Spatiotemporal Evolution and Spatial Analysis of Ecological Environmental Quality in the Longyangxia to Lijiaxia Basin in China Based on GEE.

The upper reaches of the Yellow River are critical ecological barriers within the Yellow River Basin (YRB) that are crucial for source conservation. However, environmental challenges in this area, from Longyangxia to Lijiaxia, have emerged in recent years. To assess the ecological environment quality (EEQ) evolution from 1991 to 2021, we utilized remote sensing ecological indices (RSEIs) on the Google Earth Engine (GEE) platform. Spatial autocorrelation and heterogeneity impacting EEQ changes were examined. The results of this study show that the mean value of the RSEIs fluctuated over time (1991: 0.70, 1996: 0.77, 2001: 0.67, 2006: 0.71, 2011: 0.68, 2016: 0.65, and 2021: 0.66) showing an upward, downward, and then upward trend. The mean values of the overall RSEI are all at 0.65 and above. Most regions showed no significant EEQ change during 1991-2021 (68.59%, 59.23%, and 55.78%, respectively). Global Moran's I values (1991-2021) ranged from 0.627 to 0.412, indicating significant positive correlation between EEQ and spatial clustering, and the LISA clustering map (1991-2021) shows that the area near Longyangxia Reservoir shows a pattern of aggregation, dispersion, and then aggregation again. The factor detection results showed that heat was the most influential factor, and the interaction detection results showed that greenness and heat had a significant effect on regional ecosystem distribution. Our study integrates spatial autocorrelation and spatial heterogeneity and combines them with reality to provide an in-depth discussion and analysis of the Longyangxia to Lijiaxia Basin. These findings offer guidance for ecological governance, vegetation restoration, monitoring, and safeguarding the upper Yellow River's ecological integrity.

Effect of global climate change on the sustainability of cold-water fish habitat in the alpine region: A case study on the Gymnocypris eckloni in the source region of the Yellow River.

Climate change at the global scale affects the watershed's hydrology and the river's hydrodynamic, water temperature (WT), and habitat conditions of organisms. This article proposes a quantitative assessment methodology framework for analyzing the impact of GCC on the cold-water fish habitat. This framework integrated GCC, downscaling, hydrological, hydrodynamic, water temperature, and habitat models and was applied to the source region of the Yellow River (SRYR), where there are Gymnocypris eckloni (G. eckloni) resource reduction problems. In this study, we developed a high-precision, loosely integrated hydrological, hydrodynamic, WT coupling model for SWAT-MIKE21 in the SRYR. The optimal latitude and longitude range (6° × 6°) covering the SRYR was established for downscaling, and future meteorological data under three GCC models was obtained. The main results present the discharge of spawning, and juvenile G. eckloni indicates an increasing trend from the radiation forcing low to high and from the near now to the future term. The WT increased (decreased) in April and June (May), with a maximum increase/decrease of 3.1°C (SSP370 in 2100)/1.4°C (SSP585 in 2050). The weighted useable area (WUA) demonstrated a trend of severe fluctuations in May, June, and October, and other months are equal to the base year. Total WUA (TWUA) displayed an increasing trend, with the maximum increase in spawning and juvenile period being 134.46% and 270.89%, respectively. Ultimately, the rise in confluence discharge and WT caused by GCC in the SRYR benefits spawning and juvenile G. eckloni. The results have guiding significance for the development of long-term and adaptive protection and restoration measures for G. eckloni, and provide a plan for predicting the impact of climate change on other organisms in river ecosystems in high-altitude cold regions.

Sustainable flood control strategies under extreme rainfall: Allocation of flood drainage rights in the middle and lower reaches of the yellow river based on a new decision-making framework.

Climate change has exacerbated the frequency and magnitude of extreme rainfall, which has led to the perpetuation of flooding as a hazard to humans and society. China has begun to consider introducing Flood drainage rights (FDR), a sustainable flood control measure, into non-engineering measures as a complement to engineering measures for flood control. FDR represent the right of regions to discharge regional floodwaters caused by extreme rainfall into the river, and are the primary means of controlling the amount of floodwaters from regions when regional flood capacity is exceeded. However, existing studies on quantitative FDR allocation still have limitations, and some previous methods have resulted in allocation schemes that are not entirely reasonable and fair because they do not comprehensively consider the influencing factors of FDR or the allocation method is unreasonable. This paper explores the impact of flooding on rural and agricultural areas. We incorporate the factors of agricultural economy and security and construct a system of the allocation indicators of FDR composed of five principles: Natural Environmental Endowment, General Economic and Social Development, Agricultural Economy and Security, Macro policy regulation, and Respect for Historical Background. Second, considering the influence of expert judgment and data of different time nodes on the allocation of FDR, we introduce the concepts of expert weight and time weight into the allocation model of FDR, and construct a new set of framework for the allocation of FDR, i.e., "[(expert weight + subjective weight)+(time weight + objective weight)]+decision making model ". To reduce the loss of information during the transformation of subjective judgments, we also introduced triangular fuzzy numbers for the transformation between expert judgments and numbers. Finally, we take the five provinces in the middle and lower reaches of the Yellow River as an example. Using the data from 2010 to 2021, we obtain the final allocation scheme (proportion) of FDR as Henan (33.26%) > Shaanxi (23.08%) > Inner Mongolia (21.31%) > Shanxi (14.44%) > Shandong (7.91%). On this basis, this paper utilizes sensitivity analysis and comparative validation to demonstrate the rationality and effectiveness of the method, and identifies several indicators that have a greater impact on the results of the allocation of FDR. FDR can form part of a set of integrated flood management system together with flood control projects, which greatly alleviates the drainage conflicts arising from flooding caused by extreme precipitation. Under extreme rainfall conditions, FDR improves drainage efficiency and minimizes the overall damage caused by flooding in the watershed. This study can contribute to the sustainable development of the watershed and provide a reference for the promotion and utilization of sustainable flood control measures.

Copper and temperature shaped abundant and rare community assembly respectively in the Yellow River.

Untangling assembly and microbial interaction of abundant and rare microbiota in aquatic ecosystem is pivotal for understanding how community assembly respond to environmental variables and co-occurrence patterns. Here, we explored the assembly mechanisms, their drivers, and species co-occurrence of abundant and rare microbiomes in the Yellow River using 16S rRNA gene sequencing in Lanzhou, China. Here, abundant community was ubiquitous across all sites, whereas rare community was uneven distributed. The richness and community dissimilarity of rare taxa were significantly greater than those of abundant ones. Stochastic processes structured the rare community assembly in spring and winter, while deterministic processes shaped the abundant and rare community assembly in other seasons and all sites. Copper and water temperature mediated the balance between deterministic and stochastic processes of abundant and rare community, respectively. A few abundant taxa with closer relationships frequently occupied central positions and had a great effect on other co-occurrences in the network, while the majority of keystone microbiota were rare microbiome and played a considerable part in maintaining the network structure. Our study provides some ecological proposals for water quality management and ecological stability of the Yellow River. KEY POINTS: • Deterministic process dominated abundant and rare community assembly. • Cu and TW mediated the balance of abundant and rare community assembly respectively. • Abundant taxa had a greater effect on other co-occurrences in the network.

Establishing a quantitative assessment methodology framework of water conservation based on the water balance method under spatiotemporal and different discontinuous ecosystem scales.

Water conservation (WC) is an essential terrestrial ecosystem service that mitigates surface runoff and replenishes groundwater, which has received considerable attention under the dual pressures of climate change and human activity. However, there is insufficient understanding of the trends in WC changes on temporal (annual, monthly, daily), spatial, and ecosystem scales. This study proposed a quantitative assessment methodology framework (QAMF) for analyzing the spatiotemporal variation of WC under different discontinuous ecosystems. The QAMF mainly used models and methods such as the hydrological model (SWAT), calibration and uncertainty program (SWAT-CUP), WC calculation formula (water balance method), and spatial analysis method (empirical orthogonal function and wavelet analysis). It was applied to the source region of the Yellow River (SRYR), where the ecological landscape pattern underwent varying degrees of degradation, and WC capacity decreased. The results show that: Firstly, the constructed SWAT in the SRYR had high accuracy, and the proposed formula for calculating WC was suitable for multi-temporal scale analysis of WC in spatially distributed discontinuous basins. Secondly, the annual and monthly WC were respectively 81.00-184.13 mm and -28.58-107.64 mm, and daily WC was positive during extreme precipitation periods and negative during dry periods. The regulating effect of WC was fully reflected on the daily scale, partially reflected on the monthly scale, and absent on the annual scale. Third, the crucial WC area was mainly distributed in the southeast, and there was a significant primary yearly cycle of WC in the SRYR. Finally, different ecosystems exhibited different WC capabilities, and protecting the diversity of ecosystems played an essential role in maintaining and improving the WC function in the SRYR. This project has great scientific significance and technological support for scientifically evaluating the WC capacity in the SRYR.

How to balance protection and development? A comprehensive analysis framework for territorial space utilization scale, function and pattern.

The harmonious coexistence of man and nature is a universally recognized standard to test the rational utilization of multifunctional territorial space, and the planning of territorial space adapted to nature is a scientific guide to balance ecological protection and human development. This study focuses on the inevitable relationship between the scale, function and pattern of territorial space utilization (TSU), and puts forward a process research framework of "background evaluation-advantage comparison-optimization conduction". Based on the evaluation of resource and environment suitability, this paper determines the scale of multifunctional territorial space through the potential conflict identification model of TSU. The location entropy method is used to identify the advantageous functions of the county level, and the matching characteristics of the research results and the current situation are obtained by comparing them with the current plan. Finally, from the county functional zoning to the regional TSU pattern, the corresponding optimization conduction path is designed to form a new development and protection pattern. The empirical results of research area show that: (1) The study area is suitable for urban construction and agricultural production as a whole. The ecological protection is mainly at the general important level, and there is a moderate potential conflict between the development and protection of territorial space. The space scale of urban construction, agricultural production and ecological protection are accounted for 8.77%, 78.71% and 12.52%, respectively. (2) The advantageous function of TSU in county-level administrative units is dominated by single advantageous function, and the number of composite advantageous functions is generally small. The advantageous functional types determined by this research have a high matching with the current plan. (3) Based on the analysis of the scale structure and functional use of territorial space, this paper defines the ecological space that should be strictly protected and the agricultural and urban space that should be moderately developed for production and construction, and sets up elastic development areas. Finally, a strategic pattern of "one corridor, two screens, three circles and four zones" is conducive to the realization of the beautiful vision of the unification of protection and development.

Changes in vegetation cover and its influencing factors in the inner Mongolia reach of the yellow river basin from 2001 to 2018.

Vegetation cover is one of the primary indicators of changes in ecosystems. China has implemented a few large-scale afforestation programs in the arid and semi-arid areas, including the Inner Mongolia Reach of the Yellow River Basin to prevent and control soil erosion. Although these programs have alleviated the environment problems in the region to a certain extent, the effects of the increasing vegetation greenness on the environments under climate change remain controversial for the argued large water consumption. In this study, the spatio-temporal characteristics of Normalized Difference Vegetation Index (NDVI) in the vegetation coverage area of the study area based on remote sensing data from 2001 to 2018. Meanwhile, using the Extreme Gradient Boosting (XGBoost) method - an excellent algorithm for ensemble learning methods - to forecast vegetation growth in the following ten years. The results indicated that, despite of the spatial heterogeneity, the vegetation NDVI exhibited a significant increase across the study area. Based on the NDVI trend, the area of improved vegetation in this region was much larger than the degraded area from 2001 to 2018, accounting for 85.9% and 8.6% of the total vegetation coverage area, respectively. However, the forecasting result by the Hurst index shows the future growth and carbon sequestration capacity in most areas showed a declining trend. Further, based on the Coupled Model Inter comparison Project - Phase 6 (CMIP6) data, the XGBoost method is used to predict the growth status and carbon sequestration capacity of vegetation in this area under different climate scenarios. The results showed that different climate scenarios had little effect on vegetation growth from 2019 to 2030. Results from this study may provide basis for the protection of ecological environment in the Inner Mongolia Reach of the Yellow River Basin.

Pedo-transfer functions of the soil water characteristic curves of the vadose zone in a typical alluvial plain area in the lower reaches of the Yellow River using machine learning methods.

The soil water characteristic curve (SWCC) is of great significance for studying the hydrological cycle, agricultural water management, and unsaturated soil mechanics. However, it is difficult to effectively obtain a large number of SWCCs because of the cumbersome and expensive determination experiments for SWCCs. Pedo-transfer functions (PTFs) established using soil physicochemical properties have become an effective method for solving this problem. However, due to the limitations of the establishment methods and the wide spatial variability of soil properties, it is still difficult to establish PTFs in a specific region. In order to establish the PTFs of SWCCs for the alluvial plain area of the lower reaches of the Yellow River, 233 soil samples were collected from the vadose zone in a typical area. These data were used as the data sources, and eight variables including clay, silt content, fractal dimension, bulk density, total porosity, pH value, organic matter content, and electrical conductivity were used as the influencing factors. By applying and comparing three machine learning algorithms, the PTFs of the SWCCs based on the random forest algorithm were obtained. Based on the Gini index of the random forest, the insensitive factors were eliminated and the optimal variable input mode was constructed. Based on the verification, there was little difference between the predicted water content and the measured water content. The determination coefficient R2 is 0.9308; the root mean square error (RMSE) is 0.0447; and the mean relative error (MRE) is 22.40%.

A hydrological perspective on drought risk-assessment in the Yellow River Basin under future anthropogenic activities.

Since the late 1970s, the Yellow River Basin (YRB) has experienced accelerated land-use/land cover changes (LULCC) and consumptive water use (CWU) that have imposed low-flow regimes. Upon the continuation of these anthropogenic activities in the future, significant hydrological alteration is expected. This study takes a hydrological perspective on drought to project changes in the YRB drought risk under future LULCC and CWU business-as-usual (BAU) scenarios. A combination of seasonal trend forecasting, drought indices, land-use and hydrological modeling techniques was used. Future LULCC is assessed based on two BAU scenarios to explore the patterns of LULCC with (LULCC-BAU1) and without (LULCC-BAU2) the continuation of the Chinese Grain for Green Program. The results indicated that LULCC-BAU2 will increase the risk of mild and moderate droughts, while CWU and LULCC-BAU1 will impose higher risk of severe and extreme events. LULCC-BAU1 is projected to exacerbate the duration and intensity of the agricultural/hydrological droughts. The frequency of hydrological drought under LULCC-BAU1 and CWU scenarios is projected to increase by 43% and 53% during 2021-2050. The future agricultural droughts will likely be more intense and prolonged than meteorological droughts. Hydrological droughts, however, will be characterized by prolonged but less intense drought comparing to the metrological droughts. The meteorological to agricultural drought propagation will likely be driven by LULCC under BAU1, while the meteorological to hydrological drought propagation is controlled by CWU changes.

Developmental and Histopathological Changes in the Gonads of Female Japanese Medaka Following Exposure to Water from the Yellow River, China.

Gonad development and histopathological changes typically associated with endocrine disruption were evaluated in female Japanese medaka (Oryzias latipes) exposed to river water from four representative cross-sections in the Yellow River (YR), China. Fish were held in the river water treatments from fertilization. Advanced ovarian development was observed in fish exposed to river water from Qinhe cross-section at 20 days post-hatch (dph) and in fish exposed to river water from all four cross-sections at 60 dph. Histopathological changes including increased oocyte atresia, perifollicular cell hyperplasia/hypertrophy, changes in ovarian staging, interstitial fibrosis and interstitial proteinaceous fluid were observed in the gonads of fish at 60 dph after exposure to river water from some cross-sections. Cytoplasmic retraction and karyoplasmic clumping were observed in fish exposed to river water from all four cross-sections at 60 dph. The results indicate that development and reproductive function in Yellow River fish is impaired, placing fish populations at risk.

Effects of shell sand burial on seedling emergence, growth and stoichiometry of Periploca sepium Bunge.

BACKGROUND: Sand burial plays an irreplaceable and unique role in the growth and distribution of vegetation on the Shell Dike Island in the Yellow River Delta. There are still some unknown on the effects of sand burial on the morphology, biomass, and especially the stoichiometry of Periploca sepium, as well as the relationship between these factors. RESULTS: Shell sand burial depth had a significant influence on seedling emergence, growth, and biomass of P. sepium. Shallow sand burial shortened the emergence time and improved the emergence rate, morphological and biomass of P. sepium compared to deep burial and the control. Burial depth significantly affected the nitrogen (N) and phosphorus (P) contents of the leaves. With deep burial, the carbon/nitrogen (C/N) and carbon/phosphorus (C/P) ratios decreased firstly and then increased with depth, while the nitrogen/phosphorus ratio (N/P) presented the contrary trend. Correlation analysis showed that the stoichiometry of N/P was positively correlated to morphology and biomass of P. sepium at different burial depths. Structural equation model analysis revealed that N was the largest contributor to P. sepium biomass. CONCLUSIONS: Optimal burial depth is beneficial to the seedling emergence, growth and nutritional accumulation of P. sepium. Stoichiometry has an important influence on the morphological formation and biomass accumulation.

Potentially toxic element (PTE) levels in maize, soil, and irrigation water and health risks through maize consumption in northern Ningxia, China.

BACKGROUND: Industrial and agricultural activities result in elevated levels of potentially toxic elements (PTEs) in the local environment. PTEs can enter the human body through the food chain and pose severe health risks to inhabitants. In this study, PTE levels in maize, soil, and irrigation water were detected, and health risks through maize consumption were evaluated. METHODS: Maize, soil, and irrigation water samples were collected in northern Ningxia, China. Inductively coupled plasma-optical emission spectrometry was applied to determine the contents of six PTEs. Bioaccumulation factor was used to reflect the transfer potential of a metal from soil to maize. Health risks associated with maize consumption were assessed by deterministic and probabilistic estimation. Sensitivity analysis was performed to determine variables that pose the greatest effect on health risk results. RESULTS: The levels of Pb and Cr in maize exceeded the standards, while the PTE levels in soil and irrigation water did not exceed the corresponding standards. The bioaccumulation factor values of the six PTEs in maize were all lower than 1 and followed the order of Cd > Zn = As > Cr > Cu > Pb. The hazard index (0.0986) was far less than 1 for all inhabitants implying no obvious non-carcinogenic risk. The carcinogenic risk value was 3.261 × 10- 5, which was lower than the maximum acceptable level of 1 × 10- 4 suggested by United States Environmental Protection Agency (USEPA). Females were at greater risk than males, and the age group of below 20 years had the greater risk among all the groups evaluated. Approximately 0.62% of inhabitants exceeded the level for non-carcinogenic risk, while 8.23% exceeded the level for carcinogenic risk. The As concentration and daily intake of maize contributed 35.8, and 29.4% for non-carcinogenic risk results as well as 61.0 and 18.5% for carcinogenic risk results. CONCLUSIONS: Maize was contaminated by Pb and Cr, whereas the associated soil and irrigation water were not contaminated by PTEs. Inhabitants would not suffer obvious harmful health risks through maize consumption. Arsenic level and daily intake of maize were the most sensitive factors that impact health risks.

The domestication event of the Tibetan pig revealed to be in the upstream region of the Yellow River based on the mtDNA D-loop.

OBJECTIVE: Evidence from previous reports indicates that pig domestication in East Asia mainly occurred in the Mekong region and the middle and downstream regions of the Yangtze River. Further research identified two new origin centers for domestic pigs in the Tibetan Plateau and the islands of Southeast Asia. However, due to the small sample size of Tibetan pigs, details of the origin and spread of Tibetan pigs has not yet been established. METHODS: We analyzed mitochondrial DNA control region (D-loop) variation in 1,201 individuals from nine Tibetan pig populations across five provinces. Comprehensive Tibetan pig samples were taken to perform the most detailed analysis of Tibetan pigs to date. RESULTS: The result indicate that Rkaze pigs had the lowest level of diversity, while Changdu pigs had the highest diversity. Interestingly, these two populations were both in the Tibetan Plateau area. If we calculate diversity in terms of each province, the Tibetan Plateau area had the lowest diversity, while the Chinese province of Gansu had the highest diversity. Diversity gradient analysis of major haplotypes suggested three domestication centers of Tibetan pigs in the Tibetan Plateau and the Chinese provinces of Gansu and Yunnan. CONCLUSION: We found two new domestication centers for Tibetan pigs. One is in the Chinese province of Gansu, which lies in the upstream region of the Yellow River, and the other is in the Chinese province of Yunnan.

Low population genetic differentiation in two Tamarix species (Tamarix austromongolica and Tamarix chinensis) along the Yellow River.

Geological events have been shown to be the main factors affecting the distributions and population genetic structure of species. However, the impact of the Yellow River, the second longest river in China, on the distribution and genetic structure of the endemic flora remains largely unknown. Here, we used microsatellites to evaluate the genetic structure of Tamarix austromongolica and Tamarix chinensis (343 individuals in total), two endemic tree species widely distributed along the Yellow River, as well as the role of river drainages in shaping the structure. We found that frequent gene flow resulted in low genetic differentiation among populations within species (T. austromongolica: Fst = 0.144, Nm = 1.486; T. chinensis: Fst = 0.103, Nm = 2.177); and low levels of genetic differentiation were detected between populations within species on the north and south banks. Also, high gene flow was found between populations in the upper reaches and those in the middle reaches, and middle reaches and lower reaches of the Yellow River (T. austromongolica: Fst = 0.023, Nm = 10.619; T. chinensis: Fst = 0.045, Nm = 5.306). Additionally, discriminant analysis of principal components (DAPC) and Bayesian analysis revealed a weak population structure in T. austromongolica and T. chinensis. Therefore, the Yellow River does not act as a barrier to dispersal and gene flow for Tamarix. Our findings provide support for the role of the river in shaping the spatial distribution and the genetic structure of species.

Spatial variability of soil salinity in coastal saline soil at different scales in the Yellow River Delta, China.

The objectives of this study were to explore the spatial variability of soil salinity in coastal saline soil at macro, meso and micro scales in the Yellow River delta, China. Soil electrical conductivities (ECs) were measured at 0-15, 15-30, 30-45 and 45-60 cm soil depths at 49 sampling sites during November 9 to 11, 2013. Soil salinity was converted from soil ECs based on laboratory analyses. Our results indicated that at the macro scale, soil salinity was high with strong variability in each soil layer, and the content increased and the variability weakened with increasing soil depth. From east to west in the region, the farther away from the sea, the lower the soil salinity was. The degrees of soil salinization in three deeper soil layers are 1.14, 1.24 and 1.40 times higher than that in the surface soil. At the meso scale, the sequence of soil salinity in different topographies, soil texture and vegetation decreased, respectively, as follows: depression >flatland >hillock >batture; sandy loam >light loam >medium loam >heavy loam >clay; bare land >suaeda salsa >reed >cogongrass >cotton >paddy >winter wheat. At the micro scale, soil salinity changed with elevation in natural micro-topography and with anthropogenic activities in cultivated land. As the study area narrowed down to different scales, the spatial variability of soil salinity weakened gradually in cultivated land and salt wasteland except the bare land.

Mid- and long-term runoff predictions by an improved phase-space reconstruction model.

In recent years, the phase-space reconstruction method has usually been used for mid- and long-term runoff predictions. However, the traditional phase-space reconstruction method is still needs to be improved. Using the genetic algorithm to improve the phase-space reconstruction method, a new nonlinear model of monthly runoff is constructed. The new model does not rely heavily on embedding dimensions. Recognizing that the rainfall-runoff process is complex, affected by a number of factors, more variables (e.g. temperature and rainfall) are incorporated in the model. In order to detect the possible presence of chaos in the runoff dynamics, chaotic characteristics of the model are also analyzed, which shows the model can represent the nonlinear and chaotic characteristics of the runoff. The model is tested for its forecasting performance in four types of experiments using data from six hydrological stations on the Yellow River and the Yangtze River. Results show that the medium-and long-term runoff is satisfactorily forecasted at the hydrological stations. Not only is the forecasting trend accurate, but also the mean absolute percentage error is no more than 15%. Moreover, the forecast results of wet years and dry years are both good, which means that the improved model can overcome the traditional ''wet years and dry years predictability barrier,'' to some extent. The model forecasts for different regions are all good, showing the universality of the approach. Compared with selected conceptual and empirical methods, the model exhibits greater reliability and stability in the long-term runoff prediction. Our study provides a new thinking for research on the association between the monthly runoff and other hydrological factors, and also provides a new method for the prediction of the monthly runoff.

Occurrence and Biological Effects of Endocrine Disrupting Chemicals in the Yellow River (Zhengzhou Section).

Estrogenic activities of river water from four representative cross-sections of the Yellow River (Zhengzhou section) and their effects on reproduction and development of fish were assessed. MVLN assay showed estradiol equivalents of river water from Yiluohe, Xinmanghe, Qinhe and Huayuankou cross-sections were 1.09 ± 0.11, 0.72 ± 0.01, 1.19 ± 0.19 and 0.80 ± 0.04 ng/L, respectively. Significant vitellogenin (VTG) inductions were observed in adult male Japanese madaka (Oryzias latipes) after 30 days of exposure to river water from Yiluohe and Qinhe cross-sections (p < 0.05). Hepatic-somatic index was significantly elevated in fish exposed to water from Qinhe cross-section (p < 0.05). A significant delay in time to hatching was observed in embryos treated by water from Xinmanghe cross-section (p < 0.05). Significant lower survivals were observed in fish treated by water from Yiluohe and Xinmanghe cross-sections after a full life cycle exposure (p < 0.05). Exposure of water from Yiluohe and Qinhe cross-sections induced significantly elevated VTG levels in the first sexually mature male fish (p < 0.05). Both the in vitro and in vivo bioassay demonstrate endocrine disrupting chemicals exist in the Yellow River (Zhengzhou section) and fish in Yiluohe and Qinhe cross-sections can be at a risk of reproductive and developmental impairment.

Distribution of microplastics in Lanzhou section of the Yellow River: Characteristics, ecological risk assessment, and factors analysis.

Microplastic (MP) is an emerging pollutant that has attracted attention in the environmental field, and the research of MPs in freshwater systems needs to be strengthened. To characterize the MPs in surface water and sediments of the western urban river network, water and sediment samples were collected. The results showed that the abundance of MPs in the water body of the river network ranged from 7 to 172 n/L, whereas the abundance of MPs in the sediments ranged from 7 to 144 n/kg, and the average abundance in the dry season was significantly higher than that in the rainy season. The majority of MPs (83.67 %) were < 1 mm and fibrous. The most commonly identified types of MPs were PET and PP, while the color blue was frequently observed. MPs have the potential to vertically migrate in sediments, with size, shape, density, and hydrodynamic forces being the main factors that contribute to this process. Correlation analysis results revealed that anthropogenic and meteorological factors, including precipitation, atmospheric conditions, and population density, had a discernible impact on the abundance, size, and shape of MPs. The ecological risk of MPs was assessed using the Polymer Hazardous Index (PHI), Pollution Load Index (PLI), and Potential Ecological Risk Index (PERI) methods, and the results showed that the overall ecological risk of the Lanzhou section of the Yellow River was low. This study can provide a scientific basis for monitoring and risk assessment of emerging contaminants such as MPs in the river environment.

The Yellow River is the key corridor for Tamarix austromongolica to disperse from Asia inlands to east seashores.

Plants of the Tamarix L. genus (Tamaricaceae) mainly occur in arid inlands of Asia, but a few species occur in the coastal areas of China, and the Yellow River may account for this. This study was conducted to elucidate whether and how the Yellow River affects the pattern and development of the Tamarix genus, involving two critical species of Tamarix austromongolica Nakai and Tamarix chinensis Lour. With geographical distribution data, relationships of T. austromongolica with the Yellow River and the pertaining watershed were examined using the method of random permutation. The base-diameter structures of T. austromongolica populations were investigated and compared between different riparian lands that suffer discriminative water inundation. The nearest distances from T. austromongolica locations to the Yellow River and the pertaining watershed were significantly lower than the theoretical expectations in the condition of random distribution (p < .05). In many riparian lands along the Yellow River, wild T. austromongolica populations occurred with vigorous juveniles, despite frequent human disturbances. In coastal areas near the present estuary of the river, wild T. austromongolica plants were still found. In T. austromongolica populations near the Yellow River and sea, the rates of juvenile plants were significantly higher than in other populations situated farther from the river or sea. These findings suggest that the Yellow River can facilitate the eastward dispersal of Tamarix plants that reasonably caused the evolution from T. austromongolica to T. chinensis in ancient coasts in the China east.

Enhancing vegetation formation classification: Integrating coarse-scale traditional mapping knowledge and advanced machine learning.

Mapping vegetation formation types in large areas is crucial for ecological and environmental studies. However, this is still challenging to distinguish similar vegetation formation types using existing predictive vegetation mapping methods, based on commonly used environmental variables and remote sensing spectral data, especially when there are not enough training samples. To solve this issue, we proposed a predictive vegetation mapping method by integrating an advanced machine learning algorithm and knowledge in an early coarse-scale vegetation map (VMK). First, we implemented classification using the random forest algorithm by integrating the early vegetation map as an auxiliary feature (VMF). Then, we determined the rationality of classified vegetation types and distinguished the confusing types, respectively, based on the knowledge of the spatial distributions and hierarchies of vegetation. Finally, we replaced each recognized unreasonable vegetation type with its corresponding reasonable vegetation type. We implemented the new method in upstream of the Yellow River based on GaoFen-1 satellite images and other environmental variables (i.e., topographical and climate variables). Results showed that the overall accuracy using the VMK method ranged from 67.7 % to 76.8 %, which was 10.9 % to 13.4 % and 3.2 % to 6.6 %, respectively, higher than that of the method without the early vegetation map (NVM) and the VMF method, based on cross-validation with 20 % to 60 % random training samples. The spatial details of the vegetation map using the VMK method were also more reasonable compared to the NVM and VMF methods. These results indicated that the VMK method can distinctly improve the mapping accuracy at the vegetation formation level by integrating knowledge of existing vegetation maps. The proposed method can largely reduce the requirements on the number of field samples, which is especially important for alpine mountains and arctic region, where collecting training samples is more difficult due to the harsh natural environment.