Distribution of Heavy Metals in the Tissues of Saunders’s Gulls in the Yellow River Delta

Estimation of ecological water supplement for typical bird protection in the Yellow River Delta wetland

Source apportionment of potentially toxic elements in soils of the Yellow River Delta Nature Reserve, China: The application of three receptor models and geostatistical independent simulation

In order to understand the spatial distribution, ecological risks, and pollution status of nutrients and heavy metals in the coastal tidal creek water of the Yellow River Delta (YRD), a total of 21 water samples were collected from 7 sample sites. The results indicated that along the coastline from northwest to southeast in the YRD, the concentrations of TN, TP, and NH4+-N in the water decreased and then increased; the Cu concentration increased, decreased, and then increased; and the Pb concentration decreased. The average TN/TP mass ratio indicated that the tidal creek water belonged to a potential phosphorus-restricted eutrophication state. The RI result indicated that Cu and Pb in the water were at low ecological risk, while the SSD and RQ results indicated that Cu in the water was at a high ecological risk level and had potential harm to aquatic organisms. Based on the single-factor method, the water quality of the tidal creek inside and outside the Yellow River Delta Nature Reserve belonged to Grade IV. Cu should be controlled to improve the water quality and reduce the ecological risk, especially in the Yellow River Delta Nature Reserve.

Coastal wetland is a major part of wetlands in the world. Land cover and vegetation mapping in a deltaic lowland environment is complicated by the rapid and significant changes of geomorphic forms. Remote sensing provides an important tool for coastal land cover classification and landscape analysis. The study site in this paper is the Yellow River Delta Nature Reserve (YRDNR) at the Yellow River mouth in Shangdong province, China. Yellow River Delta is one of the fastest growing deltas in the world. YRDNR was listed as a national level nature reserve in 1992. The objectives of this paper are two fold: to study the land cover status of YRDNR, and to examine the land cover change since it was declared as a nature reserve. Land cover and vegetation mapping in YRDNR was developed using multi‐spectral Landsat Thematic Mapper (TM) imagery acquired in 1995. Land cover and landscape characteristics were analyzed with the help of ancillary GIS. Land use investigation data in 1991 were used for comparison with Landsat classification map. Our results show that YRDNR has experienced significant landscape change and environmental improvement after 1992.

Elemental stoichiometry (C, N, P) of soil in the Yellow River Delta nature reserve: Understanding N and P status of soil in the coastal estuary

Estuarine habitats are a critical zone of the Earth with strong land-sea interactions, that are strongly influenced by human activities. Microplastics (MPs) pollution in the Yellow River Delta (YRD) wetland, a typical young warm-temperate estuarine wetland, has not been comprehensively studied. The morphology, abundance, particle size, and polymer composition of MPs in the surface sediments of the YRD wetland were determined, and the pollution status and ecological risk in the study area were evaluated using the pollution load index (PLI) and potential pollution risk index (PRI). The results showed that the abundance of MPs in the YRD wetland was 20-520 n·kg-1, with a median value of 150 n·kg-1. The MPs were primarily fibers in shape and black in color, with particle size over 1 mm. The polymer components were primarily rayon, polyethylene, polyester, and polyethylene terephthalate. The PLI and PRI values of the MPs in the area were between 0.04-0.96 and 0.00-171.60, respectively, indicating that the pollution of MPs in the YRD wetland was at a slightly polluted level with low ecological risk.

ContextEstuarine wetlands provide valuable ecosystem services, but 20–78% of coastal wetlands are facing the risk of loss by the end of the century. The Yellow River Delta (YRD) wetland, one of the most productive delta areas in the world, has undergone dramatic changes under the influence of a precipitous drop of sediment delivery and runoff, coupled with the invasion of Spartina alterniflora. Monitoring the spatio-temporal patterns, thresholds, and drivers of change in wetland landscapes is critical for sustainable management of delta wetlands.ObjectivesGenerate annual mapping of salt marsh vegetation in the YRD wetland from 1986 to 2022, analyze the trends of wetland patch area and landscape pattern, and explain the hydrological drivers of landscape pattern evolution.MethodsWe combined Landsat 5‒8 and Sentinel-2 images, vegetation phenology, remote sensing indices, and Random Forest supervised classification to map the typical salt marsh vegetation of the YRD. We applied piecewise linear regression to analyze YRD wetland changes and stepwise multiple linear regression to assess the impact of hydrological factors on landscape pattern.ResultsWe identified three stages of landscape pattern evolution with 1997 and 2009 as critical junctures, including the rapid expansion stage, gradual decline stage, and bio-invasion stage. In the rapid expansion stage, the wetland area expanded by 70%, while the typical salt marsh vegetation (Phragmites australis) area was reduced by 25%. In the gradual decline stage, the wetland was reduced by 21% and the Phragmites australis area was reduced by 16%. In the bio-invasion stage, coverage of Spartina alterniflora expanded rapidly, with a 68-fold increase in area relative to 2009, expanding at an average rate of 344 hm2 per year.ConclusionsAreas of total wetland, tidal flat, and Phragmites australis were significantly influenced by cumulative sediment delivery and cumulative runoff, which together explained 61.5%, 75.7% and 63.8% of their variation, respectively. Wetland and tidal flat areas increased with cumulative sediment delivery, while cumulative runoff had a weak negative effect. For Phragmites australis, cumulative runoff had a positive effect, whereas cumulative sediment delivery had a negative effect. Water resources regulation measures should be taken to prevent the degradation of wetland ecosystems, and intervention measures can be implemented during the seedling stage to control the invasion of Spartina alterniflora.

Methylobacter accounts for strong aerobic methane oxidation in the Yellow River Delta with characteristics of a methane sink during the dry season

Distribution, source diagnostics, and factors influencing polycyclic aromatic hydrocarbons in the Yellow River Delta wetland

Identification of wetland conservation and restoration priorities in regions of oil extraction in the Yellow River Delta using circuit theory modelling

The Yellow River Delta wetlands in China belong to the coastal wetland ecosystem, which is one of the youngest and most characteristic wetlands in the world. The Yellow River Delta wetlands are constantly changed by inland sediment and the influence of waves and storm surges, so the accurate classification of the coastal wetlands in the Yellow River Delta is of great significance for the rational utilization, development and protection of wetland resources. In this study, the Yellow River Delta sentinel-2 multispectral data were processed by super-resolution synthesis, and the feature bands were optimized. The optimal feature-band combination scheme was screened using the OIF algorithm. A deep learning model attention mechanism ResNet based on feature optimization with attention mechanism integration into the ResNet network is proposed. Compared with the classical machine learning model, the AM_ResNet model can effectively improve the classification accuracy of the wetlands in the Yellow River Delta. The overall accuracy was 94.61% with a Kappa of 0.93, and they were improved by about 6.99% and 0.1, respectively, compared with the best-performing Random Forest Classification in machine learning. The results show that the method can effectively improve the classification accuracy of the wetlands in the Yellow River Delta.

In recent years, the Yellow River Delta has been affected by invasive species Spartina alterniflora (S. alterniflora), resulting in a fragile ecological environment. It is of great significance to monitor the ground object types in the Yellow River Delta wetlands. The classification accuracy based on Synthetic Aperture Radar (SAR) backscattering coefficient is limited by the small difference between some ground objects. To solve this problem, a decision tree classification method for extracting the ground object types in wetland combined time series SAR backscattering and coherence characteristics was proposed. The Yellow River Delta was taken as the study area and the 112 Sentinel-1A GRD data with VV/VH dual-polarization and 64 Sentinel-1A SLC data with VH polarization were used. The decision tree method was established, based on the annual mean VH and VV backscattering characteristics, the new constructed radar backscattering indices, and the annual mean VH coherence characteristics were suitable for extracting the wetlands in the Yellow River Delta. Then the classification results in the Yellow River Delta wetlands from 2018 to 2021 were obtained using the new method proposed in this paper. The results show that the overall accuracy and Kappa coefficient of the proposed method w5ere 89.504% and 0.860, which were 9.992% and 0.127 higher than multi-temporal classification by Support Vector Machine classifier. Compared with the decision tree without coherence, the overall accuracy and Kappa coefficient were improved by 8.854% and 0.108. The spatial distributions of wetland types in the Yellow River Delta from 2018 to 2021 were obtained using the constructed decision tree. The spatio-temporal evolution analysis was conducted. The results showed that the area ofS. alternifloradecreased significantly in 2020 but it increased to the area of 2018 in 2021. In addition,S. alternifloraseriously affected the living space of Phragmites australis (P. australis) and in 4 years, 10.485 km2living space ofP. australiswas occupied byS. alterniflora. The proposed method can provide a theoretical basis for higher accuracy SAR wetland classification and the monitoring results can provide an effective reference for local wetland protection.

ABSTRACTAs an important ecosystem, wetlands play a crucial role in both regional and global environments. Accurate land-cover classification can facilitate the management and understanding of wetlands. Considering the timely and cost-effective characteristics of remote sensing, this technique was used to obtain land-cover information for the Yellow River Delta (YRD) wetland in this investigation. Landsat-8 Operational Land Imager (OLI) sensor data were selected for the data set in this study. A combined approach of multiple end-member spectral mixture analysis (MESMA) and Random Forest (RF) was developed for land-cover classification mapping of the YRD wetland. This study aimed (1) to determine whether the MESMA technique in combination with RF significantly improves the accuracy of classification in complex landscapes such as the YRD wetland, (2) to determine whether the RF classifier shows good performance in land-cover classification of the YRD wetland, and (3) to compare the proposed method with the traditional Maximum Likelihood Classifier (MLC). The proposed hybrid method showed good performance, with an overall accuracy of 89.5% and a kappa coefficient (κ) of 0.88. The inclusion of fractional information derived from MESMA can improve the classification accuracy by 2–3%. In addition, through a comparison with traditional maximum likelihood (ML) methodology, the effectiveness of the proposed approach was evaluated. Overall, the proposed approach in this study can relatively accurately delineate a land-cover classification map of the YRD wetland with Landsat-8 OLI remotely sensed data.

SummaryStaging sites are vital for large-sized migratory cranes, which require high-protein food sources during migration. In this study, we used field surveys and faecal analysis to determine the migration patterns and dietary composition of the globally threatened Red-crowned CraneGrus japonensispopulation that migrates and stages at the Yellow River Delta Nature Reserve (YRDNR), Eastern China. Analysis of 135 faecal samples collected during the migration season in 2008, 2010 and 2011 showed that 78.8% of the faeces comprised > 90% dry mass of tidal mudflat crabHelice tientsinensisremains, suggesting that tidal mudflat crab was an important source of food for these Red-crowned Cranes. Smaller percentages of two other crab species (Eriocheir sinensis,Macrophthalmus dilatatum), fish remains, ragwormsHediste diversicolorand vegetation were also detected in the faecal samples. Consumption of tidal mudflat crabs was found to increase from autumn through to spring. Surveys of tidal mudflat crabs from YRDNR revealed that female crabs have significantly smaller body size (dry mass) but higher energy reserve ratio (ash-free dry mass per body mass) compared to males. Red-crowned Cranes fed predominantly on small and medium-sized female crabs, with a female to male ratio of 5:1 in the diet, compared with the 1:2 ratio of female to male crabs found within the coastal wetland crab population. Our findings suggest that tidal mudflat crabs represent a critical food source for the migratory Red-crowned Crane population in YRDNR, and future crane conservation strategies should encompass the necessary measures to conserve the tidal mudflat crab population at this staging site.

Patterns of waterbird community composition across a natural and restored wetland landscape mosaic, Yellow River Delta, China