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36 results for “bacterial ecosystem”
October 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in October, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
November 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in November, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
March 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in March, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
September 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites
Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in September, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.
Baltimore Ecosystem Study: Stream biofilm bacterial community composition
The Baltimore Ecosystem Study stream biofilm bacterial community composition was obtained from 8 long-term sampling network sites in and near the Gwynns Falls watershed to examine how bacterial communities differ along an urban-rural gradient. Sampling was conducted at the same time as stream chemistry sampling on 18 June 2014 and 21 Oct 2014. Note: biofilm samples were taken about 50 meters east from the Carroll Park monitoring station, just under the I95 highway overpass, due to high water depth, high water flow, and lack of rock substrates for sampling. This dataset presents the number of sequences matching the taxonomic classifications in a reference database of 16S rRNA genes. See the full metadata record for detailed methods.
Fig. 2 in A report of 30 unrecorded bacterial species in Korea, isolated from marine ecosystems in 2021
Fig. 2. Neighbor-joining phylogenetic tree based on 16S rRNA gene sequences showing the relationship between the strains isolated in this study and their closest bacterial species in classes Alphaproteobacteria, Bacilli, Cytophagia, Flavobacteriia, Fusobacteriia, and Clostridia. Bootstrap values over 70% are shown.
Fig. 1 in A report of 30 unrecorded bacterial species in Korea, isolated from marine ecosystems in 2021
Fig. 1. Neighbor-joining phylogenetic tree based on 16S rRNA gene sequences showing the relationship between the strains isolated in this study and their closest bacterial species in the class Gammaproteobacteria. Bootstrap values over 70% are shown.
Fig. 3 in A report of 30 unrecorded bacterial species in Korea, isolated from marine ecosystems in 2021
Fig. 3. Transmission electron micrographs of scanning electron micrographs of cells of the strain isolated in this study. Strains: 1, HNI- BRBA38; 2, HNIBRBA54; 3, HNIBRBA100; 4, HNIBRBA151; 5, HNIBRBA189; 6, HNIBRBA220; 7, HNIBRBA244; 8, HNIBRBA255; 9, HNIBRBA270; 10, HNIBRBA272; 11, HNIBRBA274; 12, HNIBRBA350; 13, HNIBRBA370; 14, HNIBRBA397; 15, HNIBRBA406; 16, HNIBRBA489; 17, HNIBRBA506; 18, HNIBRBA601; 19, HNIBRBA666; 20, HNIBRBA682; 21, HNIBRBA683; 22, HNIBRBA684; 23, HNIBRBA685; 24, HNIBRBA688; 25, HNIBRBA773; 26, HNIBRBA833; 27, HNIBRBA853; 28, HNIBRBA855; 29, HNIBRBA866; 30, HNIBRBA1036. Scale bars are indicated in parenthesis after strain ID.
Seagrass ecosystems reduce exposure to bacterial pathogens of humans, fishes and invertebrates
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Machine learning reveals a taxonomy of bacterial sensors in Earth ecosystems
<p>Datasets and FASTA files used for the manuscript titled: "Machine learning reveals a taxonomy of bacterial sensors in Earth ecosystems." Description.ipynb contains descriptions and first 5 lines of each file.</p>
Dataset of manuscript "Divergent responses of soil bacterial and fungal communities to climate warming in an alpine tundra ecosystem"
<p>Our study conducts a translocation experiment in the alpine tundra of the Changbai Mountains to explore how climate warming will affect soil bacterial and fungal communities in the alpine tundra and what are the underlying ecological mechanisms for their potential community changes. Soil samples (n = 24) were respectively collected during the early growing season (June 5, EGS), peak growing season (July 30, PGS), and late growing season (September 20, LGS) of 2021. The uploaded data contains the soil properties and OTU abundance measurements for these soil samples, as well as air and soil temperature from June 1, 2020 to September 15, 2021. </p>
Data from: Ecosystem productivity is associated to bacterial phylogenetic distance in surface marine waters
Understanding the link between community diversity and ecosystem function is a fundamental aspect of ecology. Systematic losses in biodiversity are widely acknowledged but the impact this may exert on ecosystem functioning remains ambiguous. There is growing evidence of a positive relationship between species richness and ecosystem productivity for terrestrial macroorganisms, but similar links for marine microorganisms, which help drive global climate, are unclear. Community manipulation experiments show both positive and negative relationships for microbes. These previous studies rely, however, on artificial communities and any links between the full diversity of active bacterial communities in the environment, their phylogenetic relatedness, and ecosystem function remains hitherto unexplored. Here we test the hypothesis that productivity is associated to diversity in the metabolically active fraction of microbial communities. We show in natural assemblages of active bacteria that communities containing more distantly related members were associated with higher bacterial production. The positive phylogenetic diversity–productivity relationship was independent of community diversity calculated as the Shannon index. From our long-term (7-year) survey of surface marine bacterial communities we also found that similarly productive communities had greater phylogenetic similarity to each other, further suggesting that the traits of active bacteria are an important predictor of ecosystem productivity. Our findings demonstrate that the evolutionary history of the active fraction of a microbial community is critical for understanding their role in ecosystem functioning.
Supplementary material 1 from: Sogawa S, Tsuchiya K, Nagai S, Shimode S, Kuwahara VS (2022) Annual dynamics of eukaryotic and bacterial communities revealed by 18S and 16S rRNA metabarcoding in the coastal ecosystem of Sagami Bay, Japan. Metabarcoding and Metagenomics 6: e78181. https://doi.org/10.3897/mbmg.6.78181
Figures S1–S8
Fig. 1 in Review paper The Role of Bacterial-based Protist Communities in Aquatic and Soil Ecosystems and the Carbon Biogeochemical Cycle, with Emphasis on Naked Amoebae
Fig. 1. Protocol for respiration and microbial biomass experiments. Respiration was measured with an infrared CO gas analyzer, glu2 cose (444 µg/g soil) in solution was added as a supplement. Microbial assays for naked amoebae used a culture observation method (COM) for living amoebae routinely employed in our laboratory (e.g. Anderson 2000), glutaraldehyde-fixed portions of the soil sample were examined microscopically for bacteria and heterotrophic nanoflagellates using a fluorescent staining technique (Anderson et al. 2001). For experiments of one-week duration, sampling was done on Days 1, 4, and 8. For two-week duration experiments, sampling was done on Days 1, 8, and 15.
Data from: Ecosystem productivity is associated to bacterial phylogenetic distance in surface marine waters
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Development and evaluation of a 60-mer oligonucleotide microarray for profiling of biodegradation and bacterial 16S rRNA genes in diverse contaminated ecosystems
GEO Series GSE24353. Escherichia coli BL21; freshwater sediment metagenome; Rhodococcus jostii RHA1; Bordetella sp. IITR-02; Escherichia coli K-12; Sphingomonas sp. NM05; soil metagenome; synthetic construct; Escherichia coli DH5[alpha]. 17 samples. Type: Genome variation profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.