Search Results (1,779)

Rapid urbanization and climate change have intensified flood risk and ecological degradation along urban riverfronts. Recent literature suggests that combining green and grey infrastructure can enhance resilience while delivering ecological and social co-benefits. This study analyzes and compares five riverfront projects in China and Spain, assessing how their tactic mixes operationalize three urban flood-resilience strategies—Resist, Delay, and Store/reuse—and how these mixes translate into ecological, social, and urban impacts. A six-phase framework was applied: (1) literature review; (2) case selection; (3) categorization of resilience strategies; (4) systematization and typification of tactics into green vs. grey infrastructure; (5) percentage analysis and qualitative matrices; and (6) comparative synthesis supported by an alluvial diagram. Across cases, Delay emerges as the structural backbone—via wetlands, terraces, vegetated buffers, and floodable spaces—while Resist is used selectively where exposure and erodibility require it. Store/reuse appears in targeted settings where operational capacity and water-quality standards enable circular use. The comparison highlights hybrid, safe-to-fail configurations that integrate public space, ecological restoration, and hydraulic performance. Effective urban riverfront resilience does not replace grey infrastructure but hybridizes it with nature-based solutions. Planning should prioritize Delay with green systems, add Resist where necessary, and enable Store/reuse when governance, operation and maintenance, and water quality permit, using iterative monitoring to adapt the green–grey mix over time. Full article

Root anatomy serves as a critical indicator for understanding wetland plant adaptation strategies to environmental changes. Since water depth determines root oxygen demand while nitrogen addition regulates nutrient acquisition, the two factors exert significant and interactive effects on root anatomical structure. In this study, we established a controlled experiment employing three water depth treatments (W1: −10 cm; W2: 10 cm; W3: 30 cm), two nitrogen (N) forms (ammonium-N, nitrate-N), and four N addition levels (N0: 0 mg/L; N1: 40 mg/L; N2: 80 mg/L; N3: 160 mg/L). This design enabled us to analyze the effects of water–nitrogen interactions on the anatomical structure of reed roots to reveal wetland plants’ adaptive strategies to water-nitrogen fluctuations. The results indicate that (1) under nitrogen-free treatment, compared to the control group, the W1 treatment reduced the root aerenchyma proportion and the stele-to-root diameter ratio by 15.8% and 37.0%, respectively. In contrast, exodermis thickness increased by 32.4%, while epidermis thickness decreased by 33.7%. Under the W3 treatment, the aerenchyma proportion increased by 21.0%, the stele-to-root diameter ratio decreased by 22.2%, and exodermis thickness increased by 35.3%. (2) Compared to the nitrogen-free treatment, nitrate addition increased the root aerenchyma proportion under W1, W2, and W3 by 18.8%, 6.9%, and 18.3%. The stele-to-root diameter ratio increased by 27.9% and 12.7% under W1 and W2, but decreased by 10.8% under W3. Exodermis thickness increased by 26.3% under W2, whereas it decreased by 10.8% under W3. Epidermis thickness increased by 36.1% and 22.2% under W1 and W3, while a decrease of 12.7% occurred under W2. (3) Compared to the nitrogen-free treatment, ammonium addition increased the root aerenchyma proportion under W1, W2, and W3 by 13.6%, 13.2%, and 10.0%. The stele-to-root diameter ratio increased by 28.1% under W1 but decreased by 10.4% under W3. Conversely, exodermis thickness decreased by 20.2% under W1 while increasing by 12.6% under W3. Epidermis thickness increased by 26.3% and 20.8% under the W1 and W3 treatments. In summary, the root anatomical structure of P. australis adaptively responds to variations in water depth, nitrogen forms, and nitrogen concentrations by modulating aerenchyma proportion, the stele-to-root diameter ratio, exodermis thickness, and epidermis thickness. Future research should strengthen the study of the relationship between root anatomical traits and plant functions, to more comprehensively explore the adaptation mechanisms of wetland plants to global environmental change. Full article

The Sanjiang Plain hosts the largest freshwater wetland in Northeastern China and plays a critical role in regional climate stability. However, climate change and human activities have degraded the wetland, forming a successional gradient from the original flooded wetland to dry shrub and forest vegetation with a lower ground water level. This degradation has altered soil microbial structure and functions, reducing ecological and socio-economic benefits. Along this successional gradient, we used Biolog-ECO plates combined with soil enzyme assays (catalase, urease, sucrase, and acid phosphatase) to assess the dynamics of microbial carbon metabolic activity, measured by average well color development (AWCD). The results showed a systematic decline in AWCD values with advancing succession, revealing a pronounced reduction in overall microbial metabolic activity during wetland degradation. This trend correlated with loss of soil moisture, organic carbon, and nitrogen nutrients. Microbial communities in early successional wetland stages (i.e., original natural wetland and wetland edge) preferred labile carbon sources (e.g., carbohydrates, amino acids), while forested stages favored relatively more structural (e.g., polymers, phenolic compounds). These findings indicate that vegetation succession regulates microbial carbon metabolism by modifying soil physicochemical properties, providing insights for wetland restoration. Full article

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system. Full article

Accurate mapping of wetland vegetation is essential for ecosystem monitoring and conservation planning. Traditional workflows combining Sentinel-1 SAR, Sentinel-2 optical imagery, and topographic data have advanced vegetation classification but require extensive preprocessing and often yield fragmented boundaries and “salt-and-pepper” noise. In this study, we compare a conventional multi-sensor classification framework with a novel embedding-based approach derived from the AlphaEarth foundation model, using a cluster-guided Random Forest classifier applied to the dynamic wetland system of Narran Lake, New South Wales. Both approaches achieved high accuracy ac with test performance typically in the ranges: OA = 0.985–0.991, Cohen’s κ = 0.977–0.990, weighted F1 = 0.986–0.991, and MCC = 0.977–0.990. Embedding based maps showed markedly improved spatial coherence (lower edge density, local entropy, and patch fragmentation), producing smoother, ecologically consistent boundaries while requiring minimal preprocessing. Differences in class delineation were most evident in fire-affected and agricultural areas, where embeddings demonstrated greater resilience to spectral disturbance and post-fire variability. Although overall accuracies exceeded 0.98, these high values reflect the use of spectrally pure, homogeneous training samples rather than overfitting. The results highlight that embedding-driven methods can deliver cleaner, more interpretable vegetation maps with far less data preparation, underscoring their potential to streamline large-scale ecological monitoring and enhance the spatial realism of wetland mapping. Full article

Crabronid wasps (Hymenoptera: Crabronidae) are ecologically important predators that provide various ecological services by regulating the arthropod populations, enhancing soil processes through nesting, serving as sensitive indicators of habitat condition, and providing pollen transfer for plants. However, as other invertebrates face biodiversity threats, these wasps might be under threat from environmental changes, and we need to assess the biodiversity patterns of these wasps in Yunnan Province. Unfortunately, no information is currently available about the pattern and factors responsible for the assemblages of these wasps within our study region. This study provides the first province-level assessment of habitat suitability, species richness, assemblage structure, and environmental determinants for Crabronidae in Yunnan by integrating species distribution modeling (SDM), multivariate clustering, and ordination analyses. More than 50 species were studied to assess habitat suitability in Yunnan using MaxEnt. Model performance was robust (AUC > 0.7). Suitability patterns varied distinctly among regions. Species richness peaked in southern Yunnan, particularly in the counties of Jinghong, Mengla, Menghai, and Jiangcheng Hani & Yi. Land use/land cover (LULC) variables were the dominant predictors for 90% of species, whereas precipitation-related variables contributed most strongly to the remaining 10%. Ward’s hierarchical clustering grouped the 125 counties into three community assemblage zones, with Zone III comprising the most significant area. A unique species composition was found within a particular zone, and clear separation among zones based on environmental variation was supported by Principal Component Analysis (PCA), which explained more than 70% variability among zones. Furthermore, Canonical Correspondence Analysis (CCA) indicated that both LULC and climatic factors shaped community structure assemblages, with axes 1 and 2 explaining 70% of variance (p = 0.001). The most relevant key factors in each zone were precipitation variables (bio12, bio14, bio17), which were dominant in Zone I; for Zone II, temperature and vegetation variables were most important; and urban, wetland, and water variables were most important in Zone III. Full article

Sustainable Urban Drainage Systems (SUDSs) are essential for stormwater management in urban areas, with varying hydrological, social, ecological, and economic benefits. Nevertheless, choosing the SUDS most appropriate for public spaces poses a challenge when balancing details/specifications against community decisions, primarily social implications and perceptions. Building on the SUDS design pillar of the amenity, this study outlines a three-phase methodological framework for selecting SUDS based on social facilitation. The first phase introduces the application of the Partial Least Squares Structural Equation Modeling (PLS-SEM) and Classificatory Expectation–Maximization (CEM) techniques by modeling complex social interdependencies to find critical components related to urban planning. A Likert scale survey was also conducted with 440 urban dwellers in Tunja (Colombia), which identified three dimensions: Residential Satisfaction (RS), Resilience and Adaptation to Climate Change (RACC), and Community Participation (CP). In the second phase, the factors identified above were transformed into eight operational criteria, which were weighted using the Analytic Hierarchy Process (AHP) with the collaboration of 35 international experts in SUDS planning and implementation. In the third phase, these weighted criteria were used to evaluate and classify 13 types of SUDSs based on the experts’ assessments of their sub-criteria. The results deliver a clear message: cities must concentrate on solutions that will guarantee that water is managed to the best of their ability, not just safely, and that also enhance climate resilience, energy efficiency, and the ways in which public space is used. Among those options considered, infiltration ponds, green roofs, rain gardens, wetlands, and the like were the best-performing options, providing real and concrete uses in promoting a more resilient and sustainable urban water system. The methodology was also used in a real case in Tunja, Colombia. In its results, this approach proved not only pragmatic but also useful for all concerned, showing that the socio-cultural dimensions can be truly integrated into planning SUDSs and ensuring success. Full article

Sympatric species are closely related taxa that coexist within the same habitat through niche partitioning, and kingfishers serve as an ideal group for studying such ecological mechanisms. The present study examined the perch height in relation to foraging behaviour and hunting success of five kingfisher species: Common Kingfisher (Alcedo atthis), White-throated Kingfisher (Halcyon smyrnensis), Pied Kingfisher (Ceryle rudis), Stork-billed Kingfisher (Pelargopsis capensis), and Black-capped Kingfisher (Halcyon pileata). The study was conducted between 2021 and 2023, across seven habitat types in Kerala, India (Kadalundi–Vallikkunnu Community Reserve (KVCR) mangroves, Kallampara mangroves, Vadakkumpad mangroves, Vazhakkad agroecosystem, Mavoor wetland, Sanketham wetland, and Elathur beach). A generalized linear mixed model (GLMM) with a binomial distribution and logit link function was used to analyze hunting success across species. The model indicated that the effect of perch height on hunting success varied among species, though neither perch height nor species identity alone had a significant effect. Most species favored mid-height perches (2–5 m) for foraging, with the Common Kingfisher exhibiting moderate success across all heights and habitats. The Pied Kingfisher showed significantly reduced success at higher perches, while the Stork-billed Kingfisher achieved the highest success at mid-heights (2–5 m). The White-throated Kingfisher showed a non-significant negative association with capture success, whereas the Black-capped Kingfisher exhibited a neutral to positive relationship across perch heights. Among all variables tested, prey availability emerged as the sole significant predictor of hunting success, indicating that prey abundance is the principal determinant of foraging efficiency in tropical wetlands, rather than environmental conditions. Our findings confirm a pattern of vertical stratification in resource partitioning among sympatric kingfisher species and underscore the importance of conserving habitats that retain natural perch sites of varying heights. Full article

Coastal wetland vegetation exhibits pronounced spectral mixing, complex mosaic spatial patterns, and small target sizes, posing considerable challenges for fine-grained classification in high-resolution UAV imagery. At present, remote sensing classification of ground objects based on deep learning mainly relies on spectral and structural features, while the frequency domain features of ground objects are not fully considered. To address these issues, this study proposes a vegetation classification model that integrates spatial-domain and frequency-domain features. The model enhances global contextual modeling through a large-kernel convolution branch, while a frequency-domain interaction branch separates and fuses low-frequency structural information with high-frequency details. In addition, a shallow auxiliary supervision module is introduced to improve local detail learning and stabilize training. With a compact parameter scale suitable for real-world deployment, the proposed framework effectively adapts to high-resolution remote sensing scenarios. Experiments on typical coastal wetland vegetation including Reeds, Spartina alterniflora, and Suaeda salsa demonstrate that the proposed method consistently outperforms representative segmentation models such as UNet, DeepLabV3, TransUNet, SegFormer, D-LinkNet, and MCCA across multiple metrics including Accuracy, Recall, F1 Score, and mIoU. Overall, the results show that the proposed model effectively addresses the challenges of subtle spectral differences, pervasive species mixture, and intricate structural details, offering a robust and efficient solution for UAV-based wetland vegetation mapping and ecological monitoring. Full article

As critical urban blue–green infrastructure, urban wetland parks serve as vital venues for visitors to obtain restorative experiences. However, existing studies primarily emphasize their ecological and economic benefits, with comparatively limited attention paid to their roles in promoting public mental health and enhancing well-being. Using Yanghu Wetland Park in Changsha as a case study, this research investigates how restorative environmental perception influences visitors’ well-being through two mediating variables: environmental preference and place attachment. A total of 251 valid responses were collected through field surveys and questionnaires. Structural equation modeling (SEM) was employed to empirically examine the relationships among the variables. This study enriches the theoretical framework of environmental psychology and urban landscape behavior research. It also provides evidence-based insights into the planning and design of urban wetland parks, contributing to the enhancement of public well-being and overall life satisfaction. Full article

The floodplain landscape of the lower Yellow River is jointly shaped by natural water-sediment processes and human activities. With intensified regulation by large reservoirs and increasing human development intensity, the landscape pattern of the floodplain has undergone significant changes. Clarifying the relative contributions of natural and anthropogenic factors, as well as their interactive mechanisms, is crucial for ecological management of the floodplain. Based on 40-year long-term land-use data and hydrological and meteorological observations, this study integrates landscape metrics, the human interference index (HI), grey relational analysis, and partial least squares regression to quantify the spatiotemporal dynamics of landscape pattern in the floodplain of the lower Yellow River and to elucidate the driving mechanisms underlying landscape-pattern evolution. The results indicate that (1) during the study period, the areas of cultivated land and built-up land in the floodplain continuously increased, whereas natural wetlands and grassland decreased accordingly. Taking 2000 as a breakpoint, the rate and direction of landscape change exhibited stage-dependent differences. (2) Landscape pattern metrics changed nonlinearly: the number of patches decreased first and then increased; the patch cohesion index increased first and then declined; and Shannon’s diversity index showed an overall downward trend. These changes suggest a process of landscape consolidation induced by agricultural cultivation, followed by re-fragmentation driven by the expansion of built-up land. (3) Driving-mechanism analysis shows that the HI is the primary driver of the current changes in floodplain landscape pattern. After the operation of the Xiaolangdi Dam, water-sediment conditions tended to stabilize and flood risk in the floodplain decreased, thereby creating favourable conditions for human activities. This study highlights the stage-dependent influences of natural and anthropogenic factors on floodplain landscape evolution under dam regulation and suggests that management strategies should be adapted to the current re-fragmentation phase, prioritizing the strict control of agricultural expansion and the restoration of ecological corridors to mitigate anthropogenic interference under stable dam regulation. Full article

The Ebinur Lake Basin, a key ecological security barrier for windbreak and sand control in northern Xinjiang, is crucial to the ecological safety of western China and the northern sand-prevention belt. Combining the basin’s geographical characteristics, this study comprehensively evaluated ecosystem service functions from four dimensions: water conservation, soil and water conservation, windbreak and sand-fixation, and biodiversity maintenance. Simultaneously, it conducted an ecological sensitivity assessment from four aspects: soil erosion, desertification, land use, and salinization sensitivity. The assessments of the importance of ecosystem service function and ecological sensitivity results were combined to create a tiered zoning plan for the basin. The basin was divided into four first-level zones: the Ebinur Lake Water Area and Wetland Biodiversity Protection Zone, the Desert Vegetation Windbreak and Sand Fixation Ecological Restoration Zone, the Oasis Agricultural Ecological Function Protection Zone, and the Mountain Water Conservation Zone. Six second-level zones were also delineated: the Ebinur Lake Wetland National Nature Reserve, Gobi Vegetation Distribution and Soil Erosion Sensitive Zone, Desert Vegetation Restoration Zone, Jinghe-Bortala Valley Oasis Agricultural Ecological Function Zone, Mountain Water Conservation and Forest-Grass Protection Zone, and Sayram Lake Water Body. This assessment and zoning plan provide support and scientific basis for the basin’s comprehensive ecological management, integrated protection and governance of mountains, rivers, forests, farmlands, lakes, grasslands and deserts, as well as regional ecological development. Full article

Pharmaceuticals and personal care products (PPCPs) are emerging contaminants posing ecological risks in wastewater. Constructed wetlands (CWs) offer sustainable treatment through integrated biological processes. In this study, a biomimetic microbial CW reactor was developed using 30 L aquariums with porous media, aeration setups, and surface plants to simulate natural wetland conditions. This design combines enhanced microbial degradation strategies using fungal (Trametes versicolor), bacterial (Pseudomonas aeruginosa), and consortia degradation, integrating multiple biological pathways. Synthetic wastewater containing 100 mg/L of selected PPCPs, including caffeine, methylparaben, and trichlorocarbanilide (TCC), was used to evaluate the degradation potential of these microbial treatments. While caffeine and methylparaben were effectively targeted, TCC degradation was inconclusive due to solubility limitations in the selected solvent. Over three months, system stability, plant growth, and microbial biomass were monitored, and contaminant degradation was tracked using Nuclear Magnetic Resonance analysis. Results demonstrated that individual fungal and bacterial treatments achieved near-complete caffeine degradation (99–100%) within seven weeks, while the combined treatment accelerated this process to just four weeks. Methylparaben followed a similar trend, achieving complete degradation by the seventh week. This study highlights the potential of microbial CW systems fortified with targeted microbial consortia as a scalable solution for pollutant removal. Future work should refine microbial combinations and analytical methods to expand the range of treatable pollutants. Full article

Constructed wetlands (CWs) are acknowledged as an effective and sustainable ecological technology for the treatment of wastewater, especially in the removal of nitrate and phosphate. This study investigated the application of natural siderite as a substrate in laboratory-scale tidal flow CWs to enhance simultaneous nitrate and phosphate removal. A systematic study was conducted to evaluate the impact of critical operational parameters, including siderite dosage, influent COD/N ratio, and hydraulic retention time (HRT) on system performance. Moreover, the corresponding changes in microbial community structure were explored. The results indicated that siderite significantly improved the elimination of nitrate and phosphate. Denitrification efficiency exhibited a strong dependence on both siderite dosage and organic carbon availability. The nitrate removal increased by 19.01 ± 6.37% compared to the non-siderite control under an optimal condition. Phosphorus removal demonstrated a primary reliance on the proportion of siderite, reaching a maximum removal improvement of 77.68 ± 26.27%. Analysis of microbial diversity revealed that siderite enhanced both richness and evenness of the microbial community and facilitated the proliferation of essential denitrifying genera, specifically Dechloromonas and Thiobacillus. Full article