Seasonal Factors Research Articles

Hormonal induction and seasonal variation in male reproductive viability of the Southern Rocky Mountain boreal toad.

The Southern Rocky Mountain boreal toad (Anaxyrus boreas boreas) depends on both the rearing of wild-collected egg masses and a long-standing conservation breeding program (CBP), the latter of which heavily relies on assisted reproductive technologies (ARTs) to support wild populations. Achieving consistent reproductive success in the CBP, however, remains a significant challenge. Natural breeding has not led to a sustained increase in reproductive capacity, prompting the exploration of exogenous hormone treatments as an alternative strategy. This study specifically examined male responses to the administration of human chorionic gonadotropin (hCG), a previously tested hormone, in combination with gonadotropin-releasing hormone agonist (GnRH-A), either individually or together, to evaluate their effects on sperm induction and viability across different seasons. Insights into how hormone treatments and seasonality influence sperm acquisition can guide managers in improving breeding outcomes within ex situ populations by enhancing their understanding of reproductive health, applying hormone treatments at the optimal time of year, and determining the best timing for high quality sperm collection. These advancements can increase reproductive capacity and support long-term genetic management through biobanking. Results indicated that combining hCG and GnRH-A yielded the highest sperm quantity and quality, although further optimization of hormone dosages could improve outcomes. Seasonal factors significantly influenced hormonal efficacy, with variations in sperm concentration and quality observed across months.

Bat Viral Shedding: A Review of Seasonal Patterns and Risk Factors.

Background: Bats act as reservoirs for a variety of zoonotic viruses, sometimes leading to spillover into humans and potential risks of global transmission. Viral shedding from bats is an essential prerequisite to bat-to-human viral transmission and understanding the timing and intensity of viral shedding from bats is critical to mitigate spillover risks. However, there are limited investigations on bats' seasonal viral shedding patterns and their related risk factors. We conducted a comprehensive review of longitudinal studies on bat viruses with spillover potential to synthesize patterns of seasonal viral shedding and explore associated risk factors. Methods: We extracted data from 60 reviewed articles and obtained 1085 longitudinal sampling events. We analyzed viral shedding events using entropy values to quantitatively assess whether they occur in a consistent, pulsed pattern in a given season. Results: We found that clear seasonal shedding patterns were common in bats. Eight out of seventeen species-level analyses presented clear seasonal patterns. Viral shedding pulses often coincide with bats' life cycles, especially in weaning and parturition seasons. Juvenile bats with waning maternal antibodies, pregnant bats undergoing immunity changes, and hibernation periods with decreased immune responses could be potential risk factors influencing seasonal shedding patterns. Conclusion: Based on our findings, we recommend future longitudinal studies on bat viruses that combine direct viral testing and serological testing, prioritize longitudinal research following young bats throughout their developmental stages, and broaden the geographical range of longitudinal studies on bat viruses based on current surveillance reports. Our review identified critical periods with heightened viral shedding for some viruses in bat species, which would help promote efforts to minimize spillovers and prevent outbreaks.

Spatial and temporal distribution characteristics and source apportionment of biogenic elements using APCS-MLR model in the main inlet tributary of Danjiangkou Reservoir.

Danjiangkou Reservoir has been widely concerned as the water source of the world's longest cross basin water transfer project. Biogenic elements are the foundation of material circulation and key factors affecting water quality. However, there is no comprehensive study on the biogenic elements in tributaries of Danjiangkou Reservoir, hindering a detailed understanding of geochemical cycling characteristics of biogenic elements in this region. Guanshan River, one of the main tributaries that directly enter the Danjiangkou Reservoir, was token as the research object. Spatiotemporal distribution characteristics of basic water quality parameters and biogenic elements were studied. Water quality was comprehensively evaluated through water quality index (WQI). Absolute principal component score-multiple linear regression (APCS-MLR) model was adopted to explore the main sources of biogenic elements. Results showed that, in terms of season, the concentrations of total nitrogen (TN), total phosphorus (TP), and dissolved organic carbon (DOC) were significantly higher in wet season than in dry season, while no significant differences were found for dissolved inorganic carbon (DIC) and dissolved silica (DSi). Spatially, the concentrations of dissolved carbon, DIC, TN, and TP in the middle and lower reaches were higher than that in the upstream. DOC concentration peaked in the middle reaches, while DSi showed higher concentrations in the upstream. WQI values indicated that the river water quality was between good and excellent, although the water quality in wet season was slightly worse than that in the dry season. PCA extracted five potential sources, which accounting for 84.12% of the total variance, including rock weathering, mixed source of sewage discharge and agricultural non-point source pollution, dissolved soil CO2, seasonal factor, and agricultural non-point source pollution. These sources contributed 38.96%, 12.33%, 13.54%, 23.95%, and 11.21% to river water quality parameters, respectively. Strengthening the monitoring of biogenic elements, controlling pollutant discharge, and exploring the relationship between biogenic elements and other pollutants are important for the water environment management in this basin.

Impact of Seasonal Atmospheric Factors and Photoperiod on Floral Biology, Plant-Pollinator Interactions, and Plant Reproduction on Turnera ulmifolia L. (Passifloraceae).

Reproductive traits and plant-pollinator interactions largely depend on seasonal weather conditions, which are species-specific. Turnera ulmifolia is an ornamental plant distributed worldwide. There is little information about plant species' reproductive ecology and environmental factors' impact on it. Here, we aimed to examine the effects of seasonal atmospheric factors (e.g., temperature, light, relative humidity, rainfall) and photoperiod on flowering, interactions with flower visitors, and the reproductive success of Turnera ulmifolia in West Bengal, India. Flowering intensity peaked in hot summers and dropped in cold winters, correlating positively with temperature and humidity. Flower opening and closing occurred earlier on hot days, while flower longevity increased in winter, showing a negative correlation with temperature and humidity. Pollen and ovule production were lower in cold weather, positively linked to temperature and humidity. The self-compatible plant was moderately dependent on pollinators and had no pollination deficit in open conditions. Visitor abundance, richness, and diversity varied season-wise, with higher values during spring-summer. Based on pollinating agents, the plant showed multiple pollination modes (e.g., melittophily, myophily, myrmecophily, and psychophily). Effective pollinators were Amegilla zonata, Borbo cinnara, Halictus acrocephalus, Nomia (Curvinomia) strigata, and Tetragonula iridipennis. The fruit set (%) did not differ significantly season-wise, but the seed set remained higher in the hot days of summer than in cold winter. Therefore, it can be concluded that atmospheric factors and photoperiod significantly impact floral traits, plant-pollinator interactions, and plant reproduction.

Analysis of Dynamic Biogas Consumption in Chinese Rural Areas at Village, Township, and County Levels

Understanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based on the hourly loads of different energy types in rural China. The model requires only a small amount of publicly available input data. The model was verified using household energy survey data collected from five Chinese provinces and one year’s data from a village-scale biogas plant. The results showed that the predicted and measured biogas consumption and dynamic load were consistent. The relative error of village biogas consumption was 11.45%, and the dynamic load showed seasonal fluctuations. Seasonal correction factors were incorporated to improve the model’s accuracy and practicality. The accuracy of the RBDM was 19.27% higher than that of a static energy prediction model. Future research should verify the model using additional cases to guide the design of accurate biogas production and distribution systems.

Statistical Analysis and Forecasts of Performance Indicators in the Romanian Healthcare System.

Globally, healthcare systems face challenges in optimizing performance, particularly in the wake of the COVID-19 pandemic. This study focuses on the analysis and forecasting of key performance indicators (KPIs) for the County Emergency Clinical Hospital in Craiova, Romania. The study evaluates indicators such as average length of stay (ALoS), bed occupancy rate (BOR), number of cases (NC), case mix index (CMI), and average cost per hospitalization (ACH), providing insight into their dynamics and future trends. We performed statistical analyses on quarterly data from 2010 to 2023, employing descriptive statistics and stationarity tests (e.g., Dickey-Fuller), using ARIMA models to forecast each KPI, ensuring model validation through tests for autocorrelation, heteroscedasticity, and stationarity. The model selection prioritized Akaike and Schwarz criteria for robustness. The findings reveal that ALoS and BOR demonstrate seasonality and are influenced by colder months, and it is expected that the ALoS will stabilize to around five days by 2025. Moreover, we predict that the BOR will range between 46 and 52%, reflecting these seasonal variations. The NC forecasts indicate a post-pandemic recovery but to below pre-pandemic levels, and we project the CMI to stabilize at around 1.54, suggesting a return to consistent case complexity. The ACH showed significant growth, particularly in the fourth quarter, driven by inflation and seasonal costs, and it is projected to reach more than RON 3000 by 2025. This study highlights the utility of ARIMA models in forecasting healthcare KPIs, enabling proactive resource planning and decision-making. The findings underscore the impact of seasonality and economic factors on hospital operations, offering valuable insights for improving efficiency and adapting to post-pandemic challenges.

Seasonal and Altitudinal Effects on Chemical Composition and Rumen Degradability of Blackberry Leaves in Northwestern Italian Alps.

The blackberry poses a threat as an invasive plant in various regions worldwide, where it aggressively competes with native species and risks delicate ecosystems. Livestock grazing has emerged as a potential strategy to mitigate its spread. This study investigated the effects of seasonal variations and altitude on the chemical composition and in vitro degradability of blackberry leaves. The leaves accessible to goats were collected in the Northwestern Italian Alps across all seasons at three altitudes (low: 450 m, medium: 700 m, high: 1000 m). The findings indicated that blackberry leaves can serve as a cost-effective, high-protein, and high-fiber feed for ruminants in these regions. However, the goats exhibited a limited capacity for fiber degradation. Furthermore, the nutritional value of these leaves was significantly influenced by the season, altitude, and their interaction. Spring leaves had the highest protein content (241.9 g/kg dry matter) and the best digestibility, with lower lignin levels (69 g/kg dry matter). At higher altitudes, lignin content decreased significantly during winter compared to the other seasons, resulting in a significant increase in fiber degradability. These insights offer crucial guidance for optimizing the utilization of the blackberry plant in goat feeding systems and underscores the necessity of considering both seasonal and altitudinal factors in grazing management practices.

Unravelling viral ecology and evolution over 20 years in a freshwater lake.

As freshwater lakes undergo rapid anthropogenic change, long-term studies reveal key microbial dynamics, evolutionary shifts and biogeochemical interactions, yet the vital role of viruses remains overlooked. Here, leveraging a 20 year time series from Lake Mendota, WI, USA, we characterized 1.3 million viral genomes across time, seasonality and environmental factors. Double-stranded DNA phages from the class Caudoviricetes dominated the community. We identified 574 auxiliary metabolic gene families representing over 140,000 auxiliary metabolic genes, including important genes such as psbA (photosynthesis), pmoC (methane oxidation) and katG (hydrogen peroxide decomposition), which were consistently present and active across decades and seasons. Positive associations and niche differentiation between virus-host pairs, including keystone Cyanobacteria, methanotrophs and Nanopelagicales, emerged during seasonal changes. Inorganic carbon and ammonium influenced viral abundances, underscoring viral roles in both 'top-down' and 'bottom-up' interactions. Evolutionary processes favoured fitness genes, reduced genomic heterogeneity and dominant sub-populations. This study transforms understanding of viral ecology and evolution in Earth's microbiomes.

Machine Learning Techniques in Predicting Sales a Case Study of Jumia

The retail industry has experienced significant growth with the advent of e-commerce platforms like Jumia. Predicting sales accurately is critical for inventory management, marketing strategies, and overall operational efficiency. This paper explores the application of machine learning techniques to predict sales on Jumia, leveraging historical sales data and other relevant features to build and evaluate predictive models. Our results demonstrate that advanced machine learning models, particularly the gradient boosting machine, significantly outperform the baseline linear regression model. The gradient boosting machine achieved the lowest Mean Absolute Error (MAE) and Mean Squared Error (MSE), highlighting its superior prediction accuracy. Feature importance analysis revealed that pricing, promotional activities, and seasonal factors are key drivers of sales. These findings indicate that machine learning can effectively capture sales patterns, providing valuable insights for decision-makers.

The Growth and Yield of Shallots and Melons Based on the Interseasonal Windbreaks Cropping System in Anticipation of Climate Change

Melon is one of the fruits favored by Indonesian people, as well as shallots which are often used as a spice for Indonesian cuisine. The demand for these two commodities are increased continuously, but the land for agriculture purpose is limited. Utilization marginal land of coastal sand is a solution to deal with increasingly limited agricultural land. Marginal land of coastal sand has limiting factors such as high wind speed that carrying salt which can cause salinity stress for plants. In addition, it is necessary to add soil amendments such as manure and clay to improve soil structure. The purpose of this study was to distinguish the effect of season types, windbreak types, and types of plants used on the growth and yield of melon and shallot plants on coastal land, and to determine the interaction between season types, windbreak types, and plant types on growth and yields of melon and shallot. This study used a Completely Randomized Block Design (CRBD) of Split-Split Plots with three factors and three replications. The first factor is the type of season (dry and rain). The second factor is the type of windbreaker (without windbreaker, 1.5 m plastic windbreaker, 3 rows corn windbreaker, alley corn windbreaker). The third factor is the type of plant [salinity sensitive plants (melon) and salinity resistant plants (shallots)]. The result of the observation data were observed by means of variance and the Duncan’s Multiple Range Test (DMRT) 5% test was performed. The variables observed in the plant growth component were plant height, number of leaves, leaf area, fresh weight of root, fresh weight of plants, and dry weight of plants. The variables observed in the plant yield components were fresh weight of tubers, fresh weight of fruits, and crop yield. There is an interaction between the seasonal factor and the type of plant on the variables of fresh weight of tubers. There is an interaction between the types of windbreakers and the types of plants on the variables of fresh weight of root, fresh weight of tubers, dry weight of plants. There is an interaction between the type of season and the type of wind break in melon and shallot plants in almost all the observed variables. The 1.5 m plastic windbreaker is more effective in the rainy season on melon and shallot plants. This is because during the dry season the level of salinity is higher (0,74 mS/cm) than the rainy season (0,61 mS/cm). Plastic windbreakers are the highest windbreakers and can reduce wind speed which carries salt particles on salinity-sensitive melon plants and salinity-resistant shallot plants.

Violence Agains Womens : A Transversal Study About 142 Cases in Sidi Bel Abbes, Algeria

A recent study in Sidi Bel Abbès highlights the alarming prevalence of domestic violence, with 142 cases analyzed. The majority of victims endure physical violence, particularly targeting the head, inflicted predominantly by their spouses. Socio-economic vulnerability, including financial dependence, significantly limits women's ability to escape abusive situations. Seasonal and cultural factors, such as the back-to-school period and Ramadan, exacerbate household tensions and increase the likelihood of violence. The assaults, often involving slaps and severe blows, leave both physical injuries and lasting psychological trauma. This violence serves as a mechanism of control and reflects the patriarchal dynamics of society. The findings underscore the urgent need for interventions, including financial and psychological support for victims, alongside awareness campaigns to challenge societal norms. Collaborative efforts between community initiatives and public policies are essential to effectively combat domestic violence and support survivors.

PREVALÊNCIA DE DOENÇAS RESPIRATÓRIAS EM CRIANÇAS: IMPACTOS SAZONAIS E ESTRATÉGIAS DE PREVENÇÃO

Introduction: The prevalence of respiratory diseases among pediatric populations constitutes a substantial public health concern, shaped by inherent biological susceptibilities and environmental determinants. Temporal variations critically influence the occurrence and severity of these diseases. Material and Methods: In this study, recent literature on respiratory diseases in children was analyzed, focusing on seasonal factors, environmental impacts, and prevention strategies such as vaccination, hygiene, and indoor air pollution control. Results and discussion: Respiratory diseases, such as Influenza, Bronchiolitis, and Asthma, demonstrated higher incidence during periods of low temperatures and high humidity. In colder months, increased viral transmission was associated with prolonged stays in enclosed spaces. Conversely, in tropical climates, rainy periods heightened risks due to factors related to humidity and mold exposure. Vaccination, hygiene practices, and improved ventilation in indoor environments showed significant reductions in severe cases. Seasonality has a direct impact on the dynamics of respiratory diseases. It is essential to adopt and promote measures such as awareness campaigns, vaccination, and reductions in indoor air pollution. However, the implementation of these strategies is limited by socioeconomic barriers. Conclusion: Seasonal impacts and the adoption of preventive measures are fundamental to reducing the prevalence of respiratory diseases in children, allowing for an improvement in their quality of life.

STFNet: A Spatiotemporal Fusion Network for Forest Change Detection Using Multi-Source Satellite Images

Forest resources have important ecological and environmental values, and monitoring forest changes using remote sensing images is essential for resource management and ecological protection. However, current forest change detection methods fail to simultaneously integrate fine spatial information with temporal dynamic data, making them susceptible to pseudo changes induced by seasonal factors. In this paper, we propose a forest change detection method called STFNet that integrates multi-source spatiotemporal information. By combining fine spatial details of high-resolution images with dynamic information from time-series images, STFNet enhances the accuracy of forest change detection, alleviating the problem of information fusion difficulties caused by inconsistent granularity in spatiotemporal spectral features from different sources. In STFNet, we propose a cross-attention-based temporal differential feature fusion module (CATFF) to capture spatiotemporal dependencies within time-series images and a multiresolution contextual differential feature fusion module (MCDF) to achieve efficient spatial contexture fusion across multiresolution images. To validate our method, we conduct experiments using Gaofen and Sentinel-2 satellite images. Experimental results demonstrate that STFNet achieves excellent performance with an F1-score of 87.65%, outperforming state-of-the-art methods by at least 2.02%. Our ablation study further confirms the effectiveness of our method in leveraging time-series information to detect forest changes and suppress seasonal interference.

Practical issues of emollient use in winter for patients with atopic dermatitis: expert resolution

In September 2024, a meeting of the Expert Council took place, featuring leading specialists in the fields of allergology, pediatrics, and dermatology. The working group discussed the issue of seasonal exacerbations of atopic dermatitis (AD), as well as the main triggering factors and their role. Experts reviewed the criteria that a modern emollient used for the care of patients with atopic dermatitis should meet; they discussed the role of moisturizers in preventing seasonal exacerbations of atopic dermatitis based on previously conducted studies. Suggestions were made for further informational and organizational activities aimed at expanding the knowledge of patients and doctors about seasonal environmental factors significant for patients with AD, their impact on the condition of the epidermal barrier, their role in the development of seasonal exacerbations, and the possibilities for prevention using modern emollients.

Spatial and Temporal Variations of Surface Air Temperature (1962–2022) across Physiographic Regions in the Koshi Basin, Nepal

This study analyzed the seasonal and annual trends of maximum temperature (Tmax), minimum temperature (Tmin), and mean temperature (Tavg) across the physiographic regions (Himalaya, High Mountain, Middle Mountain, Siwalik, and Terai) of the Koshi Basin using observed data from 23 stations between 1962 and 2022. Missing temperature data were filled using the lapse rate method. The Mann-Kendall (M-K) test was employed to assess the consistency of the temperature dataset. The analysis revealed distinct regional and seasonal temperature trends in the Koshi Basin. The seasonal variations were prominent, especially in the Monsoon and Winter. In the Middle Mountain and High Mountain regions, Tmax increased significantly during the Pre-monsoon season, while Tmin decreased substantially during the Monsoon and Winter. Conversely, the Siwalik and Terai regions experienced more pronounced cooling Himalayas, especially during the Monsoon and Winter. Overall, the Himalayas and High Mountain regions exhibited a cooling trend until the late 1990s, followed by a warming trend. The Middle Mountain region demonstrated similar patterns, with a significant temperature increase after the 1990s. The Siwalik and Terai regions experienced a general cooling trend, although the Siwalik region exhibited some fluctuations. The significant regional variations in temperature trends were the key findings. Similarly, the Himalayas and High Mountains showed a cooling-warming shift in the late 1990s. All these findings underscore the importance of considering both regional and seasonal factors when studying temperature trends in the Koshi Basin.

Queen bee egg-laying dynamics: evaluation of Roger-Delon and Warre hives

The aim of the present study is to evaluate the egg-laying dynamics of queen bees in Roger-Delon and Warre hives located in an apiary at an altitude of less than 1000 m. The study was conducted during the active season of 2023, in an apiary located at an altitude of 860 m in south-western Bulgaria, Pernik district. The bee colonies were balanced before the beginning of the experiment. Two groups of 6 colonies were formed from each Roger-Delon and Warre system. Sealed worker brood was measured until the appearance of constant nectar flow (April – June), and after the appearance of constant nectar flow (September – November). There is currently a need to examine and quantify the egg-laying dynamics of queens in new hive systems. Queen egg-laying activity is affected by a variety of seasonal, nutritional and social factors. According to the results obtained, the average sealed worker brood in Warre hives and Roger-Delon hives are 10484±1031 cm2 and 9564±1057 cm2 (mean±SD) respectively, for the whole period until appearance of constant nectar flow.

PEMASARAN KOMODITAS TERIPANG (Holothuroidea) DI KECAMATAN TANIMBAR SELATAN KABUPATEN MALUKU TENGGARA BARAT

Sea cucumbers are a delicious food that is favored by the Chinese community and holds high economic value in the market. They are also traded in dried or preserved forms. According to the Fisheries and Marine Database study, various economically valuable species of sea cucumbers have been identified in the West Southeast Maluku Regency, such as Holothuria scrabra, Holothuria fuscogilva, Holothuria edulis, Telenota ananas, Telenota anax, and Tripeneustes gratilla. This research aims to examine the marketing channels and the factors influencing the production of sea cucumber commodities. The results of the study indicate that: 1) the marketing channel for sea cucumber commodities in Tanimbar Selatan District operates as a one-level marketing system. The marketing functions performed by various marketing entities are as follows: producers carry out six marketing functions, local collectors perform all eight marketing functions, and processing enterprises undertake seven marketing functions. The marketing map illustrates that the distribution of sea cucumber commodities occurs in Tanimbar Selatan, involving producers and local collectors, and extends to inter-provincial regions involving local traders and processing enterprises. 2) the total marketing cost for sea cucumber commodities is IDR 22.860,546 for a single marketing period. The marketing entity incurring the highest cost is local collectors (73.51%), followed by consumers (25.83%), and producers (0.65%). Moreover, the marketing margin for sea cucumbers is IDR 32.164/kg. From this margin and the costs incurred, the average profit at the producer level is IDR 214.397/kg, while the average profit at the local collector level is IDR 29.241/kg. 3) simultaneously, the factors of the fishing season, education, price, and transportation costs significantly impact the production volume of sea cucumbers. However, when analyzed separately, only the fishing season factor significantly affects the production volume, while the other three factors do not have a substantial impact.

Groundwater quality assessment for drinking and irrigation: A case study in the Cauvery River Basin (CRB) of Tiruchirappalli District, Tamil Nadu, India

ABSTRACT The long-term impacts of human activities on groundwater quality in the Cauvery River Basin are not well understood, particularly the combined effects of urbanization, industrialization, and agriculture. Seasonal factors, such as precipitation and water-table fluctuations, also influence groundwater chemistry, affecting its suitability for drinking and irrigation. This research aims to assess the hydrochemical characteristics of groundwater and evaluate its long-term suitability for these purposes, considering both natural and anthropogenic factors. A total of 56 groundwater samples were collected and analyzed for various physicochemical and biochemical parameters. The results showed that the most prevalent ions are bicarbonate (27.3%), chloride (24.1%), and calcium (16.6%), followed by sulfate, magnesium, sodium, and others. The Piper and Gibbs plots indicated that most groundwater samples belong to the mixed calcium chloride facies, and rock–water interaction is the dominant natural mechanism, with some anthropogenic influences, respectively. The GIS-based drinking water quality index (DWQI) map showed that 66% of the samples were of excellent to good quality for drinking without treatment, while the remaining samples were of moderate quality and nearly unsuitable for drinking, requiring further treatment. However, most of the groundwater samples were suitable for irrigation based on irrigation water quality indices.

The Seasonal Environmental Factors and Phytoplankton Composition of Lake Paldang, the Largest Water Source in South Korea

This study aimed to determine the seasonal variations in the growth and species composition of phytoplankton in Lake Paldang, South Korea’s largest freshwater body, based on environmental factors. Weekly surface water samples were collected and analyzed for three years (2015–2017). A total of 160 species of phytoplankton were distributed across eight divisions. Diatoms were dominant in all seasons except summer and their seasonal equivalents. All seven indices—Shannon, equitability, Simpson, Menhinick, evenness, dominance, and Berger-Parker—presented a clear trend in September, which may be attributed to rainfall in July. Canonical correspondence analysis (CCA) was employed to analyze the relationship between the occurrence and the abundance of phytoplankton species and environmental factors. The results showed that WTE, TP, PO4-P, and rainfall were negatively correlated with Ulnaria acus, Asterionella formosa, and Stephanodiscus hantzschii, whereas Scenedesmus sp. and Merismopedia tenuissima presented positive correlations. Microcystis demonstrated positive correlations with TOC, NH3-N, and HRT, and appeared primarily in the summer and fall of 2015, a dry season. According to the Palmer pollution index, which is calculated based on phytoplankton species, Lake Paldang showed no signs of pollution for the top 99.8% of phytoplankton species, but was evaluated as organically polluted for overall phytoplankton, especially in spring and summer.

Effects of urbanisation and seasons on the relationship between frozen road conditions and road traffic injury: a longitudinal study of national emergency medical service data in South Korea

BackgroundFrozen road conditions could be a factor in road traffic injuries, and seasonality and urbanisation level are potential influencing factors. However, few studies have considered this relationship. Therefore, we examined...