Search Results (312)

This research investigated the temporal dynamics of the anthropogenic impact of fishing pressure on the resilience of the fish species Sarotherodon melanotheron (Rüppel, 1858) in the African Lake Toho, located in southwest Benin. The sampling and analysis of monthly length frequency data were conducted from April 2002 to March 2003 and from April 2022 to March 2023 using the FAO-ICLARM Stock Assessment Tool (FiSAT II software program (version 1.2.2.). The analysis of the S. melanotheron population in Lake Toho revealed a significantly diminishing resilience potential, reflected mainly in general reductions in both the average size and weight of individuals. There was a notable reduction in the size of Sarotherodon melanotheron individuals caught between 2002–2003 and 2022–2023, reflecting the increased pressure on juvenile size classes. Catches are now concentrated mainly on immature fish, revealing increasing exploitation before sexual maturity is reached. An analysis of maturity stages showed a decrease in the percentage of mature individuals in the catches (69.27% in 2002–2003 compared to 55.07% in 2022–2023) and a reduction in the number of mega-spawners (4.53% in 2002–2003 compared to 1.56% in 2022–2023). Growth parameters revealed a decrease in asymptotic length (from 32.2 cm to 23.8 cm) and longevity (from 9.37 years to 7.89 years), while the growth coefficient slightly increased. The mean size at first capture and optimal size significantly declined, indicating increased juvenile exploitation. The total and natural mortalities increased, whereas the fishing mortality remained stable. The exploitation rate remained high, despite a slight decrease from 0.69 to 0.65. Finally, the declines in the yield per recruit, maximum sustainable yield, and biomass confirm the increasing fishing pressure, leading to growth overfishing, recruitment overfishing, reproductive overfishing, and, last but not least, a decreasing resilience potential. These findings highlight the growing overexploitation of S. melanotheron in Lake Toho, compromising stock renewal, fish population resilience, sustainability, and production while jeopardizing local food safety. Full article

This paper describes the spatiotemporal distribution and risk factors of African Swine Fever (ASF) in Uganda for the period of 2010 through 2023. The study utilized a comprehensive dataset from monthly reports (2010–2023) from District Veterinary Officers (DVOs), the Ministry of Agriculture, Animal Industry and Fisheries (MAAIF), and the Food and Agriculture Organization, Uganda. Using GPS coordinates, ASF cases were mapped using QGIS to show ASF distribution and spread in Uganda. Moran’s I analysis was used to delineate clusters of ASF. A total of 1521 ASF cases were recorded. The data show that cases of ASF were disseminated throughout the country, with more cases of ASF documented in the central region and border districts (hotspots for ASF), and few cases were reported in Acholi, Karamoja, and Lango, Ankole, West Nile, and Kigezi sub-regions. The time series analysis revealed incidences of ASF disease occurring year-round; notable peak cases were observed in some districts, and districts with ≥30,000 pigs reported higher cases of ASF. The Moran’s I (≥1) analysis showed that ASF is either aggregated (p = 0.01), especially in central districts bordering Tanzania and lake shores, or sporadic in occurrence. The disease was present in 66% of the districts, with ASF occurring throughout the year. More cases were aggregated in central and border districts and districts with large pig populations (≥30,000). Sporadic cases were reported in districts bordering the DRC, Sudan, Kenya, the lake shores, Karamoja, Acholi, and Lango sub-regions. Full article

The use of pharmaceuticals and personal care products (PPCPs) is steadily growing as the world’s population both increases and ages. Many of these products are released into the environment via municipal wastewater treatment plants and onsite wastewater treatment systems (septic tanks). Consequently, it is essential to ascertain whether these contaminants pose any risk to aquatic organisms who live in the water bodies receiving this waste. Risk quotients (RQ) are a commonly used method to do so. For our pilot study, we undertook such analysis for three trophic levels: algae, crustaceans, and fish from two small lakes, one fed by septic tanks and the other not. This research was conducted in 2021 from the end of the dry season and through most of the wet season in west central Florida, USA. Of the 14 PPCPs measured, six had RQs that posed a risk to all three trophic levels. This risk increased during the wet season. Both lakes, regardless of whether they directly received PPCPs from septic tanks or not, had some level of risk. However, the lake without septic tanks had a smaller risk, both in elevated RQs and the occurrence to the various species. Of the PPCPs measured, DEET, caffeine, and theophylline posed the greatest risk. Full article

Shallow lakes are highly vulnerable to pollution due to their small water volume. Those that receive effluent from the drainfields of onsite wastewater treatment systems (septic tanks) may contain pharmaceuticals and personal care products (PPCPs) that escaped removal during treatment. This study examined the effects of seasonal rainfall variability on the assemblages and concentrations of fourteen PPCPs in two shallow lakes in West–Central Florida, USA: one surrounded by residents equipped with septic tanks and the other located within a nature preserve. Water samples were collected weekly during an 18-week interval from April to August 2021. Liquid chromatography–mass spectrometry analyses revealed the omnipresence of five PPCPs: theophylline, caffeine, cotinine, DEET, and testosterone, although acetaminophen, ibuprofen, and sulfamethoxazole were also common. Of all the PPCPs detected, theophylline, DEET, and acetaminophen concentrations were higher during the wet season in the septic tank-influenced lake, while caffeine, cotinine, and testosterone concentrations decreased. In the lake located in the nature preserve, theophylline, caffeine, and acetaminophen levels increased in the wet season. In contrast, cotinine, DEET, and testosterone levels decreased. Overall, more compounds were detected during the wet season, with highly hydrophobic PPCPs (fluoxetine, atorvastatin, and octocrylene) only present during this period. Full article

Urban historic parks face the dual challenge of achieving the living preservation of historic buildings while enhancing contemporary visitor satisfaction. In the context of accelerating urbanization and growing demand for immersive cultural experiences, it is increasingly important to conserve historical and cultural values while maintaining relevance and emotional engagement. This study adopts a mixed-methods approach to develop a predictive model for visitor satisfaction within the framework of living preservation, using Yingzhou West Lake in Fuyang City, Anhui Province, as a representative case. Qualitative methods were employed to identify key landscape narrative dimensions, while quantitative data from structured questionnaires highlighted critical experiential elements such as environmental restoration perception, flow experience, and cultural identity. Three machine-learning algorithms—random forest, Support Vector Machine (SVM), and XGBoost—were applied, with the most accurate model used to analyze the relative contribution of each component to visitor satisfaction. The findings revealed that immersive experiential elements play a central role in shaping satisfaction, while physical and cultural elements, particularly historic buildings and their contextual integration, provide essential structural and emotional support. This study offers data-driven insights for the adaptive reuse and interpretive activation of historic architecture, proposing practical strategies to harmonize cultural continuity with visitor engagement in the sustainable management of urban historic parks. Full article

Pangong Tso, a typical plateau lake exhibiting an east-to-west gradient from freshwater to saline conditions, was used to simulate the migration and transformation of nitrogen compounds under different salinity conditions. This study systematically investigates the effects of salinity on nitrogen cycling and transformation in Pangong Tso sediments from 12 sites through controlled laboratory experiments and field monitoring across 120 sites. The data analysis method includes correlation analysis, ANOVA, structural equation modeling (SEM), and mixed-effects modeling (MEM). The results demonstrate that salinity significantly affects nitrogen cycling in plateau lakes. Salinity inhibits nitrification, resulting in an accumulation of ammonium nitrogen (NH₄⁺-N), while simultaneously suppressing gaseous nitrogen emissions through the inhibition of denitrification. Salinity has a significant negative effect on nitrite nitrogen (NO₂⁻-N), which is attributable to enhanced redox-driven transformations under hypersaline conditions. A salinity threshold of approximately 9‰ was identified, above which nitrite oxidation was strongly inhibited, consistent with the known high salinity sensitivity of nitrite-oxidizing bacteria (NOB). Higher salinity levels correlated positively with increased NH₄⁺-N and total nitrogen (TN) concentrations in overlying water (p < 0.01), and were further supported by observed increases in dissolved organic nitrogen (DON) and dissolved total nitrogen (DTN) along with rising salinity, and vice versa. Full article

Limited surface energy and mass flux data hinder the understanding of glacier retreat mechanisms on the Qinghai–Tibet Plateau (QTP). Glaciers in the west Nyainqentanglha Range (WNR) supply meltwater to the densely populated Lhasa River basin (LRB) and Nam Co, the QTP’s second-largest endorheic lake. In this study, we used a glacier mass balance model based on the degree-day method (GMB-DDM) to understand the response of glacier changes to climate warming. The spatiotemporal variation in degree-day factors for ice (DDF_ice; plural form: DDFs_ice) was assessed to characterize the sensitivity of glacier melt to warming over 44 years in the WNR. Our results demonstrate that the GMB_DDM effectively captured the accelerated mass loss and regional heterogeneity of WNR glaciers from 2000 to 2020, particularly the intensified negative balance after 2014. Moreover, glacier ablation was more sensitive to warming in the WNR during 2000–2020 than 1976–2000, with DDF_ice increases of 21% ± 8% in the LRB and 31% ± 10% in the Nam Co basin (NCB). Increased precipitation during the ablation season and reduced glacier surface albedo can explain the increased sensitivity to warming during 2000–2020. These findings could support sustainable water resource management in the LRB, NCB, and the surrounding areas of the QTP. Full article

The distribution of moisture content in stacked tea leaves during processing significantly influences tea quality. Visualizing this moisture distribution is crucial for optimizing processing parameters. In this study, we utilized hyperspectral imaging (HSI) technology combined with machine learning algorithms to evaluate the moisture content and its distribution in the stacked tea leaves in West Lake Longjing and Tencha green tea products during the processing flow line. A spectral quantitative determination model was developed, achieving high accuracy (${\mathrm{R}}_{\mathrm{p}}^2$ > 0.940) The model demonstrated strong generalization ability, allowing it to predict moisture content in both types of tea. Through hyperspectral imaging, we visualized moisture distribution in seven key processing steps and observed that moisture content was non-uniform, with the leaf tips and petioles having higher moisture levels than the leaf surface. This study offers a novel solution for real-time moisture monitoring of stacked tea leaves in tea production, ensuring consistent product quality. Future research could focus on refining model transfer techniques and exploring additional tea varieties to further enhance the generalization of the approach. Full article

The terrestrial spatial patterns were affected by human activities, primarily on regional land use (LU) changes, with habitat quality (HQ) serving as a prerequisite for achieving regional sustainable development. Assessing and predicting the spatiotemporal evolution characteristics of regional LU changes and HQ is critical for formulating regional LU strategies and enhancing ecosystem service functions. Using the Poyang Lake Region as our research object, this research employs LU data and utilizes the ‘InVEST’ model and hot-spot analysis to quantitatively evaluate the spatiotemporal changes in HQ during 2000–2020. The PLUS model is then applied to predict LU and HQ trends from 2020 to 2050. The findings are as follows: (1). From 2000 to 2020, the areas of forestland, shrubland, sparse woodland, paddy fields, and dryland in the Poyang Lake Region showed a decreasing trend, with reductions mainly occurring in urban expansion zones such as Nanchang City and largely converted into urban construction land. (2). Since 2000, HQ in the Poyang Lake Region has shown a slight retrogressive evolution, with significant spatial heterogeneity. HQ spatially exhibits a pattern of improvement radiating outward from major cities. (3). Predictions for 2030 to 2050 indicate that HQ in the Poyang Lake Region will continue to decline, with the most significant downward trends occurring in urban built-up areas and their peripheries. The spatiotemporal characteristics reveal an expansion ring around Poyang Lake and an east–west urban expansion corridor linking Pingxiang, Yichun, Xinyu, Nanchang, Fuzhou, Yingtan, and Shangrao. This study provided a research basis for LU direction and urban planning policies in the Poyang Lake Region and its surrounding areas, while also contributing to the construction of agrarian security patterns and the enhancement of ecosystem service levels in the region. Full article

Recently published marine geophysical and seafloor drilling data permit a substantive reappraisal of the rifting and spreading that formed the South China Sea (SCS). The SCS rifted margins are different from those of the Atlantic type, having higher strain rates, younger orogenic crust, and distributed syn-rift magmatism. Rifting ~66–11 Ma and spreading 30–14 Ma split a Cretaceous Andean arc and forearc, producing >700 km of seafloor spreading in the east and a ~2000-km-wide rifted margin in the west. Luconia Shoals–Dangerous Grounds–Reed Bank–north Palawan–SW Mindoro were separated from China when the SCS opened. Brittle faulting of the upper crust was decoupled from ductile flow and magmatic intrusion of the lower crust, producing wide rifting with thin spots held together by less extended surrounds. Sediments accumulated in inter-montane lakes. Transform faults formed at/after breakup to link offset spreading segments. Spreading in the eastern subbasin from C11n to C5AD was at rates averaging 62 mm/yr, 30–24 Ma, decreasing to 38.5 mm/yr younger than 23 Ma. Spreading reorganization was common as margin segments broke up to the SW and spreading directions changed from ~N-S before 23 Ma to NW-SE after 17 Ma. 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

Under the dual pressures of global warming and accelerated urbanization, urban green spaces (UGS) serve as crucial yet paradoxical elements, alleviating urban heat island (UHI) effects while emitting biogenic volatile organic compounds (BVOCs) that exacerbate air pollution; however, their spatial trade-offs remain underexplored. This study bridges this gap by developing an Urban Heat Mitigation Index (HMI) and a BVOC flux accounting framework integrating remote sensing and field observations. The results showed that (1) the cooling effect exhibits significant spatial heterogeneity, with continuous green networks around West Lake and along the Qiantang River forming efficient cooling corridors (HMI > 0.75), while fragmented green spaces in northeastern areas show weaker cooling effects (HMI < 0.35); (2) BVOC emission intensity displays a “high suburbs-low centers” pattern, with suburban areas emitting 1.9–2.3 times more BVOCs than urban centers, while BVOC-induced PM_2.5 (0.02–0.05 μg m⁻³) and O₃ (12–33 μg m⁻³) concentrations in city centers still pose significant health risks; (3) spatial analysis reveals a weak positive correlation between HMI and BVOC emissions (Moran’s I = 0.096, p < 0.05), with four distinct coupling patterns identified: “high cooling-low emissions” (17.5% of area), “low cooling-high emissions” (1.1%), “high cooling-high emissions” (18.7%), and “low cooling-low emissions” (3.9%). This study provides quantitative evidence for optimizing UGS layouts to balance ecological benefits and environmental risks, emphasizing the importance of vegetation screening and spatial allocation in sustainable urban planning. Full article

The transition towards carbon neutrality and sustainable urban development necessitates innovative strategies for managing multi-energy supply stations (MESS), which integrate oil, gas, electricity, and hydrogen to support diversified energy demands. Existing revenue prediction models for MESS lack interpretability and multi-energy adaptability, hindering actionable insights for sustainable operations. This study proposes a novel Shapley additive explanations (SHAP)-driven machine learning framework for multi-energy supply station revenue forecasting. By leveraging real-world consumption data from Hangzhou West Lake Tanghe Station, we constructed a dataset with nine critical parameters, including energy types, transaction frequency, and temporal features. Four machine learning models—decision tree regression, random forest (RF), support vector regression, and multilayer perceptron—were evaluated using MAE, MSE, and R² metrics. The RF model achieved an R² of 0.98, demonstrating superior accuracy in predicting hourly gross transaction values. SHAP analysis further identified consumption volume and transaction frequency as the most influential factors, providing actionable insights for operational optimization. This research not only advances the scientific management of MESS but also contributes to carbon emission reduction by enabling data-driven resource allocation. The proposed framework offers policymakers and industry stakeholders a scalable tool to accelerate urban energy transitions under carbon neutrality goals, bridging the gap between predictive analytics and sustainable infrastructure planning. Full article

Background: Walleye (Sander vitreus), a valuable sportfish and an important ecological apex predator, exhibits genetic structuring across their range and localized structuring as a result of stocking. Methods: Walleye from 17 sampling locations across West Virginia were sequenced using a ddRAD protocol, generating various SNP datasets to assess population structuring and genomic diversity, with specific emphasis on the native Eastern Highlands strain. Different minor allele frequency filter thresholds were tested to assess impacts on genetic diversity and differentiation metrics. Results: High genetic differentiation was observed between the Eastern Highlands and Great Lakes strains, with further sub-structuring within the Eastern Highlands strain between the Ohio River populations and the other populations. Increasing MAF thresholds generally reduced the distinctiveness of clusters, but the overall inference of the number of clusters was minimally impacted. Genetic diversity metrics indicated some variability among Eastern Highlands walleye populations, with isolated populations, including the New River and Summersville Lake, showing higher inbreeding coefficients. MAF filters generally increased diversity metrics, but the trend of diversity metrics among populations remained relatively consistent. Several SNPs were found to be potentially undergoing selection, with the minor allele frequencies of these SNPs being found to be highest in Summersville Lake, highlighting potential adaptive divergence between the riverine populations and a large lentic system. Conclusions: The use of any MAF filter generated the same trends of population structuring and genomic diversity inferences regardless of the MAF threshold used. Further management of Eastern Highlands walleye in West Virginia needs to emphasize protecting the genetic integrity of the Kanawha River population and ongoing genomic screening of broodstock to conserve native genetic diversity. Full article

Harmful algal blooms (HABs) have emerged as a significant environmental challenge, impacting aquatic ecosystems, drinking water supply systems, and human health due to the combined effects of human activities and climate change. This study investigates the performance of deep learning models, particularly the Transformer model, as there are limited studies exploring its effectiveness in HAB prediction. The chlorophyll-a (Chl-a) concentration, a commonly used indicator of phytoplankton biomass and a proxy for HAB occurrences, is used as the target variable. We consider multiple influencing parameters—including physical, chemical, and biological water quality monitoring data from multiple stations located west of Lake Erie—and employ SHapley Additive exPlanations (SHAP) values as an explainable artificial intelligence (XAI) tool to identify key input features affecting HABs. Our findings highlight the superiority of deep learning models, especially the Transformer, in capturing the complex dynamics of water quality parameters and providing actionable insights for ecological management. The SHAP analysis identifies Particulate Organic Carbon, Particulate Organic Nitrogen, and total phosphorus as critical factors influencing HAB predictions. This study contributes to the development of advanced predictive models for HABs, aiding in early detection and proactive management strategies. Full article