The aim of the study was the analysis of the occurrence of specific antibodies against HEV among hunters and foresters who are at risk to be exposed. The study group consisted of 210 hunters (23-80 years old) and 60 foresters (22-64 years old). Anti-HEV IgG were present in 3.81% of the samples of the hunters and in 5% of the samples of the foresters. The statistical analysis shows no significant differences in the results anti-HEV IgG between the groups of hunters and foresters (p = 0.5278). Significantly higher anti-HEV IgG titers were found in the older age group (> 55 years old).
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http://dx.doi.org/10.5604/01.3001.0010.7882 | DOI Listing |
J Environ Manage
January 2025
71 Smith Ave., Bureau of Water Supply, New York City Department of Environmental Protection, Kingston, NY, 12401, USA.
The paired watershed monitoring approach is widely used to investigate hydrologic processes and water quality, providing streamflow and water quality records for long-term trend analysis, as well as data for developing and testing hydrologic models. In this study we use 20 years of streamflow and water quality data, along with a watershed model, to examine sources of stream nutrients and their changes over time in two small streams within the New York City water supply system. We compare sources and trends in stream nitrate and dissolved phosphorus in the urbanized Amawalk watershed with those of the predominantly forested Boyd Corners watershed in the Croton system of reservoirs.
View Article and Find Full Text PDFNat Ecol Evol
January 2025
Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, UK.
Rapid growth in bio-logging-the use of animal-borne electronic tags to document the movements, behaviour, physiology and environments of wildlife-offers opportunities to mitigate biodiversity threats and expand digital natural history archives. Here we present a vision to achieve such benefits by accounting for the heterogeneity inherent to bio-logging data and the concerns of those who collect and use them. First, we can enable data integration through standard vocabularies, transfer protocols and aggregation protocols, and drive their wide adoption.
View Article and Find Full Text PDFNat Commun
December 2024
Anthropology Department, University of California Santa Cruz, Santa Cruz, CA, USA.
Strontium isotope (Sr/Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving Sr/Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the Sr/Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression.
View Article and Find Full Text PDFEcology
December 2024
Wildlife Research and Monitoring Section, Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada.
Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission-fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals.
View Article and Find Full Text PDFSci Data
December 2024
Land & Carbon Lab, World Resources Institute, Washington, DC, USA.
The paper describes the production and evaluation of global grassland extent mapped annually for 2000-2022 at 30 m spatial resolution. The dataset showing the spatiotemporal distribution of cultivated and natural/semi-natural grassland classes was produced by using GLAD Landsat ARD-2 image archive, accompanied by climatic, landform and proximity covariates, spatiotemporal machine learning (per-class Random Forest) and over 2.3 M reference samples (visually interpreted in Very High Resolution imagery).
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