Showing 151 - 165 of 166

This data set provides the peat microbial biomass carbon (MBC) and nitrogen (MBN), extractable organic carbon (EOC) and extractable nitrogen (EN) at the time of peat coring for Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2014-2017 from the Spruce and Peatland Responses Under...

This data set provides the ingrowth peat microbial biomass carbon (MBC) and nitrogen (MBN), extractable organic carbon (EOC) and extractable nitrogen (EN) for Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatland Responses Under Changing Environments...

This data set provides the ingrowth peat extracellular enzyme potential (EE) for before and during Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatlands Under Changing Environments (SPRUCE). EE potential was quantified and calculated following a...

This data set provides ITS fungal community composition via DNA and cDNA sequence analysis at the time of peat coring for Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2014-2017 from the Spruce and Peatlands Under Changing Environments (SPRUCE). Samples were extracted using a Qiagen...

This data set provides the ITS fungal community composition via DNA and cDNA sequence analysis for peat and sand ingrowth cores collected before and during Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatlands Under Changing Environments (SPRUCE)...

This data set provides the 16S microbial community composition via DNA sequence analysis at the time of peat coring at the South End bog in 2013. These samples were collected outside the experimental enclosures and are pre-treatment with no experimental manipulation. These are part of the Spruce and...

Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. Model Soil Consortium 2 (MSC-2) Bacterial Isolate Genomes. [Data Set] PNNL DataHub. https://doi.org/10.25584/PNNLDH/1986536 Model Soil Consortium 2 (MSC-2) Bacterial Isolate Genomes...

Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. 16s data from MSC-2 growth. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33231 16s data from MSC-2 growth 3 fastq of 16s amplicon data of MSC2 1 csv file of raw...

Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. Metatranscriptomic data from MSC-2. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33232 Metatranscriptomic data from MSC-2 12 fastq files (6 forward read, 6 reverse...

Last updated on 2023-05-31T16:35:53+00:00 by LN Anderson PerCon SFA: Sequencing of Sorgoleone Promoting Rhizobacteria Isolates Whole genome sequencing (WGS) of sorgoleone utilizing rhizobacteria strains Pseudomonas sorgoleonovorans SO81 , Burkholderia anthina SO82 , and Acinetobacter pittii SO1 , as...

Last updated on 2023-03-21T18:35:22+00:00 by LN Anderson SAGE-RTP RT-PCR Amplicon Sequencing Barcode Count Analysis Promoter expression data for five bacterial species associated with the Serine recombinase Assisted Genome Engineering (SAGE) research project. Raw Measurement Data NCBI BioProject...

Last updated on 2024-04-19T19:12:08+00:00 by LN Anderson PerCon SFA: Profiling sorghum-microbe interactions with a specialized photoaffinity probe identifies key sorgoleone binders in Acinetobacter pitti Mass spectrometry-based global proteome analysis and SoDA-PAL photoaffinity probe labeled...

This dataset presents land surface parameters designed explicitly for global kilometer-scale Earth system modeling and has significant implications for enhancing our understanding of water, carbon, and energy cycles in the context of global change. Specifically, it includes four categories of...

Extreme weather events, including fires, heatwaves(HWs), and droughts, have significant impacts on earth, environmental, and power energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning...

Please cite as : Wu R., A.E. Zimmerman, and K.S. Hofmockel. 2023. RNA viruses in grassland soils (Prosser, WA). [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33706 The data is comprised of RNA viral sequences that were bioinformatically screened from the de novo assemblies of...