Search Results (118)

The ten-year fishing ban on the Yangtze River aims to restore aquatic biodiversity and rebuild fishery resources. Megalobrama skolkovii, a key species in the basin, was investigated using 2024 data to provide a preliminary assessment of its population structure, stock dynamics, and early recovery. Age analysis (n = 243) showed that 1–6-year-olds were dominated by fish aged 3 (35%), with few older than 4, indicating moderate structural truncation. Growth parameters modeled by the von Bertalanffy Growth Function yielded L_∞ = 61.89 cm and k = 0.25 year⁻¹, with a weight–growth inflection age of 4.4 years. Natural mortality (M = 0.48 year⁻¹) was estimated using Pauly’s empirical formula, and total mortality (Z = 0.55 year⁻¹) was estimated from the catch curve analysis. While fishing mortality (F) was statistically indistinguishable from zero, a plausible low-intensity fishing scenario was explored to assess potential impacts of residual activities. Length-based indicators (LBIs) showed P_mat = 46.05%, P_opt = 9.51%, and P_mega = 6.88%, suggesting reproductive recovery but incomplete structural restoration. These preliminary findings reveal an asymmetrical recovery trajectory, whereby physiological improvements and enhanced recruitment have occurred, yet full structural restoration remains incomplete. This underscores the need for continued, long-term conservation and monitoring to support population resilience. Full article

As the largest freshwater lake in China, Poyang Lake plays a crucial role in hydrological processes. Conventional models often fail to capture the time-lagged relationships between meteorological drivers and runoff responses, while lacking regional generalization capability. To address these limitations, this study proposes a novel XAJ-LSTM-TFM hybrid model that accounts for time-lagged hydrological responses and enhances the regional applicability of the Xinanjiang model. The model innovatively integrates the physical mechanisms of the Xinanjiang model with the temporal learning capacity of LSTM networks. By incorporating intermediate hydrological variables (including interflow and groundwater flow) along with 1–3 day lagged meteorological features, the model achieves an average 15.3% improvement in Nash–Sutcliffe Efficiency (NSE) across five sub-basins, with the Ganjiang Basin attaining an NSE of 0.812 and a 25.7% reduction in flood peak errors. The results demonstrate superior runoff simulation performance and reliable generalization capability under intensive anthropogenic activities. Full article

Recreational fisheries increasingly intersect with the habitats of flagship species, i.e., species that attract public attention and drive conservation efforts, raising potential ecological conflicts. This study investigated the spatial coupling between recreational fisheries and three flagship species in the Yangtze River Basin: the Chinese alligator (Alligator sinensis), the Yangtze finless porpoise (Neophocaena phocaenoides), and the scaly-sided merganser (Mergus squamatus). Drawing on over 10,000 fishing Points of Interest recorded between 2015 and 2024 and over 300 verified species occurrences, this study applied a Random Forest model with spatial integration and a Maximum Entropy model to examine estimated current distributions and forecast interactions from 2025 to 2035. Flagship species habitat suitability was modeled and projected at a spatial resolution of 1 km, while recreational fishing density was resolved on a coarser grid of 1.875° × 1.25° in latitude–longitude dimensions. Results reveal a substantial increase in high-risk overlap zones. For example, high-density fishing areas within high-suitability habitats for the scaly-sided merganser expanded from 0 km² in 2015 to 85,359 km² in 2024. Projections indicate continued intensification of such overlaps, particularly in regions including Ma’anshan–Wuhu, the Taihu–Chaohu–Poyang lake system, and Yibin. These findings offer robust, model-driven evidence of growing spatial conflicts and offer actionable insights for ecosystem-based governance. The methodological framework is transferable and supports broader applications in other regions and species under ecological sustainability goals. 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

Under the global urbanization context, irrational land use patterns have exacerbated ecosystem imbalance. Developing watershed ecological risk assessment methods based on adaptive cycle theory holds significant scientific importance for flood risk prevention. This study established a watershed ecological risk assessment framework within the adaptive cycle framework, focusing on the Poyang Lake Ecological Economic Zone in the middle-lower Yangtze River Basin. The results revealed that high-risk ecological areas clustered around the Poyang Lake water system with scattered urban distribution, while medium-risk zones dominated the study area. Low-risk regions primarily concentrated in the Yuanhe Plain of southwestern region. The system exhibited significant spatial heterogeneity in “exposure” and “disturbance” risks. Medium–high exposure pixels accounted for 43.3% with a dispersed distribution, whereas disturbance pixels concentrated in Poyang Lake waters and developed urban areas (64.34%), indicating that disturbance exerted a stronger influence on risk assessment outcomes. Governance practices demonstrated that policy preferences may introduce biases into watershed ecological risk evaluations. Multi-scenario simulations using an Ordered Weighted Averaging (OWA) algorithm identified risk-uncertain zones in southeastern hilly areas and northern Poyang Lake waters, while distinguishing stable high/low-risk regions unaffected by decision-making influences. These findings provide critical references for formulating sustainable watershed management strategies. Full article

Sediment is a core part of lake ecosystems, and its organic matter (OM) content is a key indicator of lake ecological health and regional carbon cycling. OM provides nutrients for phytoplankton and algae in water, thereby influencing the degree of lake eutrophication. However, excessively high OM content may trigger water eutrophication, alter sediment’s physical and chemical properties, and ultimately threaten the stability and health of ecosystems. This study innovatively selected Poyang Lake, Taihu Lake, Qinghai Lake, and Hulun Lake from China’s four major geographical regions to systematically investigate sediments’ OM content, sources, and distribution characteristics at different times. The results showed that the organic matter content of sediments in lakes from different regions varied significantly and was influenced by multiple factors, such as watershed characteristics, eutrophication levels, human activities, and climate change. Poyang Lake and Taihu Lake, characterized by high levels of agricultural activities and urbanization within their basins, exhibit significant fluctuations in organic matter content, with total organic carbon (TOC) levels ranging from 0.35% to 2.9% and 0.7% to 2.4%, respectively. In contrast, Qinghai Lake and Hulun Lake, influenced by natural conditions and ecological policies, show relatively stable TOC levels, ranging from 1.3% to 2.75% and 1.25% to 3.58%, respectively. By analyzing sediments’ OM content and combining methods such as organic carbon, nitrogen isotopes, and organic C/N ratios, it is possible to effectively assess the ecological health of lakes, provide critical data support for pollution control, and play a significant role in carbon cycle management. Full article

The “Ten-Year Fishing Ban” policy in the Yangtze River Basin aims to restore ecological diversity but poses significant challenges for the fishermen in their transition to alternative livelihoods. This study focuses on fishermen who worked on Poyang Lake, using the sustainable livelihood framework and the theory of planned behavior, combined with fuzzy-set qualitative comparative analysis (fsQCA) and descriptive statistics, to explore the interaction effects of livelihood capital, ecological cognition, and compensation policies on fishermen’s behavioral responses. Key findings include the following: natural, financial, and psychological capital are core drivers of enhanced ecological cognition, with combined effects significantly increasing sensitivity to policy and environmental changes through pathways like “ecological transition drive”, “knowledge adaptation support”, and “multi-cooperation synergy”. Attitude, perceived behavioral control, and compensation policy transparency are crucial for positive responses, while social norms and policy fairness can compensate for individual motivation deficits, forming pathways like “ecological drive-policy recognition” and “norm drive-social support”. Current issues such as low compensation standards, insufficient retraining, and gender differences limit policy effectiveness. Optimizing measures like differentiated fishing permits, dynamic compensation mechanisms, and cultural empowerment are needed to balance ecological protection and social equity. The study suggests enhancing financial and psychological capital, improving vocational training systems, and increasing policy transparency to provide theoretical and practical references for sustainable global fisheries management. 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

The variation in water level at Jiujiang Station (JJS) directly affects flow exchange between the Yangtze River and the Poyang Lake. Quantitative research on the influencing factors of water level changes at JJS is of great importance for water supply and eco-environment protection in the Poyang Lake region. In this study, the Mann-Kendall method was used to test the trend of water level variation, and the impacts of riverbed incision and flow volume changes on water level at JJS were macroscopically analyzed using the observed monthly flow data series from 1981 to 2021. Furthermore, Long Short-Term Memory (LSTM) neural network model was used to simulate the impacts of outflow discharge of Three Gorges Reservoir (TGR) and flow discharge of the interval basin between TGR and JJS on water level at JJS; the partial dependence plot was adopted to analyze the impact of single feature variable variation on the simulation results. The results show that, after the TGR was put into operation in 2003, the water level changes at JJS mainly occurred during the impoundment period, the annual average storage of TGR was decreased 6.9 billion m³, and the annual average runoff volume at JJS was decreased 11.5 billion m³, which resulted in the average water levels at JJS being decreased 1.74 m and 2.11 m in September and October, respectively. The annual average runoff of JJS was increased 4.5 billion m³ with TGR replenishment of 1.8 billion m³ from December to March of the following year. Impacted by riverbed incision, the water levels at JJS were decreased 0.59 m and 0.99 m in September and October and increased 0.63 m from December to March. Every additional 5000 m³/s (1000 m³/s) of TGR outflow discharge could increase 1.0 m (0.16 m) the water level at JJS in September and October (from December to March of the following year). Full article

Climate change has significantly altered plant habitats within the Earth’s surface system, reshaping the global distribution and succession of vegetation. The spatiotemporal simulation of vegetation dynamics is essential for effective ecosystem management and conservation at regional scales. In this study, an improved method is developed to analyze the vegetation patterns and scenarios in the Poyang Lake basin, based on the High-Accuracy Surface Modeling (HASM) method and the improved Holdridge Life Zone (HLZ) ecosystem model. HASM is applied to generate high-resolution (250 m × 250 m) spatial grid data for key climate parameters, including mean annual biotemperature (MAB), total annual precipitation (TAP), and potential evapotranspiration ratio (PER), for each decade from 1961 to 2050. The distribution thresholds of vegetation types are calculated based on current vegetation data, MAB, TAP, PER, longitude, latitude, and elevation datasets. In the improved HLZ ecosystem model, the classification parameters of vegetation types have been expanded from three to six. The simulation results indicate that cultivated vegetation, subtropical coniferous forest, and subtropical grassland are the dominant vegetation types, accounting for 75.88% of the total area. Between 2020 and 2050, subtropical coniferous forest is projected to experience the greatest decrease in area, shrinking by an average of 2.65 × 10³ km² per decade. In contrast, subtropical evergreen–deciduous broadleaf mixed forest is expected to undergo the largest increase, expanding by an average of 1.96 × 10³ km² per decade. Vegetation types in high-altitude regions exhibit the most rapid changes, with an average decadal variation of 15.26%, whereas low-altitude regions show relatively slower changes, averaging 0.52% per decade. Overall, subtropical grassland, subtropical coniferous forest, and subtropical evergreen–deciduous broadleaf mixed forest in the Poyang Lake basin demonstrate high sensitivity to projected climate change scenarios. Full article

From 2020 to 2022, hydrological extremes such as severe floods and droughts occurred successively in Jiujiang city, Poyang Lake Basin, posing a threat to regional water quality safety. The chlorophyll-a (Chl-a) concentration is a key indicator of river eutrophication. Until now, there has been a lack of empirical research exploring the Chl-a trend in inland water in Jiujiang in the context of hydrological extremes. In this study, Sentinel-2 satellite remote sensing data sourced from the Google Earth Engine (GEE) cloud platform, along with hourly water quality data collected from monitoring stations in Jiujiang city, Jiangxi Province, China, are utilized to develop a quantitative inversion model for the Chl-a concentration. The Chl-a concentrations for various inland water types were estimated for each quarter from 2020 to 2022, and the spatiotemporal distribution was analyzed. The main findings are as follows: (1) the quantitative inversion model for the Chl-a concentration was validated via in situ measurements, with a coefficient of determination of 0.563; (2) the spatial estimates of the Chl-a concentration revealed a slight increasing trend, increasing by 0.1193 μg/L from 2020 to 2022, closely aligning with the monitoring-station data; (3) an extreme drought in 2022 led to less water in inland water bodies, and consequently, the Chl-a concentration displayed a significant upward trend, especially in Poyang Lake, where the mean Chl-a concentration increased by approximately 1 μg/L from Q1 to Q2 in 2022. These findings revealed the seasonal changes in the Chl-a concentrations in inland waters in the context of extreme hydrological events, thus providing valuable information for the sustainable management of water quality in Jiujiang city. Full article

Between 2022 and 2023, four systematic fish surveys were carried out in the Poyang Lake basin (PLB), capturing 49,192 fish (7017 kg) and identifying 120 species from 10 orders, 21 families, and 70 genera. Cypriniformes were the most dominant, accounting for 79 species. The spring and autumn surveys collected 25,734 and 23,458 individuals, respectively, with corresponding biomasses of 3978 kg and 3038 kg. Dominant species (IRI > 1000) in the study area included Hemiculter leucisculus, Megalobrama skolkovii, Hypophthalmichthys molitrix, and Aristichthys nobilis. Additionally, critically endangered species such as Ochetobius elongatus, Myxocyprinus asiaticus, and Acipenser sinensis as well as exotic species like Cirrhinus mrigala and euryhaline species like Cynoglossus gracilis and Hyporhamphus intermedius were observed. Hierarchical clustering grouped the survey stations into three distinct areas (PYS, XBMS, and XBUS), with the ANOSIM analysis showing highly significant differences (R = 0.893, p < 0.01). Redundancy analysis (RDA) indicated that in spring, total phosphorus (TP) and temperature were the main factors influencing variability (80.50%), while in autumn, temperature, oil, and pH were the key factors (75.20%). This study emphasizes the predictable changes in fish community composition caused by environmental gradients and highlights the need for ongoing monitoring to effectively manage and protect the ecosystem, particularly in the post-fishing ban period. Full article

Fertilizer carbon emissions contribute the largest proportion to agricultural carbon emissions in China, while the extension of low-carbon fertilization technologies (LCFTs) is an effective measure to address this issue. Research suggests that the relational networks surrounding farmers significantly influence their carbon reduction behavior. This study conducted a field survey of 239 large-scale grain producers in August 2022 on China’s Poyang Lake Basin, which is the nation’s largest freshwater lake and a vital agricultural production area. Using cross-sectional data, probit and ordered probit models were employed to analyze the impacts of multidimensional relational networks (market, government, and social networks) on the adoption of LCFTs by large-scale grain producers. Additionally, a mediating-effect model was used to examine the pathways through which relational networks influence LCFT adoption. The findings indicated that relational networks not only increased the likelihood of large-scale grain producers adopting LCFTs but also enhanced the intensity of adoption. However, the effects of different relational networks on low-carbon behavior varied. The market network exerted the most prominent influence on LCFT adoption, followed by the social and government networks. A mediation analysis identified information sharing, demonstration effects, and resource guarantees as the mediating pathways between multidimensional relational networks and LCFT adoption by large-scale grain producers. Furthermore, a heterogeneity analysis revealed that the effects of multidimensional relational networks on LCFT adoption differed across generations and carbon intensity levels. The impact was greater among older grain producers than the younger generation, and those in the high-carbon-intensity group exhibited a stronger incentive compared to the medium- and low-carbon-intensity groups. Full article

The ecological urban agglomeration around Poyang Lake represents a critical development area in the Yangtze River basin. The spatiotemporal characteristics of the net primary productivity (NPP) of vegetation are explored from the perspective of the city’s functional position, providing important insights for the city to achieve the dual-carbon target and green development. The study evaluates the spatiotemporal variations in NPP from 2003 to 2022 in the eco-urban agglomeration around Poyang Lake, using the CASA model. Its variation characteristics were explored in detail from a completely new perspective and scope using indicators such as cycle amplitudes, CV coefficients, Hurst indices, and others. Results indicate seasonal fluctuations and significant variations between urban areas and vegetation, with implications for sustainable development. The annual NPP ranged from 200 to 800 gC/(m²·a), with a change rate of 0.58 gC/(m²·a) and evident seasonal fluctuations in the study area. Notably, urban core cities like Jiujiang and Nanchang exhibit lower NPP and decreasing trends. Scenic areas showed high forest cover and vigorous NPP changes, highlighting the need for targeted urban ecological management to enhance green development. Additionally, the seasonal fluctuations in NPP were notably influenced by specific land use types and local economic conditions. In areas with high vegetation cover, the seasonal characteristics of NPP are pronounced, while they are less evident in regions with strong urban economic conditions. Full article

Runoff research serves as the foundation for watershed management, and the relationship between runoff and landscape pattern represents a crucial basis for decision-making in the context of watershed ecological protection and restoration. However, there is a paucity of research investigating the multi-scale spatial relationship between runoff and landscape patterns. This study employs the Poyang Lake Basin (PLB) as a case study for illustrative purposes. The construction of the soil and water assessment tool (SWAT) model is the initial step in the process of carrying out runoff simulation, which in turn allows for the analysis of the spatial–temporal characteristics of runoff. Subsequently, Pearson’s correlation analysis, global linear regression and geographically weighted regression (GWR) models are employed to examine the impact of landscape composition on runoff. Finally, the spatial relationship between runoff and landscape pattern is investigated at the landscape and class scales. The results of the study demonstrate the following: (1) runoff in the PLB exhibited considerable spatial–temporal heterogeneity from 2011 to 2020. (2) Forest was the most prevalent landscape type within the PLB. Landscape composition’s impact on runoff exhibited non-linear characteristics, with forest, cropland, barren, and grassland influencing runoff in decreasing order. (3) A spatial relationship between runoff and landscape pattern was observed. At the landscape scale, patch diversity significantly influenced runoff, and reducing patch diversity primarily increased runoff. At the class scale, forest and cropland patch areas had the greatest impact on runoff, potentially enhanced by improving patch edge density. (4) Nine sub-basins needing ecological restoration were identified, with restoration pathways developed based on spatial relationships between runoff and landscape patterns. This study elucidates the impact of landscape composition and pattern on runoff, thereby providing a basis for informed decision-making and technical support for the ecological restoration and management of the watershed. Full article