Study region: The Daliyabuyi Oasis at the terminal of the Keriya River, China. Study Focus: Water scarcity acts as the primary limiting factor for vegetation growth in arid regions. However, studies on the response of desert vegetation to changes in water conditions remain limited. This study used stable isotope method combined with the MixSIAR model, and stem sap flow measurement methods to analyze the seasonal variations in water use patterns and transpiration of vegetation under different water conditions. New hydrological insights: The results showed that as the groundwater depth increased, the water use pattern of Populus euphratica (p. euphratica) trees shifts from shallow soil water to deep water sources. Compared with the shallow groundwater depth sample plots, the proportion of shallow soil water use by p. euphratica in the deep groundwater depth sample plot decreased by 16.66%, while the use of near-groundwater layer soil water and groundwater increased by14.23% and by13.07%, respectively. The influence of tree age on the water use pattern is weak. Throughout the growing season, transpiration of P. euphratica gradually increased from May to July and decreased from August to October.The daily average transpiration of large and small trees was 87.43 L & sdot;d-1 and 11.24 L & sdot;d-1 , respectively. Meanwhile, as transpiration of p. euphratica increased, groundwater use significantly increased. Compared with May, the use of groundwater by p. euphratica in July increased by 26.64%. In addition, flood replenishment increased shallow soil water use by p. euphratica (12.05%), and enhanced transpiration. This study provides insights into water use and adaptability of p. euphratica.

Populus euphratica is a key constructive species in desert ecosystems and plays a vital role in maintaining their stability. However, effective automated methods for accurately delineating its distribution outlines are currently lacking. This study used the mainstream area of the Tarim River as a case study and proposed a technical solution for identifying the distribution outline of Populus euphratica using multi-source thematic classification data. First, cropland thematic data were used to optimize the accuracy of the Populus euphratica classification raster data. Discrete points were removed based on density to reduce their impact on boundary identification. Then, a hierarchical identification scheme was constructed using the alpha-shape algorithm to identify the boundaries of high- and low-density Populus euphratica distribution areas separately. Finally, the outlines of the Populus euphratica distribution polygons were smoothed, and the final distribution outline data were obtained after spatial merging. The results showed the following: (1) Applying a closing operation to the cropland thematic classification data to obtain the distribution range of shelterbelts effectively eliminated misclassified pixels. Using the kd-tree algorithm to remove sparse discrete points based on density, with a removal ratio of 5%, helped suppress the interference of outlier point sets on the Populus euphratica outline identification. (2) Constructing a hierarchical identification scheme based on differences in Populus euphratica density is critical for accurately delineating its distribution contours. Using the alpha-shape algorithm with parameters set to α = 0.02 and α = 0.006, the reconstructed geometries effectively covered both densely and sparsely distributed Populus euphratica areas. (3) In the morphological processing stage, a combination of three methods—Gaussian filtering, equidistant expansion, and gap filling—effectively ensured the accuracy of the Populus euphratica outline. Among the various smoothing algorithms, Gaussian filtering yielded the best results. The equidistant expansion method reduced the impact of elongated cavities, thereby contributing to boundary accuracy. This study enhances the automation of Populus euphratica vector data mapping and holds significant value for the scientific management and research of desert vegetation.

Riparian ecosystems in arid regions are affected by the dynamics of both surface-and groundwaters. However, understanding the dynamics and interactions of surface-and shallow groundwaters on vegetation within extremely arid desert oases remains challenging, in part because of a paucity of monitoring data. This study examined hydrologic-vegetation interactions in the Daliyaboyi Oasis, in the Taklimakan Desert, China. Specifically, daily variations in depth to groundwater (DTG) were collected in the oasis from 2013 to 2018 in four shallow groundwater wells. Monthly values of the Automated Water Extraction Index (AWEInsh) and the Normalized Difference Vegetation Index (NDVI) were also extracted from Landsat imagery during this six-year period. During summer and autumn flood seasons, the DTG decreased synchronously with flood events, indicating that surface water recharged groundwater. Conversely, during winter and spring, DTG generally reach an intra-annual minimum while surface waters were at their lowest level, suggesting that groundwater replenishes surface water. The maximum change in the DTG was 0.97-3.30 m during summer and autumn and 1.36-2.40 m during winter and spring. Vegetation predominantly expanded toward the northwest, in conjunction with changes in surface water, indicating that surface water exerts a beneficial effect on vegetation growth. Human induced alterations in surface water areas did not change the timing of intra-annual peaks and lows in surface water areas. The correlation between DTG and NDVI was predominantly affected by groundwater recharge and the degree of anthropogenic influence. Under natural hydrological conditions, vegetation was strongly reliant on groundwater; however, this dependence diminishes in regions subjected to significant human activity. The optimal DTG for vegetation growth was 3-4 m. The ecological response of dominant vegetation (Populus euphratica) lags behind increases in surface water and decreased DTG by approximately one year. This study addresses the limitations resulting from the absence of groundwater monitoring data in previous research, providing novel perspectives and insights into the hydrological and ecological processes of the Keriya River Basin and the extremely arid desert oases globally.

Populus euphratica is a critical constructive species in arid desert regions, serving as a “natural barrier” for oasis protection. The sustainable management of Populus euphratica forests is directly related to regional ecological security, and the fine identification of sparse Populus euphratica forests is essential for the conservation of natural Populus euphratica forests. Currently, most mapping studies on Populus euphratica distribution focus on the extraction of dense, contiguous Populus euphratica forests, with insufficient attention paid to the identification of sparse Populus euphratica forests. This study utilizes Gaofen-2 (GF-2) satellite imagery as the data source and takes a typical sparse Populus euphratica forests distribution area in the Tarim River Basin as the study site. It systematically evaluates the performance of nine mainstream deep learning models, including U-Net, DeepLabV3+, and SegFormer, in the task of sparse Populus euphratica forests identification. The results indicate that: (1) The false-color sample set, synthesized from near-infrared, red, and green bands, contributes to improved model accuracy. Compared to the true-color (red, green, blue bands) dataset, the average Intersection over Union (IoU) of the nine models shows a relative improvement of approximately 20%. (2) For the sparse Populus euphratica forests identification task based on the false-color dataset, four models—U-Net, U-Net++, MA-Net, and DeepLabV3+—exhibited excellent performance, with IoU exceeding 75%. (3) Using U-Net as the baseline model, this study integrated the max-pooling indices mechanism, atrous spatial pyramid pooling, and residual connection modules to construct a semantic segmentation network tailored for sparse Populus euphratica forests, named Sparse Populus euphratica Segmentation Network (SPS-Net). This model achieved an IoU of 80%, a relative improvement of approximately 6.3% over the baseline model, and demonstrated good stability in large-scale classification tests. The identification scheme for sparse Populus euphratica forests constructed using GF-2 imagery and deep learning models proposed in this study can provide effective technical support for the refined monitoring and protection of natural Populus euphratica forests.

Dryland soils of the Caspian region of western Kazakhstan are exposed to environmental stress, including drought, alkalinity, low soil organic matter content, and anthropogenic pressure. In this preliminary study, bacterial communities were investigated in 18 soil samples collected from six sampling groups across Makat (M1, M2), Isatay (I1, I2), and Beyneu (B1, B2) districts. Soil physicochemical properties were measured, and bacterial diversity was analyzed using 16S rRNA gene sequencing of the V3-V4 region. Community composition analysis indicated spatial heterogeneity among the sampled groups. M1 and I1 showed the highest taxon richness, whereas B2 contained the highest number of unique taxa. Genus-level profiles showed that B1 and M2 were mainly associated with Rubrobacter and related actinobacterial taxa; B2 contained higher proportions of Marinobacter, Tychonema, Qipengyuania, and Halomonas; and I2 was enriched with Antarcticibacterium, Salinimicrobium, Rhodococcus, Gillisia, Marinobacter, Dietzia, and Pontibacter. Correlation analysis showed that several bacterial taxa were associated with soil organic matter content, total nitrogen, total phosphorus, exchangeable cations, and pH, although the overall Mantel relationship between soil properties and community structure was not significant. FAPROTAX-based prediction indicated differences in putative heterotrophic, nitrogen-related, sulfur-related, and hydrocarbon-associated functional categories among sites. Because FAPROTAX predictions are based on taxonomic composition, these results should be interpreted only as putative functional potential and not as evidence of actual microbial metabolic activity. These findings suggest that the sampled Caspian dryland soils contain distinct bacterial assemblages and taxa with potential ecological relevance; however, their role in dryland soil resilience or bioremediation should be verified through future culture-based, metagenomic, and functional validation studies.

The toxic effects of soil heavy metals and microplastics on plants have been extensively documented, with some researchers having conducted studies exploring the combination of these two factors. Preliminary findings indicate that their combined action can “reduce biomass, exacerbate oxidative stress, and inhibit photosynthesis,” and the potential mechanisms of this combined toxicity are currently being explored. However, these combined effects remain unclear, with conflicting conclusions across studies. Research subjects are relatively fragmented, and systematic summaries are lacking. This paper systematically reviews current research findings on the combined toxic effects of microplastics and Cd on plants, specifically focusing on the following factors: (1) the mechanisms and influencing factors of Cd adsorption by microplastics: electrostatic adsorption is the primary mechanism, and soil environmental factors are significant influencers; (2) microplastics’ altering of the available Cd content in soil: soil environmental conditions can be modified to increase or decrease available Cd concentrations; (3) The “synergistic or antagonistic” toxic effects of microplastics and Cd on plants. Future research directions warranting in-depth investigation are also identified in this study.

Micro- and nanoplastics (MNPs) are a new type of pollutant that are widely present in terrestrial ecosystems due to agricultural plastics, sludge use, deposition, and litter degradation. Plants can absorb them through the soil and atmosphere, with adverse effects on plant growth and development. Several studies have reported the effects of MNPs on plant physiology, biochemistry, and toxicity. However, the food chain risk of plant uptake of MNPs has not been systematically studied. This review synthesizes current research on plant MNP pollution, focusing on the uptake and transport mechanisms of MNPs by plants, influencing factors, and health hazards. The size, type, and surface charge characteristics of MNPs, as well as environmental conditions, are key factors affecting MNP absorption and accumulation in plants. Furthermore, when MNP-enriched plants are consumed by humans and animals, the accumulated MNPs can diffuse through the bloodstream to various organs, impairing physiological functions and causing a range of health problems. While a comprehensive, traceable investigation of the transmission of MNPs through the terrestrial food chain remains unconfirmed, health risk signals are unequivocal—dietary intake is the primary route of human exposure to MNPs, with direct evidence of their bioaccumulation in human tissues. Addressing this critical research gap, i.e., systematically verifying the full terrestrial food chain translocation of MNPs, is therefore pivotal for conducting robust and comprehensive assessments of the food safety and health risks posed by MNPs. This study analyzed a total of 154 literature sources, providing important theoretical insights into the absorption, transport, and accumulation of MNPs in plants, as well as the health risks associated with their transfer to humans through the food chain. It is expected to provide valuable reference for the research on the transfer of MNPs in the “soil-plant-human” chain.

Abstract Populus euphratica, the only native tree species along the Tarim River, is ecologically crucial for stabilizing landscapes and conserving biodiversity in arid region. However, its irregular canopy structure and sparse distribution complicate large-scale forest assessments. To overcome this, we developed a two-stage random forest model integrating backpack and unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR) data covering 10,143 plots of (30 m × 30 m), satellite imagery, and environmental variables. First, we derived structural attributes: leaf area index (R2 = 0.83, RMSE = 0.21), canopy cover (R2 = 0.80, RMSE = 0.07), foliage height diversity (R2 = 0.76, RMSE = 0.28), and canopy height (R2 = 0.67, RMSE = 2.04 m). Spatially, these attributes exhibited a general decreasing trend from the upper to the lower reaches, with reductions in their mean values ranging from 17.8% (canopy height) to 30.7% (foliage height diversity). These were then used to estimate aboveground biomass (R2 = 0.78, RMSE = 32.91 Mg ha–1). Our approach generated the first 30m-resolution continuous maps of Populus euphratica structure and biomass across the 1,321 km Tarim River basin. Total aboveground carbon stock was 73.50 Tg C, with a mean density of 65.93 ± 21.80 Mg C ha–1. Validation against forest inventory data confirmed superior performance over global biomass products (rRMSE = 36.26%). This study can provide fundamental data and theoretical support for the monitoring, management, and conservation of riparian forests in arid regions.

As the largest desert in China, the Taklimakan Desert features unique mobility and alternating mega-dune and inter-dune landscapes with rich dune types. Most areas of the sand sea were explored in the early 20th century. However, the eastern Taklimakan Desert characterized by extremely tall dunes, had received little attention until 2022 owing to transportation inconveniences. This study examined the alternating mega-dune and inter-dune landscapes in the eastern Taklimakan Desert, through spatial analysis and field surveys. Results demonstrate that the tallest mega-dunes are distributed primarily to the east of the central desert, with the occurrence of approximately 240 mega-dunes exceeding 150 m in height. The height-spacing relationship of mega-dunes with different orders exhibits a weak correlation, suggesting that the dune formation and evolution are more complex than previously documented; this could be attributed to the factors other than solely the wind regime. Additionally, from the field survey, we found that sand availability is the dominant factor for constraining the sustained growth of mega-dunes. A pattern coarsening may be responsible for the development of the dune fields in the eastern Taklimakan Desert, thus yielding constraints on the development of mega-dunes, and other dune fields on Earth as well.

Climate warming and human activities have altered water resource distribution in desert areas, accelerated water infiltration and evaporation, disrupted the water cycle, and increased drought stress in riparian forests. However, the effects of climate varying environmental conditions on intrinsic water use efficiency (iWUE) and tree growth in Populus euphratica Oliv. remain unexplored. Using tree-ring width and δ13C composition data, we analyzed the growth and iWUE of P. euphratica across three sample plots with varying groundwater depths in the Daliyaboyi Oasis. We found that P. euphratica basal area increment (BAI) and iWUE significantly increased across all sampling plots from 1980 to 2003 with no significant changes from 2004 to 2022. In the shallow-groundwater sample plot, P. euphratica BAI and iWUE were significantly positively correlated with temperature (TEM), vapor pressure difference (VPD), and runoff (RO) and significantly negatively correlated with relative humidity (RH). Conversely, in the deep-groundwater sample plot, P. euphratica iWUE was significantly and positively correlated with RH and negatively with VPD. The correlation between the intercellular and atmospheric CO2 concentration ratio (Ci/Ca) and meteorological factors shifted from non-significant to significant with increasing groundwater depth. Ci/Ca variations in P. euphratica were significantly positively correlated with TEM, VPD, and RO and significantly negatively correlated with RH. Thus, with continued climate warming, P. euphratica in deep-groundwater sample plots may face severe drought stress and growth declines in the future. Understanding the dynamic relationship between iWUE and BAI under varying environmental conditions is crucial for predicting forest responses to climate change and informing conservation strategies.

Drought stress limits plant survival and yield in arid regions. Uncovering the molecular mechanisms of drought tolerance is key to developing resilient crops. This study used Arabidopsis thaliana as a model to perform an in silico analysis of miRNA-mRNA interactions linked to post-transcriptional drought response. Using the MirTarget program, 274 miRNAs and 48,143 gene transcripts were analyzed to predict high-confidence miRNA-mRNA interactions based on binding free energies (-79 to -129 kJ/mole). Predicted binding sites were located in the CDS, 5'UTR, and 3'UTR regions of target mRNAs. Key regulatory interactions included ath-miR398a-c and ath-miR829-5p targeting ROS detoxification genes (CSD1, FSD1); ath-miR393a/b-5p and ath-miR167a-c-5p targeting hormonal signaling genes (TIR1, ARF6); and the miR169 family, ath-miR414, and ath-miR838 targeting drought-related transcription factors (NF-YA5, DREB1A, WRKY40). Notably, ath-miR414, ath-miR838, and the miR854 family showed broad regulatory potential, targeting thousands of genes. These findings suggest the presence of conserved regulatory modules with potential roles in abiotic stress tolerance. While no direct experimental validation was performed, the results from Arabidopsis thaliana provide a useful genomic framework for hypothesis generation and future functional studies in non-model plant species. This work provides a molecular foundation for improving drought and salt stress tolerance through bioinformatics-assisted breeding and genetic research.

Populus euphratica is a crucial foundation species within desert riparian forests in Central Asia and an important component of desert carbon sinks. However, these forests currently face significant threats of widespread decline. To quantitatively investigate the relationship between environmental changes and the health of P. euphratica on a large scale, this study combined a UAV deep learning model with GF-2 satellite imagery to achieve high-precision extraction of P. euphratica, with an extraction accuracy of 91.5%. Subsequently, spatial distributions of nine environmental factors, including soil moisture, salinity, and groundwater depth, were derived using random forest models, to quantify the importance of each factor. The results indicated that suitable habitats for P. euphratica were primarily concentrated where water availability was moderate and salinity was moderate. The growth of P. euphratica is constrained by the combined stresses of limited water availability and salinity. Groundwater depth, surface water distribution, and soil moisture collectively accounted for 66.4% of the influencing factors while electrical conductivity and sodium ion concentrations accounted for an additional 20.4%. Excessive salinity significantly increased branch mortality and cavity rates and reduced the crown width to diameter ratio, indicating potential structural damage and reduced vitality due to salinity stress. This study systematically quantified the comprehensive impact of water-salt gradients on multiple growth indicators of P. euphratica. The findings enhance our understanding of vegetation dynamics in the Taklamakan Desert, provide scientific evidence for the management of oasis vegetation and water resources in arid regions, and emphasize the importance of considering the water-salt balance during ecological water transfers.

Climate change is affecting hydrological processes and water resources in Northwest China. However, this constitutes a challenge to drought adaptation strategies for desert oasis vegetation. This study used dendrochronological methods to analyzed the relationship between the radial growth of Populus euphratica and environmental factors at eight sample sites in the Taklamakan Desert with different groundwater depths and discussed the resistance and recovery of P. euphratica to drought. The results showed that the tree-ring width index (TRI) of P. euphratica showed a gradual increase but the rate of increase decreased with increasing of groundwater depth. Correlations between P. euphratica TRI and streamflow, temperature, and precipitation were significant in the shallow groundwater sample sites, whereas correlations were not significant in the deep groundwater sample sites. In deep groundwater sample sites, the correlation between TRI and palmer severity drought index (PDSI) was significant and the variations in PDSI and TRI were similar, indicating that TRI was closely related to the water supply and demand relationship of the sample sites. As the depth to groundwater and the intensity of drought increased, the resistance of P. euphratica decreased and its recovery increased. In summary, the response of P. euphratica radial growth to climate factors, change in growth rate, ecological resilience in the Daliyaboyi Oasis depend on changes in the habitat's hydrological environment. Revealing the response of P. euphratica radial growth to drought under different hydrological conditions can provide basic guidance for ecological conservation and development under climate change and a scientific basis for ecological water transfer to oases.

Climate warming and intensified human activities threaten the stability of oasis ecosystems in arid regions, increasing water resource pressure and vegetation degradation. Existing methods fail to fully capture hydrological-vegetation interactions, and research on groundwater depth thresholds remains limited. The Keriya River, which extends deep into the heart of the Taklamakan Desert, serves as a crucial window into the water balance between humans and oases. This study, using multi-temporal Sentinel-2 remote sensing imagery, water resource observation data, and ground survey data from 2016-2024, extracted data on farmland area and watershed area in the middle and lower reaches of the Keriya River over multiple years. An analytical framework integrating remote sensing monitoring, machine learning, and groundwater modeling was constructed to systematically assess the impact of regional farmland expansion on groundwater dynamics and desert riparian forests. Results revealed farmland increased by 31.17 km2 year-1. Due to the increase in human water use in the middle reaches, decreasing groundwater levels by 0.04-0.05 m year-1 and straining ecological water supplies. Populus euphratica forest decreased by 4.04 km2 year-1, while drought-resistant Tamarix chinensis communities expanded by 3.67 km2 year-1, indicating a shift to secondary vegetation. Spatial variations in the fractional vegetation cover indicated a significant decline in vegetation health along the oasis peripheries, with pronounced degradation trends in areas with insufficient surface water supply. Model projections indicate that, if current trends persist, 34.5 % of the total oasis area will have groundwater levels shallower than 6 m by 2120, i.e., below the groundwater level suitable for the growth of desert riparian forests. This would put the oasis ecosystem at risk of large-scale degradation, resulting in long-term and irreversible impacts on protected areas. The methodology improved spatiotemporal resolution, quantitative simulation, and multi-source process integration and provides a novel pathway for investigating hydrological-ecological dynamics in arid regions and scientific evidence for water resource management and ecological conservation. Controlled farmland expansion, improve the legal and regulatory standards system, optimized water usage, and a long-term ecological water supplementation mechanism are recommended to sustain the oasis ecosystem.

Study Region: The Daliyaboyi Oasis at the tail of the Keriya River in the Tarim Basin, China. Study Focus: Groundwater is an important water source for riparian forest in arid region. However, studies on the response of riparian forest to fluctuation of groundwater depths are still limited. This study used stable isotope method combined with the MixSIAR model to examine the inter-annual influence of the fluctuations of groundwater depth on water use of T. ramosissima at the Daliyaboyi Oasis. New Hydrological Insights: The results showed that the fluctuations of groundwater depth decreased from 5.20 m in 2018-1.68 m in 2023 at the sampling period. Meanwhile, the surface soil water content (0-100 cm) showed a significant increasing trend. Accordingly, T. ramosissima switched its main water sources from deep soil water to shallow water. According to the results of MixSIAR model, in 2018-2020, T. ramosissima mainly used deep soil water, with the uptake proportions of 39.12 f 0.01 %, 44.23 f 0.02 %, and 43.21 f 0.02 %, respectively. In 2022-2023, T. ramosissima mainly used shallow soil water, with the uptake proportions of 40.16 f 0.01 %, and 36.44 f 0.03 %, respectively. Unexpectedly, the uptake proportion of T. ramosissima to groundwater was relatively constant, with the value ranged from 28.27-37.54 %, did not change obviously with the decreasing of groundwater depth. This study provides insights into the resistance of water use of the desert riparian forest to the fluctuation of groundwater depths.

In the context of climate change, dramatic fluctuations in extreme hydrological events pose threats to ecosystem properties, resulting in the destruction of biodiversity and ecosystem functions. Desert–wetland ecosystems are ecologically important in inland river basins in arid zones; however, the mechanisms by which biodiversity affects desert–wetland ecosystem multifunctionality remain unknown, leading to the lack of a necessary theoretical basis for targeted conservation strategies. In this study, we evaluated the ecosystem multifunctionality of the Daliyabuyi Oasis, using averaging and multiple threshold approaches. The relative contributions of community-weighted mean traits, diversity indices, and environmental factors to ecosystem multifunctionality were analyzed. The results showed that the multifunctionality of desert–wetland ecosystems was mainly driven by the mass ratio effect. Community-weighted mean height was recognized as the most critical factor due to its significant positive effect on ecosystem multifunctionality. Surface water disturbance may exert a negative indirect effect on multifunctionality through community height, while groundwater depth could have a positive indirect effect on multifunctionality through three mediating variables: Soil total dissolved solids, phylogenetic diversity, and community height. This study supports the intermediate disturbance hypothesis from the perspective of ecosystem function and clarifies the continuum of multifunctionality among surface water, groundwater-soil, and vegetation-ecosystem interactions. It emphasizes that floodplain habitats can have additional negative impacts on multifunctionality. The results of this study aim to offer scientific insights for conserving ecosystem multifunctionality based on community attributes and to present new perspectives on the evolution of desert-wetland ecosystems in the context of global change.

Desert riparian forests are a vital component of desert ecosystems and play a key role in maintaining their stability. However, these forests are currently facing the threat of large-scale disappearance. As such, effectively assessing the impact of changes in surface water and groundwater on the growth state of desert riparian forests, particularly evaluating the relationship between long-term environmental changes and riparian forests on a large scale, has become a critical research focus. This study combined multi-temporal Sentinel-2 remote sensing data with a random forest model to analyze the spatiotemporal dynamics of riparian forests and water resources from 2016 to 2023. The results demonstrate the significant influence of water resource changes on the growth, mortality, and distribution of desert riparian forests in arid regions. The findings reveal distinct roles of surface water and groundwater: surface water primarily drives vegetation regeneration, while groundwater supports sustained growth and development. Furthermore, the early arrival of surface water before the growing season significantly accelerates the phenological period of vegetation, with surface water in March exerting the strongest regulatory effect on annual vegetation growth. The study highlights the complex eco-hydrological feedback mechanisms formed by the interaction between surface and groundwater, which act as key drivers of riparian forest dynamics. These findings provide valuable scientific insights for water resource management and the ecological conservation of riparian forests in arid regions.

Plastic film mulching has long been used in agriculture to enhance productivity, resulting in the substantial input of microplastics derived from plastic film mulching (PFM-MPs) into agricultural soils. However, the impacts of these residues on soil remain unclear. Therefore, in this study, we investigated a 17-year mulched cotton field using integrated physical-chemical-microbiological analyses to explore how PFM-MPs influence the soil structure and microbial communities. The results show that PFM-MP abundance increased significantly with mulching duration (from 683.33 to 9633.33 items/kg) and was predominantly enriched in macroaggregates and mesoaggregates, with soil aggregate stability (mean weight diameter) increasing by approximately 7.8-fold. Multiple lines of analysis identified PFM-MPs as the dominant factor influencing aggregate stability. Furthermore, PFM-MPs enhanced interparticle cohesion by regulating the electrochemical properties of soil particle surfaces, thereby optimizing interparticle interactions and indirectly promoting aggregate stability through the accumulation of hydrophobic plasticizers (e.g., phthalate esters), which increased soil water repellency (contact angle: 9.73 degrees -> 23.10 degrees). Amplicon sequencing of 16S rRNA genes revealed pronounced shifts in microbial community composition, characterized by increased relative abundances of Proteobacteria, Gemmatimonadetes, and Acidobacteriota; in addition, the Shannon diversity index increased significantly from 5.69 to 6.72. Finally, partial least squares path modeling clarified that PFM-MPs enhance aggregate stability primarily by modulating soil electrochemical properties and hydrophobicity, thereby altering microbial communities. In summary, there results fills a critical knowledge gap regarding the effects of PFM-MPs on soil aggregates and microbial communities in agricultural soils, thus inform evidence-based policies aimed at managing plastic pollution and ensuring sustainable agriculutural management.

Hexavalent chromium (Cr(VI)) poses a serious threat to the environment and human health owing to its inherent toxicity. Photocatalysis technology has garnered widespread attention owing to its efficiency and environmental friendliness. However, existing photocatalysts are constrained by light conditions, low reduction rates, and lack of studies in real wastewater. In this study, biomass carbon dots (P-CDs) were synthesized from peanut shell powder, then combined with chitosan (CS) and TiO2 to create a novel photocatalyst (9:1 1 % P-CDs/TiO2@CS). The photocatalyst exhibited a smaller band gap and a broader light absorption range than TiO2, while the porous structure of the hydrogel increased the contact area between P-CDs/TiO2@CS and Cr(VI), thereby enhancing its photocatalytic performance. Our study demonstrates that under simulated sunlight using a xenon lamp, 0.2 g of 9:1 1 % P-CDs/TiO2@CS reduced 50 mg/L Cr(VI) at a rate of 99.64 % in 30 min (pH 7). The photocatalyst also exhibited excellent reduction capabilities for Cr(VI) across a pH range (pH 2-9), at different concentrations (10, 20, 30, 40, 50, and 60 mg/L), and in various real wastewater samples (influent, effluent, and electroplating wastewater). After five cycles, the reduction rate was still maintained at 90.38 %. Experiments conducted under natural sunlight and ion interference further confirmed its outstanding photocatalytic performance and stability in real-world applications. Free radical trapping experiments indicated that electrons (e-) and holes (h+) were the primary active species. Additionally, antibacterial experiments showed that the reactive oxygen species generated by the photocatalyst under light irradiation effectively inhibited the proliferation of Escherichia coli. Thus, P-CDs/TiO2@CS holds significant potential for practical application in environmental wastewater treatment.