Start Of Season Research Articles

Clockwork precision: egg-laying-induced rise of body temperature is seasonally programmed in a wild bird

There is long time interest about the phenology of plants and animals living in seasonal environments as research in that field would help to understand the coping mechanisms leading to a higher fitness. For instance, it has been shown several decades ago that birds prepare themselves 2–4 months before the actual start of the breeding season by slowly growing reproductive organs. In parallel, the resting metabolic rate increase during reproduction in various vertebrates including mammals, reptiles, and birds. Recently, it has been reported that body temperature of a marine bird species was reaching an annual peak during egg-laying, raising the question about the seasonal dynamic of this important physiological feature. Using data loggers implanted in the abdominal cavity of female Common Eiders (Somateria mollissima mollissima) for a full year, we show here that daily body temperature (Tb.daily) is slowly increasing first and then accelerating at the approach of the laying period. Because the rise of Tb.daily is tightly associated with egg-laying in this species, we also analysed the influence of ambient temperature (water and air) and photoperiod on this seasonal dynamic. Based on the various mechanisms at work and a parsimonious interpretation of the data, we conclude that photoperiod is the main cue driving the seasonal breeding program of eiders. Although the laying dates of the instrumented females were highly clustered over a period of 4 years, we speculated that the remaining variation observed was the result of eco-physiological challenges occurring over the years.

The Impact of Seasonal Climate on Dryland Vegetation NPP: The Mediating Role of Phenology

Dryland ecosystems are highly sensitive to climate change, making vegetation monitoring crucial for understanding ecological dynamics in these regions. In recent years, climate change, combined with large-scale ecological restoration efforts, has led significant greening in China’s arid areas. However, the mechanisms through which seasonal climate variations regulate vegetation growth are not yet fully understood. This study hypothesizes that seasonal climate change affects net primary productivity (NPP) of vegetation by influencing phenology. We focused on China’s Windbreak and Sand-Fixation Ecological Function Conservation Areas (WSEFCAs) as representative regions of dryland vegetation. The Carnegie–Ames–Stanford Approach (CASA) model was used to estimate vegetation NPP from 2000 to 2020. To extract phenological information, NDVI data were processed using Savitzky–Golay (S–G) filtering and threshold methods to determine the start of season (SOS) and end of season (EOS). The structural equation model (SEM) was constructed to quantitatively assess the contributions of climate change (temperature and precipitation) and phenology to variations in vegetation NPP, identifying the pathways of influence. The results indicate that the average annual NPP in WSEFCAs increased from 55.55 gC/(m2·a) to 75.01 gC/(m2·a), exhibiting uneven spatial distribution. The pathways through which seasonal climate affects vegetation NPP are more complex and uneven. Summer precipitation directly promoted NPP growth (direct effect = 0.243, p < 0.001) while also indirectly enhancing NPP by significantly advancing SOS (0.433, p < 0.001) and delaying EOS (−0.271, p < 0.001), with an indirect effect of 0.133. This finding highlights the critical role of phenology in vegetation growth, particularly in regions with substantial seasonal climate fluctuations. Although the overall ecological environment of WSEFCAs has improved, significant regional disparities remain, especially in northwestern China. This study introduces causal mediation analysis to systematically explore the mechanisms through which seasonal climate change impacts vegetation NPP in WSEFCAs, providing new insights into the broader implications of climate change and offering scientific support for ecological restoration and management strategies in arid regions.

Exploring the relationships between ground observations and remotely sensed hazelnut spring phenology.

Crop phenology is very important in regular crop monitoring. Generally, phenology is monitored through field observation surveys or satellite data. The relationships between ground observations and remotely sensed derived phenological data can enable near-real-time monitoring over large areas, which has never been attempted on hazelnuts. In this study, we extracted phenological metrics derived from MODIS Enhanced Vegetation Index (EVI) in hazelnut production regions and compared them with the spring ground phenological data (BBCH scale) from orchards located in the same area of Turkey over the period from 2019 to 2022. We observed a specific temporal dynamic between remote sensing phenometrics and ground observations. The metrics Greenup, Upturning Date, and Threshold 20% metrics corresponded to the early of EVI growth and were synchronous with the female flowering of hazelnut and ending before bud break. The metrics Threshold 50% and Start of season were associated with the steepest portion of the EVI curve, i.e., canopy greening and thickening, and occurred between ovaries enlargement and leaves unfolding. The metrics Peak of Season, Stabilization Date, and Maturity corresponded to the end of spring vegetative growth. The main outcomes are that (i) female flowering occurred before 20% of vegetation development (BBCH 64P occurred about one month before Threshold 20%), (ii) phenometrics from satellite remote sensing (i.e., Upturning Date and Threshold 20%) well-reflected leaf emergence (rs = 0.30 and rs = 0.32, respectively; p < 0.05) and unfolding (rs = 0.35 and rs = 0.39, respectively; p < 0.05), and (iii) cluster appearance temporally aligned with the peak of the EVI curve (Stabilization Date and BBCH 71P differed by around 4 days). Our method is transferable to operational phenology monitoring, and future applications will consider the senescence season and the effect of environmental variability on the comprehension of vegetation dynamics.

A case study of the 2023 highly pathogenic avian influenza (HPAI) outbreak in tern (Sternidae) colonies on the east coast of the Republic of Ireland

ABSTRACT Capsule:HPAI H5N1 had a significant impact on breeding Common Terns Sterna hirundo, Arctic Terns Sterna paradisaea and Roseate Terns Sterna dougallii on the east coast of the Republic of Ireland (ROI) in 2023, with a lesser impact on Sandwich Terns Thalasseus sandvicensis and only two cases among Little Terns Sternula albifrons. Aims: To document the outbreak of HPAI H5N1 in the tern colonies on the east coast of ROI during the 2023 breeding season. Methods:Precautions were taken from the start of the breeding season, including personal protective equipment (PPE) and safe operating procedures. Regular meetings were held between BirdWatch Ireland and the National Parks and Wildlife Service (NPWS) to respond to the emerging situation. Once HPAI was confirmed in a colony, all ringing and nest visits were stopped. Carcass removal was carried out at all affected colonies and most carcasses were incinerated. Results: Common Terns suffered the highest mortality across all colonies in 2023, with smaller but notable numbers of dead Roseate Terns and Arctic Terns, but very few Sandwich Terns and only two Little Tern deaths were attributed to HPAI. Conclusion: Regular meetings between relevant organizations were invaluable in preparing for outbreaks and ensuring an adaptive approach as the situation changed over time and between colonies. There was no way of knowing if the actions taken were effective, as the pattern of virus spread between species and sites remains poorly understood. Future clarity over the role of various state agencies and other relevant bodies in responding to HPAI in wild birds, greater sharing of real-time information, and pre-arranged agreements to ensure rapid testing and disposal of carcasses, would be useful to ensure an effective response to future outbreaks.

Evaluation of the spatial responses in vegetation phenology to drought and the analysis of their driving factors in China

The warming and drying trend accompanying climate change challenges global ecosystem stability. Vegetation phenology, which can serve as a sensitive indicator of climate change, is crucial in understanding ecosystem carbon cycling and climate-carbon cycle feedback. Therefore, assessing the phenological responses to drought is essential for addressing climate change. In this study, vegetation phenology data [including the start and end of season (SOS, EOS) and length of growing season (LOS)] and the Palmer drought severity index (PDSI) were employed to analyze the impacts of drought on plant phenology in China by maximum Pearson correlation coefficients and partial least squares regression. The findings showed that drought significantly affected the timing of phenology, delaying senescence in approximately 62% of China and extending the growing season in about 53% of the country, indicating the critical role of water availability in vegetation biomass. Preseason nocturnal warming was found to advance SOS, delay EOS, and extend LOS across China, with significant effects observed in approximately 60% of the country. Meanwhile, daytime warming delayed SOS, delayed EOS and extended LOS in 50∼60% of the regions. Moreover, preseason precipitation is conducive to advanced SOS, delayed EOS and extended LOS in northern China and areas susceptible to drought. It is suggested that vegetation management should be strengthened to mitigate the impact of climate change in temperate and drought-prone regions in China since climate warming will lead to frequent droughts.

Influenza Vaccine Effectiveness Against Illness and Asymptomatic Infection in 2022-2023: A Prospective Cohort Study.

Previous estimates of vaccine effectiveness (VE) against asymptomatic influenza virus infection based on seroconversion have varied widely and may be biased. We estimated 2022-2023 influenza VE against illness and asymptomatic infection in a prospective cohort. In the HEROES-RECOVER cohort, adults at increased occupational risk of influenza exposure across 7 US sites provided weekly symptom reports and nasal swabs for reverse transcription-polymerase chain reaction (RT-PCR) influenza testing. Laboratory-confirmed influenza virus infections were classified as symptomatic (≥1 symptom) or asymptomatic during the week of testing. Participants reported demographic information and vaccination through surveys; most sites verified vaccination through medical record and immunization registry review. Person-time was calculated as days from the site-specific influenza season start (September-October 2022) through date of infection, study withdrawal, or season end (May 2023). We compared influenza incidence among vaccinated versus unvaccinated participants overall, by symptom status, and by influenza A subtype, using Cox proportional hazards regression adjusted for site and occupation. We estimated VE as (1 - adjusted hazard ratio) × 100%. In total, 269 of 3785 (7.1%) participants had laboratory-confirmed influenza, including 263 (98%) influenza A virus infections and 201 (75%) symptomatic illnesses. Incidence of laboratory-confirmed influenza illness among vaccinated versus unvaccinated participants was 23.7 and 33.2 episodes per 100 000 person-days, respectively (VE: 38%; 95% CI: 15%-55%). Incidence of asymptomatic influenza virus infection was 8.0 versus 11.6 per 100 000 (VE: 13%; 95% CI: -47%, 49%). Vaccination reduced incidence of symptomatic but not asymptomatic influenza virus infection, suggesting that influenza vaccination attenuates progression from infection to illness.

NDVI or PPI: A (Quick) Comparison for Vegetation Dynamics Monitoring in Mountainous Area

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.

Phenological Monitoring of Irrigated Sugarcane Using Google Earth Engine, Time Series, and TIMESAT in the Brazilian Semi-arid

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).

Influence of Vegetation Phenology on the Temporal Effect of Crop Fractional Vegetation Cover Derived from Moderate-Resolution Imaging Spectroradiometer Nadir Bidirectional Reflectance Distribution Function–Adjusted Reflectance

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.

Moss spores: overlooked airborne bioparticles in an urban environment.

Moss spores are present in aerobiological samples, but their low representation, lack of known allergenic properties, and difficult identification have led to their being overlooked by aerobiologists so far. The data about their presence in the atmosphere and the factors that influence them are, however, important from the biodiversity conservation point of view, since they give us information about their ability to spread to new habitats. In this pilot study, we analysed their presence in the atmosphere of Bratislava city, Slovakia (2018-2023), using Burkard volumetric sampler, and determined the most significant factors influencing its temporal distribution. The size category of 13-18 µm was the most represented in the samples. Environmental factors influenced the daily spore concentrations and the characteristics of the whole spore season. The start of the Main Spore Season (MSS) depended mainly on the temperatures in November-January, initiating earlier growth of sporophytes in the following year, while the intensity of the MSS was influenced by high humidity in April, stimulating the formation of spores in sporangia. The daily concentration of airborne moss spores was mostly influenced by the actual temperature and wind speed, promoting the release and dispersal of spores, and precipitation lowering their levels due to the "wash-out" effect, although no intradiurnal pattern was observed. More data from other locations is needed to determine the role of atmospheric spore transport for the conservation of moss species facing anthropogenic climatic change.

Using the Observed Variations of the Start Date of the Rainy Season over Central America for Its Reliable Seasonal Outlook

Abstract We introduce a simple method to define the start and the end of the rainiest part of the year as the first and the last day of the year when the daily rain rate is more or less than the annual mean climatological rain rate for a region or at a given grid point of the rainfall analysis, respectively. A novelty of this work is the adoption of a perturbation technique to generate a total of 1001 ensemble members to account for observational and analysis uncertainties. This allows for a probabilistic estimate of the start and retreat dates of the rainy season at the granularity of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), version 6, rainfall analysis over Central America. The seasonal cycle of the IMERG rainfall analysis is also found to verify with in situ observations in the region. Many large-scale climate drivers affect regional rainfall, often with complex interactions that affect the onset date, retreat date, and magnitude of the seasonal rainfall cycle, making it difficult to predict the length or total quantity of seasonal rainfall using climate drivers alone. Once an onset date is established, however, this metric alone can be more indicative of both the length and total seasonal rainfall anomaly than predicting how the climate drivers will interact to affect the quantity and duration of upcoming seasonal rainfall. The local relationships of the start date with seasonal length and rainfall anomaly are leveraged to produce effective seasonal outlooks of the rainy season for the region by just monitoring the start date variations. Significance Statement The start date and retreat date of the rainy season in Central America are defined every year, precisely to a specific date from our proposed definition of it. This is possible because the region exhibits a strong seasonality of the rainfall. As a result, the year-to-year (interannual) variation of the seasonal rainfall during the rainy season is also determined by the variations in the length of the season that are usually overlooked in fixed calendar seasons. We define the start or retreat date of the rainy season as the first or the last day of the year when the daily rain rate exceeds or falls below the average daily rainfall from 2001 to 2022, respectively. We also find that both start and retreat date variations independently influence the length and total seasonal rainfall of the rainy season. Consequently, these relationships are leveraged to provide an outlook of the forthcoming rainy season from the diagnosis of the variations of its onset date, which is shown to be an effective predictor with significant useful seasonal prediction skills.

Assessing the phenological state of evergreen conifers using hyperspectral imaging time series

Phenology is a reliable indicator of vegetation condition and ecological changes in the environment. Plant Spectral Phenology (PSP) offers the potential for the development of automated, rapid, and wide-area vegetation monitoring systems. The spectral characteristics of plants (vegetation) are employed as metrics of PSP, which can be sensed both proximally and remotely. A key objective is to undertake a comparative analysis of the results of PSP versus those of phenology based on visual observations. The resolution of this issue is of paramount importance for the coordination of phenological studies at diverse levels (ground, surface, and remote), thus ensuring the continuity of phenological studies conducted prior to the advent of PSP. This issue is particularly pronounced in the case of evergreen conifers. The present study focuses on four evergreen conifers: Thuja occidentalis, Platycladus orientalis, Pinus sylvestris and P. nigra subsp. pallasiana. Hyperspectral imaging was performed under laboratory conditions using a Cubert UHD-185 hyperspectral camera. Concomitantly, phenological observations were conducted. The spectral time series yielded 79 chlorophyll-sensitive and carotenoid-sensitive Vegetation Indices (VIs), which were then used to construct double logistic functions. A significant proportion of the VIs exhibited a high degree of correctness with regard to the aforementioned functions, as indicated by the value of R2 exceeding 0.7. The values of the principal stages of seasonal development of evergreen conifers, namely the Start of Season (SOS), End of Season (EOS), Position of Peak value (POP) and Length of Season (LOS), were calculated using double logistic functions. These stages were matched to the phenological phases of development of the experimental plants. The values of SOS, EOS, POP and LOS varied significantly depending on the VIs used as a metric as well as the evergreen conifers. The lowest variability by metrics is observed in SOS, while the maximum is observed in EOS and POP. The results obtained may be of importance for the choice of criterion for the comparison of PSP with phenology based on visual observations and the most suitable VIs for these purposes.

Interactions of climate, topography, and soil factors can enhance the effect of a single factor on spring phenology in the arid/semi-arid grasslands of China

Understanding the interactions among climate, topography, and soil factors on vegetation spring phenology can help reveal the feedback mechanisms of vegetation ecosystems in response to environmental conditions and climate change. Nonetheless, the coupling effects of these environmental elements on vegetation start of season (SOS) are still poorly understood. We took Xinjiang Province, a typical arid/semi-arid region, as the research area and quantitatively analyzed the explanatory power and interactions of climate, topography, and soil factors on grassland SOS through the geographical detector model based on the data extracted by Timesat 3.3 software. The results showed that: (1) From 2001 to 2020, early SOS predominantly occurred from 75 to 105 days in Northern Xinjiang. While later SOS was widespread in Southern Xinjiang from 105 to 135 days. The area of the SOS advanced region was larger than that of the delayed region; (2) There was obvious spatial hierarchical heterogeneity between SOS and climate, topography, and soil factors. Altitude, maximum temperature, and soil type were the primary drivers of SOS changes in the study area (P < 0.001); (3) The interactions among environmental factors strengthened the explanatory power of individual factors, either through mutual reinforcement or non-linear effects. The interactions between elevation and climate factors were particularly significant, with an explanatory power above 0.3. This study highlighted the importance of the coupling effects of environmental variables on SOS and suggested that drives should be considered more comprehensively in future analyses.

The linkage between functional traits and drone-derived phenology of 74 Northern Hemisphere tree species

Tree phenology is a major component of the global carbon and water cycle, serving as a fingerprint of climate change, and exhibiting significant variability both within and between species. In the emerging field of drone monitoring, it remains unclear whether this phenological variability can be effectively captured across numerous tree species. Additionally, the drivers behind interspecific variations in the phenology of deciduous trees are poorly understood, although they may be linked to plant functional traits. In this study, we derived the start of season (SOS), end of season (EOS), and length of season (LOS) for 3099 individuals from 74 deciduous tree species of the Northern Hemisphere at a unique study site in southeast Germany using drone imagery. We validated these phenological metrics with in-situ data and analyzed the interspecific variability in terms of plant functional traits. The drone-derived SOS and EOS showed high agreement with ground observations of leaf unfolding (R2 = 0.49) and leaf discoloration (R2 = 0.79), indicating that this methodology robustly captures phenology at the individual level with low temporal and human effort. Both intra- and interspecific phenological variability were high in spring and autumn, leading to differences in the LOS of up to two months under almost identical environmental conditions. Functional traits such as seed dry mass, chromosome number, and continent of origin played significant roles in explaining interspecific phenological differences in SOS, EOS, and LOS, respectively. In total, 55 %, 39 %, and 45 % of interspecific variation in SOS, EOS, and LOS could be explained by the Boosted Regression Tree (BRT) models based on functional traits. Our findings encourage new research avenues in tree phenology and advance our understanding of the growth strategies of key tree species in the Northern Hemisphere.

Fingerprinting of emerging contaminants in L'Albufera natural park (Valencia, Spain): Implications for wetland ecosystem health

Wetlands are crucial ecosystems that are increasingly threatened by anthropogenic activities. L'Albufera Natural Park, the second-largest coastal wetland in Spain, faces significant pressures from surrounding agricultural lands, industrial activities, human settlements, and associated infrastructures, including treated wastewater inputs. This study aimed at (i) establishing pathways of emerging pollutants entering the natural wetland using both target and non-target screening (NTS) for management purposes, (ii) distinguishing specific contamination hotspots through Geographic Information System (GIS) and (iii) performing basic ecological risk assessment to evaluate ecosystem health. Two sampling campaigns were conducted in the spring and summer of 2019, coinciding with the start and end of the rice cultivation season, the region's primary agricultural activity. Each campaign involved the collection of 51 samples. High-resolution mass spectrometry (HRMS) was employed, using a simultaneous NTS approach with optimized gradients for pesticides and moderately polar compounds, along with complementary NTS methods for polar compounds, to identify additional contaminants of emerging concern (CECs). Quantitative analysis revealed that fungicides comprised a substantial portion of detected CECs, constituting approximately 50% of the total quantified pesticides. Tebuconazole emerged as the predominant fungicide, with the highest mean concentration (>16.9 μg L−1), followed by azoxystrobin and tricyclazole. NTS tentatively identified 16 pesticides, 43 pharmaceuticals and personal care products (PPCPs), 24 industrial compounds, and 12 other CECs with high confidence levels. Spatial distribution analysis demonstrated significant contamination predominantly in the southwestern region of the park, gradually diminishing towards the north-eastern outlet. The composition of contaminants varied between water and sediment samples, with pharmaceuticals predominating in water and industrial compounds in sediments. Risk assessment, evaluated through risk quotient calculations based on parent compound concentrations, revealed a decreasing trend towards the outlet, suggesting wetland degradation capacity. However, significant risk levels persist throughout much of the Natural Park, highlighting the urgent need for mitigation measures to safeguard the integrity of this vital ecosystem.

An evaluation of 2015–2019 United States respiratory syncytial virus hospitalizations as a framework to develop potential strategies for the preventiosn of the hospital burden among infants

New options for RSV prevention are available for the 2023/2024 RSV season, nirsevimab, a monocolonal antibody, and RSVpreF maternal vaccine, that target infants entering their first RSV season. Countries vary in implementation of one or both strategies to reduce the RSV burden among infants. This study utilized retrospective cohort data from 47 children's hospitals in the United States Pediatric Health Information Systems (PHIS) database between 2015 and 2019. Patients hospitalized with RSV or bronchiolitis aged 0-15 months were included based on birth timing relative to the RSV season. Annualized hospitalization rates per 100,000 were calculated from extrapolated population estimates. Recommended prevention strategies were applied to age cohorts to compare protection afforded by nirsevimab and maternal immunization strategies. 72,209 RSV hospitalizations were included in the study. Compared to those born nine months prior to the season (n=2116; 375/100,000 per year), those born at the start of the season were 9.44 (9.02-9.89) times as likely to be hospitalized for RSV (n=19,979; 3542/100,000 per year). Both strategies would prevent most of these hospitalizations. Maternal immunization would not prevent hospitalizations of infants aged two or 3monthsat season start, who were respectively 2.95 (2.80-3.10) and 2.22 (2.11-2.34) times as likely to be hospitalized. Proportionally more preterm infants were hospitalized in their second RSV season, resulting in less protection (up to 40% to >80% unprotected). These findings suggest without a more narrowly targeted strategy, current nirsevimab recommendations may not be as cost efficient for infants born further outside of the RSV season, and those born later in the season who are more likely to be hospitalized in subsequent seasons. Conversely, it may be more beneficial to begin maternal immunization further in advance of the season. Immunization strategies should be based on the RSV seasons within specific regions. None.

Deer Hunting Season and Firearm Violence in US Rural Counties

Firearm violence is a major public health problem in the US. However, relatively little research has focused particular attention on firearm violence in rural areas, and few studies have used research designs that draw on exogenous variation in the prevalence of firearms to estimate the association between firearm presence and shootings. To investigate the association between the start of deer hunting season and shootings in rural counties in the US. In this cohort study, data from all rural US counties in states with available data on the timing of deer hunting season were matched with data on shootings from the Gun Violence Archive from January 1, 2014, to December 31, 2021. Shootings in the first 3 weeks of deer hunting season were compared with the week prior to the start of deer hunting season. The main outcome was daily total shootings. The association between the start of deer hunting season and shootings was estimated using Poisson regression models to analyze change within counties while controlling for relevant calendar year, month of year, and seasonal effects. The sample included 854 rural counties with a mean (SD) population of 16 416 (18 329) per county and 5.4 (13.3) annual shootings per 100 000 people. The county fixed-effects specification analyzing the association between deer hunting season and shootings showed that relative to the week prior to deer hunting season, the incidence rate ratio for total shootings was 1.49 (95% CI, 1.13-1.95) for the first week of deer hunting season and 1.41 (95% CI, 1.02-1.94) for the second week of deer hunting season. Estimates remained consistent when excluding hunting accidents and were most pronounced in states with more hunting licenses per capita. In this cohort study of the association between the start of deer hunting season and firearm violence, results showed that the start of deer hunting season was associated with a substantial increase in shootings. The findings highlight the role of firearm prevalence in gun violence and suggest the need for focused policies designed to reduce firearm violence in areas with substantial hunting activity during the first weeks of deer hunting season.

The Influence of Futsal Players' Initial Physical Condition on the Occurrence of Injuries.

Although there are some studies that have linked fitness parameters and sports injuries, the literature remains controversial. The aim of the study was to prospectively analyze the influence of initial physical condition parameters on the development of injury in the first three months of the sports season in futsal players. A total of 68 players (24.26±4.63 years old) were assessed before the start of the sports season in relation to certain physical condition parameters, such as body composition (bioimpedance), lower limb power (countermovement jump, CMJ) and muscle strength (isokinetic dynamometer). The injured players showed significantly worse initial performance in the CMJ compared to the uninjured players (p<0.001). There were no significant differences between groups in body composition and muscle strength. Lower power values were associated with a higher risk of injury in the first few months of the sports season (OR=0.92; 95% CI=0.88-0.99). Muscle power was an independent predictor of injury in the first few months of the sports season in futsal players, indicating that improving players' physical condition could help reduce the number of injuries.

Risk of healthcare visits from influenza in subjects with diabetes and impacts of early vaccination

IntroductionThe objective of this study was to determine the burden of influenza disease in patients with or without diabetes in a population of American adults to understand the benefits of...

Nutritive value and condensed tannins of tree legumes in silvopasture systems

Introducing legumes into C4-dominated tropical pastures, may enhance their sustainability but has some pasture management constraints. One potential alternative is using arboreal legumes, but several of these species have relatively high condensed tannin (CT) concentrations, which negatively impact forage quality. There is limited knowledge, however, on how arboreal legume leaf CT content varies over the year and how this might impact forage quality. The objective of this 2 year study was to assess the seasonal variation of CT and nutritive value for ruminants of the tropical tree legumes gliricidia [Gliricidia sepium (Jacq.) Kunth ex. Walp.] and mimosa (Mimosa caesalpiniifolia Benth). The research was carried out in the sub-humid tropical region of Brazil on well-established pastures in which either legume was present with signalgrass (Urochloa decumbens Stapf.). We determined CT and nitrogen concentrations, in vitro digestible organic matter (IVDOM), and leaf δ13C and δ15N from January to October of 2017 and 2018. All parameters were affected (P < 0.05) by the interaction between legume species and sampling time, with generally higher leaf CT content for mimosa than gliricidia, and both were reduced at the start of the dry season, although much more drastically for mimosa. The IVDOM was strongly affected by CT content and increased at the start of the dry season, coincidentally when C4 grass forage quality typically decreased. There is a marked species effect, with CT from gliricidia impacting IVDOM more than the same CT content from mimosa. While N concentration from mimosa also increased at the start of the dry season, that for gliricidia did not vary over the year. We conclude that although these arboreal legumes have relatively high CT contents, these reduce during the dry season when CT concentrations coinciding with a reduced forage quality as the protein content for C4 grasses is usually inadequate in this season.