Search Results (59,337)

Underwater radiated noise from small recreational vessels can have significant ecological impacts on near-shore habitats, yet it is often overlooked in soundscape assessments. The objective of this study is to present measured source levels for small recreational vessels and to evaluate an existing source level model (JOMOPANS-ECHO model). The existing model was developed based on data from larger vessels, and the current study focuses on how to modify it for smaller vessels with different hull types. Errors associated with shallow water measurements are also discussed; more specifically, existing methods for accounting for propagation loss are evaluated. Controlled measurements were conducted at five coastal sites for 25 vessels spanning different hull forms, propulsion systems, and operational speeds. Frequency-dependent source level spectra were derived and categorised by hull class (planing, semi-displacement, displacement). The results show clear speed-dependent increases in source level for planing and semi-displacement vessels at higher frequencies (>250 Hz), whereas data for displacement vessels were insufficient to establish statistical trends. The JOMOPANS-ECHO model consistently overestimates the speed dependence. The parameterisations developed here provide class- and speed-specific models suitable for integration into soundscape mapping and cumulative impact assessments. Full article

Sustainable river management depends on indices that balance human water demands with ecological flow requirements while accounting for hydrological variability. Existing water scarcity and withdrawal indices are largely based on monthly or annual aggregates, often neglecting daily variability and the effects of drought buffering. This study introduces the Extractable Water Index (EWI), a novel, dimensionless metric that quantifies the sustainable potential for water extraction using daily flow records. The EWI integrates mean available flow, flow variability, low-flow thresholds, and storage contributions into a single expression, thereby capturing both hydrological dynamics and ecological protections. Two scenarios were evaluated, (i) no-storage and (ii) with-storage, with the latter employing a semi-analytical approximation to represent a reservoir or pond. The EWI was applied to 20 daily river flow series for 16 river basins in Sri Lanka. Under no-storage conditions, thresholds were defined as follows: EWI < 0.45 indicates low extraction potential; 0.45 < EWI < 0.60 indicates moderate extraction potential; and EWI > 0.75 indicates high extraction potential. The results demonstrate that even modest storage can substantially enhance sustainable withdrawals. The EWI provides a transparent, reproducible decision-support tool that complements environmental flow standards and prioritizes rivers based on extractability. The EWI provides a valuable tool for estimating water extraction potential within the Sri Lankan context. This index can be applied across diverse hydroclimatic regimes and, when combined with threshold validation, can predict extraction requirements under varying seasonal flow conditions. Full article

Background: Interpersonal emotion regulation (iER) is the process of managing others’ emotions and is critical during early adolescence, when social awareness and peer dependence increase. Little is known about how sex and gender role orientation shape adolescents’ iER. This study examined whether early adolescents differ in their use of person-focused (acceptance) versus problem-focused (positive engagement) strategies and whether these differences depend on context and measurement method. Methods: Data were collected from 322 adolescents (141 girls, 181 boys; aged 10–14 years, M = 12.47, SD = 1.55). The cross-sectional online study used a multi-method design comprising open-ended visual vignettes, a standardised questionnaire, and a serious game task. Participants also completed a validated gender-role self-concept measure assessing femininity and masculinity. Analyses were conducted using Poisson and logistic regressions with sex, femininity, and masculinity as predictors. Results: Across tasks, adolescents preferred problem-focused over person-focused strategies. Girls and those higher in femininity reported or generated more acceptance-based strategies, whereas boys and those higher in masculinity favoured positive engagement. These effects were evident in reflective measures (vignettes and questionnaire) but not in the interactive game, where sex and gender differences were absent. Conclusions: Findings suggest that gendered socialisation processes shape how adolescents regulate others’ emotions, particularly when behaviour is consciously reported. However, in ecologically valid contexts, these differences diminish, indicating shared capacities for adaptive interpersonal regulation across genders. Full article

The political transition in Syria following the fall of the Al-Assad regime in December 2024 has renewed debates about refugee return. This study examines Syrian refugees’ intentions to return from Jordan and the factors shaping these decisions using a mixed-method design. A stratified random sample of 1070 refugees residing in host areas and camps was surveyed through telephone interviews, complemented by four focus group discussions and two key informant interviews with experts. Although 61% of respondents expressed an intention to return, only 20% indicated concrete or immediate plans, suggesting that return remains largely aspirational rather than imminent. Access to housing and property (55%), economic condition (46%), and safety and security (40%) emerged as central determinants, indicating that structural barriers, rather than regime change alone, shape decision-making. Qualitative findings further reveal that emotional attachment to Syria sustains return aspirations, yet financial hardship, debt in Jordan, and housing destruction in Syria constrain refugees’ capabilities to act. These findings underscore that voluntary, safe, and dignified repatriation depends not only on addressing structural barriers in Syria, but also on maintaining essential protection and support for Syrian refugees in Jordan. Full article

Carbon storage of terrestrial ecosystems is highly susceptible to land use/cover change (LUCC). In order to optimize land use patterns and advance the dual carbon goals (carbon peaking and carbon neutrality), it is imperative to clarify the role of LUCC in controlling regional terrestrial carbon storage. This study utilized a land use dataset spanning from 1990 to 2020 and incorporated 12 pivotal driving factors. Based on these data and factors, this study constructs four distinct future development scenarios: natural development scenario (ND), cropland protection scenario (CP), ecological protection scenario (EP), and urban development scenario (UD). By integrating the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) with the Patch-Generating Land Use Simulation model (PLUS), this study simulated the dynamic changes in land use types and the spatiotemporal evolution of carbon storage in the Qinba Mountains (QBMs). The results revealed that between 1990 and 2020, built-up area and water area experienced substantial expansion with growth rates of 67.89% and 20.39%, respectively. In addition, cropland decreased by 3.09% and grassland decreased by 2.49%. Notably, cropland exhibited the most pronounced conversion intensity among all land use types during this period. Correspondingly, the total terrestrial carbon storage in the study area declined slightly from 7471.08 × 10⁶ t in 1990 to 7437.25 × 10⁶ t in 2020. Forestland dominated the regional carbon pool, accounting for an average of 47.67% of the total carbon storage over the three decades. Further analysis identified natural factors as the primary drivers of LUCC and associated carbon storage changes, with DEM exerting the greatest influence, followed by mean annual temperature and mean annual precipitation. Projection analyses for 2030 reveal divergent carbon storage outcomes across different land use scenarios relative to the 2020 baseline. Under the natural development (ND) and urban development (UD) scenarios, total carbon stocks are projected to decline by 37.63 × 10⁶ t and 19.99 × 10⁶ t, respectively. Conversely, implementation of conservation-oriented strategies yields substantial increases, with the cropland protection (CP) and ecological protection (EP) scenarios enhancing carbon storage by 16.87 × 10⁶ t and 13.07 × 10⁶ t, respectively. These findings underscore the critical role of protection-focused land use policies in strengthening ecosystem carbon sequestration capacity. The study provides a scientific foundation for formulating targeted forestry management policies and enhancing the terrestrial ecosystems’ capacity to act as carbon sinks in mountainous areas. Full article

The disorderly expansion of Moso bamboo (Phyllostachys edulis) into adjacent forests has become a serious ecological issue in southern China; however, the response of soil microbial communities remain unclear. This study investigated the succession patterns of bacterial and fungal communities through high-throughput sequencing and soil physicochemical analysis across three expansion stages in subtropical China: mixed coniferous–broadleaf forests, bamboo–forest transition zones, and pure Moso bamboo stands. The results indicate that Moso bamboo expansion altered soil bacterial and fungal beta-diversity without changing alpha-diversity. Random forest and redundancy analyses revealed distinct microbial group drivers. Bacterial communities were driven by available phosphorus (37.1% explained variance), with expansion intensifying soil phosphorus limitation and selecting for groups adapted to low-phosphorus environments (e.g., Acidobacteria). Fungal communities were primarily influenced by bulk density (21.3% explained variance), as the bamboo rhizosphere system altered soil physical structure, resulting in a significant loss of ectomycorrhizal fungi (e.g., Russula) and a corresponding decline in Basidiomycota abundance. This study confirms that Moso bamboo expansion reorganizes the soil microbial ecosystem through two pathways: chemical nutrient limitation and physical space remodeling. By revealing the subterranean ecological consequences of Moso bamboo expansion, this study provides a theoretical foundation for sustainable management of subtropical forests. Full article

Suspended sediment concentration (SSC) strongly influences estuarine erosion–deposition processes, navigation safety, and coastal engineering stability. However, conventional remote sensing techniques are limited to surface SSC and cannot characterize vertical sediment structures. In this study, Landsat 8 OLI imagery was combined with in situ SSC profiles from six stations in the Guan River Estuary–Haizhou Bay system to retrieve full-depth sediment distributions. A band-combination inversion model using (B3 + B2)/B1 achieved the highest accuracy (R² = 0.679), and an improved vertical distribution model was developed by incorporating turbulent shear (G) into the Rouse framework. Results indicate that surface SSC ranged from 0.15 to 0.86 kg/m³, while middle- and bottom-layer SSC reached up to 1.20 kg/m³ and 1.77 kg/m³, respectively, exhibiting a consistent east–high and west–low spatial pattern. Settling velocity (SSV) varied from 3 × 10⁻⁶ to 1.49 × 10⁻² m/s and showed a positive correlation with SSC at low concentrations and a negative correlation at high concentrations due to flocculation effects. This integrated framework provides a rapid, low-cost method for full-water-column sediment assessment in estuaries and coastal zones, supporting engineering design, navigation maintenance, and sediment management. A better understanding of sediment transport processes in Haizhou Bay is important for maintaining shoreline stability and ecological balance in this semi-enclosed coastal system. The findings of this study provide a scientific basis for sediment management and environmental regulation, which can contribute to the long-term sustainable development of coastal environments in the Yellow Sea region. Full article

Accurate urban green space (UGS) mapping is essential for assessing urban ecosystem health and supporting sustainable development planning. However, deep learning-based UGS segmentation from Red–Green–Blue (RGB) remote sensing imagery faces two major challenges. First, the absence of near-infrared (NIR) information in RGB imagery hinders the ability to discriminate spectrally similar classes, such as vegetation and non-vegetation. Second, conventional convolutions with fixed receptive fields struggle to model the complex and irregular boundaries characteristic of UGS. To address these challenges, this study combined the Normalized Green–Red Difference Index with the Deformable Convolutional Network Lab (NGRDI-DCNLab) model, a semantic segmentation model tailored specifically for RGB-only imagery. Based on the DeepLabV3+ framework, the model introduced three core improvements: (1) The Normalized Green–Red Difference Index (NGRDI) was incorporated to compensate for the absence of NIR information, enhancing the spectral separability of vegetation pixels. (2) Standard convolutions in the decoder were replaced with deformable convolutions, enabling the network to more effectively adapt to irregular boundaries of UGS. (3) An NGRDI-weighted loss function was designed to assign higher weights to challenging samples and uncertain boundary regions, guiding the model toward more accurate edge delineation. Comprehensive evaluations on two public high-resolution datasets—the Wuhan Dense Labeling Dataset (WHDLD) and the Beijing subset of the Urban Green Space-1m dataset (UGS-1m_Beijing)—demonstrated that the NGRDI-DCNLab model outperformed existing popular deep learning models (like Unet++, etc.). Specifically, the deformable convolution effectively enhances the feature modeling capability for irregular boundaries; incorporating the NGRDI vegetation index as a fourth channel strengthens spectral feature representation and improves the distinction between vegetation and non-vegetation; and adding the dynamic NGRDI-weighted loss enables targeted learning for challenging samples. Through the synergistic effect of these three modules, the model achieves mean Intersection over Union (MIoU) scores of 84.77% and 77.66%, as well as F1-scores of 91.75% and 87.27%, on the WHDLD and UGS-1m_Beijing datasets, respectively. Furthermore, the model exhibited certain generalization capability on the unmanned aerial vehicle (UAV) dataset, the Urban Drone Dataset 6 (UDD6), attaining an MIoU of 87.43%. Our results confirm that high-precision UGS extraction is achievable using only RGB remote sensing imagery, providing a cost-effective and practical technical solution for refined urban governance and ecological monitoring. Full article

Post-recycling plastic waste contamination in freshwater ecosystems represents an escalating environmental threat, while algal blooms continue to generate vast quantities of underutilized biomass. Addressing both challenges, this study investigated the co-hydrothermal liquefaction of Chlorella pyrenoidosa with representative post-recycling plastic wastes polypropylene, polyethylene terephthalate, and Nylon-6 as a dual-resource valorization strategy. Experiments were conducted in a 1000 mL high-pressure batch reactor at 350 °C for 30 min, with varying biomass-to-plastic feed ratios. Systematic product characterization, including functional group, elemental analysis, Van Krevelen diagrams, and heating value assessment, was employed to elucidate synergistic effects and evaluate product quality. Results revealed that co-processing with polyethylene terephthalate achieved the highest biocrude yield of 71.5%, with an enhanced higher heating value of 35.7 MJ kg⁻¹, surpassing the 62.4% yield from microalgae alone. Nylon-6 blends also improved oil yield to 69.6% while producing aqueous fractions enriched with ε-caprolactam, indicating the recovery of valuable nitrogenous monomers. In contrast, PP exhibited limited reactivity toward oil generation but produced carbon-rich biochar with a higher heating value up to 41.4 MJ kg⁻¹, comparable to high-grade solid fuels. Mechanistic analyses confirmed that plastics acted as hydrogen donors, promoting deoxygenation, radical stabilization, and selective depolymerization, thereby improving both liquid and solid fuel fractions. By employing ecologically relevant freshwater feedstocks from Thailand, this work advances beyond prior studies dominated by marine biomass or synthetic surrogates, providing realistic insights into resource integration within polluted inland waters. The co-hydrothermal liquefaction process simultaneously mitigates eutrophication-driven algal blooms and persistent plastic pollution while generating fuels and functional carbon materials, directly contributing to a circular bioeconomy. The demonstrated synergy between biological and synthetic wastes highlights a scalable, catalyst-free route to energy-dense biofuels and multifunctional biochar. These outcomes align strongly with SDG which offer a pragmatic framework for waste-to-energy transition in freshwater-dependent regions. Full article

Soda lakes are ecologically significant habitats characterized by high salinity, alkaline pH, and intense evaporation. These milieus are hostile to most life, though these lakes could be a rich source for discovering novel halotolerant and halophilic cyanobacterial taxa. The Indian subcontinent is endowed with shallow saline–alkaline lakes whose cyanobacterial diversity has been little explored. The present study was undertaken to explore the cyanobacterial diversity in an inland saline–alkaline lake (Sambhar Lake) in India using a polyphasic approach. Two thin, filamentous strains encapsulated within thick sheaths and capable of nodule formation under normal light conditions were recovered. Both isolates exhibited growth at up to 4% salinity, indicating their halotolerant nature. The studied strains exhibited <95% 16S rRNA gene similarity with closely related taxa from the genera Thainema and Insularia and formed a distinct evolutionary lineage in phylogenetic tree supported by a high bootstrap value. Additionally, the secondary structures of the 16S-23S Internal Transcribed Spacer (ITS) regions (D1-D1′ and BoxB) of the studied strains showed remarkable differences from phylogenetically closely related taxa, indicating these strains represent a new genus in the Nodosilineales: Krienitziella sambharensis gen. et sp. nov., in accordance with the International Code of Nomenclature for Algae, Fungi, and Plants (ICN). Full article

Geometric morphometrics is an important component of quantitative research on insect morphology, widely applied in taxonomy, intraspecific variation, and phylogenetic studies. However, systematic research in this field remains limited, with few comprehensive summaries of research trends, hotspots, and core theories. This study, based on scientometric methods, analyzed 1321 publications indexed in the Web of Science database up to 31 December 2025, and presents a meta-scientific review from a macro perspective, revealing the research trends, hotspots, and future directions in the field. The results show that: (1) annual publications exhibit overall growth, while research methods evolved from single landmark analysis to multimodal and interdisciplinary approaches; (2) scientists from Brazil, the USA, and France are major contributors, with studies spanning morphology, taxonomy, and ecology; (3) taxonomic studies centered on wing shape analysis constitutes a major research hotspot, closely related to phylogeny, allometry, and sexual dimorphism; (4) highly co-cited studies provide the main theoretical and methodological foundations for the field. Future research, building on existing hotspots, will further integrate geometric morphometrics with genomics, ecological functional data, three-dimensional geometric morphometrics, and artificial intelligence-assisted approaches to advance integrative taxonomy within interdisciplinary and data-driven frameworks. Full article

Platonia insignis Mart. (Clusiaceae) is a native fruit tree of great ecological and socioeconomic importance in the Brazilian Amazon and Cerrado. However, habitat loss is threatening its genetic variability. We investigated whether habitat fragmentation across the Amazon, Cerrado, and transition zones shapes the genetic diversity and population structure of five natural populations of P. insignis, using ISSR markers. Leaf samples from 13–15 individuals per population were collected, and DNA was extracted using the CTAB protocol. Twelve ISSR primers amplified 149 loci, used to estimate genetic parameters. AMOVA showed that 73.58% of genetic variation occurred within populations and 26.41% among populations (F_ST = 0.261). Amazonian populations exhibited the highest genetic diversity, while transition zone populations had the lowest values. The Cerrado population was genetically distinct and maintained moderate intrapopulation diversity. Bayesian clustering, PCoA, and UPGMA revealed three genetic groups corresponding to the sampled regions. Transitional populations showed high genetic admixture, indicating their role as potential corridors for gene flow. Our results highlight the need to preserve genetically diverse Amazonian populations, safeguard the Cerrado population as an evolutionarily significant unit, and maintain transitional populations to promote landscape connectivity. The study provides a genetic baseline to support conservation and management of P. insignis germplasm resources. Full article

Fungal endophytes are microorganisms that inhabit plant tissues without causing disease and emerge as critical mediators of plant stress tolerance, nutrient acquisition, and ecosystem resilience under diverse climate change scenarios. Their unique position within the host allows them to modulate physiological responses more closely than external microbiota. This review explores how endophytic fungi contribute to plant adaptation under climate-induced stresses such as heat, salinity, drought, pollution, and nutrient limitation, with a focus on molecular crosstalk, functional trait modules, and metabolic trade-offs. Key findings emphasize multilayered signaling systems, including MAMP/DAMP recognition, phytohormone regulation, immune tuning, ROS dynamics, and effector deployment, while emerging mechanisms such as cross-kingdom RNA and extracellular vesicle (EV)-mediated exchange are discussed as promising but currently limited in empirical validation within many endophytic systems. Endophytes also enhance nutrient exchange through conditional carbon-for-benefit trade and may shape rhizosphere microbiota and soil activities through plant-mediated inputs. Integrative multi-omics approaches provide predominantly correlational insights into the mechanistic basis of these effects, linking molecular function to ecosystem and community outcomes. These insights have potential applications in climate-resilient agriculture, phytoremediation, and ecosystem restoration; however, their large-scale implementation requires further field-based validation and context-specific assessment. Future priorities should focus on trait-based selection, ecological modeling, and biosafety evaluation to translate microbial functions into reliable field-level strategies that support sustainable crop performance under accelerating environmental stress. Full article

Sustainable tourist route design is a critical challenge in industrial heritage planning. While prior tourism routing algorithms predominantly minimize physical distance, and conventional heritage planning focuses on the static preservation of abandoned sites, both lack the multi-objective adaptability required for “living” industrial landscapes. In such dynamic environments, active production, tourism, and ecological conservation intricately coexist. To address this gap, this study proposes a novel, data-driven route planning framework, taking the Tianjin Changlu Salt Field as a case study. The genuine novelty lies in integrating multi-objective network optimization with spatial design implementation. The site is abstracted into a topological network comprising 13 nodes and 19 edges. Multi-attribute edge weights—incorporating spatial distance, travel time, landscape attractiveness, and ecological sensitivity—are quantified using entropy weighting fused with subjective preferences. Using the Floyd–Warshall algorithm, three theme-based touring routes are generated. Unlike traditional methods, this workflow actively translates algorithmic outputs into concrete spatial strategies, such as bypassing ecologically sensitive zones and transforming production facilities into perceptible landscape nodes. Comparative evaluations demonstrate that these optimized routes achieve higher comprehensive utility than baseline and designer-generated schemes, offering a pioneering, reproducible paradigm for the sustainable renewal of living industrial heritage. Full article