Search Results (1,038)

Antimicrobial resistance (AMR) is a major One Health challenge driven by antimicrobial misuse in human medicine, veterinary practice, animal production, and polluted environments. Migratory birds move among wetlands, farms, wastewater-affected habitats, landfills, and coastal ecosystems and may acquire and redistribute antimicrobial-resistant bacteria (ARB) and antimicrobial resistance genes (ARGs) across ecological and political boundaries. This perspective synthesizes evidence on exposure sources, bacterial reservoirs, resistance determinants, cross-species interfaces, and surveillance priorities while explicitly distinguishing four claims: detection or carriage, persistence in individual birds, redistribution along migratory routes, and onward transmission to recipient hosts or environments. Published studies report multidrug-resistant Escherichia coli, Klebsiella pneumoniae, Salmonella spp., Enterococcus spp., and Campylobacter spp., with determinants including blaCTX-M, blaTEM, blaNDM, mcr, tet, sul, and qnr genes. The eight evidence groups summarized here constitute an illustrative, non-comprehensive selection; they are predominantly observational surveys or screenings, and none reconstructs a complete source–bird–destination–recipient transmission chain. Taxon-specific ecology modifies exposure: gulls and storks frequently exploit refuse and wastewater, waterfowl and shorebirds connect aquatic habitats, whereas passerines often reflect more local point-source contamination. Current evidence therefore supports migratory birds primarily as mobile sentinels and opportunistic carriers of anthropogenic AMR, while acknowledging possible natural or ancestral resistance in avian-associated microbiota. Future surveillance should combine longitudinal sampling, baseline cohorts such as pre-migratory nestlings, paired bird–water–soil–sediment sampling, whole-genome sequencing, plasmid profiling, telemetry, environmental DNA, wastewater-based epidemiology, and interoperable veterinary reporting. Practical mitigation requires antimicrobial stewardship, wastewater and landfill control, farm biosecurity, and coordinated veterinary, environmental, and public-health action. Full article

Accurate evapotranspiration (ET) estimates are essential for hydrological assessment, water-resource management, and wetland conservation, yet global ET products often disagree in heterogeneous coastal environments. This study compared ERA5-Land, GLDAS Noah, TerraClimate, MERRA-2, MOD16A2GF, and PML_V2 across Hong Kong during 2001–2020 and examined their applicability to the Mai Po Marshes. The products were standardized to annual water-depth equivalents and evaluated using descriptive statistics, the Friedman repeated-measures test, Holm-adjusted Wilcoxon signed-rank tests, lag-1 autocorrelation analysis, and standard and Hamed–Rao modified Mann–Kendall tests. Spatial uncertainty was quantified using the inter-product coefficient of variation and summarized by land-cover class. Mean annual ET ranged from 530.09 mm yr⁻¹ for GLDAS to 1182.80 mm yr⁻¹ for ERA5-Land. Product differences were significant (χ²(5) = 94.74, p < 0.001; Kendall’s W = 0.947), and all pairwise contrasts remained significant after Holm correction. GLDAS was the only product with a significant increasing trend (Sen’s slope = 4.88 mm yr⁻², p < 0.001), while the remaining products showed no significant trends. Within Mai Po, ET estimates differed among products but showed negligible variation among aggregated wetland habitat classes. The findings support uncertainty-aware, multi-product interpretation for regional ET monitoring and cautious application to compact coastal wetlands. Full article

High-resolution Normalized Difference Vegetation Index (NDVI) data are essential for monitoring fine-scale coastal environmental dynamics, yet persistent cloud cover, rapid geomorphic change, and strong spatial heterogeneity limit the availability of temporally continuous observations. Existing spatiotemporal fusion approaches can partially address these limitations, but many rely primarily on data-driven feature learning and do not explicitly incorporate geographic information, leading to boundary blurring, structural inconsistency, and sensitivity to background noise in complex coastal environments. This study presents a geographically constrained Transformer-based framework for 2 m NDVI spatiotemporal reconstruction in coastal landscapes named Coastal-Prior-Embedded Global–Local Fusion Transformer (Coastal-GLFT). The approach integrates high-resolution Gaofen-6 panchromatic and multispectral imagery with high-frequency wide-field-view observations and auxiliary geographic datasets describing elevation, coastline proximity, and land use/land cover. Geographic priors were incorporated as explicit spatial constraints, while a spatiotemporal gating mechanism and global–local fusion architecture were used to improve the representation of temporal variation and multi-scale spatial structure. The method was evaluated using a multi-temporal dataset for the Yellow River Delta comprising 49 high-resolution scenes and 137 coarse-resolution scenes acquired between 2020 and 2025. Compared with representative physics-based, convolutional neural network, generative adversarial network, and Transformer-based fusion methods, the proposed approach reduced reconstruction error by approximately 5–72%, increased signal fidelity by approximately 1–12%, and improved structural similarity by approximately 2–52%. Compared with the strongest Transformer-based baseline, SwinSTFM, Coastal-GLFT reduced RMSE from 0.0896 to 0.0855, increased PSNR from 36.19 dB to 37.09 dB, and improved SSIM from 0.8551 to 0.8742. Qualitative analysis further demonstrated improved preservation of boundary structure, spatial continuity, and heterogeneous coastal features, including aquaculture ponds, tidal creeks, and fragmented wetlands. These results indicate that integrating geographic constraints with multi-scale Transformer-based reconstruction can improve the fidelity and structural consistency of high-resolution NDVI reconstruction in complex coastal environments. The framework provides a basis for fine-scale coastal vegetation monitoring and land-cover analysis, while future work should assess transferability across diverse coastal systems and improve computational scalability. Full article

Rapid changes in coastal salt marsh vegetation highlight the need for accurate monitoring to support sustainable management. This study aims to track annual salt marsh landscape dynamics and discuss vegetation succession mechanisms. A novel approach was proposed to improve the discrimination of different plant species by integrating phenological features derived from NDVI time series, thereby enhancing salt marsh classification. The results showed that the proposed method achieves an overall accuracy of 93.6%, significantly outperforming schemes based solely on spectral indices (81.6%) or combined spectral and textural features (85.5%) (p < 0.05). The overall accuracy of annual classification maps for the Yancheng National Nature Reserve wetland from 1994 to 2025 averaged 90.5%, with a minor fluctuation of 2.8%, demonstrating the accuracy and reliability of this method for long-term monitoring of salt marsh landscapes. Annual classification maps revealed that the encroachment of Spartina alterniflora and Phragmites australis has intensified the fragmentation of Suaeda salsa. Notably, eradication efforts targeting Spartina alterniflora appear to have contributed to controlling this invasive species (decreasing by 33.22 km²) and restoring native species (increasing by 2.56 km²). This method serves as a reference for advancing salt marsh landscape classification frameworks. Full article

Living shorelines are widely promoted as nature-based solutions to coastal erosion and wetland protection, yet hardened shoreline structures continue to dominate even in jurisdictions with explicit policy mandates prioritizing living shorelines. In this research, we examine why non-optimal shoreline modification outcomes persist in Virginia (USA) despite a regulatory framework designed to promote ecological alternatives. We use primary data from interviews with wetlands board members, marine contractors, and nonprofit organizations and findings from a secondary survey of shoreline property owners to analyze shoreline management as a multi-sector collaborative decision-making process. Findings show that shoreline outcomes are shaped less by individual regulatory decisions than by recurrent interaction mechanisms across sectors that operate upstream of permit review. Contractors play a critical agenda-setting role by shaping the alternatives presented to property owners, while social norms, anticipatory adaptation to regulatory expectations, and informal decision heuristics constrain option sets before projects reach wetlands boards. Formal co-management institutions are therefore asked to arbitrate projects that are already highly constrained, limiting their ability to advance policy goals. Improving policy fidelity requires attention to decision sequencing, intermediary incentives, and structural feedback dynamics, rather than simply refining permitting guidance. Targeting upstream decision points and interaction mechanisms offers greater potential to align shoreline management outcomes with living shoreline policy objectives. Full article

Emerging contaminants (ECs), including pharmaceuticals, endocrine disruptors, pesticides, PFAS, and microplastics, are increasingly detected in aquatic environments due to their persistence, bioactivity, and limited removal by conventional treatment processes. These challenges are intensified in hyper-arid regions where desalination and wastewater reuse dominate water supply, concentrating contaminants and creating unique exposure pathways. The Arabian Gulf is one of the most environmentally stressed marine systems, characterized by hypersalinity, extreme temperatures, dense coastal development, and strong petrochemical influence. Despite its major role in global petrochemical and plastic production, the region lacks coordinated monitoring and regulatory frameworks, creating significant gaps in understanding EC occurrence, fate, and risks. Treatment systems designed for temperate climates often underperform under Gulf conditions, enabling contaminants to persist, accumulate in sediments, and enter marine food webs. This review examines the occurrence, behaviour, and removal challenges of ECs in the Gulf, where concentrations frequently exceed international benchmarks due to wastewater reuse, desalination brine discharge, maritime activities, and oil-related pollution. Regional factors such as hypersalinity, high temperatures, and petrochemical interactions further influence contaminant persistence and toxicity. Conventional treatments show reduced efficiency, while alternatives such as halophyte-based wetlands and brine valorisation show promise. However, key gaps remain in nanoplastics, PFAS speciation, and cumulative exposure, requiring coordinated monitoring and unified GCC regulations. Full article

Mangrove ecosystems are among the most productive and carbon-dense coastal forests globally, playing a critical role in plant diversity conservation and climate regulation. However, spatial variability in plant diversity, biomass allocation, and vegetation biomass carbon storage remains insufficiently quantified at regional scales, particularly in biogeographically complex regions such as Hainan Island, China. Here, we investigated four representative mangrove regions in Hainan Province: Dongzhai Port (DPMD), Qinglan Port (QPMD), Yalong Bay (YBMD), and Xinying Port (XPMD). Based on 73 field plots (0.5 ha each), we quantified species composition, community diversity, importance value index (IVI), organ-level biomass allocation (leaves, stems, and roots), and vegetation biomass carbon storage using species-specific allometric equations and published carbon concentration factors. A total of 12 mangrove species from 7 families were recorded, with Rhizophora stylosa Griff. consistently dominating across all sites (IVI range: 19.8–58.7%). Significant spatial heterogeneity was observed in all measured parameters. QPMD exhibited the highest total biomass (92.2 t ha⁻¹) and plant vegetation biomass carbon storage (40.1 t C ha⁻¹), whereas YBMD showed the lowest biomass (26.1 t ha⁻¹) and XPMD exhibited the strongest species dominance (Simpson’s D = 0.58). Stem biomass contributed the largest proportion (60–80%) across all sites, while root and leaf allocation varied significantly among regions, reflecting differences in community structure and stand characteristics. Vegetation biomass carbon storage patterns closely followed biomass distribution, demonstrating the dominant role of vegetation productivity in determining plant carbon accumulation. Our results reveal substantial spatial variation in mangrove diversity, biomass production, and vegetation biomass carbon storage. This study provides essential baseline information on mangrove vegetation biomass carbon stocks for region-specific conservation prioritization and climate mitigation strategies in tropical China. Full article

Under the combined impacts of climate change and intensified human activities in coastal zones, mangrove ecosystems are increasingly exposed to degradation, fragmentation, and declines in ecological functions. It is therefore important to systematically examine the progress and evolution of the research hotspots in remote sensing monitoring of mangroves. In this study, 942 publications on mangrove remote sensing monitoring from 2000 to 2025 were retrieved from the China National Knowledge Infrastructure (CNKI) and the Web of Science Core Collection, comprising 485 CNKI records and 457 Web of Science records. CiteSpace 6.4.R2 was used to conduct bibliometric and knowledge-mapping analyses of publication trends, geographic distribution, author collaboration networks, keyword co-occurrence, keyword cluster timelines, and burst keywords. The results show that research on mangrove remote sensing monitoring generally increased over time, with marked growth after 2015. Research topics gradually shifted from early studies on mangrove distribution mapping, land-use change, and image classification to multi-source remote sensing applications, change detection, biomass estimation, blue carbon assessment, and machine learning- and deep learning-based methods. Author collaboration networks provide a descriptive overview of collaboration patterns and suggest that cross-team and cross-regional collaboration still needs to be strengthened. Keyword co-occurrence, cluster timeline, and burst keyword results indicate that remote sensing monitoring, machine learning, deep learning, random forest, support vector machine, object-based image analysis, ALOS PALSAR, ALOS-2 PALSAR-2, blue carbon, carbon stock, aboveground biomass, ecosystem services, and forest degradation are important themes in this field. Future research should further strengthen multi-source remote sensing data integration, cross-regional validation of intelligent algorithms, degradation monitoring indicator systems, uncertainty assessment, and long-term time-series analysis. These efforts will improve the accuracy, comparability, and management applicability of mangrove remote sensing monitoring and provide scientific support for coastal ecological conservation, mangrove restoration, and blue carbon governance. Full article

Coastal wetlands are important sinks for heavy metals, yet the linkage between vertical redistribution, quantitative source contributions, and ecological–health risk drivers remain insufficiently understood. This study collected the stratified sediment samples from three depth intervals (0–20, 20–40, and 40–60 cm) from 28 representative sites in the coastal wetlands of western Bohai Bay, and evaluated the spatial distribution, vertical variation, pollution status, potential sources, and ecological–human health risks of eight heavy metals (Cr, Ni, Cu, Zn, As, Cd, Hg, and Pb). The mean concentrations were below the Class I limits of the Marine Sediment Quality Standard. Most metals were close to or slightly below regional background values, whereas Cu and As showed mild enrichment and Cr was higher than values reported for Bohai Bay and Hangzhou Bay. Vertical profiles were generally homogeneous, with weak enrichment of specific metals, probably due to sediment resuspension, tidal disturbance, and bioturbation. Pollution assessment based on the geoaccumulation index (Igeo), Nemerow pollution index (P_N), and pollution load index (PLI) consistently indicated low contamination levels, with Hg and Pb as the main contributors to the regional pollution load. Source apportionment indicated that heavy metals were jointly influenced by lithogenic background (38.9%), atmospheric deposition (31.1%), and local anthropogenic activities (30.0%). Ecological risk assessment showed that the integrated risk index (RI) remained within the low-risk category, although Hg consistently fell within the moderate-risk range and Cd approached the moderate-risk threshold. Health risk assessment showed that both non-carcinogenic and carcinogenic risks were within acceptable limits for all receptor groups. Children had higher risks in core residential areas, whereas adults showed higher risks in non-core industrial–agricultural zones because of increased exposure frequency. The source–risk analysis indicates that non-carcinogenic risk is mainly associated with background-derived Cr, whereas carcinogenic risk is primarily linked to anthropogenic As inputs. These findings indicate that source contributions and risk contributions are not necessarily consistent, highlighting the need for source-oriented risk management in industrialized coastal wetlands. Full article

The Laspias River and Lissos River sustain the hydrological and ecological functioning of the Vistonida Lake wetland complex, a protected Natura 2000 site and Ramsar Convention Wetland of International Importance, by regulating nutrient transport and supporting aquatic biodiversity. Thus, the water quality of the rivers Laspias and Lissos and their adjacent coastal zones located in the prefectures of Xanthi and Rhodope (NE Greece) respectively was monitored regarding key metal concentrations for a period of two years. The monitoring of these watersheds and coastal zones was based on seven sampling stations in the Laspias River, twelve stations in the Lissos River and four stations in each river’s coastal zone. During water monitoring of both rivers, a wide range of chemical elements was analyzed to assess water quality. In the present work, the heavy metal pollution index (HPI) and the heavy metal evaluation index (HEI) were assessed in both rivers and their coastal area for four successive seasons. The mean HPI and HEI values for the Laspias River were 54.66 ± 10.82 and 1.45 ± 0.22, whereas the respective indices in the Lissos River were 14.43 ± 4.14 and 0.39 ± 0.14. The mean HPI and HEI values for the adjacent coastal zones of the Laspias and Lissos Rivers were 7.42 ± 1.52 and 0.14 ± 0.05, as well as 10.39 ± 0.83 and 0.23 ± 0.02, respectively. Therefore, the average HPI values for both rivers and their coastal zones were below the proposed threshold (<100), while the HEI of the Laspias River classified the water quality in the second category (slightly affected, HEI from 1.0 to 2.0 due to the effect of Mn) and the Lissos River in the first category (very pure/pure, HEI < 1), respectively, considering drinking water thresholds. The HEI indices of their coastal zones characterized the water quality as very pure/pure. Full article

The Mississippi River Delta region is of national and international relevance in terms of agriculture, energy, river navigation, and fisheries. Being one of the most engineered rivers in the world, the Mississippi River has been intensively altered over the past 150 years. The river alterations included the construction of dams, levees, diversions, channelization, spillway flood control systems, and many others. These engineering practices have significantly modified the natural hydrology and sediment dynamics of the river and its deltaic region. While these interventions have provided critical benefits such as flood protection, improved navigation, and economic development, they have also led to profound environmental and ecological consequences. The reduction in sediment delivery to the Mississippi River Delta has accelerated land loss, contributing to the disappearance of coastal wetlands at an alarming rate. The land loss has diminished critical habitats for wildlife, reduced storm surge protection for coastal communities, and disrupted the delta’s natural ability to adapt to fast subsidence. The long-term sustainability of the delta is further threatened by the compounding effects of climate change, including rising sea levels, increased storm intensity, and extreme precipitation and drought conditions. This paper examines the effects, consequences, and future risks of the major river engineering practices on the Mississippi River Delta and provides strategic recommendations that balance human needs with changing natural conditions to ensure sustainability. Specific recommendations include river diversion upstream of New Orleans, better strategies to deal with floods and droughts, strategic maintenance or removal of portions of levees, hybrid coastal-inland human migration, improved transportation connections between coast and inland, and better preparation for future ecosystem shifts. This review is needed because river engineering has made the Mississippi River Delta economically vital yet increasingly vulnerable to sediment loss, wetland collapse, saltwater intrusion, flooding, and population decline. By synthesizing these linked natural and human consequences, it provides a timely framework for rethinking delta sustainability under climate change. Full article

Coastal lagoon Salt Ponds are highly valuable wetland systems where traditional salt production coexists with ecosystems of significant ecological importance, often characterized by high environmental sensitivity. In data-scarce coastal settings, particularly those located near river channels and drainage networks, assessing multiple environmental hazards remains a major challenge. This study proposes a simplified and transferable methodological framework for multi-hazard assessment in coastal Salt Pond environments (DAFFLE; Data Acquisition Fluvial Flooding and Liquefaction Evaluation), with particular emphasis on areas where field data are limited and fluvial processes and seismic effects may interact. The approach integrates three main components: first, improved terrain modelling using global elevation datasets and ICESat-2 laser altimetry data to better represent very flat coastal areas; second, flood hazard simulation by modelling water depths under different flood scenarios to map potential inundation; third, liquefaction susceptibility is assessed using surficial geological data and key geomorphological parameters, producing simplified probabilistic hazard maps informed by existing seismic hazard datasets or scenario-based assumptions. The proposed framework provides a scalable and practical tool for first-order multi-hazard assessment in vulnerable coastal Salt Pond environments. It supports comparative hazard analyses and decision-making in regions where detailed site-specific data and extensive field investigations are not available, offering a consistent baseline for coastal lagoon Salt Pond risk evaluation and management. Full article

In coastal wetlands, Tamarix chinensis often occurs as patches intermixed with Phragmites australis, Suaeda salsa, and saline–alkaline bare soil. This mixed distribution makes tamarisk prone to omission in medium-resolution remote sensing classification, while the recall of the target species is often masked by a relatively high overall accuracy. In this study, we focused on the Yellow River Delta National Nature Reserve and developed a multi-source feature set using summer 2025 Sentinel-2, Sentinel-1, and UAV/GPS data, comprising spectral, SAR, phenological, and red-edge-oriented features. To enhance the separability between tamarisk and co-occurring herbaceous vegetation, we introduced a red-edge–vegetation-cover coupling feature (RE_cov) based on their contrasting responses in the red-edge region. Within an XGBoost framework, we evaluated the marginal contribution of this feature using feature ablation, replacement, and spatial block cross-validation. The full feature set achieved an AUC of 0.8042, a recall of 0.9340, and an overall accuracy of 0.8194 on an independent test set. Ablation and replacement experiments showed that the red-edge-oriented features contributed to both model separability and tamarisk recall, and this contribution remained evident under spatial block validation. We further converted the pixel-level extraction results into local tamarisk density grades, revealing a pattern of a few clustered cores embedded within a broad low-density background. These results suggest that target-species-oriented red-edge–vegetation-cover coupling features can improve tamarisk recall while maintaining acceptable overall accuracy, providing a spatial product to support zoned patrol and management in protected coastal wetlands. Full article

Coastal saline–alkaline land has considerable potential for soil carbon sequestration, but how different land-use types affect microbial resource limitation and carbon-use efficiency (CUE) in coastal saline–alkaline soils remains unclear. Four representative land-use types, namely bare land (BL), wetland (WL), grassland (GL), and forest land (FL), were investigated in the coastal saline–alkaline soils of the Yellow River Delta. Soil physicochemical properties, microbial biomass, and extracellular enzyme activities were measured, and ecoenzymatic stoichiometry, microbial resource limitation, and CUE were subsequently calculated. Compared with BL, vegetated land-use types decreased electrical conductivity by 52.1–95.8%, while soil water content, soil nutrient indicators, and microbial biomass indicators increased by 47.1–77.5%, 2.6–136.8%, and 2.2–274.4%, respectively. WL was mainly phosphorus-limited, whereas BL, GL, and FL were primarily nitrogen-limited. Despite relatively high soil organic carbon and nutrient availability, GL showed the strongest N limitation and was the only land-use type showing C limitation. Model-estimated CUE ranged from 0.544 to 0.579 and followed the order FL > BL > WL > GL. Random forest analysis showed that soil physicochemical properties contributed most to CUE variation (42.9%). Structural equation modeling further indicated that soil physicochemical properties were indirectly associated with CUE, mainly through stoichiometric characteristics and microbial resource limitation, showing positive and negative associations, respectively. These findings provide microbial evidence for optimizing land-use patterns, vegetation restoration, and carbon-oriented ecological restoration in coastal saline–alkaline land. Full article

Tidal-flat changes during typhoon events are controlled by compound interactions among waves, tides, runoff, sediment transport, and vegetation resistance. However, rapid prediction remains challenging because high-resolution process-based morphodynamic models are computationally expensive. This study developed an observation-supported coastal morphodynamic emulator for rapid prediction of typhoon-induced tidal-flat erosion and deposition in the Jiuduansha Wetland, Yangtze Estuary. Multi-source field observations collected during Typhoons Bebinca and Pulasan in September 2024 were first used to validate a coupled MIKE21 FM model. The validated model was then applied to generate hydrodynamic and morphodynamic samples for emulator training and testing. Generalized Lagrangian mean velocity and bottom shear stress were selected as physically meaningful inputs. Current-timestep bed-level change was predicted using a UNet model enhanced with the Convolutional Block Attention Module (CBAM), hereafter referred to as CBAM-UNet. The numerical model reproduced the observed processes with acceptable accuracy, with Skill values of 0.98–0.99 for water level, 0.83–0.84 for wave height, and 0.82 for suspended sediment concentration. Compared with the conventional UNet, CBAM-UNet reduced the final cumulative RMSE from approximately 17.2 mm to 8.8 mm, corresponding to an error reduction of about 49%. Under prescribed wave, runoff, and tidal perturbations, the emulator reproduced the main erosion–deposition patterns, with final cumulative RMSE values of approximately 6.67 mm, 5.43 mm, and 10.68 mm, respectively. Across validation cases, replacing the morphodynamic module with the emulator reduced the average runtime by 42.50%. These results indicate that observation-supported morphodynamic emulation can support rapid tidal-flat assessment under compound typhoon forcing. Full article