Search Results (501)

Mountain stream ecosystems are often considered among the least disturbed freshwater environments; however, increasing land-use pressures may affect their ecological integrity even under apparently high-water quality conditions. This study aimed to assess the relative influence of landscape, physicochemical, and hydromorphological factors on benthic macroinvertebrate communities in three sub-catchments (Ambroz, Jerte, and Tiétar) of the Sierra de Gredos (Central Spain). A total of 33 sampling sites were surveyed, and macroinvertebrate assemblages were analyzed in relation to environmental variables using partial Redundancy Analysis (pRDA) and variance partitioning. All sites were classified as having “Excellent” ecological status based on the Iberian Biological Monitoring Working Party (IBMWP) index. However, multivariate analyses revealed clear spatial patterns and responses to environmental gradients. Results indicated that catchment-scale landscape characteristics defined the pool of potential colonizers, while local physicochemical and hydromorphological conditions acted as secondary filters structuring macroinvertebrate assemblages. Landscape variables explained the largest fraction of variance in community structure (30.6%), followed by physicochemical parameters (29.0%) and hydromorphological indices (24.9%), with a significant shared component (16.5%) indicating interactions among drivers. Agricultural land use, particularly in the Jerte sub-catchment, was associated with shifts in community composition, favoring tolerant taxa such as Diptera, while sub-catchments dominated by natural vegetation supported higher richness of sensitive groups, including Ephemeroptera and Plecoptera. These findings highlight the importance of multi-scale processes in structuring mountain stream communities and reveal limitations of traditional biotic indices in detecting early ecological changes. The results support the integration of catchment-scale variables into ecological assessment frameworks and emphasize the need for preventive, basin-scale management strategies to maintain ecological integrity under increasing anthropogenic pressure. Full article

To investigate the relationship between fishery resources community structure (mainly fish and crustaceans) and environmental factors in the artificial reef waters off Nanri Island, surveys were conducted in November 2021, 2022, and 2023. Shannon–Wiener diversity index (H′), Margalef richness index (D), Pielou evenness index (J′), and resource density index (RD) were employed to characterize the community structure. From 2021 to 2023, DO and petroleum hydrocarbons exhibited significant interannual variation (p < 0.05), whereas DIP, DIN, and SS showed highly significant interannual variation (p < 0.01). Spatially, DO, COD, DIN, and petroleum hydrocarbons varied more than other factors. Both diversity and richness indices rose over the study period, with mean H′ rising from 1.693 to 1.942 and mean D from 2.107 to 2.474. The evenness index (J′) declined in 2022 but then increased to 0.787. In contrast, the resource density index (RD) dropped sharply in 2022 (107.2) and partially recovered in 2023 (155.4), though it remained below the 2021 level (218.5). Redundancy analysis revealed that five environmental variables (DIP, DIN, petroleum hydrocarbons, SS, and DO) primarily shaped the fishery resource community structure in the artificial reef area. This study provided reference data for artificial reef management and sustainable fishery development. Full article

Biological soil crusts (BSCs) play key roles in arid, semi-arid regions and ecological marginal habitats. This study focused on four types of sand-fixing plantations established in 1990 in alpine sandy land (Salix psammophila, SL; Caragana korshinskii, NT; Salix cheilophila, WL; Populus simonii, XYY). Soil samples were collected from bare sand, algae crusts, and moss crusts. Soil particle size distribution, physicochemical properties, and enzyme activity were determined. Then bacterial communities were analyzed using high-throughput (Illumina) sequencing and the correlations among these three factors were examined. The results showed that: (1) From bare sand to algae and moss crusts, the content of fine particles (clay + silt) gradually increased. (2) Soil water content (SWC), nutrients and enzyme activities increased progressively. (3) In the study area, the dominant bacterial phyla of BSCs included Pseudomonadota, Cyanobacteria, Actinobacteriota and Vibrionota. Principal Coordinates Analysis (PCoA) and Analysis of Similarities (ANOSIM) results showed that BSCs drive the differentiation of bacterial communities during succession, while forest stands influence their spatial distribution. (4) Spearman’s correlation and redundancy analysis (RDA) showed that available phosphorus (AP), alkaline hydrolyzable nitrogen (AN), soil organic matter (SOM), catalase (CAT), pH, soil water content (SWC), and alkaline phosphatase (ALP) are key physicochemical factors shaping the bacterial community structure of BSCs. Mantel’s test confirmed that these variables mediated BSCs’ bacterial community structure. This study elucidates the mechanisms underlying ecological restoration via BSCs and provides a theoretical basis for future restoration efforts in alpine sandy land. Full article

Essential oils from aromatic plants are gaining traction as naturally derived preservative and antioxidant ingredients, yet the quantitative relationships between field climate conditions and both oil yield and food relevant bioactivity remain poorly characterised. Here, we characterised the leaf essential oil of Melaleuca bracteata F. Muell. “Revolution Gold” across a complete annual cycle using a fixed plant, multiscale spatio temporal sampling framework. Leaf samples were collected at four seasonal time points (March, June, September, and December) and four diurnal time points (06:00, 12:00, 16:00, and 21:00) from a single field individual in Meizhou, Guangdong, China. Gas chromatography–mass spectrometry (GC-MS) profiling identified 51 volatile constituents, with methyl eugenol dominating the composition (up to 93.67% in summer). Oil yield peaked in summer (2.43 mL kg⁻¹ dry weight) and was lowest in spring (1.28 mL kg⁻¹ dry weight). DPPH radical scavenging and ABTS radical cation decolorisation assays revealed that antioxidant activity was highest in summer harvested oils, with IC₅₀ values of 7.68 mg mL⁻¹ (DPPH) and 8.85 mg mL⁻¹ (ABTS), consistent with peak methyl eugenol accumulation. Permutation-based multiple regression (999 permutations; R² = 0.947) identified seasonal precipitation as the strongest positive predictor of oil yield (β = 11.22, p < 0.05), while temperature exerted a significant negative influence (β = −11.21, p < 0.05). Non-metric multidimensional scaling (NMDS) and permutational multivariate analysis of variance (PERMANOVA) confirmed highly significant seasonal clustering of compositional profiles (F = 15.258, p = 0.001) against negligible diurnal structuring (F = 0.178, p =0.991). Redundancy analysis (RDA) attributed 71.03% of total compositional variance to the climatic predictor set. Pearson correlation analysis established significant positive associations between methyl eugenol content and antioxidant capacity (r > 0.80, p < 0.05). These findings provide an integrated, climate resolved basis for harvest timing optimisation of M. bracteata and identify summer as the strategically optimal harvest window for yield and bioactive functionality. Full article

The need for reliable biological indicators to support soil biomonitoring is increasing, particularly in agricultural systems where management practices and environmental pressures interact to influence soil ecological integrity. Among soil fauna-based indicators that measure soil health, the Soil Biological Quality indices based on microarthropods (QBS-ar) and earthworms (QBS-e) provide functional measures of soil condition, however their combined application remains largely unexplored. In this study, for the first time both indices were applied simultaneously to assess soil biological quality in the same agroecosystem. The context was that of contrasting agricultural systems (strip cropping vs. pure stands) in a real-farm experimental set-up. Additional biological variables and soil physico-chemical parameters were also considered. Statistical analyses included Spearman correlations, linear mixed-effect models (LMMs), and redundancy analysis (RDA). QBS-ar and QBS-e showed contrasting responses to management systems, with higher QBS-ar values under strip cropping and higher QBS-e values in pure stands. No significant relationship was observed between the two indices. Multivariate analyses indicated that both indices were significantly influenced by management and environmental variables, although with different patterns of association. QBS-ar appeared more responsive to variation in topsoil conditions, whereas QBS-e was associated with broader soil properties and seasonal community dynamics. These results indicate that QBS-ar and QBS-e capture complementary aspects of soil biological quality and should not be used interchangeably. Their combined use improves the interpretation of soil biological responses to agricultural management and associated environmental pressures. Overall, this study highlights the potential of soil fauna-based indices as practical tools for biomonitoring in agroecosystems and supports further exploration on the comparative responses of biological indexes. Full article

Dams are widely distributed in global water bodies and cause severe impacts on aquatic ecosystems. In this study, the Sizao River Basin was selected to explore the effects of dams on the macroinvertebrate community, including functional feeding groups (FFGs). Macroinvertebrate communities and environmental variables were monitored seasonally in April, August, October, and November of 2025. A total of 27 taxa were identified, including 3 phyla, 8 orders, and 15 families. Species richness, abundance, biomass, species diversity, and FFGs diversity in the gate-regulated section were generally lower than those in other river sections. Gatherer–collector dominated FFGs across the Sizao River Basin and accounted for most of the dominant species. An ecosystem assessment based on FFGs suggests that ecosystem attributes of macroinvertebrate communities were fragmented. The longitudinal spatial distribution of FFGs was roughly in line with the predications of the river continuum concept. Redundancy Analysis (RDA) indicated that the permanganate index (COD_Mn) and dissolved oxygen (DO) were major environmental variables affecting macroinvertebrate community structure, and DO and salinity (SAL) were major variables affecting FFGs. The explanatory power of RDA for FFGs was higher than that for macroinvertebrate community structure. These findings provide valuable insights into protecting aquatic ecosystems in gate-regulated water bodies. Full article

Glomalin-related soil protein (GRSP) is pivotal for sustaining soil organic carbon (SOC) stability in tropical forest ecosystems. Nevertheless, how SOC stability responds to altitude and soil layer variations, as well as the quantitative contributions of GRSP to SOC and soil nitrogen, remain poorly understood in lowland tropical forests. Here, we conducted a field-based investigation to characterize the distribution patterns of SOC, readily oxidizable organic carbon (ROC), GRSP, and other key soil physicochemical properties across different soil layers. We further comprehensively evaluated the SOC stability and quantified the contributions of GRSP to soil C and N pools at two altitudes in a lowland tropical forest. The results revealed that altitude exerted a significant effect on SOC contents, with substantially higher SOC stability observed at the high altitude (400 m) relative to low altitude (100 m). Vertically, SOC and ROC contents were significantly higher in the surface soil layer (0–20 cm) than in the deep layer (20–100 cm), while deep soil exhibited stronger SOC stability compared with surface soil. The contributions of GRSP to SOC and total N (TN) varied distinctly across altitudes and soil layers: GRSP contributed more substantially to SOC and TN at low altitude than at high altitude, and its contribution was also greater in surface soil than in deep soil. Both easily extractable (EE-GRSP) and total GRSP (T-GRSP) were significantly positive correlated with ROC, SOC, and TN (p < 0.05). Redundancy analysis (RDA) further indicated that the ROC served as the primary regulatory factor governing the variation in SOC, EE-GRSP, and T-GRSP at both altitudes. Additionally, soil available phosphorus (AP) and C/P also drove the SOC and GRSP at low altitude, while pH, TN, and C/N regulated the SOC and GRSP at high altitude. Therefore, we propose that the altitudes and soil layers synergistically modulate the SOC stability and the contributions of GRSP to SOC in lowland tropical forests. These findings highlight the necessity of incorporating altitude and soil layer heterogeneity into evaluation and modeling of carbon cycles in tropical forests. Full article

Eukaryotic organisms play a critical role in maintaining agricultural ecosystem functions and crop health. Irrigation practices and water salinity significantly affect eukaryotic communities, yet the interactive effects of drip irrigation depth and water salinity on these communities remain unclear. This study aimed to investigate the interactive effects of drip irrigation depth and water salinity on the diversity, community structure, and functional groups of winter wheat rhizosphere eukaryotes, and to examine their relationships with soil environmental factors. A two-year field experiment was conducted in Cangzhou, Hebei Province, with two drip irrigation depths (5 cm shallow, 25 cm deep) and two irrigation water salinity levels (2 g·L⁻¹, 3 g·L⁻¹). High-throughput sequencing was used to analyze rhizosphere microbial communities, and α/β diversity, species composition, LEfSe differential analysis, and redundancy analysis (RDA) were performed to assess the effects of environmental factors. Results showed that both irrigation depth and water salinity significantly influenced α/β diversity and community structure of soil eukaryotes. The 5 cm shallow + 2 g·L⁻¹ salinity treatment favored species richness, while the 25 cm deep + 3 g·L⁻¹ treatment promoted community evenness. Dominant taxa responded selectively, with Annelida markedly suppressed and groups such as Streptophyta and Chytridiomycota enriched under different treatments. Network analysis revealed that key microbial taxa occupied central positions in interspecies interactions. RDA indicated that soil pH, nitrogen, potassium, and organic matter were important drivers of community structure. In conclusion, drip irrigation depth and water salinity synergistically shape soil eukaryotic community structure. These findings provide a scientific basis for optimizing drip irrigation depth, utilizing brackish water, and enhancing agricultural ecosystem functions. Full article

Pollutants often exist in tailings and surrounding areas as complex mixtures, and the resulting combined effects make it difficult to identify the primary target pollutants, particularly common inorganic anions. To address this, high-throughput 16S rRNA gene sequencing was used to characterize the microbial community structure in groundwater around rare earth tailing ponds, and multivariate statistical analyses were applied to link community patterns to specific environmental variables. A total of 14 groundwater samples were collected from seven sites (two spatial replicates per site) along a contamination gradient. The results showed distinct differences in microbial community composition between the control site and the tailing-pond-impacted sites. Nitrosomonas was the dominant genus at highly contaminated sites, while halotolerant genera such as Seohaeicola, Pusillimonas, and Oceanibaculum also showed elevated relative abundances. Redundancy analysis (RDA) with forward selection identified the co-occurring elevated concentrations of NH₄⁺ and SO₄²⁻ (originating from tailing pond leachate) as the environmental variables most strongly associated with microbial community structure (p < 0.05). In contrast, the microbial community at the control site WLJ-5, located farthest from the tailing pond, was markedly different. These findings suggest that shifts in microbial community composition and the prevalence of specific microorganisms may serve as potential bioindicators to assist in identifying the dominant contaminant types in groundwater around rare earth tailing ponds. Full article

Background: Toddaliae Asiaticae Radix (TA) boasts a long history of medicinal application. However, origin traceability and quality assessment of the widely distributed original plant Toddalia asiatica have not been fully elucidated. Methods: A hybrid framework integrating targeted metabolomics, network pharmacology (NP), and machine learning (ML) was established. By optimizing key parameters, a high-coverage and rapid method for multiple categories compounds was developed using ultra-high performance liquid chromatography-multiple reaction monitoring tandem mass spectrometry (UPLC-MRM MS/MS). Using samples collected across 16 geographical regions, redundancy analysis (RDA) and pattern recognition techniques were applied to explore environment-sensitive metabolites. Taking into account five types of diseases, NP analysis was employed to obtain the bioactive components and their contribution weight in disease treatment. Subsequently, core Quality Markers (Q-Markers) with dual functions of responsive to geographic variations and biologically relevant to therapeutic efficacy were figured out, and were used to establish origin scoring model and discrimination model. Results: The geographical metabolic characteristics of the TA from broad regions in China were thoroughly analyzed, and 60 geographically sensitive compounds were identified. Through NP analysis, 27 core Q-Markers were locked. The bioactivity-weighted scoring model based on Q-Markers revealed the consistency of regional rankings as well as minor fluctuations across five diseases. ML demonstrated that the Q-Markers preserved regional discrimination performance, and the introducing of practical-oriented weights enhanced overall discriminative confidence. Conclusions: This research decodes the Geographical metabolic characteristics of TA, and highlights the necessity of function-oriented prioritization of drug resources. Full article

Tillage practices can change the soil environment (including soil properties and enzyme activity) and the rhizosphere microbial community, thereby inducing changes in root growth and the nutrient uptake capacity. This study was carried out on a long-term (since 1983) tillage field experimental platform. It aimed to explore the effects of tillage practices and growth stages on maize root development, soil properties, and the rhizosphere microbial community. The results can provide a theoretical basis for the further analysis of crop–soil–microbial interactions. In our study, we investigated the abundance and diversity of the rhizosphere microbial community and their relationship with root growth characteristics and soil factors under long-term (since 1983) conventional tillage (CT), subsoil tillage (ST), and no-tillage (NT) practices using quantitative PCR and high-throughput 16S/ITS sequencing. In 2020, at the 30-days-after-silking (VT 30) stage, NT increased the root length, root dry weight, N accumulation, and N uptake rate of maize roots compared with CT by 16.7%, 16.3%, 41.9%, and 41.9%, respectively. In 2020, at the 12th leaf (V12) and VT 30 stages of maize, NT significantly increased the contents of soil total nitrogen (by 16.3% and 11.0%, respectively), total carbon (by 23.9% and 12.9%, respectively), soil organic matter (by 24.8% and 10.3%, respectively), and soil urease activity (by 5.5% and 5.6%, respectively) compared with CT. Moreover, NT significantly increased the bacterial and fungal abundances compared with CT. Redundancy analysis (RDA) showed that the variation in the microbial structure correlated markedly with the alteration in root indicators, soil properties, and enzyme activities. Long-term no-tillage improved the abundance and diversity of rhizosphere microbial communities by increasing the soil total nitrogen, total carbon, and soil organic matter, and promoted the N accumulation of roots and their uptake rate. Full article

Essential amino acids and unsaturated fatty acids are key nutritional indicators. The human body preferentially absorbs these compounds, which have beneficial effects on health. In aquatic ecosystems, plankton communities serve as the primary food source for aquatic organisms, playing a crucial role in shaping their nutritional composition. In this study, we collected populations of Macrobrachium nipponense and corresponding water samples from ten distinct geographical locations across China. These sites included five freshwater resources and five saline–alkaline water resources. This study measured the ionic composition and plankton community structure of water samples, and analyzed the nutritional components of M. nipponense, aiming to identify indicator taxa linked to the nutritional value in this species. The results show significant differences in both nutritional components and plankton community structures between freshwater and saline–alkaline environments. This suggests a correlation between specific plankton taxa and the nutritional value of M. nipponense. Using relative sequence abundance data from metabarcoding, linear discriminant analysis effect size (LEfSe) analysis identified six plankton indicator taxa at the genus level. Their abundance differed significantly between the two habitat types. The saline–alkaline region had three associated taxa: Cyclotella, Brachionus, and Chaetoceros. In contrast, Arctodiaptomus, Cryptomonas, and Limnoithona were identified as indicator taxa for freshwater regions. Redundancy analysis (RDA) and Pearson correlation analysis revealed that, with the exception of the SY site, the abundance of Chaetoceros and Brachionus in saline–alkaline waters tracked with levels of K⁺, Ca²⁺, and HCO₃⁻. Meanwhile, at the SZ site, plankton community richness rose with CO₃²⁻. Furthermore, the potential correlations between plankton indicator taxa and the formation of specific nutritional components in M. nipponense were explored. These findings highlight the complex interactions among ionic composition, plankton indicator taxa, and nutritional value in M. nipponense. Ultimately, this study can support the development of artificial techniques to regulate the nutritional components of this commercially important species. Full article

Thermophilic microbial inoculant (CI) has been demonstrated to optimize the green waste composting (GWC) process. The pathways through which it enhances lignocellulose degradation remain unclear. This study evaluated composting performance under four treatments: CI, effective microorganisms (EM), Phanerochaete chrysosporium (WF), and natural composting (CK). To elucidate the biological differences between efficient lignocellulose-degrading systems and CK, metagenomic analyses were conducted on CI and CK based on lignocellulose degradation rates. The results indicated that CI inoculation did not negatively affect the compost heating process and produced a nitrogen-rich, safe, and mature compost product. Compared to other treatments, CI increased the lignocellulose degradation rate by 3.66% to 31.8%. Metagenomic analysis revealed that CI inoculation enriched genes encoding glycoside hydrolases (GHs), glycosyl transferases (GTs), carbohydrate esterases (CEs), and carbohydrate-binding modules (CBMs) across multiple composting phases, positively impacting dominant carbohydrate-active enzyme (CAZyme) families including AA3, CE1, and CE7. CI inoculation also elevated the relative abundance of lignocellulose-degrading microorganisms (0.70~2.73%), simplified microbial network structure, and strengthened microbial cooperation. Within the microbial network, Chryseolinea, Protaetiibacter, and unclassified_f__Burkholderiaceae were identified as core taxa involved in lignocellulose degradation. Redundancy analysis (RDA) identified temperature as the primary factor influencing biological factors, with CI improving composting efficiency by optimizing the microenvironment. Collectively, this work provides a novel strategy for microbial inoculant application in composting and offers new perspectives for identifying core taxa, contributing to advancing composting efficiency. Full article

Rising temperatures, driven by global climate change, are profoundly altering high-latitude ecosystems, influencing vegetation phenology and productivity. However, understanding the long-term, nuanced responses of these ecosystems remains a critical challenge. Soil warming experiments have served as useful tools for understanding these shifts. However, many of these studies have relied on a single measure, predominantly the Normalized Difference Vegetation (NDVI), measured at a single level of warming. This approach often fails to separate structural greening from underlying physiological responses. To address these gaps, this study provided a comprehensive snapshot assessment of growing season vegetation dynamics in a subarctic grassland ecosystem in Iceland that had been exposed to continuous geothermal soil warming for over 60 years. Using high-resolution multispectral drone imagery, twelve different vegetation indices (VIs) were derived to assess not only greenness but also physiological stress and photosynthetic efficiency across a range of mean annual soil temperatures (MATs). Using linear regression and redundancy analysis (RDA), the responses of these indices to warming and their relationships with other environmental drivers, such as standing biomass and plant nutrient concentrations (nitrogen and phosphorus), were analyzed. The results revealed significant positive linear relationships between most of the indices and MATs across the 5 to 11 °C range. This indicated that higher MATs led to increased biomass and structural growth, without revealing any significant thresholds or tipping points in vegetation response within the observed warming range. However, the Photochemical Reflectance (PRI) showed a significant negative relationship with warming, suggesting a decoupling between structural greening and photosynthetic light-use efficiency. Furthermore, RDA results indicated that, while most of the VIs were primarily driven by biomass, the decline in PRI was likely a compounding effect of physical canopy self-shading and plant phosphorus constraints. Ultimately, this study demonstrated that, while these subarctic grasslands exhibited local evidence of “Arctic greening” under further warming, multispectral drone remote sensing could detect underlying physiological adjustments and nutrient constraints that traditional greenness indices might overlook, providing a more nuanced understanding of ecosystem response. Full article

Litter decomposition regulates the quantity and quality of plant-derived carbon (C) and nitrogen (N) inputs to soil and is closely associated with microbial community structure. However, how elevated ozone (O₃) and nitrogen (N) addition interactively affect residual litter inputs and their associations with soil microbial communities remains poorly understood, especially in agroforestry systems. Here, we conducted a 12-month in situ litter decomposition experiment using two poplar clones (107 and 546) under ambient or elevated O₃ with or without N addition (60 kg N ha⁻¹ yr⁻¹) at an O₃-FACE platform in northern China. Litter mass and chemical traits were measured during decomposition, and endpoint soil microbial community structure was characterized using phospholipid fatty acid (PLFA) profiling. Treatment effects and litter–microbe associations were evaluated using linear mixed-effects models, correlation analysis, and redundancy analysis (RDA). Endpoint litter mass remaining was significantly affected by O₃, clone identity, and their interactions with N addition, while endpoint litter chemical traits showed trait-specific responses. PLFA-derived microbial community indices also showed treatment- and clone-dependent responses, particularly in bacterial groups, AM fungi, and the fungal-to-bacterial ratio. Endpoint litter mass remaining showed the strongest statistical association with PLFA-derived microbial community structure, whereas individual nutrient concentrations showed weaker independent effects. These findings suggest that O₃- and N-induced changes in residual litter quantity and quality are associated with shifts in PLFA-derived microbial community structure. Because PLFA characterizes microbial community structure rather than process rates, these findings should be interpreted as evidence of structural microbial reorganization associated with altered residual litter inputs, rather than direct evidence of changes in C or N cycling rates. Full article