil physicochemical properties, and microbial community characteristics were determined to explore the effects of afforestation on soil Rmin and its potential mechanisms of action. The results suggested that soil Rmin was ranked in the order of L42 (0.41 mg kg⁻¹ d⁻¹) > F (0.39 mg kg⁻¹ d⁻¹) > L21 (0.23 mg kg⁻¹ d⁻¹) (p < 0.05) along the afforestation sequence, with no significant difference between L42 and F. Compared to the L42, the NL exhibited significantly lower soil Rmin (0.23 mg kg⁻¹ d⁻¹) (p < 0.05). The changes in soil Rmin during the afforestation were significantly positively related to soil total N (TN) and organic carbon (SOC) concentrations, but significantly negatively related to pH (p < 0.05). Furthermore, the abundances of Proteobacteria and Acidobacteria (bacteria) and Ascomycota (fungi) were also closely correlated with soil Rmin. Structural equation modeling (SEM) analysis further indicated that the afforestation mainly regulated soil Rmin by altering soil temperature (ST) and NH₄⁺-N content. Meanwhile, soil NH₄⁺-N content could also exert a significantly positive effect on soil Rmin by influencing the microbial community. In conclusion, afforestation effectively altered soil Rmin, which was even higher in the plantation than in natural forests. This finding further enhances our understanding of forest restoration and land management practices on soil N cycling in temperate regions. Full article

Although foamed lightweight soil is widely used for its light weight and high strength, its insufficient dynamic performance under cyclic loading and the poorly understood reinforcement mechanism have become key bottlenecks restricting its optimized application. To investigate the dynamic characteristics and influencing factors of geogrid-reinforced foamed lightweight soil (GRFLS), laboratory dynamic triaxial tests were conducted using a DJSZ-100D dynamic–static triaxial testing system. The effects of the number of geogrid layers and wet density on the dynamic mechanical properties were examined, with analysis focused on failure patterns, backbone curves, dynamic strength, dynamic shear modulus, and damping ratio. The results indicate that the inclusion of geogrids effectively restrained the propagation of longitudinal cracks in the foamed lightweight soil. The hyperbolic backbone curves were well characterized by the Hardin–Drnevich model. An increase in wet density significantly enhanced the dynamic strength, and an optimal number of two reinforcement layers was identified based on the reinforced strength–stress ratio. The dynamic elastic modulus and damping ratio of GRFLS increased with growing dynamic strain. Compared with the unreinforced condition, the initial dynamic elastic modulus of the specimens with two geogrid layers increased by an average of 15.6%, and the maximum damping ratio increased by an average of 12.9%. While both geogrid reinforcement and higher wet density effectively increased the dynamic elastic modulus, only an increase in wet density notably improved the damping ratio. Finally, predictive models for the enhanced dynamic elastic modulus and damping ratio, which incorporate wet density and the number of reinforcement layers, were established. These models indirectly reflect the dynamic deviator stress–strain relationship of GRFLS. This study provides a theoretical basis for engineering construction. Full article

Picea koraiensis Nakai is a precious tree species in Northeast China with excellent traits, but research on thinning effects on its growth remains limited, especially regarding soil-thinning–growth interactions. This study focused on a 50-year-old Picea koraiensis plantation in the Mengjiagang Forest Farm, Jiamusi. Four thinning intensities were set: CK (no thinning), T1 (10%–20%), T2 (20%–30%), and T3 (40%–50%). Short-term (1–3 years) stand growth, soil properties, microbial biomass, and extracellular enzyme activities were measured, with stand volume and large-diameter timber yield estimated via self-established equations. Results showed that T3 significantly promoted average DBH (1.98 × CK) and tree height growth (1.60 × CK). T2 achieved the highest increases in stand volume (38.07 m³/ha) and large-diameter timber yield (56.02 m³/ha), exceeding other treatments by 1.20–7.12 m³/ha and 5.60–11.64 m³/ha, respectively. Stand growth indices were positively correlated with thinning intensity, soil microbial biomass carbon, and soil C/P ratio; DBH and height also correlated with soil catalase activity. Thinning intensity has a direct effect on stand growth. Meanwhile, observational data show that it is significantly correlated with changes in soil organic carbon fractions and soil extracellular enzyme activity, and these correlations may constitute potential pathways that indirectly affect stand growth. Moderate-intensity thinning (20%–30%) is recommended for scientific tending and large-diameter timber cultivation of middle-aged Picea koraiensis plantations in this region. Full article

Polycyclic aromatic hydrocarbons (PAHs) in farmland soils pose potential ecological and human health risks, yet their contamination characteristics and source-related risks in farmland soils across different river basins in China remain insufficiently understood. This present study analyzed 84 farmland soil samples from northeast (primarily the middle and lower reaches of the Songhua River and Liao River basin), central (primarily the middle reaches of the Yellow River basin and Dongting Lake system), northwest (primarily the middle and upper reaches of the Yellow River and Yarlung Zangbo River basin), and southern (primarily the upper reaches of the Pearl River and Yangtze River basin) China in order to assess the contamination characteristics, sources, ecological risks, and human health risks associated with 16 US EPA priority PAHs in the samples. The findings suggest that the 16 aggregate PAHs’ concentrations in Chinese farmland soils varied from 63.9 to 9637.7 μg/kg, with an average of 1919.3 μg/kg. A gradual decline was observed from north to south, with dibenz[a,h]anthracene (DahA) accounting for the highest proportion at 14.3%. Correlation analysis, principal component analysis, and positive matrix factorization jointly indicated that fossil fuel combustion, high-temperature combustion, and traffic-related emissions were the main PAH inputs to farmland soils. The results of the ecological risk assessment indicated that the northeastern region exhibited the highest PAH ecological risk, with 41.2% of sample plots demonstrating severe PAH contamination. Conversely, the southern region exhibited the lowest PAH ecological risk, with 73.9% of the sample plots demonstrating no ecological risk. The human health risk assessment found that non-carcinogenic risks for both children and adults were within safe limits, while carcinogenic risks for both groups were relatively high. DahA was identified as the primary carcinogen, accounting for 45.9% and 70.3% of the total carcinogenic risk for children and adults, respectively. Oral ingestion was the primary route of exposure. This study provides an integrated basin-scale assessment of PAH contamination and source-related risks in Chinese farmland soils, supporting targeted management of PAH inputs in agricultural environments. Full article

This study investigated the epidemiology and incidence of citrus Huanglongbing (HLB) disease in citron (Citrus medica L.) under varying field conditions. This research specifically aimed to quantify disease severity, assess populations of the primary vector, the Asian citrus psyllid (Diaphorina citri), and identify potential alternative host plants sustaining the vector and the pathogen. Field surveys were executed across three sites characterised by distinct elevations and management practices. Site-level soil nutrient profiles exhibited moderate acidity (pH 4.67–5.74) and significant differences in organic matter and nitrogen. These findings suggest that localised deficiencies in calcium and boron may exacerbate disease severity, contributing to the varied epidemiological patterns observed across sites. Analysis revealed that both HLB disease severity and D. citri population density were significantly influenced by altitude, field condition, and orchard management. The low-elevation site (860 m above sea level (ASL)), characterised by poor maintenance, exhibited the highest mean psyllid populations (averaging 13 individuals per sticky trap per day) and the most severe disease symptoms. Conversely, the high-elevation site (1674 m ASL) displayed significantly lower infection rates and healthier tree conditions. Symptomatic citron trees across all sites consistently exhibited characteristic HLB foliar and fruit symptoms (blotchy mottle and lopsided fruits). Quantitative Polymerase Chain Reaction (qPCR) successfully detected the causal agent, Candidatus Liberibacter asiaticus (CLas), in symptomatic citron samples from all locations, with the highest relative fold-change (2^−ΔΔCt = 4628.24). Crucially, multiple developmental stages of D. citri were observed infesting the common weed Bidens pilosa. Furthermore, qPCR confirmed the presence of CLas DNA within the B. pilosa tissue itself (2^−ΔΔCt = 210.84). This finding constitutes the first field-based evidence that B. pilosa can serve as a novel alternative host that supports both the D. citri vector and the CLas pathogen. These results establish citron as a highly susceptible host and identify B. pilosa as a new, critical epidemiological link in the HLB transmission cycle, thereby underscoring the necessity for integrated, landscape-level disease management strategies. Full article

In recent decades, summer extreme high-temperature (EHT) events in the Sichuan–Chongqing (SC) region of southwestern China have become increasingly frequent under global warming. Carbon dioxide removal (CDR) is considered a key strategy for achieving the temperature targets of the Paris Agreement; however, the response of regional EHT events to CDR remains poorly understood. Based on CN05.1 observations and idealized CO₂ ramp-up and ramp-down experiments from the CMIP6 Carbon Dioxide Removal Model Intercomparison Project (CDRMIP), this study investigates the historical characteristics of summer EHT events over eastern SC and their responses to CDR. The results show that historical EHT events have become more frequent, longer-lasting, and more intense, indicating an overall intensification of regional high-temperature risk. Under idealized CO₂ pathways, regional mean temperature and EHT frequency exhibit pronounced asymmetric and hysteretic responses, with positive anomalies persisting even after CO₂ returns to its initial level. This asymmetric response is closely associated with the enhanced slow oceanic response during the ramp-down period. Stronger El Niño-like and Indian Ocean Dipole-like SST warming intensifies the South Asian High and western Pacific subtropical high, favoring elevated summer temperatures and increased EHT events over eastern SC. Soil moisture also heats the atmosphere by altering the surface latent heat flux in the southwestern part of the study region during ramp-down period. These findings not only improve the understanding of regional extreme event responses in the SC region under carbon neutrality, but also confirm the positive effect of carbon neutrality targets on mitigating regional extreme climate change, thereby highlighting the urgent need to control CO₂ emissions. Full article

Soil stoichiometric characteristics, as sensitive indicators of soil nutrient supply capacity and ecosystem stability, have emerged as a frontier research focus in biogeochemical cycling and ecological studies. However, the spatial variations of soil stoichiometric characteristics and driving factors in desert steppes remain unclear. Therefore, we investigated soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP) contents and their ratios (C:N, C:P and N:P) in desert steppes in the Ili River basin, China. Results showed that: (1) in the Ili River basin, the SOC, TN, and TP contents were 30.27, 0.77, and 0.79 g·kg⁻¹, respectively, while the soil stoichiometry ratios of C:N, C:P, and N:P were 47.33, 35.48, and 1.13, respectively. All indicators demonstrated moderate variability, while soil C:P showed strong variability. (2) Significant seasonal variations were observed in SOC, TN, TP and stoichiometric ratios (p < 0.05), and soil stoichiometric characteristics were positively correlated with elevation. (3) According to Bayesian linear regression models and partial least squares-partial maximum likelihood (PLS-PM) models, climate was the principal driver of soil C, N, and their stoichiometric ratios, with mean annual temperature (MAT) and minimum temperature (Tmin) being the most influential determinants. These findings provide preliminary insights into the spatiotemporal variation patterns of soil chemical characteristics in desert steppe ecosystems of the Ili River basin. This study contributes to a deeper understanding of nutrient cycling processes within desert steppe ecosystems and offers a degree of scientific support. Full article

Urban microtopography plays an important role in regulating soil processes and vegetation performance in newly constructed green spaces, yet its effects on surface runoff, soil nutrients, and plant growth remain insufficiently quantified in urban relocation sites. This study investigated how slope gradient, slope position, and slope curvature influence surface runoff, soil nutrient distribution, and tree growth in Shanghai Expo Cultural Park. Field monitoring was conducted in 36 plots planted with Cinnamomum camphora and Ginkgo biloba in 2017, 2020, and 2024. Microtopographic characteristics were quantified using terrestrial and handheld three-dimensional laser scanning, point-cloud processing, and digital elevation models (DEMs), and plant growth, calculated runoff, and soil physiochemical properties were analyzed using analysis of variance (ANOVA) and regression analysis. Annual DBH increments were greatest on meso slopes (mean = 0.558 cm), followed by gentle slopes (0.513 cm) and abrupt slopes (0.511 cm). Growth was also greater at slope-tail positions than at slope-head positions and greater on concave slopes than on convex slopes. The mean calculated runoff increased from gentle to meso and abrupt slopes, and soil organic matter, total nitrogen, hydrolysable nitrogen, available phosphorus, available potassium, and cation exchange capacity were generally higher at slope-tail positions. These results indicate that micrographic design affects tree growth mainly through runoff-mediated redistribution of water and soil nutrients. These findings provide practical guidance for optimizing microtopographic design, tree species selection, and soil management in urban green spaces established on relocation sites. Full article