Search Results (173)

In river-connected lake regions, both land use and hydrological regime changes may affect the ecosystem services; however, few studies have attempted to elucidate their complex influences. In this study, the spatiotemporal dynamics of eight ecosystem services (crop production, aquatic production, water yield, soil retention, flood regulation, water purification, net primary productivity, and habitat quality) were investigated through remote-sensing images and the InVEST model in the Dongting Lake Region during 2000–2020. Results revealed that crop and aquatic production increased significantly from 2000 to 2020, particularly in the northwestern and central regions, while soil retention and net primary productivity also improved. However, flood regulation, water purification, and habitat quality decreased, with the fastest decline in habitat quality occurring at the periphery of the Dongting Lake. Land-use types accounted for 63.3%, 53.8%, and 40.3% of spatial heterogeneity in habitat quality, flood regulation, and water purification, respectively. Land-use changes, particularly the expansion of construction land and the conversion of water bodies to cropland, led to a sharp decline in soil retention, flood regulation, water purification, net primary productivity, and habitat quality. In addition, crop production and aquatic production were higher in cultivated land and residential land, while the accompanying degradation of flood regulation, water purification, and habitat quality formed a “production-pollution-degradation” spatial coupling pattern. Furthermore, hydrological fluctuations further complicated these dynamics; wet years amplified agricultural outputs but intensified ecological degradation through spatial spillover effects. These findings underscore the need for integrated land-use and hydrological management strategies that balance human livelihoods with ecosystem resilience. Full article

South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments with heavy metals (HMs). This study investigated the distribution, mobility, and influencing factors of HMs at the sediment–water interface. To this end, sediment samples were analyzed from three key regions (Xiangjiang River estuary, Zishui River estuary, and northeastern South Dongting Lake) using traditional sampling methods and Diffusive Gradients in Thin Films (DGT) technology. Analysis of fifteen HMs (Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, V, Cr, Cu, Tl, Co, and Fe) revealed significant spatial heterogeneity. The results showed that Cr, Cu, Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, and Fe exhibited high variability (CV > 0.20), whereas V, Tl, and Co demonstrated stable concentrations (CV < 0.20). Concentrations were found to exceed background values of the upper continental crust of eastern China (UCC), Yangtze River sediments (YZ), and Dongting Lake sediments (DT), particularly at the Xiangjiang estuary (XE) and in the northeastern regions. Speciation analysis revealed that V, Cr, Cu, Ni, and As were predominantly found in the residual fraction (F4), while Pb and Co were concentrated in the oxidizable fraction (F3), Mn and Zn appeared primarily in the exchangeable fractions (F1 and F2), and Cd was notably dominant in the exchangeable fraction (F1), suggesting a high potential for mobility. Additionally, DGT results confirmed a significant potential for the release of Pb, Zn, and Cd. Contamination assessment using the Pollution Load Index (PLI) and Geoaccumulation Index (Igeo) identified Pb, Bi, Ni, As, Se, Cd, and Sb as major pollutants. Among these, Bi and Cd were found to pose the highest risks. Furthermore, the Risk Assessment Code (RAC) and the Potential Ecological Risk Index (PERI) highlighted Cd as the primary ecological risk contributor, especially in the XE. The study identified sediment grain size, pH, electrical conductivity, and nutrient levels as the primary influencing factors. The PMF modeling revealed HM sources as mixed smelting/natural inputs, agricultural activities, natural weathering, and mining/smelting operations, suggesting that remediation should prioritize Cd control in the XE with emphasis on external inputs. Full article

Rodents are the main wildlife species in the Dongting Lake area and can even cause significant biological disasters. In order to investigate the relationship between rodent communities and vegetation, the relationship between rodent population characteristics and vegetation cover between 2000 and 2020 was analyzed. The results showed that the rodent community in Dongting Lake has obvious spatial and temporal variability, and that Microtus fortis and Apodemus agrarius are currently the main rodent species in the area, with a higher population density in eastern Dongting Lake. Meanwhile, rodent fatness varied significantly between seasons, with the highest rodent fatness in winter at most survey sites. There was also significant spatial and temporal variability in vegetation cover, and the overall trend was increasing. There was a significant relationship between vegetation cover and rodent population density and fatness, and the relationship varied by rodent species. Microtus fortis population density was significantly correlated with medium to high levels of vegetation cover, but fatness was significantly correlated with low to medium levels of vegetation cover. The relationship between population density, fatness, and vegetation cover of A. agrarius is opposite to that of M. fortis. The study confirms that M. fortis is still the main pest rodent species in the Dongting Lake area, but the monitoring of A. agrarius and vegetation cover should be strengthened. Full article

Wetlands are critical components of the global carbon cycle, yet their carbon sink dynamics under hydrological fluctuations remain insufficiently understood. This study employed the Carnegie-Ames-Stanford Approach (CASA) model to estimate the net ecosystem productivity (NEP) of the Dongting Lake wetland and explored the spatiotemporal dynamics and driving mechanisms of carbon sinks from 2000 to 2022, utilizing the Theil-Sen median trend, Mann-Kendall test, and attribution based on the differentiating equation (ADE). Results showed that (1) the annual mean spatial NEP was 50.24 g C/m²/a, which first increased and then decreased, with an overall trend of −1.5 g C/m²/a. The carbon sink was strongest in spring, declined in summer, and shifted to a carbon source in autumn and winter. (2) Climate variability and human activities contributed +2.17 and −3.73 g C/m²/a to NEP, respectively. Human activities were the primary driver of carbon sink degradation (74.30%), whereas climate change mainly promoted carbon sequestration (25.70%). However, from 2000–2011 to 2011–2022, climate change shifted from enhancing to limiting carbon sequestration, mainly due to the transition from water storage and lake reclamation to ecological restoration policies and intensified climate anomalies. (3) NEP was negatively correlated with precipitation and water level. Land use adjustments, such as forest expansion and conversion of cropland and reed to sedge, alongside maintaining growing season water levels between 24.06~26.44 m, are recommended to sustain and enhance wetland carbon sinks. Despite inherent uncertainties in model parameterization and the lack of sufficient in situ flux validation, these findings could provide valuable scientific insights for wetland carbon management and policy-making. Full article

This study focuses on the Dongting Lake region in China and evaluates ecological vulnerability using the Sensitivity–Resilience–Pressure (SRP) framework, integrated with Spatial Principal Component Analysis (SPCA) to calculate the Ecological Vulnerability Index (EVI). The EVI values were classified into five levels using the Natural Breaks (Jenks) method, and spatial autocorrelation analysis was applied to reveal spatial differentiation patterns. The Geodetector model was used to analyze the driving mechanisms of natural and socioeconomic factors on EVI, identifying key influencing variables. Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. Model performance was assessed using ROC–AUC, accuracy, recall, confusion matrix, and Kappa coefficient, and the best-performing model was interpreted using SHAP (SHapley Additive exPlanations). The results indicate that: ① ecological vulnerability increased progressively from the core wetlands and riparian corridors to the transitional zones in the surrounding hills and mountains; ② a significant spatial clustering of ecological vulnerability was observed, with a Moran’s I index of 0.78; ③ Geodetector analysis identified the interaction between NPP (q = 0.329) and precipitation (PRE, q = 0.268) as the dominant factor (q = 0.50) influencing spatial variation of EVI; ④ the Random Forest model achieved the best classification performance (AUC = 0.954, F1 score = 0.78), and SHAP analysis showed that NPP and PRE made the most significant contributions to model predictions. This study proposes a multi-method integrated decision support framework for assessing ecological vulnerability in lake wetland ecosystems. Full article

[Objective] To quantify key ecosystem services within the Dongting Lake region, clarify the trade-off/synergy relationships, and detect the driving factors in order to support the ecological sustainable development of the Dongting Lake region. [Methods] Using the InVEST model, taking the area around Dongting Lake as the study area, four ecosystem services including water yield, carbon storage, soil conservation, and habitat quality were quantitatively assessed. Interdependencies between ecosystem services were assessed using correlation analysis to quantify trade-offs/synergies, and the geodetector model was used to detect their driving factors. [Results] (1) From 2000 to 2020, the soil retention service and water yield service in the Dongting Lake area showed an increasing trend over time. The total water yield increased from 4.93 × 10¹⁰ m³ to 6.71 × 10¹⁰ m³, while the total soil retention increased from 4.46 × 10⁹ t to 5.77 × 10⁹ t; habitat quality and total carbon storage continued to decline, with habitat quality decreasing from 0.6906 to 0.6785 and carbon storage decreasing from 1.480 × 10⁹ t to 1.476 × 10⁹ t. (2) In the study area, significant synergistic effects existed between carbon storage and habitat quality, carbon storage and soil retention, carbon storage and water yield, habitat quality and soil retention, and soil retention and water yield. However, there was a significant trade-off relationship between habitat quality and water yield. (3) During the study period, ecosystem service trade-offs and synergy relationships in the Dongting Lake area were jointly influenced by natural factors and human activities. Ranked by the magnitude of driving factor influence, they were land use type, land use intensity, vegetation coverage, temperature, and nighttime light. [Conclusions] Synergies dominated the ecosystem services in the research region, and the influence of natural factors behind them was greater than that of human activities. These research conclusions offer a scientific foundation for the institutional construction of the ecological compensation mechanism in the Dongting Lake basin. Full article

For a long time, drought disasters have brought about a wide range of negative impacts on human socio-economics. Especially in large basins with many tributaries, once hydrological drought occurs synchronously in several tributaries, the hydrological drought condition in the mainstream will be aggravated, which will lead to more serious losses. However, there is still a lack of research on the probabilistic risk of simultaneous hydrologic droughts in various areas of large watersheds. In this study, the Standardized Runoff Index was used to characterize hydrological drought, and the Standardized Runoff Index (SRI) sequence characteristics of each region were analyzed. Subsequently, a multiregional hazard encounter probability distribution model with an R-vine structure was constructed with the help of the vine copula function to study the risk pattern of simultaneous hydrological drought in multiple tributaries under environmental changes. The model results showed that the probability of the four basins gradually decreased from 7.5% to 0.16% when the SRI changed from ≤−0.5 to ≤−2.0, indicating that the likelihood of the joint distribution of the compound disaster decreases with increase in the drought extremes. Meanwhile, the probability of hydrological drought in the three major basins showed significant spatial differences, and the risk ranking was Dongting Lake Basin > Poyang Lake Basin > Han River Basin. The model constructed in this study reveals the disaster risk law, provides theoretical support for the measurement of hydrological drought risk in multiple regions at the same time, and is of great significance for the prediction of compound drought disaster risk. Full article

Rural post-poverty alleviation areas are not on a solid developmental footing and therefore remain at risk of returning to poverty in the midst of rapid urbanization. Vulnerability assessment of socio-ecological systems is critical for identifying risks and enhancing resilience in rural areas transitioning out of poverty. Based on research data from 2012, 2017, and 2022 in the post-poverty alleviation areas of Hunan Province, this research establishes a Vulnerability-Scoping-Diagram (VSD) assessment framework for rural development vulnerability and Spatially-Explicit-Resilience-Vulnerability (SERV) analysis model from a socio-ecological system perspective. It comprehensively analyzes the spatial and temporal variations of the Rural Development Vulnerability Index (RDVI) in the study area. Geodetector is used to explore the main factors influencing the spatial and temporal variability of RDVI, and vulnerability type zones are classified by combining the dominant elements method. The findings indicate that: (1) The rural development vulnerability index of post-poverty alleviation areas in Hunan Province has obvious characteristics of spatial and temporal differentiation. The RDVI in western Hunan and southern Hunan is always high, while the RDVI in ChangZhuTan and Dongting Lake regions decreases year by year. (2) The RDVI of post-poverty alleviation areas in Hunan Province is determined by the three dimensions of exposure, sensitivity, and adaptability, exhibiting significant spatial and temporal variations. (3) Spatial autocorrelation analysis showed that areas with similar rural socio-ecological vulnerability in post-poverty alleviation areas of Hunan Province were significantly clustered spatially. (4) The core influencing factors of RDVI in Hunan’s post-poverty alleviation areas have shifted from natural disaster risk to multiple risk dimensions encompassing social resource load and ecological environment risk superimposition, resulting in more complex and diversified influencing factors. (5) By combining results from the RDVI assessment with the dominant elements method, the regions can be classified into multiple vulnerability type districts dominated by multiple elements or single-element dominance, leading to corresponding development suggestions. The study aims to examine the process of changes in vulnerability within rural development in post-poverty alleviation areas and its causal factors from a socio-ecological system perspective. This will provide a foundation for policy formulation to consolidate the results of post-poverty alleviation and promote the sustainable development of rural areas. Full article

Heavy metal pollution of lake sediments is one of the prominent ecological and environmental problems worldwide, and it is of great significance to conduct research on heavy metal pollution in lake sediments to protect the ecological environment, safeguard human health, and promote sustainable development. As an integral part of Dongting Lake, Datong Lake holds a crucial ecological position. More than 10 years ago, due to a series of factors, including excessive fertilizer application and fishing, the water quality of Datong Lake declined, resulting in varying degrees of contamination by Cd, Mn, and other heavy metals in the sediments. After 2017, Datong Lake began to establish a mechanism for protecting and managing the lake, and its ecological and environmental problems have been significantly improved. To clarify the current situation of heavy metal contamination in the sediments of Datong Lake, 15 sediment samples were collected from the lake, and the contents of soil heavy metals Cd, As, Pb, Cr, Cu, Mn, Ni, and Zn were determined. A Monte Carlo simulation was introduced to carry out the ecological and human health risk evaluation of the sediments in the study area to overcome the problem of low reliability of the results of ecological and human health risk evaluation due to the randomness and incompleteness of the environmental data as well as the differences in the human body parameters. The results and conclusions show that (1) the average values of Cd, Pb, Cr, Cu, Mn, Ni, and Zn contents in the sediments of Datong Lake are higher than the background values of soil elements in the sediments of Dongting Lake, and the average values of As contents of heavy metals are lower than the background values of the soil, and the heavy metal contamination in the sediments in the study area is dominated by slight contamination, and the possibility of point-source contamination is slight. (2) The results of both the Geo-accumulation index and Enrichment factor evaluation showed that the degree of heavy metal contamination of sediments was Ni > Cu > Cr > Mn > Cd > Pb > Zn > As. (3) The average value of the single ecological risk index of heavy metal elements, in descending order, was as follows: Cd > As > Pb > Cu > Ni > Cr > Zn > Mn; all the heavy metal elements were at the level of light pollution, and the average value of the comprehensive ecological risk index was 32.83, which is a slight ecological risk level. (4) Both non-carcinogenic and carcinogenic risks for all populations in the study area remain low following heavy metal exposure via ingestion and dermal pathways. Ecological and health risk assessments identified As and Cd as exhibiting significantly higher sensitivity than other heavy metals. Consequently, continuous monitoring and source-tracking of these elements are recommended to safeguard long-term ecological integrity and public health in the region. Full article

The Middle Yangtze River Urban Agglomeration, a critical ecological barrier in China, faces escalating pressures from rapid urbanization and climate change, leading to fragmented landscapes and degraded ecosystem services. To address the synergistic challenges of ecological protection and risk management, this paper takes the urban agglomeration in the middle reaches of the Yangtze River as the study area, and obtains the source patches through morphological spatial pattern analysis. Based on the spatial distribution of risky source areas, ecological blind zones are cut down by optimizing buffer zones and merging fragmented patches. Finally, a composite ecological network is constructed through circuit theory superimposed on the dual network method. The results showed that (1) there are 16 ecological source patches and 16 risk source patches in the study area. Six complementary ecological sources and four new ecological sources were obtained through the blind zone reduction strategy. The percentage of ecological blind zones reduced from 58.4% to 39.5%. (2) The integrated nodes with 11,366 connecting edges were identified. The integrated nodes are distributed around the central Jiuling-Mafushan Mountains, mainly in the western and southern areas of the Dongting Lake Plain. (3) Primary integration nodes are critical for network stability, with a 75% node failure threshold triggering systemic collapse. The proposed strategy of “mountain protection–plain control–railway monitoring” is consistent with China’s territorial and spatial planning. By incorporating the risk network into the conservation framework, this study provides feasible insights for balancing development and sustainability in ecologically fragile areas. Full article

Groundwater is one of the most critical drinking water resources on Earth, and its safety significantly impacts the ecological environment and human health. This study focuses on the pollution characteristics, sources, and health risks of potentially toxic elements (PTEs) in the groundwater of the Dongting Lake basin in China. It highlights the concentration distribution and pollution causes of common toxic elements such as manganese (Mn), copper (Cu), zinc (Zn), arsenic (As), mercury (Hg), iron (Fe), chloride ions (Cl⁻), and fluoride ions (F⁻). The results indicate that the Mn concentration reached 28.6 times the background value, followed by Cu at 16.7 times. The groundwater pollution level in the study area reached a severe contamination level, with Zn classified as severely polluted and Mn categorized as moderately to heavily polluted. Approximately 47.05% of the study area was severely contaminated by PTEs. The study further reveals that the primary sources of pollution are anthropogenic activities, including agricultural fertilization, industrial discharges, and urbanization processes, which have significantly elevated PTE concentrations in groundwater. Additionally, natural geochemical processes contribute substantially to the high concentrations of specific elements in certain areas. Health risk assessments indicate that long-term exposure to PTEs in groundwater may pose various potential threats to human health, particularly in terms of carcinogenic and non-carcinogenic risks. Children are identified as the most vulnerable group. This research provides a systematic scientific basis for the management of groundwater pollution in the Dongting Lake basin, emphasizing that the current pollution levels pose serious threats to regional ecosystems and public health. The findings not only offer guidance for groundwater management in the Dongting Lake basin but also serve as a valuable reference for groundwater pollution management in similar regions. Full article

As sensitive human-environment systems, lake-intensive regions are critical governance areas for advancing global low-carbon development. Rapid economic growth has intensified the imbalance between economic carbon sources and ecological carbon sinks in these regions. However, methods for measuring territorial space carbon budgets tailored to “production–living–ecological” functions are underdeveloped, and the mechanisms driving carbon imbalance risks remain unclear. To address these issues, this study develops a spatial measurement model for “carbon sources-carbon sinks” in the Dongting Lake region. Using exploratory spatiotemporal data analysis, this study identifies grid-scale variation patterns in carbon budgets. Finally, using the logarithmic mean Divisia index (LMDI) decomposition model, this study examines the driving mechanisms of carbon budgets from a territorial space perspective. The results indicate the following: (1) The territorial space of the Dongting Lake region follows a pattern where “ecological spaces surround production spaces, with living spaces interspersed among water network spaces”. Between 2005 and 2020, functional transitions primarily occurred between agricultural production spaces and forest or water ecological spaces. (2) The study area’s territorial space carbon budgets increased annually, though the growth rate slowed. Construction land was the most significant carbon emission source in territorial space. Spatially, carbon budgets exhibit a radial pattern, with high values concentrated in plains near water bodies, gradually decreasing inland. Spatiotemporal differentiation followed a north–south development trend along the water system axis. High-High clusters were concentrated in municipal areas with dense water networks. In contrast, Low-Low clusters appeared in peripheral mountainous regions to the west, east, and south. (3) Land-use efficiency had the most potent inhibitory effect on carbon budgets, cumulatively reducing carbon emissions by 1.37 × 10⁸ tC. Economic development had the strongest positive effect, adding 1.31 × 10⁸ tC in carbon emissions. Therefore, the Dongting Lake region should promote intensive land use, adjust industrial structures, and develop a green ecological economy to achieve sustainable carbon source–sink management. Full article

Air pollution has become a major environmental issue, posing severe threats to human health and ecosystems. Accurately predicting future regional air quality is crucial for effective air pollution control and management strategies. This study proposes a novel deep learning-based approach. First, Kriging interpolation was applied to meteorological indicators such as temperature, humidity, and wind speed, as well as climate-altering gas indicators like CO₂, SO₂, and NO₂ recorded at monitoring stations to obtain their spatial distributions over the entire region. Subsequently, a long short-term memory neural network (SwinLSTM) incorporating Swin Transformer feature extraction was employed to learn the correlations from regional meteorological data and historical air quality records. This model overcomes the limitation of traditional CNNs by capturing long-range spatial dependencies when processing two-dimensional meteorological data through its sliding window attention mechanism. Ultimately, it outputs air quality predictions in both spatial and temporal dimensions. This study collected data from 29 stations across four cities surrounding China’s Dongting Lake for experimentation. Predictions for PM2.5 and PM10 levels over the entire lake area were made for 1, 6, and 24 h. The results demonstrate that the proposed SwinLSTM architecture significantly outperforms the current mainstream ConvLSTM architecture, with an average R-squared improvement of 5%, establishing a new state-of-the-art model for spatiotemporal air quality prediction. Full article

Anthropogenic and climatic stresses threaten water security across the Yangtze River Basin (YZRB), which safeguards the population and economic development that is responsible for nearly half China’s GDP. Understanding trends and drivers of open surface water in the YZRB is crucial yet remains poorly investigated. This study proposes a new method to eliminate shadow impacts on water extraction, achieving 96% accuracy, and develops a long-term dataset from 1986 to 2022 using Landsat imagery on the Google Earth Engine platform. Trends in water area changes were analyzed for source region, typical river and lake dominated regions of YZRB, and partial least squares regression was used to attribute the major climatic and anthropogenic drivers of water change. The results show that water area generally increased by 39.88%, with divergent trends across regions. Source and river dominated regions both exhibited notable growths by 49.43% and 37.01%, respectively. Increases in the water area in the source region comes from both lakes and rivers, driven by increasing temperature and precipitation in permafrost regions, while increases in river dominated regions come from permanent water induced by construction of mega dams. Changes of the water body in lake dominated regions are mainly influenced by seasonal water and show varied trends. Poyang and Dongting lakes have decreasing water area, from 3354.24 to 2168.82 km² and 1504.79 to 850.47 km², respectively, which are both attributed to the impoundment of the Three Gorges Reservoir and alterations in precipitation patterns. While Tai Lake Basin experienced an increase from 1986 to 2003 due to expanded anthropogenic water bodies, it was followed by a decline after 2003 which was driven by urbanization. We therefore suggest systematically optimizing reservoir dispatching and land–water configurations to balance economic, societal, and environmental benefits. Full article

X-ray electron probe microanalyzer technology was used to study the microchemistry and habitat history of Coilia nasus collected from the Dawanzhou section of the Yangtze River between May and June 2023. The Sr/Ca ratio from the otolith core to the otolith diameter was low (640–1100 µm), representing the first stage of development. In the second stage, C. nasus exhibited two distinct types. The first type, which included individuals 5HK05 and 6HK03, exclusively inhabited brackish estuarine waters. The second type, comprising 13 individuals, resided in higher-salinity seawater environments (Sr/Ca > 7). Furthermore, individuals 5HK01, 5HK03, 5HK07, and 6HK05 displayed a phase with a high Sr/Ca ratio compared to other fish. Freshwater coefficient analysis indicated that C. nasus in the Dawanzhou water area was unlikely to continue upstream to Dongting Lake in the middle reaches of the Yangtze River but may have entered Poyang Lake through its mouth or reproduced in its upper reaches. Analysis of sexual maturity and migration history suggested that the Dawanzhou section primarily serves as a migration channel for C. nasus, with a potential spawning ground for this high-value fish located nearby. Full article