Poly(butylene adipate-co-terephthalate) (PBAT) is a promising polymer with excellent mechanical properties and biodegradability. However, knowledge gaps between its degradation and mineralization processes in soil hampers its environmental impact and application potential. In this study, we elucidated the degradation process of PBAT, starting with the degradation of high-molecular-weight polymers into 30 intermediates, before ultimately mineralized into CO2. Bacteria and fungi drove the degradation and mineralization of these intermediates. We discovered that PBAT was synergistically degraded by combinations of 27 bacterial and fungal biomarkers rather than by single biomarkers dominated by Bacteroidota, Acidobacteriota, and Ascomycota. These combinations of related functional genes perform various functions at every stage of PBAT degradation, including breaking down molecular structures, degrading intermediates, and mineralization. Bacterial biomarkers showed greater diversity than fungal biomarkers in degrading PBAT. Our findings provide useful insights into the degradation of PBAT in soil and a foundation for systematically evaluating and controlling the environmental behavior and safety of PBAT in soil.

Developing environmentally sustainable biodegradable multifunctional bio-composite films is an effective strategy for ensuring food chain security. This study initially prepared inclusion complexes (HP-(3-CD@EGCG) of Hydroxypropyl-(3-cyclodextrin (HP-(3-CD) and EGCG to ameliorate the stability of EGCG. Then HP-(3-CD@EGCG and different ratios of lignin were incorporated into gelatin solution through cross-linking polymerization to prepare an antioxidant, antibacterial and biodegradable composite film (HP-(3-CD@EGCG/Lignin/Gelatin). The results illustrated that HP-(3-CD crosslinked with EGCG and the encapsulation rate of EGCG reached 82.26%, and lignin increased the comprehensive characteristics of the gelatin-based composite films. The hydrophobicity of the composite films increased with increasing lignin concentration, reaching a water contact angle of 117.33 degrees; Furthermore, the mechanical characteristics and UV-light/water/oxygen barrier capacity also increased significantly. The composite films showed excellent antioxidant and antimicrobial properties, which also verified in the preservation of tomatoes and oranges, extending the shelf life of the fruit. It is worth mentioning that lignin has no effect on the biodegradability of the composite film, and the degradation rate in the soil reached 80% on the 10th day. In summary, biodegradable multifunctional environmentally friendly composite films based on gelatin and loaded with lignin and HP-(3-CD@EGCG inclusion complexes are anticipated to be applied in fruit and vegetable preservation.

Landslides pose significant risks to human life and infrastructure, particularly in mountainous regions like Inje, South Korea. This study aims to develop detailed landslide susceptibility maps (LSMs) using statistical (i.e., Frequency Ratio (FR), Logistic Regression (LR)) models and a hybrid integrated approach. These models incorporated various factors influencing landslides, including aspect, elevation, rainfall, slope, soil depth, slope length, and landform, derived from comprehensive geospatial datasets. The FR method assesses the likelihood of landslides based on historical occurrences relative to specific factor classes, while the LR method predicts landslide susceptibility through the statistical modeling of multiple predictor variables. The results from the FR, LR, and hybrid methods showed that the cumulative area covered by high and very high landslide susceptibility zones was 13.8%, 13.0%, and 14.28%, respectively. The results were validated using Receiver Operating Characteristic (ROC) curves and the Area Under the Curve (AUC), revealing AUC values of 0.83 for FR, 0.86 for LR, and 0.864 for the hybrid method, indicating high predictive accuracy. Subsequently, we used K-mean clustering algorithms on the hybrid LSI to identify the higher LSI cluster of the region. Furthermore, sensitivity analysis based on landslide density confirmed that all methods accurately identified high-risk areas. The resulting LSMs provide critical insights for land-use planning, infrastructure development, and disaster risk management, enhancing predictive accuracy and aiding in the prevention of future landslide damage.

Background and AimsGlobal climate change is intensifying the co-occurrence of abiotic stresses, particularly combined waterlogging/submergence and salinity, posing severe and escalating threats to woody plant ecosystems critical for biodiversity, carbon storage, and soil stabilization. Despite extensive research on herbaceous species, understanding of woody plant responses remains fragmented and disproportionately focused on specific groups like mangroves and halophytes. This review aims to synthesize and critically evaluate the current state of knowledge on the integrated physiological, morphological, and molecular responses of diverse woody plants to this challenging combined stress scenario.MethodsA comprehensive synthesis and analysis of existing scientific literature was conducted. This involved systematically examining empirical studies, comparative analyses, and theoretical frameworks related to the responses of various woody plant species to the concurrent application of waterlogging/submergence and salinity stress, drawing comparisons to single-stress effects and herbaceous model systems.ResultsThe majority of woody plants exhibit synergistic, more detrimental effects under combined stress compared to either stress alone. Key manifestations include significantly heightened inhibition of photosynthesis, severe disruption of ion (particularly Na+ and Cl-) homeostasis leading to toxicity, and exacerbated oxidative damage. Woody plants utilize core stress tolerance mechanisms analogous to herbaceous species, such as ion exclusion/compartmentalization, activation of enzymatic and non-enzymatic antioxidant systems, and osmotic adjustment via compatible solute accumulation. Crucially, they also deploy distinctive structural and long-term adaptive strategies, including the development of specialized organs (pneumatophores, hypertrophic lenticels), deep root systems for accessing less saline groundwater, and physiological acclimation processes leveraging their perennial nature. Nevertheless, critical knowledge gaps persist, particularly concerning the underlying molecular signaling networks, the mechanisms of long-term adaptation over years/decades, and the specific responses of mature trees in natural ecosystems.ConclusionSignificant gaps hinder a comprehensive understanding of how woody plants cope with combined waterlogging/submergence and salinity stress. To advance fundamental knowledge and inform effective ecological restoration strategies for climate-resilient landscapes, future research must prioritize the application of integrated multi-omics approaches (genomics, transcriptomics, proteomics, metabolomics), the development of high-efficiency genetic transformation techniques for recalcitrant woody species, the deployment of advanced high-throughput phenotyping platforms, and crucially, long-term field-based studies simulating realistic future stress scenarios.

Local site conditions recognized as a determining factor in assessing the extent of seismic hazard and damage distribution during earthquakes. Present study emphasizes seismic hazard of international business corridor of Agartala town capital of Tripura, one of the northeastern state of India categorized as highest seismic zone (zone V) attributing seismic response of local subsoil deposits under site-specific scenario earthquake motions including liquefaction susceptibility prediction. One-dimensional nonlinear ground response analysis with input of geotechnical parameters was carried using DEEPSOIL (2018) program across central zone of Agartala city and liquefaction susceptibility analysis are performed based on standard penetration test (SPT) utilizing well-established empirical relationship. The novelty of results lies in use of site-specific dynamic parameters of subsoil and synthetic ground motions based on scenario earthquake. Besides, numerical model was validated with a recent past liquefaction case study in Tripura which also attributes key highlight of this study. Key seismic hazard parameters in the form of peak ground acceleration (PGA), amplification factor (Af), and predominant frequencies (fn) are presented through geographical information based spatial maps. These maps provide crucial inputs for planners and designers for future urban planning along with seismic strengthening of existing infrastructures. This comprehensive approach offers new perspectives on seismic hazard assessment and future management plan in this region.

This study explores the mechanical properties and synergistic mechanisms of silty sand modified with guar gum (GG) and polypropylene fiber (PP fiber) through a series of unconfined compressive strength (UCS) tests, direct shear tests, and direct tensile tests. The test results reveal that the unconfined compressive strength (UCS) of silty sand can be dramatically improved by incorporating GG, boosting its strength by up to 23 times compared to the natural soil. Adding PP fiber further enhances the UCS and effectively mitigates brittle failure. GG dominates the increase in shear strength by enhancing cohesion, while the PP fiber optimises the shear stability by increasing the internal friction angle. The shear strength of the GG-PP fiber-enhanced soil can be boosted by 235% compared to natural soil. The synergistic effect of GG and PP fibers enables the tensile strength of the improved silty sand to reach 122.75 kPa, representing a 34.15% increase compared to soil with only GG incorporated. However, if the fiber content is too high (> 0.5%), the tensile strength will decrease due to increased porosity. The study found that GG enhances the cohesion between soil particles through hydrated gel, and the PP fiber inhibits crack propagation and improves ductility through the bridging effect. The two form a bonding-bridging synergistic system, which significantly optimises the mechanical properties of the soil. This combined improvement scheme has both high strength and high ductility and can replace traditional inorganic cementitious materials, providing new ideas and methods for the application of silty sand in roadbed engineering, slope reinforcement, and other fields.

Global warming subjects soil organisms to elevated temperature stress, while simultaneously altering the detoxification processes for pollutants within these organisms. The combined stressors of increased temperature and pollutants may impose synergistic stress on soil fauna, necessitating detailed investigation. Here, we exposed Collembola (Folsomia candida) to imidacloprid (a neonicotinoid pesticide) in combination with a range of constant temperatures in a full-factorial experimental design to assess the integrated impacts on survival, growth, and bioaccumulation. The results revealed that high temperatures and imidacloprid synergistically inhibited the survival of F. candida. Under 6.4 mg/kg imidacloprid exposure, survival rates decreased by 41.38 % at 30.2 degrees C and 68.75 % at 30.5 degrees C, compared to the same temperature treatments without imidacloprid exposure. Bayesian model analysis confirmed a significant synergistic interaction between imidacloprid and temperature on survival. Interestingly, at elevated temperatures, the internal concentration of imidacloprid in F. candida significantly decreased, while the soil concentration of the insecticide remained stable. This suggests that the observed synergistic effect is not due to increased pollutant accumulation within F. candida at higher temperatures, but rather the exhaustion of energy resources needed for detoxification and thermal stress management. This dualstressor-induced energy competition underpins the synergistic interactions observed. Our findings highlight the significant synergistic effects of high temperatures and imidacloprid on Collembola, underscoring an increased ecological risk under such conditions.

The occurrence of hurricanes in the southern U.S. is on the rise, and assessing the damage caused to forests is essential for implementing protective measures and comprehending recovery dynamics. This work aims to create a novel data integration framework that employs LANDSAT 8, drone-based images, and geographic information system data for change detection analysis for different forest types. We propose a method for change vector analysis based on a unique spectral mixture model utilizing composite spectral indices along with univariate difference imaging to create a change detection map illustrating disturbances in the areas of McDowell County in western North Carolina impacted by Hurricane Helene. The spectral indices included near-infrared-to-red ratios, a normalized difference vegetation index, Tasseled Cap indices, and a soil-adjusted vegetation index. In addition to the satellite imagery, the ground truth data of forest damage were also collected through the field investigation and interpretation of post-Helene drone images. Accuracy assessment was conducted with geographic information system (GIS) data and maps from the National Land Cover Database. Accuracy assessment was carried out using metrics such as overall accuracy, precision, recall, F score, Jaccard similarity, and kappa statistics. The proposed composite method performed well with overall accuracy and Jaccard similarity values of 73.80% and 0.6042, respectively. The results exhibit a reasonable correlation with GIS data and can be employed to assess damage severity.

The intensification of land use has contributed to the emergence of environmental impacts such as soil loss, silting of water bodies, and reduction of biodiversity, among others. Using models capable of seasonally diagnosing environmental damage is essential in territorial planning and management, demonstrating the spatial distribution of the environment's sensitivity to developing erosion processes and quantitatively valuing soil loss. Thus, assuming a significant relationship exists between the seasonal variation in environmental fragility and the validated estimate of soil loss, reflecting the conservation status of the river basin. Therefore, this work aims to analyze the seasonal Environmental Fragility (EF) from the autumn of 2019 to the summer of 2020 using the soil loss estimate. Data such as slope, erodibility, erosivity, and the normalized difference vegetation index (NDVI) were used to achieve this. Statistical tests were also applied to assess the significance level of the models in the seasonal evaluation and the validation based on ground truth points. The results showed seasonal differentiation in the EF and the soil loss estimation. Spring was the one that resulted in the most extensive area classified as high EF (27%) and with an estimated soil loss of 0.3733 t.ha-1month-3. The summer presented the highest soil loss estimation with an average value of 0.4393 t.ha -1month-3. Autumn (0.07683 t.ha-1 month-3) and winter (0.0569 t.ha-1 month-3) showed the lowest rates of soil loss, and the most prominent areas were classified in the low class of EF, as a result, mainly of the erosivity of the rains. The results indicated by the seasonal models of EF and soil loss were validated through erosion points using spatial statistics tests.

Determining and characterising locations vulnerable to flooding can help in reducing damage and the number of fatalities. During the monsoon season, East India's Subarnarekha River frequently floods to a significant degree. In current work, we suggest a unique hybrid strategy for preparing the entire catchment's Flood Susceptibility Mapping (FSM). The study area's FSM was conducted by considering 10 flood conditioning factors utilising the Best-Worst Method (BWM) and a multi-parametric Analytical Hierarchy Process (AHP) as per expert knowledge. Meanwhile, the proposed strategy incorporates a Decision Making Trial and Evaluation Laboratory (DEMATEL) for examining causal linkages and dependencies between different elements affecting the flooding process. Several statistical matrices were used to compare the suggested strategy of BWM and AHP. Based on our findings, we concluded that the integration of DEMATEL with AHP and BWM (ID BWM, ID AHP) was more effective than alternative strategies. The findings show that out of 10 flood conditioning factors, slope, elevation, distance from the river, drainage density, Topographic wetness Index (TWI), Land Use Land Cover (LULC), Normalised Difference Vegetation Index (NDVI), precipitation, soil texture, and curvature, factors that have the biggest effects on the local flooding phenomenon are elevation, slope, precipitation, and distance from the river. For validating the efficacy of the flood susceptibility map, Area under the Receiver Operating Characteristic Curve (AUC-ROC) was adopted and demonstrated, showing a pretty high accuracy of (0.92 or 92% and 0.94 or 94%) for ID AHP and ID BWM, respectively. Our research findings provide a highly affordable and useful answer to the flooding problems of basin Subarnarekha.