The eutrophic Bohai Sea receives large amount of suspended material, nutrients and contaminant from terrestrial runoff, and exchanges waters with the northern Yellow Sea through a narrow strait. This coastal region provides an ideal model system to study microbial biogeography. We performed high-throughput sequencing to investigate the distribution of bacterial taxa along spatial and environmental gradients. The results showed bacterial communities presented remarkable horizontal and vertical distribution under coastal gradients of spatial and environmental factors. Fourteen abundant taxa clustered the samples into three distinctive groups, reflecting typical habitats in shallow coastal water (seafloor depth ≤ 20 m), sunlit surface layer (at water surface with seafloor depth >20 m) and bottom water (at 2-3 m above sediment with seafloor depth >20 m). The most significant taxa of each cluster were determined by the least discriminant analysis effect size, and strongly correlated with spatial and environmental variables. Environmental factors (especially turbidity and nitrite) exhibited significant influences on bacterial beta-diversity in surface water (at 0 m sampling depth), while community similarity in bottom water (at 2-3 m above sediment) was mainly determined by depth. In both surface and bottom water, we found bacterial community similarity and the number of OTUs shared between every two sites decreased with increasing geographic distance. Bacterial dispersal was also affected by phosphate, which was possible due to the high ratios of IN/IP in this coastal sea area.
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http://dx.doi.org/10.7717/peerj.4272 | DOI Listing |
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December 2024
College of Economics and Management, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including the management of agricultural carbon reduction, emerging as a mainstream approach. This study examines 268 prefecture-level cities in China, measuring the carbon emission efficiency of city agriculture from 2001 to 2022. By integrating social network analysis and a modified gravity model, the study reveals the characteristics of the spatial association network of city agricultural carbon emission efficiency in China.
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December 2024
Department of Biology, University of South Dakota, 414 East Clark Street, Vermillion, SD, 57069-2390, USA.
Psychological distress, including anxiety or mood disorders, emanates from the onset of chronic/unpredictable stressful events. Symptoms in the form of maladaptive behaviors are learned and difficult to treat. While the origin of stress-induced disorders seems to be where learning and stress intersect, this relationship and molecular pathways involved remain largely unresolved.
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December 2024
British Antarctic Survey, High Cross, Madingley Road, Cambridge, UK.
Marine microplastic is pervasive, polluting the remotest ecosystems including the Southern Ocean. Since this region is already undergoing climatic changes, the additional stress of microplastic pollution on the ecosystem should not be considered in isolation. We identify potential hotspot areas of ecological impact from a spatial overlap analysis of multiple data sets to understand where marine biota are likely to interact with local microplastic emissions (from ship traffic and human populations associated with scientific research and tourism).
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December 2024
Kombolcha Institute of Technology, Wollo University, Dessie, Ethiopia.
Alcohol-based fuels have shown high compatibility with spark-ignition (SI) engines, which require improvements in fuel efficiency and emissions reduction to meet modern environmental standards. While extensive research has been conducted on ethanol and other lower-order alcohols, there has been comparatively limited investigation into higher-order alcohols like butanol and pentanol as fuel alternatives. Previous studies on pentanol-gasoline blends in SI engines have demonstrated improved engine performance and reduced emissions.
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December 2024
Department of Computing and Information Systems, Sunway University, 47500, Petaling Jaya, Selangor Darul Ehsan, Malaysia.
Urban mobility prediction is crucial for optimizing resource allocation, managing transportation systems, and planning urban development. We propose a novel framework, GeoTemporal LSTM (GT-LSTM), designed to address the intricate spatiotemporal dynamics of urban environments. GT-LSTM integrates temporal dependencies with geographic information through a multi-modal approach that combines attention mechanisms and Recurrent Neural Networks (RNNs).
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