Soil microbial diversity is huge and a few grams of soil contain more bacterial taxa than there are bird species on Earth. This high diversity often makes predicting the responses of soil bacteria to environmental change intractable and restricts our capacity to predict the responses of soil functions to global change. Here, using a long-term field experiment in a California grassland, we studied the main and interactive effects of three global change factors (increased atmospheric CO2 concentration, precipitation and nitrogen addition, and all their factorial combinations, based on global change scenarios for central California) on the potential activity, abundance and dominant taxa of soil nitrite-oxidizing bacteria (NOB). Using a trait-based model, we then tested whether categorizing NOB into a few functional groups unified by physiological traits enables understanding and predicting how soil NOB respond to global environmental change. Contrasted responses to global change treatments were observed between three main NOB functional types. In particular, putatively mixotrophic Nitrobacter, rare under most treatments, became dominant under the 'High CO2+Nitrogen+Precipitation' treatment. The mechanistic trait-based model, which simulated ecological niches of NOB types consistent with previous ecophysiological reports, helped predicting the observed effects of global change on NOB and elucidating the underlying biotic and abiotic controls. Our results are a starting point for representing the overwhelming diversity of soil bacteria by a few functional types that can be incorporated into models of terrestrial ecosystems and biogeochemical processes.
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http://dx.doi.org/10.3389/fmicb.2016.00628 | DOI Listing |
Sci Rep
December 2024
Merchant Marine College, Shanghai Maritime University, Shanghai, 201306, China.
The intelligent identification of wear particles in ferrography is a critical bottleneck that hampers the development and widespread adoption of ferrography technology. To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. The proposed TCBGY-Net uses YOLOv5s as the backbone network, which is enhanced with several advanced modules to improve detection performance.
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December 2024
Weather Program Office, Ocean and Atmospheric Research, NOAA, Silver Spring, MD, USA.
Tropical cyclone risks are expected to increase with climate change. One such risk is extreme ocean waves generated by surface winds from these systems. We use synthetic databases of both historical (1980-2017) and future (2015-2050) tropical cyclone tracks to generate wind fields and force a computationally efficient wave model to estimate significant wave heights across all global tropical cyclone basins.
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December 2024
Department of Drug Prohibition and Public Security, Criminal Investigation Police University of China, Shenyang, 110035, China.
Methamphetamine use disorder has emerged as a significant public health concern globally. This study endeavors to elucidate the alterations in expression changes of miRNAs in the plasma of methamphetamine use disorder and elucidate the alterations in miRNA expression in the plasma of individuals with methamphetamine use disorder and investigate the relationship between these differentially expressed miRNAs and the disorder itself, cravings for methamphetamine, and associated mental disorders. Furthermore, the study seeks to clarify the expression of downstream target molecules of specific miRNAs in the plasma of methamphetamine use disorder, assess the diagnostic utility of these miRNAs and their target molecules, explore their potential as biomarkers, and identify potential targets for the diagnosis and treatment of methamphetamine use disorder.
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December 2024
State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Polychlorinated naphthalenes (PCNs) are persistent organic compounds that are regulated by the Stockholm Convention. Here, we estimate historical emissions from PCN production and use (1912-1987) and unintentional emissions from 20 categories (2000-2020). A random forest regression model projects emissions for 2020-2050.
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December 2024
Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
Record breaking atmospheric methane growth rates were observed in 2020 and 2021 (15.2±0.5 and 17.
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