Search Results (3,317)

The wild tomato (Solanum sisymbriifolium) is a globally distributed shrubby weed with both negative and positive impacts, including its invasive properties and the potential for pharmaceutical and traditional medicinal uses. Despite its ecological significance, the plant’s reproductive biology and pollination ecology remain poorly understood. This study aimed to investigate the floral biology, pollination ecology, and plant reproduction of the weed species. Some flower traits, such as flowering intensity, flower display size, and pollen and ovule production, peaked during spring, summer, and the monsoon, while flower longevity and stigmatic receptivity were the longest in winter. The plant species was self-compatible (ISI = 0.02), heavily depended on pollinators (IDP = 0.72), and experienced minimal pollination limitation (D = 0.10) under open-pollination conditions. Flower visitors’ traits (e.g., abundance, diversity, and richness) were higher in the spring, summer, and the monsoon, and these were lower in winter. The vital pollination service was provided by Amegilla zonata, Ceratina binghami, Lasioglossum cavernifrons, Nomia (Curvinomia) striata, Tetragonula pagdeni, Xylocopa aestuans, Xylocopa amethystina, Xylocopa fenestrata, and Xylocopa latipes. Reproductive success, as indicated by fruit and seed set, varied seasonally, being higher during the spring–monsoon period and lower in winter. These findings support effective management of this weed species and help conserve the associated bee populations. 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

The spatiotemporal changes and driving mechanisms of rain-on-snow (ROS) events and their intensities are crucial for responding to disasters triggered by such events. However, there is currently a lack of detailed assessment of the seasonal variations and driving mechanisms of ROS events and their intensities in China. Therefore, this study utilized daily meteorological data and daily snow depth data from 513 stations in China during 1978–2020 to investigate spatiotemporal variations of ROS events and their intensities. Also, based on the detrend and partial correlation analysis model, the driving factors of ROS events and their intensity were explored. The results showed that ROS events primarily occurred in northern Xinjiang, the Qinghai–Tibet Plateau, Northeast China, and central and eastern China. ROS events frequently occurred in the middle and lower Yangtze River Plain in winter but were easily overlooked. The number and intensity of ROS events increased significantly (p < 0.05) in the Changbai Mountains in spring and the Altay Mountains and the southeast part of the Qinghai–Tibet Plateau in winter, leading to heightened ROS flood risks. However, the number and intensity of ROS events decreased significantly (p < 0.05) in the middle and lower Yangtze River Plain in winter. The driving mechanisms of the changes for ROS events and their intensities were different. Changes in the number of ROS events and their intensities in snow-rich regions were driven by rainfall days and quantity of rainfall, respectively. In regions with more rainfall, these changes were driven by snow cover days and snow water equivalent, respectively. Air temperature had no direct impact on ROS events and their intensities. These findings provide reliable evidence for responding to disasters and changes triggered by ROS events. Full article

Particulate matter (PM), mainly PM_0.5, represents a significant concern for human health, particularly relating to lung homeostasis, and more research is required to ascertain its tissue tropism and the molecular pathways involved. In this study, we first focus on classical in vitro toxicological endpoints (cytotoxicity and cell growth) in human bronchial and alveolar epithelial cell lines mimicking the two pulmonary target tissues. Air samples were collected in five Italian cities (Brescia, Lecce, Perugia, Pisa, Turin) during winter and spring. To better decipher the PM_0.5 effects on pulmonary cells, a further winter sampling was performed in Brescia, and studies were extended to assess tumour promotion, oxidative stress, and the activity of Matrix metalloproteases (MMP). The results confirmed that the effect of air pollution is linked to the seasons (winter is usually more cytotoxic than spring) and is correlated with the peculiar characteristics of the cities studied (meteoclimatic conditions, economic/anthropogenic activities). Alveolar cells were often less sensitive than bronchial cells. All PM samples from Brescia inhibited intercellular communication mediated by gap junctions (GJIC), increased the total content in glutathione, and decreased the reduced form of glutathione, whereas the Reactive Oxygen Species (ROS) content was almost constant. Long-term treatments at higher doses of PM decreased MMP2 and MMP9 activity. Taken together, the results confirmed that PM is cytotoxic and can potentially act as tumour promoters, but the mechanisms involved in oxidative stress and lung homeostasis are dose- and time-dependent and quite complex. Full article

Poyang Lake, a large floodplain lake, plays a crucial role in the ecological safety and quality of life in surrounding areas. Over the past decade (2013–2022), amid economic development and environmental changes, the water environment of Poyang Lake has encountered complex challenges. This study evaluated the water quality of Poyang Lake in a recent 10-year span by the water quality index (WQI), trophic level index (TLI) and a newly constructed comprehensive evaluation index, and it analyzed the trend of water quality change under extreme events. Meanwhile, the main factors affecting the water quality of Poyang Lake were analyzed by partial least squares (PLS), a multivariate statistical method that accounts for multicollinearity. The results indicate that: (1) The water quality of Poyang Lake in summer and autumn is slightly worse than that in spring and winter. Each water quality index reflects the distinct states of the water environment in Poyang Lake. (2) Each water quality evaluation index responds differently to influencing factors. (3) Extreme flood and drought events have markedly different impacts on the water environment of Poyang Lake, exhibiting significant spatial heterogeneity. Domestic sewage discharge and total water resources have a relatively great impact on the water environment of Poyang Lake. The results of this study provide important insights for water quality management and policy formulation in Poyang Lake, supporting sustainable regional development. Full article

Pear (Pyrus pyrifolia) is an important deciduous fruit tree that requires a specific period of low-temperature accumulation to trigger spring flowering. The warmer winter caused by global warming has led to insufficient winter chilling, disrupting floral initiation and significantly reducing pear yields in Southern China. In this study, we integrated targeted phytohormone metabolomics, full-length transcriptomics, and proteomics to explore the regulatory mechanisms of dormancy in ‘Mixue’, a pear cultivar with an extremely low chilling requirement. Comparative analyses across the multi-omics datasets revealed 30 differentially abundant phytohormone metabolites (DPMs), 2597 differentially expressed proteins (DEPs), and 7722 differentially expressed genes (DEGs). Integrated proteomic and transcriptomic expression clustering analysis identified five members of the dormancy-associated MADS-box (DAM) gene family among dormancy-specific differentially expressed proteins (DEPs) and differentially expressed genes (DEGs). Phytohormone correlation analysis and cis-regulatory element analysis suggest that DAM genes may mediate dormancy progression by responding to abscisic acid (ABA), gibberellin (GA), and salicylic acid (SA). A dormancy-associated transcriptional regulatory network centered on DAM genes and phytohormone signaling revealed 35 transcription factors (TFs): 19 TFs appear to directly regulate the expression of DAM genes, 18 TFs are transcriptionally regulated by DAM genes, and two TFs exhibit bidirectional regulatory interactions with DAM. Within this regulatory network, we identified a novel pathway involving REVEILLE 6 (RVE6), DAM, and CONSTANS-LIKE 8 (COL8), which might play a critical role in regulating bud dormancy in the ‘Mixue’ low-chilling pear cultivar. Furthermore, lncRNAs ONT.19912.1 and ONT.20662.7 exhibit potential cis-regulatory interactions with DAM1/2/3. This study expands the DAM-mediated transcriptional regulatory network associated with bud dormancy, providing new insights into its molecular regulatory mechanisms in pear and establishing a theoretical framework for future investigations into bud dormancy control. Full article

The Wyrtki Jet (WJ), a pivotal surface circulation system in the equatorial Indian Ocean, exerts significant regulatory control over regional climate dynamics through its intense eastward transport characteristics, which modulate water mass exchange, thermohaline balance, and cross-basin energy transfer. To address the scarcity of in situ observational data, this study developed a satellite remote sensing-driven multi-parameter coupled model and reconstructed the WJ’s seasonal variations using the XGBoost machine learning algorithm. The results revealed that wind stress components, sea surface temperature, and wind stress curl serve as the primary drivers of its seasonal dynamics. The XGBoost model demonstrated superior performance in reconstructing WJ’s seasonal variations, achieving coefficients of determination (R²) exceeding 0.97 across all seasons and maintaining root mean square errors (RMSE) below 0.2 m/s across all seasons. The reconstructed currents exhibited strong consistency with the Ocean Surface Current Analysis Real-time (OSCAR) dataset, showing errors below 0.05 m/s in spring and autumn and under 0.1 m/s in summer and winter. The proposed multi-feature integrated modeling framework delivers a high spatiotemporal resolution analytical tool for tropical Indian Ocean circulation dynamics research, while simultaneously establishing critical data infrastructure to decode monsoon current coupling mechanisms, advancing early warning systems for extreme climatic events, and optimizing regional marine resource governance. Full article

Accurate short-term passenger forecasts help regional airports align capacity with demand and plan investments effectively. Drawing on quarterly traffic data for 2010–2024 supplied by the Polish Civil Aviation Authority, this study employs Holt–Winters exponential smoothing to predict passenger volumes at Szczecin–Goleniów Airport for 2025. Additive and multiplicative formulations were parameterized with Excel Solver, using the mean absolute percentage error to identify the better-fitting model. The additive version captured both the steady post-pandemic recovery and pronounced seasonal peaks, indicating that passenger throughput is likely to rise modestly year on year, with the highest loads expected in the summer quarter and the lowest in early spring. These findings suggest the airport should anticipate continued growth and consider adjustments to terminal capacity, apron allocation, and staffing schedules to maintain service quality. Because the Holt–Winters method extrapolates historical patterns and does not incorporate external shocks—such as economic downturns, policy changes, or public health crises—its projections are most reliable over the short horizon examined and should be complemented by scenario-based analyses in future work. This study contributes to sustainable airport management by providing a reproducible, data-driven forecasting framework that can optimize resource allocation with minimal environmental impact. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

This study presents the living coccolithophore communities and the morphological variability of Emiliania huxleyi in the South Aegean Sea from three sampling regions during winter-early spring (March 2017, March 2019) and summer (August 2019). Emphasis is given to March 2017 to monitor the variations in coccolithophore assemblages after an exceptionally cold event in December 2016, which resulted in newly produced dense waters that ventilated the Aegean deep basins. The assemblages displayed distinct seasonality with the predominance of E. huxleyi and Syracosphaera molischii during winter-early spring, associated with the water column mixing. By contrast, summer assemblages were featured by holococcolithophores and typical taxa of warm, oligotrophic upper waters. It seems that the phytoplanktonic succession as well as the nutrient supply to the upper euphotic layers were affected by the water column perturbation during the extreme winter of 2016–2017, which led to strong convective mixing and dense water formation. The decreased coccosphere densities during March 2017, accompanied by the notable presence of diatoms, were most probably associated with a prolonged diatom bloom, causing delay in the development of the coccolithophore community and resulting in a nitrogen-limited setting. Emiliania huxleyi morphometry showed the characteristic seasonal calcification trend of the Aegean, with the dominance of smaller coccoliths in the summer and increased coccolith length and width during the cold season. The intense cold conditions and wind-induced mixing during the winter of 2016–2017 possibly increased the absorption of atmospheric CO₂ in surface waters, causing increased acidity and the subsequent presence of etched/undercalcified E. huxleyi coccoliths and other taxa, most probably implying in situ calcite dissolution. Full article

The updated MODIS Collection 6.1 (C6.1) Dark Target (DT) aerosol optical depth (AOD) is extensively utilized in aerosol-climate studies in China. Nevertheless, the long-term accuracy of this data remains under-evaluated, especially for the forested areas. This study was undertaken to substantiate the accuracy of MODIS Terra (MOD04) and Aqua (MYD04) at 3 km resolution AOD retrievals at six forested sites in China from 2004 to 2022. The results revealed that MODIS C6.1 DT MOD04 and MYD04 datasets display good correlation (R = 0.75), low RMSE (0.20, 0.18), but significant underestimation, with only 53.57% (Terra) and 52.20% (Aqua) of retrievals within expected error (EE). Both the Terra and Aqua struggled in complex terrain (Gongga Mt.) and high aerosol loads (AOD > 1). In northern sites, MOD04 outperformed MYD04 with better correlation and a relatively high number of retrievals percentage within EE. In contrast, MYD04 outperformed MOD04 in central region with better R (0.69 vs. 0.62), and high percentage within EE (68.70% vs. 63.62%). Since both products perform well in the central region, MODIS C6.1 DT products are recommended for this region. In southern sites, MOD04 product performs relatively better than MYD04 with a marginally higher percentage within EE. However, MYD04 shows better correlation, although a higher number of retrievals fall below EE compared to MOD04. Seasonal biases, driven by snow and dust, were pronounced at northern sites during winter and spring. Southern sites faced issues during biomass burning seasons and complex terrain further degraded accuracy. MOD04 demonstrated a marginally superior performance compared to MYD04, yet both failed to achieve the global validation benchmark (66% within). The proposed results highlight critical limitations of current aerosol retrieval algorithms in forest and mountainous landscapes, necessitating methodological refinements to improve satellite-based derived AOD accuracy in ecological sensitive areas. Full article

This study aims to analyse the effect of selected variation factors on the ejaculate characteristics of boars and to characterise changes in ejaculate characteristics in Landrace, Large White, Duroc, and Pietrain boars during their use for artificial insemination. The original value of this work lies in the estimation of the percentage share of individual components of variability in shaping the traits of boar ejaculate. A total of 943 ejaculates collected from 77 boars used for artificial insemination were analysed. This study began when the boars were at 8–9 months old. Ejaculates were collected in nine consecutive months from the start of the boars’ use. Immediately after collection, they were analysed for ejaculate volume, sperm concentration, percentage of sperm with progressive motility, total number of spermatozoa, and number of insemination doses per ejaculate. The results were analysed according to three criteria: breed of boar (Landrace, Large White, Duroc, and Pietrain), age of boar (up to 10 months, 11–13 months, 14–17 months, and more than 17 months), and season (spring, summer, autumn, and winter). The analysis of the variation in ejaculate characteristics took into account the share of each factor (boar breed, boar age, and season) in the variation, as well as the interactions between factors. The effects of the three factors and interactions between them were calculated using an ANOVA (analysis of variance). The variation was shown to depend mainly on the breed and age. These two factors and the interaction between them determine about 80% of the variation in ejaculate characteristics. The season also has an effect, but its share in the influence of variation on ejaculate characteristics is relatively small. Ejaculates from Landrace boars are the most favourable for insemination, with a large volume, a relatively high sperm concentration, and the highest number of sperm. The highest number of insemination doses can be prepared from Landrace ejaculates—on average, 2.7–6.7 more doses than from the other breeds. Duroc boar ejaculates are most distinctive, with a very low volume but a very high sperm concentration and the highest sperm motility. The ejaculates of Pietrain boars showed the opposite pattern, with the largest volume but the lowest sperm concentration. The sexual development of young boars, expressed as an increase in ejaculation performance, progresses during their first year of insemination use. Full article

Rivers play a crucial role in the hydrological cycle and serve as essential freshwater resources for both human populations and ecosystems. Climate change significantly alters precipitation patterns and river discharge variability. However, the impact of precipitation patterns (rainfall and snowfall) and air temperature on river discharge in coastal zones remains inadequately understood. This study focused on Toyama Prefecture, located along the Sea of Japan, as a representative coastal area. We analyzed over 30 years of datasets, including air temperature, precipitation, snowfall, and river discharge, to assess the effects of climate change on river discharge. Trends in hydroclimatic datasets were assessed using the rescaled adjusted partial sums (RAPS) method and the Mann–Kendall (MK) non-parametric test. Furthermore, a correlation analysis and the Structural Equation Model (SEM) were applied to construct a relationship between precipitation, temperature, and river discharge. Our findings indicated a significant increase in air temperature at a rate of 0.2 °C per decade, with notable warming observed in late winter (January and February) and early spring (March). The average river fluxes for the Jinzu, Oyabe, Kurobe, Shou, and Joganji rivers were 182.52 m³/s, 60.37 m³/s, 41.40 m³/s, 38.33 m³/s, and 18.72 m³/s, respectively. The tipping point for snowfall decline occurred in 1992, marked by an obvious decrease in snowfall depth. The SEM showed that, although rainfall dominated the changes in river discharge (loading = 0.94), the transition from solid (snow) to liquid (rain) precipitation may alter the river discharge regime. The percentage of flood occurrence increased from 19% (1940–1992) to 41% (1993–2020). These changes highlight the urgent need to raise awareness about the impacts of climate change on river floods and freshwater resources in global coastal regions. Full article

The observations of atmospheric, oceanic, and sea ice data from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition were used to analyze the influence of snow redistribution and melt-pond processes on the evolution of sea ice thickness (SIT) in 2019 and 2020. To mitigate the effect of missing atmospheric observations from the time of the expedition, we used ERA5 atmospheric reanalysis along the MOSAiC drift trajectory to force the single-column sea ice model Icepack. SIT simulations from six combinations of two melt-pond schemes and three snow-redistribution configurations of Icepack were compared with observations and analyzed to investigate the sources of model–observation discrepancies. The three snow-redistribution configurations are the bulk scheme, the snwITDrdg scheme, and one simulation conducted without snow redistribution. The bulk scheme describes snow loss from level ice to leads and open water, and snwITDrdg describes wind-driven snow redistribution and compaction. The two melt-pond schemes are the TOPO scheme and the LVL scheme, which differ in the distribution of melt water. The results show that Icepack without snow redistribution simulates excessive snow–ice formation, resulting in an SIT thicker than that observed in spring. Applying snow-redistribution schemes in Icepack reduces snow–ice formation while enhancing the congelation rate. The bulk snow-redistribution scheme improves the SIT simulation for winter and spring, while the bias is large in simulations using the snwITDrdg scheme. During the summer, Icepack underestimates the sea ice surface albedo, resulting in an underestimation of SIT at the end of simulation. The simulations using the TOPO scheme are characterized by a more realistic melt-pond evolution compared to those using the LVL scheme, resulting in a smaller bias in SIT simulation. Full article

Concerning rising salinity and declining freshwater supply in the U.S. Southern Great Plains, alternative crop production choices using marginal saline irrigation water are irresistible. The study investigated plant traits related to salt tolerance in greenhouse canola (Brassica napus L.) in 2022 and 2023. Spring and winter canola, including ten genotypes each, were evaluated at six salinity levels (0; control, 2, 4, 6, 8, and 8 dS m⁻¹ EC). Plant height, stem mass, leaf area, and specific leaf area (SLA) showed a negative linear response, while quadratic relationships were observed in biomass and leaf mass with increased salinity levels. Substantial negative salinity impacts on plant traits occurred at ≥6 dS m⁻¹ EC (p ≤ 0.01) except for SLA. Overall, winter canola genotypes: Athena, Ericka, CP320WRR, CP115W, and CP225WRR, and spring genotypes: Empire, Monarch, Profit, and Westar, were relatively more salt-tolerant than others. Spring canola showed greater salinity tolerance than winter canola. Salinity stress resulted in differential responses of greater leaf mass in winter canola but more efficient leaf area production in spring canola. SLA and stem mass were highly correlated with most parameters. Findings indicate SLA and stem mass are potential salt tolerance traits in canola and warrant further investigations and validation. Full article