Search Results (982)

The sea ice extent in the Weddell Sea exhibited a positive trend from the start of satellite observations in 1978 until 2016 but has shown a decreasing trend since then. This study analyzes seasonal and interannual variations in sea ice thickness using ICESat-2 laser altimetry data over the Weddell Sea from 2019 to 2022. Sea ice thickness was calculated from ICESat-2’s ATL10 freeboard product using the Improved Buoyancy Equation. Seasonal variability in ice thickness, characterized by an increase from February to September, is more pronounced in the eastern Weddell sector, while interannual variability is more evident in the western Weddell sector. The results were compared with field data obtained between 2019 and 2022, showing a general agreement in ice thickness distributions around predominantly level ice. A decreasing trend in sea ice thickness was observed when compared to measurements from 2003 to 2017. Notably, the spring of 2021 and summer of 2022 saw significant decreases in Sea Ice Extent (SIE). Although the overall mean sea ice thickness remained unchanged, the northwestern Weddell region experienced a noticeable decrease in ice thickness. Full article

Cold ecosystems are experiencing a warming rate that is twice as fast as the global average and are particularly vulnerable to the consequences of climate change. In mountain ecosystems, it is particularly important to monitor vegetation to understand ecosystem dynamics, biodiversity conservation, and the resilience of these fragile ecosystems to global change. Hence, we used satellite data acquired by Sentinel-2 to perform a comparative assessment of the Normalized Difference Vegetation Index (NDVI) and the Plant Phenology Index (PPI) in mountainous regions (canton of Valais-Switzerland in the European Alps) for monitoring vegetation dynamics of four types: deciduous trees, coniferous trees, grasslands, and shrublands. Results indicate that the NDVI is particularly noisy in the seasonal cycle at the beginning/end of the snow season and for coniferous trees, which is consistent with its known snow sensitivity issue and difficulties in retrieving signal variation in dense and evergreen vegetation. The PPI seems to deal with these problems but tends to overestimate peak values, which could be attributed to its logarithmic formula and derived high sensitivity to variations in near-infrared (NIR) and red reflectance during the peak growing season. Concerning seasonal parameters retrieval, we find close concordance in the results for the start of season (SOS) and end of season (EOS) between indices, except for coniferous trees. Peak of season (POS) results exhibit important differences between the indices. Our findings suggest that PPI is a robust remote sensed index for vegetation monitoring in seasonal snow-covered and complex mountain environments. Full article

Monitoring sugarcane phenology is essential since the globalized market requires reliable information on the quantity of raw materials for the industrial production of sugar and alcohol. In this context, the general objective of this study was to evaluate the phenological seasonality of the sugarcane varieties SP 79-1011 and VAP 90-212 observed from the NDVI time series over 19 years (2001–2020) from global databases. In addition, this research had the following specific objectives: (i) to estimate phenological parameters (Start of Season (SOS), End of Season (EOS), Length of Season (LOS), and Peak of Season (POS)) using TIMESAT software in version 3.3 applied to the NDVI time series over 19 years; (ii) to characterize the land use and land cover obtained from the MapBiomas project; (iii) to analyze rainfall variability; and (iv) to validate the sugarcane harvest date (SP 79-1011). This study was carried out in sugarcane growing areas in Juazeiro, Bahia, Brazil. The results showed that the NDVI time series did not follow the rainfall in the region. The sugarcane areas advanced over the savanna formation (Caatinga), reducing them to remnants along the irrigation channels. The comparison of the observed harvest dates of the SP 79-1011 variety to the values estimated with the TIMESAT software showed an excellent fit of 0.99. The mean absolute error in estimating the sugarcane harvest date was approximately ten days, with a performance index of 0.99 and a correlation coefficient of 0.99, significant at a 5% confidence level. The TIMESAT software was able to estimate the phenological parameters of sugarcane using MODIS sensor images processed on the Google Earth Engine platform during the evaluated period (2001 to 2020). Full article

In the context of climate change, the current rise in temperature, changes in precipitation, and extreme weather events are exceptional and impact biodiversity. Using the Mann–Kendall trend test, change-point analysis, and linear mixed models, we investigated the long-term trends (1978–2022) of water temperature and flow in the Po River, Italy’s largest river, and examined changes in the fish community over the same period. Our findings indicate that the daily water temperature of the Po River increased by ~4 °C from 1978 to 2022, with a significant rise starting in 2005. The river’s daily discharge showed higher variability and decreased from 2003 onwards. The number of days per year with water temperatures above the summer average increased steadily by 1 day per year, resulting in over 40 additional days with above-average temperatures in the last four decades. The number of summer days above the seasonal average water temperature was the most influential factor affecting fish diversity. Total fish species richness and native species richness significantly decreased between 1978 and 2022 with the increasing number of days above the summer average water temperature, while non-native species increased. Our results demonstrate that the Po River is experiencing significant impacts from global warming, affecting freshwater communities. Full article

The air quality (AQ) of a given location depends mostly on two factors: emissions and meteorological conditions. For most places on Earth, the meteorology of an area changes seasonally. For central Europe, winters are associated with poor dispersion conditions, which, in combination with high emissions from local heating systems, lead to significantly higher concentrations than during summer. In this study, the seasonality of AQ is analysed using hourly measurements from 44 monitoring stations in Slovakia for the years 2007–2023 for NO₂, PM₁₀ and PM_2.5. Two factors are used to evaluate the seasonality—the difference and ratio of the winter and summer mean concentrations. It was found that the seasonal difference has been gradually decreasing for all pollutants since 2017. In the case of PM_2.5, the seasonal ratio drops from a value of around 2.5 in 2018 to approximately 1.7 in 2023. While in the past, the seasonal ratio was the highest for PM_2.5, in the last three years it is the highest for NO₂ with values larger than 2. Our results imply that summer sources of PM emissions start to play a more important role for the AQ than in the past. The observed seasonality was compared with two full-year chemical-transport model simulations. Full article

This study examined the relationship between body composition and on-field, in-game physical performance in female collegiate soccer players. Body composition, including total mass, fat mass, and lean tissue mass for the lower extremities and total body, was measured in 10 starting players using dual energy x-ray absorptiometry (DXA). On-field, in-game physical performance was tracked via a global positioning system (GPS) over 14 regular-season games, measuring total distance and distance covered in six speed zones. Players covered 4544.7 ± 495.2 m in the first half of the game and significantly less distance in the second half (3356.5 ± 1211.7 m, p = 0.004). A repeated measures ANOVA revealed decreased distances in jogging, low-, and moderate-intensity running during the second half compared to the first half of the game (p < 0.001). Lower total-body fat mass, total-body fat percentage, and lower-extremities fat mass were correlated with greater distances at moderate- and high-intensity running during the second half and entire game (r values from −0.644 to −0.745, p < 0.01 to 0.04). These findings suggest that body composition can influence the distance covered at moderate- and high-intensity running speed during competitive games. Training strategies aimed at reducing fat mass and incorporating high-intensity training may benefit female soccer players and enhance team success. Full article

Moderate-Resolution Imaging Spectroradiometer (MODIS) Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) products are being increasingly used for the quantitative remote sensing of vegetation. However, the assumption underlying the MODIS NBAR product’s inversion model—that surface anisotropy remains unchanged over the 16-day retrieval period—may be unreliable, especially since the canopy structure of vegetation undergoes stark changes at the start of season (SOS) and the end of season (EOS). Therefore, to investigate the MODIS NBAR product’s temporal effect on the quantitative remote sensing of crops at different stages of the growing seasons, this study selected typical phenological parameters, namely SOS, EOS, and the intervening stable growth of season (SGOS). The PROBA-V bioGEOphysical product Version 3 (GEOV3) Fractional Vegetation Cover (FVC) served as verification data, and the Pearson correlation coefficient (PCC) was used to compare and analyze the retrieval accuracy of FVC derived from the MODIS NBAR product and MODIS Surface Reflectance product. The Anisotropic Flat Index (AFX) was further employed to explore the influence of vegetation type and mixed pixel distribution characteristics on the BRDF shape under different stages of the growing seasons and different FVC; that was then combined with an NDVI spatial distribution map to assess the feasibility of using the reflectance of other characteristic directions besides NBAR for FVC correction. The results revealed the following: (1) Generally, at the SOSs and EOSs, the differences in PCCs before vs. after the NBAR correction mainly ranged from 0 to 0.1. This implies that the accuracy of FVC derived from MODIS NBAR is lower than that derived from MODIS Surface Reflectance. Conversely, during the SGOSs, the differences in PCCs before vs. after the NBAR correction ranged between –0.2 and 0, suggesting the accuracy of FVC derived from MODIS NBAR surpasses that derived from MODIS Surface Reflectance. (2) As vegetation phenology shifts, the ensuing differences in NDVI patterning and AFX can offer auxiliary information for enhanced vegetation classification and interpretation of mixed pixel distribution characteristics, which, when combined with NDVI at characteristic directional reflectance, could enable the accurate retrieval of FVC. Our results provide data support for the BRDF correction timescale effect of various stages of the growing seasons, highlighting the potential importance of considering how they differentially influence the temporal effect of NBAR corrections prior to monitoring vegetation when using the MODIS NBAR product. Full article

Time series forecasting plays a critical role in business planning by offering insights for a competitive advantage. This study compared three forecasting methods: the Holt–Winters, Bagging Holt–Winters, and Box–Jenkins methods. Ten datasets exhibiting linear and non-linear trends and clear and ambiguous seasonal patterns were selected for analysis. The Holt–Winters method was tested using seven initial configurations, while the Bagging Holt–Winters and Box–Jenkins methods were also evaluated. The model performance was assessed using the Root-Mean-Square Error (RMSE) to identify the most effective model, with the Mean Absolute Percentage Error (MAPE) used to gauge the accuracy. Findings indicate that the Bagging Holt–Winters method consistently outperformed the other methods across all the datasets. It effectively handles linear and non-linear trends and clear and ambiguous seasonal patterns. Moreover, the seventh initial configurationdelivered the most accurate forecasts for the Holt–Winters method and is recommended as the optimal starting point. Full article

Solar energy is an important alternative energy source, and it is essential to forecast solar power generation for efficient power management. Due to the seasonal characteristics of weather features, seasonal data partition strategies help develop prediction models that perform better in extreme weather-related situations. Most existing studies rely on fixed season partitions, such as meteorological and astronomical, where the start and end dates are specific. However, even if the countries are in the same Northern or Southern Hemisphere, seasonal changes can occur due to abnormal climates such as global warming. Therefore, we propose a novel unfixed seasonal data partition based on Symbolic Aggregate Approximation (SAX) to forecast solar power generation. Here, symbolic representations generated by SAX are used to select seasonal features and obtain seasonal criteria. We then employ two-layer stacked LSTM and combine predictions from various seasonal features and partitions through ensemble methods. The datasets used in the experiments are from real-world solar panel plants such as in Gyeongju, South Korea; and in California, USA. The results of the experiments show that the proposed methods perform better than non-partitioned or fixed-partitioned solar power generation forecasts. They outperform them by 2.2% to 3.5%; and 1.6% to 6.5% in the Gyeongju and California datasets, respectively. Full article

The cultivation or ‘tillage’ system is one of the most important elements of agrotechnology. It affects the condition of the soil, significantly modifying its physical, chemical, and biological properties, and the condition of plants, starting from ensuring appropriate conditions for sowing and plant growth, through influencing the efficiency of photosynthesis and ultimately, the yield. It also affects air transmission and the natural environment by influencing greenhouse gas (GHG) emissions potentially. Ultimately, the cultivation system also has an impact on the farmer, providing the opportunity to reduce production costs. The described experiment was established in 1998 at the Brody Agricultural Experimental Station belonging to the University of Life Sciences in Poznań (Poland) on a soil classified as an Albic Luvisol, while the described measurements were carried out in the 2022/2023 season, i.e., 24 years after the establishment of the experiment. Two cultivation methods were compared: Conventional Tillage (CT) and No Tillage (NT). Additionally, the influence of two factors was examined: nitrogen (N) fertilization (0 N—no fertilization, and 130 N–130 kg N∙ha⁻¹) and the growth phase of the winter wheat plants (BBCH: 32, 65 and 75). The growth phase of the plants was assessed according to the method of the Bundesanstalt, Bundessortenamt and CHemische Industrie (BBCH). We present the results of soil properties, soil respiration, wheat plants chlorophyll fluorescence, and grain yield. In our experiment, due to low rainfall, NT cultivation turned out to be beneficial, as it was a key factor influencing the soil properties, including soil organic carbon (SOC) content and soil moisture, and, consequently, creating favorable conditions for plant nutrition and efficiency of photosynthesis. We found a positive effect of NT cultivation on chlorophyll fluorescence, but this did not translate into a greater yield in NT cultivation. However, the decrease in yield due to NT compared to CT was only 5% in fertilized plots, while the average decrease in grain yield resulting from the lack of fertilization was 46%. We demonstrated the influence of soil moisture as well as the growth phase and fertilization on carbon dioxide (CO₂) emissions from the soil. We can clearly confirm that the tillage system affected all the parameters discussed in the work. Full article

Polar mesospheric clouds (PMCs) are ice crystal clouds formed in the mesosphere of high-latitude regions in both the northern (NH) and southern hemispheres (SH). Peak height is an important physical characteristic of PMCs. Satellite observation data from solar occultation for ice experiments (SOFIE) during seven PMC seasons from 2007 to 2014 show that the difference between the height of the mesopause and the peak height of the PMCs (Z_mes-Z_max) were inversely correlated with the atmospheric mesopause temperature. The Z_mes-Z_max averages for all seasons for the NH and SH were 3.54 km and 2.66 km, respectively. They were smaller at the starting and ending stages of each PMC season and larger in the middle stages. Analysis of the individual cases and statistical results simulated by the PMCs 0-D model also revealed the inverse correlations between the Z_mes-Z_max and mesopause temperature, with correlation coefficients of −0.71 and −0.62 for the NH and SH, respectively. The corresponding rates of change of Z_mes-Z_max with respect to mesopause temperature were found to be −0.21 km/K and −0.14 km/K, respectively. The formation mechanism of PMCs suggests that a lower temperature around the mesopause can lead to a greater distance and longer time for ice crystals to condense and grow in clouds. Thus, ice crystals sediment to a lower height, making the peak height of the PMCs further away from the mesopause. In addition, disturbances in small-scale dynamic processes tend to weaken the impact of temperature on the peak height of PMCs. Full article

Extreme rainfall can severely affect all vegetation types, significantly impacting crop yield and quality. This study aimed to assess the response and recovery of vegetation phenology to an extreme rainfall event (with total weekly rainfall exceeding 500 mm in several cities) in Henan Province, China, in 2021. The analysis utilized multi-sourced data, including remote sensing reflectance, meteorological, and crop yield data. First, the Normalized Difference Vegetation Index (NDVI) time series was calculated from reflectance data on the Google Earth Engine (GEE) platform. Next, the ‘phenofit’ R language package was used to extract the phenology parameters—the start of the growing season (SOS) and the end of the growing season (EOS). Finally, the Statistical Package for the Social Sciences (SPSS, v.26.0.0.0) software was used for Duncan’s analysis, and Matrix Laboratory (MATLAB, v.R2022b) software was used to analyze the effects of rainfall on land surface phenology (LSP) and crop yield. The results showed the following. (1) The extreme rainfall event’s impact on phenology manifested directly as a delay in EOS in the year of the event. In 2021, the EOS of the second growing season was delayed by 4.97 days for cropland, 15.54 days for forest, 13.06 days for grassland, and 12.49 days for shrubland. (2) Resistance was weak in 2021, but recovery reached in most areas by 2022 and slowed in 2023. (3) In each year, SOS was predominantly negatively correlated with total rainfall in July (64% of cropland area in the first growing season, 53% of grassland area, and 71% of shrubland area). In contrast, the EOS was predominantly positively correlated with rainfall (51% and 54% area of cropland in the first and second growing season, respectively, and 76% of shrubland area); however, crop yields were mainly negatively correlated with rainfall (71% for corn, 60% for beans) and decreased during the year of the event, with negative correlation coefficients between rainfall and yield (−0.02 for corn, −0.25 for beans). This work highlights the sensitivity of crops to extreme rainfall and underscores the need for further research on their long-term recovery. Full article

The key to a sustainable future is the reduction in humankind’s impact on natural systems via the development of new technologies and the improvement in source apportionment. Although days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth’s orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from the literature to influence emission cycles and atmospheric chemistry. For the first time since it started data gathering operations, CO (carbon monoxide), CO₂ (carbon dioxide), CH₄ (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy, have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements from 2016 to 2022. The results demonstrate that the analyzed GHGs (greenhouse gasses) and aerosols respond differently to weekly cycles throughout the seasons, and these findings provide completely new insights into source apportionment characterization. Moreover, the results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends in CO, CO₂, CH₄ and eBC on an absolute scale, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects on the environment and human health. Full article

Oxidative stress and chronic inflammation create a perpetual cycle in the elderly, where impaired immune function amplifies susceptibility to oxidative damage, and oxidative stress further weakens the immune response. This cycle is particularly detrimental to the respiratory system of the elderly, which is an easy target for constant exogenous harmful attacks during cold/flu season or under heavy air pollution. Herbal medicines that protect respiratory function are seen as safer alternatives to conventional therapies; however, there is limited availability of scientifically validated, safe, and effective natural supplements for these conditions. In this study, we evaluated a standardized bioflavonoid composition, UP446, that contains bioactives from the roots of Scutellaria baicalensis and the heartwoods of Acacia catechu as a natural and nutritional supplement for its antioxidative and immunoregulatory effects in oxidative stress-accelerated aging and chemically induced immune suppression mouse models. Immunosenescence was induced through the repeated subcutaneous inoculation of D-galactose (D-Gal) at a dose of 500 mg/kg/day in CD-1 mice. UP446 was administered orally at doses of 100 mg/kg and 200 mg/kg starting in the fifth week of immunosenescence induction. This study lasted a total of ten weeks. All mice received a quadrivalent influenza vaccine 2 weeks before termination. Whole blood, serum, spleen homogenate, and thymus tissues were processed for analysis. Cyclophosphamide (Cy)-induced immunosuppression was triggered by three consecutive injections of cyclophosphamide at 80 mg/kg/day, followed by the oral administration of UP446 for 18 days at doses of 100 mg/kg and 200 mg/kg. Blood was collected from each animal at necropsy, and serum was isolated for IgA and IgG ELISA analysis. UP446 was found to improve immune response, as evidenced by the stimulation of innate (NK cells) and adaptive immune responses (T cells and cytotoxic T cells), an increase in antioxidant capacity (glutathione peroxidase), the preservation of vital immune organs (the thymus), and a reduction in NFκB. UP446 also increased serum levels of IgA and IgG. The findings presented in this report demonstrate the antioxidative, anti-inflammatory, and immune-regulatory activities of UP446, suggesting its potential use in respiratory conditions involving immune stress due to aging, oxidative stress, and/or pathogenic challenges. Full article

Olea europaea L. pollen is one of the main causes of pollinosis and respiratory diseases in the Iberian Peninsula (IP). The aim of this study was to provide a pollen calendar in different regions of the IP, which could help allergists and allergic patients in the management of Olea europaea allergic diseases, and to update/complement what has already been reported on olive trees’ aeropalynology in this region. Airborne Olea pollen dynamics were analyzed over a period of 8 years in a total of 21 localities, 7 in Portugal and 14 in Spain. Airborne pollen monitoring was carried out using the Hirst-type spore trap method and following the recommendations of the Quality Control Working Group of the European Aerobiology Society. The daily pollen count, the annual pollen profile, the Annual Pollen Integral (APIn), the Seasonal Pollen Integral (SPIn) and the Pollen Peak, all expressed in number of pollen grains per cubic metre of air, together with the main pollen season and its characteristics, the Start Day, the End Day and the length of the pollen season, were calculated for each sampling station. Differences in mean Olea pollen concentration between odd and even years were also analyzed. On average, the main pollen season (MPS) started in April/May and ended in June, with Pollen Peaks recorded in May, except in Burgos, where it was recorded in June. The longest MPS occurred in Lisbon, Oviedo and Valencia (53 days) and the shortest in Vitoria (25 days). A high daily pollen concentration (i.e., >200 grains/m³) was recorded between 1 and 38 days along the year in all sampling stations of the southwest quadrant of the IP and in Jaén. A biannual pattern, characterized by alternating years of high and low pollen production, was found in the southwest of the IP. In conclusion, the study provided a deeper understanding of the pollination behaviour of olive trees in the IP and allowed the establishment of a representative Olea pollen calendar for this region. In addition, our results suggest the usefulness of investigating more detailed relationships between annual Olea pollen, allergen sensitization and symptoms, both for allergists involved in the study and management of allergic respiratory diseases caused by this species and for the self-management of disease in allergic subjects. Full article