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8 results for “Stordalen Mire”

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zenodo52/100

Summaries of temperature and water table depth prior to peat sampling in Stordalen Mire, 2011-2017

<div> This dataset provides summaries of temperature (T) and water table depth (WTD) conditions prior to the collection of peat samples from Stordalen Mire, Sweden, in July of 2011-2017. These summaries include the following files: <h2>t_wtd_summaries_July2011-2017samplings.csv</h2> </div> This file gives summary statistics over various time intervals for the following environmental measurements: <ul> <li>AirTemperature: Mean daily air temperature (°C), obtained from automatic sensors at the nearby Abisko Scientific Research Station (ANS) (station ID 188790; the source file [ANS_Daily_Wx_Jul84_Dec17.txt] is not included due to sharing restrictions).</li> <li>WTD: Water table depths (cm), obtained from <a href="https://doi.org/10.5281/zenodo.10420396">Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)</a> (from Patrick Crill et al.).</li> </ul> The time intervals for these summaries are defined relative to the peat sampling date at each site (see <a href="https://doi.org/10.5281/zenodo.12827096">EMERGE Sample Metadata Sheet for Samples with Microbiomes</a>), which varies by site and year. The specific intervals are defined as follows: <ul> <li>7d: 7 days prior to the sampling date, plus the sampling date itself.</li> <li>14d: 14 days prior to the sampling date, plus the sampling date itself.</li> <li>21d: 21 days prior to the sampling date, plus the sampling date itself.</li> <li>28d: 28 days prior to the sampling date, plus the sampling date itself.</li> <li>growing: Time from beginning of growing season (defined as June 1) until (and including) the sampling date.</li> <li>all_growing: Entire growing season (June 1 – Sept. 30).</li> </ul> For clarity, the start and end dates for each time interval (inclusive) are also given under the columns Start_Date and End_Date, where End_Date=Sampling_Date for all intervals except all_growing. Summary statistics for each interval include: measurement count (n), median (median), mean (mean), and standard deviation (sd), and are given under the column names beginning with these statistic labels. IMPORTANT NOTE:  For temperature, these statistics are calculated based on the average temperature measured on each day, meaning that the standard deviations do NOT account for within-day temperature variation. To provide short-term (1 day) temperature variation context for each sampling date, the within-day mean, minimum, and maximum air temperatures for the sampling date only (taken directly from the corresponding row & columns in the source ANS data file) are provided in the columns samplingdate_mean_AirTemperature, samplingdate_min_AirTemperature, and samplingdate_max_AirTemperature. <div> <div> <h2>wtd_summaries_July2011-2017samples.csv</h2> </div> This file gives the percentage of time that each peat sample's depth midpoint (DepthAvg__) was at or below the water table depth (WTD), over each of the longer time intervals (≥21 days) defined above for the temperature & WTD summaries. (Intervals <21 days are not included due to the lower frequency of WTD measurements, which results in low n for shorter intervals.) The first few columns are taken directly from the <a href="https://doi.org/10.5281/zenodo.12827096">EMERGE Sample Metadata Sheet for Samples with Microbiomes</a>, for the samples collected in July of 2011-2017 from the MainAutochamber sites. The last set of columns include the following, with the time interval labels (defined as in the above temperature summaries) appended at the end of each column name: <ul> <li>n_WTD_*: Number of WTD measurements used in the calculation.</li> <li>pct_time_below_WTD_*: Fraction (relative to 1) of measured WTDs over the given time interval that were at or above the DepthAvg__ for each sample, which equates to the fraction of measurement timepoints during which the given sample was at or below the WTD. This is the same method used for calculating "% Time below water table" in Figure 6 of <a href="https://doi.org/10.1038/s41396-018-0065-5">Singleton et al. (2018)</a>. For palsa sites, this value is automatically set to 0 based on the lack of a water table at all timepoints in the analysis.)</li> </ul> As above, the WTD values used for these calculations were obtained from <a href="https://doi.org/10.5281/zenodo.10420396">Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)</a> (Patrick Crill et al.). <h1>Funding acknowledgments</h1> This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. This research was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440. The temperature summary has been made possible by data provided by Abisko Scientific Research Station and the Swedish Infrastructure for Ecosystem Science (SITES). We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. </div>

opencc-by-4.0Nov 2024View details →

zenodo48/100

Autochamber CH4 Fluxes and δ13C Values at Stordalen Mire

Autochamber-based CH4 fluxes and δ13C values measured with a Tunable Infrared Laser Direct Absorption Spectrometer (TILDAS, Aerodyne Research Inc.); and ancillary data, including CO2 fluxes (measured with a LGR Greenhouse Gas Analyzer), temperatures, atmospheric pressure, and photosynthetically active radiation (PAR). In addition to the data published here, data from 2011 is also available in the supplementary files to <a href="https://doi.org/10.1038/nature13798">McCalley et al. (2014)</a> under the <a href="https://static-content.springer.com/esm/art%3A10.1038%2Fnature13798/MediaObjects/41586_2014_BFnature13798_MOESM61_ESM.xlsx">Source data to Fig. 1</a> link.   METHODS: Methane fluxes were measured using a system of 8 automatic gas-sampling chambers made of transparent Lexan (n=3 each in the palsa and bog habitats, and n=2 in the fen habitat). Chambers were initially installed in the three habitat types at Stordalen Mire in 2001 (Bäckstrand et al., 2008) and the chamber lids were replaced in 2011 with the current design, similar to that described by Bubier et al 2003. Chambers cover an area of 0.2 m2 (45 cm x 45 cm), with a height ranging from 15-75 cm depending on habitat vegetation. At the Palsa and bog site the chamber base is flush with the ground and the chamber lid (15 cm in height) lifts clear of the base between closures. At the fen site the chamber base is raised 50–60 cm on lexon skirts to accommodate large stature vegetation. The chambers are instrumented with thermocouples measuring air and surface ground temperature, and water table depth and thaw depth are measured manually 3–5 times per week. The chambers are connected to the gas analysis system, located in an adjacent temperature-controlled cabin, by 3/8” Dekoron tubing through which air is circulated at approximately 2.5 L min-1. Each chamber lid is closed once every 3 hours for a period of 8 min, with a 5 min flush period before and after lid closure. We measured methane concentration using a Tunable Infrared Laser Direct Absorption Spectrometers (TILDAS, Aerodyne Research Inc.) connected to the main chamber circulation using ¼” Dekoron tubing (McCalley et al 2014). Calibrations were done every 90 min using 3 calibration gases spanning the observed concentration range (1.8–10 ppm). For each autochamber closure we calculated flux using a method consistent with that detailed by Bäckstrand et al 2008 for CO2 and total hydrocarbons, using a linear regression of changing headspace CH4 concentration over a period of 2.5 min. Eight 2.5 min regressions were calculated, staggered by 15 sec, and the most linear fit (highest r2) was then used to calculate flux. Daily average flux for each chamber was used to calculate daily flux and standard error for each cover type. References: Bäckstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R. & Bastviken, D. Total hydrocarbon flux dynamics at a subarctic mire in northern Sweden. Journal of Geophysical Research 113, (2008). Bubier, J. L., Crill, P. M., Mosedale, A., Frolking, S. & Linder, E. Peatland responses to varying interannual moisture conditions as measured by automatic CO2 chambers. Global Biogeochemical Cycles 17, (2003). McCalley, C.K., B.J. Woodcroft, S.B. Hodgkins, R.A. Wehr, E-H. Kim, R. Mondav, P.M. Crill, J.P. Chanton, V.I. Rich, G.W. Tyson, S.R. Saleska (2014), Methane dynamics regulated by microbial community response to permafrost thaw, Nature, 514:478-481, doi:10.1038/nature13798.   FILES: Files are named with the year or date range, followed by a suffix indicating data resolution: <ul> <li>*_CH4output_clean_ckm.txt - Individual measurements of CH4 fluxes (CH4Flux), CO2 fluxes (CO2flux; for select years), and δ13C signature of emitted CH4 (Flux13CH4) for each chamber closure. CH4FluxRsq is the R2 value of the linear fit used to calculate CH4 flux, CO2Rsq is the R2 value of the linear fit used to calculate CO2 flux, and Flux13CH4_stdev is the standard deviation of the δ13C signature (standard deviation of the intercept of the Keeling plot).</li> <li>*_DailyCH4output_ckm.txt - Daily average CH4 fluxes (CH4Flux) and δ13C values (13CH4), grouped by site: Palsa, Bog, Fen, and Chamber 9 (bog/fen transition); along with standard deviations (stdev) and standard errors (se) of the flux or δ13C for each site type. For the Palsa, Bog, and Fen sites, these averages are calculated by chamber (n=3 for Palsa and Bog, n=2 for Fen), so each chamber's daily average is calculated, and then a daily average for that site is calculated as the average of the chambers. For Chamber 9 (bog/fen intermediate; n=1 chamber), averages are calculated by day as there are no chamber replicates.</li> </ul> MEASUREMENT UNITS (same for both file types): <ul> <li>CH4 flux: mg CH4 m−2 hr−1</li> <li>CO2 flux: mg C m−2 h−1</li> <li>δ13C: &permil;</li> <li>Temperature: °C</li> <li>Air pressure: mbar</li> <li>PAR: µmol photons m−2 s−1</li> </ul>   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440. Autochamber measurements between 2013 and 2017 were supported by a grant from the US National Science Foundation MacroSystems program (NSF EF 1241037, PI Varner).

opencc-by-4.0May 2023View details →

zenodo48/100

Metagenome-assembled genomes from Stordalen Mire, Sweden (MAGs v2)

This release (MAGs v2) is a major new version of this metagenome-assembled genome (MAG) set. All previous releases on this page (which only differ in the metadata) are designated "MAGs v1." The current release (MAGs v2) uses CheckM2 v1.0.2 filtering (≥70% completeness, ≤10% contamination) to expand this dataset to include 36,419 MAGs, with the following subcategories: <ul> <li>Cronin_v1:  Manually-curated subset of the "Field" category from MAGs v1.</li> <li>Cronin_v2:  MAGs from raw bin filtering on the same assemblies used to generate Cronin_v1.</li> <li>Woodcroft_v2:  MAGs from raw bin filtering on the same assemblies used to generate the MAGs reported in <a href="https://doi.org/10.1038/s41586-018-0338-1">Woodcroft & Singleton et al. (2018)</a>.</li> <li>SIPS:  Updated genomes from samples originating from a stable isotope probing (SIP) incubation experiment by Moira Hough et al. ("SIP" in MAGs v1), re-analyzed due to read truncation and sample linkage issues in MAGs v1.</li> <li>JGI:  Expanded set of genomes from the Joint Genome Institute's metagenome annotation pipeline.</li> </ul>   FILES: <ul> <li>Emerge_MAGs_v2.tar.gz - Archive containing the MAG files (.fna).</li> <li>metadata_MAGs_v2_EMERGE.tsv - Table containing source sample names and accessions, GTDB taxonomy information, CheckM2 quality reports, NCBI GenomeBatch- and MIMAG(6.0)-formatted sample attributes and other metadata for the MAGs. </li> </ul>   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute (<a href="https://emerge-bii.github.io">https://emerge-bii.github.io/</a>), funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632. DE-SC0010580. and DE-SC0016440. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. Data collected at the Joint Genome Institute was generated under the following awards: <ul> <li>The majority of sequencing at JGI was supported by BER Support Science Proposal 503530 (DOI: <a href="https://doi.org/10.46936/10.25585/60001148">10.46936/10.25585/60001148</a>), conducted by the U.S. Department of Energy Joint Genome Institute (<a href="https://ror.org/04xm1d337">https://ror.org/04xm1d337</a>), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.</li> <li>Sequencing of SIP samples was performed under the Facilities Integrating Collaborations for User Science (FICUS) initiative (proposal 503547; award DOI: <a href="https://doi.org/10.46936/fics.proj.2017.49950/60006215">10.46936/fics.proj.2017.49950/60006215</a>) and used resources at the DOE Joint Genome Institute (<a href="https://ror.org/04xm1d337">https://ror.org/04xm1d337</a>) and the Environmental Molecular Sciences Laboratory (<a href="https://ror.org/04rc0xn13">https://ror.org/04rc0xn13</a>), which are DOE Office of Science User Facilities. Both facilities are sponsored by the Office of Biological and Environmental Research and operated under Contract Nos. DE-AC02-05CH11231 (JGI) and DE-AC05-76RL01830 (EMSL).</li> </ul>

opencc-by-4.0Oct 2024View details →

zenodo48/100

Autochamber CH4 Fluxes at Stordalen Mire, 2014 (from LGR)

METHODS: Fluxes were measured using a system of 8 automatic gas-sampling chambers made of transparent Lexan (n=3 each in the palsa and bog habitats, and n=2 in the fen habitat). Chambers were initially installed in the three habitat types at Stordalen Mire in 2001 (Bäckstrand et al., 2008) and the chamber lids were replaced in 2011 with the current design, similar to that described by Bubier et al 2003. Chambers cover an area of 0.2 m2 (45 cm x 45 cm), with a height ranging from 15-75 cm depending on habitat vegetation. At the Palsa and bog site the chamber base is flush with the ground and the chamber lid (15 cm in height) lifts clear of the base between closures. At the fen site the chamber base is raised 50–60 cm on lexon skirts to accommodate large stature vegetation. The chambers are connected to the gas analysis system, located in an adjacent temperature-controlled cabin, by 3/8” Dekoron tubing through which air is circulated at approximately 2.5 L min-1. Each chamber lid is closed once every 3 hours for a period of 8 min, with a 5 min flush period before and after lid closure. Gas concentration in the chamber headspace was measured with a Los Gatos Research (LGR) Fast Greenhouse Gas Analyzer, with timing control and data acquisition using a Campbell CR10x (Holmes et al., 2022). References: Bäckstrand, K., Crill, P. M., Mastepanov, M., Christensen, T. R. & Bastviken, D. Total hydrocarbon flux dynamics at a subarctic mire in northern Sweden. Journal of Geophysical Research 113, (2008). Bubier, J. L., Crill, P. M., Mosedale, A., Frolking, S. & Linder, E. Peatland responses to varying interannual moisture conditions as measured by automatic CO2 chambers. Global Biogeochemical Cycles 17, (2003). <div> <div>Holmes, M. E., Crill, P. M., Burnett, W. C., McCalley, C. K., Wilson, R. M., Frolking, S., Chang, K. ‐Y., Riley, W. J., Varner, R. K., Hodgkins, S. B., IsoGenie Project Coordinators, IsoGenie Field Team, McNichol, A. P., Saleska, S. R., Rich, V. I., Chanton, J. P. (2022). Carbon accumulation, flux, and fate in Stordalen Mire, a permafrost peatland in transition. Global Biogeochemical Cycles, 36, e2021GB007113, doi:10.1029/2021GB007113.</div> </div> McCalley, C.K., B.J. Woodcroft, S.B. Hodgkins, R.A. Wehr, E-H. Kim, R. Mondav, P.M. Crill, J.P. Chanton, V.I. Rich, G.W. Tyson, S.R. Saleska (2014), Methane dynamics regulated by microbial community response to permafrost thaw, Nature, 514:478-481, doi:10.1038/nature13798.   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440. These autochamber measurements were also supported by a grant from the US National Science Foundation MacroSystems program (NSF EF 1241037, PI Varner).

opencc-by-4.0Nov 2024View details →

zenodo44/100

Metagenome-assembled genomes from Stordalen Mire, Sweden (2019) (MAGs from long-read, short-read, & hybrid assemblies)

METHODS: Soil samples (6 total) were collected at the Stordalen Mire site in 2019 from two depths (1-5 & 20-24 cm below ground) across three habitats (Palsa, Bog, and Fen). DNA was extracted based on the protocol described by <a href="http://dx.doi.org/10.17504/protocols.io.yxmvm244bg3p/v1">Li et al. (2024)</a>. For short reads, libraries were prepared at the Joint Genome Institute (JGI) with the KAPA Hyperprep kit, and sequenced with Illumina NovaSeq 6000. For long reads, libraries were prepared with the SMRTbell Express Template Prep Kit 2.0 (PacBio), then sequenced using PacBio Sequel IIe at JGI. PacBio data was processed at JGI to form filtered CCS (Circular Consensus Sequencing) reads.  Assemblies were generated with short-only, long-only, and hybrid read sources: Short-only was assembled with <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411777/">metaSPAdes</a> (v3.15.4) using <a href="https://zenodo.org/records/10806928">Aviary</a> (v0.5.3) with default parameters. Long-only was assembled with <a href="https://www.nature.com/articles/s41592-020-00971-x">metaFlye</a> (v2.9-b1768) using <a href="https://zenodo.org/records/10806928">Aviary</a> (v0.5.3) with default parameters. Hybrid assembly was performed using <a href="https://zenodo.org/records/10806928">Aviary</a> v0.5.3 with default parameters. This involved a step-down procedure with long-read assembly through <a href="https://www.nature.com/articles/s41592-020-00971-x">metaFlye</a> (v2.9-b1768), followed by short-read polishing by <a href="https://genome.cshlp.org/content/27/5/737">Racon</a> (v1.4.3), <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112963">Pilon</a> (v1.24) and then Racon again. Next, reads that didn't map to high-quality metaFlye contigs were hybrid assembled with <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411777/">SPAdes (--meta option)</a> and binned out with <a href="https://peerj.com/articles/7359/">MetaBAT2</a> (v2.1.5). For each bin, the reads within the bin were hybrid assembled using <a href="https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005595">Unicycler</a> (v0.4.8). The high-coverage metaFlye contigs and Unicycler contigs were then combined to form the assembly fasta file. Genome recovery was performed using <a href="https://zenodo.org/records/10806928">Aviary</a> v0.5.3 with samples chosen for differential abundance binning by <a href="https://zenodo.org/records/10939393">Bin Chicken</a> (v0.4.2) using <a href="https://zenodo.org/records/7130825">SingleM metapackage S3.0.5</a>. This involved initial read mapping through <a href="https://zenodo.org/records/10531254">CoverM</a> (v0.6.1) using <a href="https://academic.oup.com/bioinformatics/article/34/18/3094/4994778">minimap2</a> (v2.18) and binning by <a href="https://peerj.com/articles/1165/">MetaBAT</a>, <a href="https://peerj.com/articles/7359/">MetaBAT2</a> (v2.1.5), <a href="https://www.nature.com/articles/s41587-020-00777-4">VAMB</a> (v3.0.2), <a href="http://doi.org/10.1038/s41467-022-29843-y">SemiBin</a> (v1.3.1), <a href="https://zenodo.org/records/10460259">Rosella</a> (v0.4.2), <a href="https://www.nature.com/articles/nmeth.3103">CONCOCT</a> (v1.1.0) and <a href="https://academic.oup.com/bioinformatics/article/32/4/605/1744462">MaxBin2</a> (v2.2.7). Genomes were analyzed using <a href="https://www.nature.com/articles/s41592-023-01940-w">CheckM2</a> (v1.0.2) and clustered at 95% ANI using <a href="https://zenodo.org/records/10526086">Galah</a> (v0.4.0).   FILES: <ul> <li>EMERGE_MAGs_2019_long-short-hybrid.tar.gz - Archive containing the MAG files (.fna).</li> <li>metadata_MAGs_2019_EMERGE.tsv - Table containing source sample names and accessions, GTDB classifications, CheckM2 quality information, NCBI GenomeBatch- and MIMAG(6.0)-formatted attributes, and other metadata for the MAGs.</li> </ul>   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute (<a href="https://emerge-bii.github.io/">https://emerge-bii.github.io/</a>), funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632. DE-SC0010580. and DE-SC0016440. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. Data from the Joint Genome Institute (JGI) was collected under BER Support Science Proposal 503530 (DOI: <a href="https://doi.org/10.46936/10.25585/60001148">10.46936/10.25585/60001148</a>), conducted by the U.S. Department of Energy Joint Genome Institute (<a href="https://ror.org/04xm1d337">https://ror.org/04xm1d337</a>), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

opencc-by-4.0Nov 2024View details →

zenodo44/100

Virus operational taxonomic units (vOTUs) from Stordalen Mire, Sweden

This file is a collection of 5,051 virus operational taxonomy units (vOTUs) that were identified from samples collected from Stordalen Mire, a long-term ecological research site in Abisko, Sweden. Peat soil was sampled from the active layer across 3 different thaw stages (palsa, bog, and fen) between 2010-2017. From 379 bulk metagenomes, virus sequences were identified in silico using VirSorter1 (with additional stringent filtering criteria). Virus sequences above 5kb in length were then clustered into vOTUs (using a threshold of 95% identity and 80% coverage). This vOTU dataset is the basis of a research paper, entitled 'Virus ecology and 7-year temporal dynamics across a permafrost thaw gradient,' (Sun and Pratama, et al., in prep.), which provides insights into permafrost viruses and their role in terrestrial carbon cycling.   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute (<a href="https://emerge-bii.github.io">https://emerge-bii.github.io/</a>), funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632. DE-SC0010580. and DE-SC0016440. A portion of this research was performed under the Facilities Integrating Collaborations for User Science (FICUS) program (proposal: 10.46936/10.25585/60001148) and used resources at the DOE Joint Genome Institute (<a href="https://www.google.com/url?q=https://ror.org/04xm1d337&sa=D&source=docs&ust=1674859614742521&usg=AOvVaw2XgXYw9eI4JIXRMKn3S9Se">https://ror.org/04xm1d337</a>) and the Environmental Molecular Sciences Laboratory (<a href="https://www.google.com/url?q=https://ror.org/04rc0xn13&sa=D&source=docs&ust=1674859614742655&usg=AOvVaw3UXdoHIFmVjc-mXUhDXYQt">https://ror.org/04rc0xn13</a>), which are DOE Office of Science User Facilities operated under Contract Nos. DE-AC02-05CH11231 (JGI) and DE-AC05-76RL01830 (EMSL).

opencc-by-4.0Oct 2023View details →

zenodo40/100

Manual active layer and and water table depth measurements from the autochamber sites at Stordalen Mire, northern Sweden (2003-2017)

Files: <ul> <li>Active_Layer_Water_Table_03-17.xlsx - Data file, with main data in the "DATA" tab.</li> <li>IsoGenieSite_AL_WTD_MapsVisualNotes_200310.pdf - Visual notes on the measurement locations.</li> </ul> The following site labels (with chamber numbers in parentheses) correspond to the main autochamber sites: <ul> <li>Dry (1,3,5) = Palsa Autochamber Site</li> <li>Mesic (2,4,6) = Sphagnum Autochamber Site</li> <li>Wet (7,8) = Eriophorum Autochamber Site</li> </ul> Water table depth (W D) was measured in wells. Active layer depth (A L) was measured by inserting a metal rod into the surface. The original instruction page is included in page 3 of the pdf. All depths are in centimeters (cm) below peat surface (i.e. peat or Sphagnum spp. vegetation surface = 0), with negative values indicating depth below the surface and positive values (for water table) indicating height of standing water above the surface. Blank data in the Palsa or water table column means no water table observed. Staff gauge was added July 2006 at the edge of a small pond in the fen visible from the shack, with measurements reported in meters. All other measures are in cm.   FUNDING: We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. This research is a contribution of the EMERGE Biology Integration Institute, funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. The IsoGenie Project (which funded much of the work at these sites during the measurement period) was funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632, DE-SC0010580, and DE-SC0016440.

opencc-by-4.0Dec 2023View details →

zenodo36/100

Stordalen Mire July 2016 Metatranscriptome Data from McGivern et al.

Tabs MetaT = information for the 27 metatranscriptomes metaT_genes = gene level mapping data metaT_MAGs = MAG level mapping data   FUNDING: This research is a contribution of the EMERGE Biology Integration Institute ((https://emerge-bii.github.io/), funded by the National Science Foundation, Biology Integration Institutes Program, Award # 2022070. We thank the Swedish Polar Research Secretariat and SITES for the support of the work done at the Abisko Scientific Research Station. SITES is supported by the Swedish Research Council's grant 4.3-2021-00164. This study was also funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research, grant #s DE-SC0004632. DE-SC0010580. and DE-SC0016440. A portion of this research was performed under the Facilities Integrating Collaborations for User Science (FICUS) program (proposal: 10.46936/fics.proj.2017.49950/60006215 and 10.46936/10.25585/60001148) and used resources at the DOE Joint Genome Institute (<a href="https://www.google.com/url?q=https://ror.org/04xm1d337&sa=D&source=docs&ust=1674859614742521&usg=AOvVaw2XgXYw9eI4JIXRMKn3S9Se">https://ror.org/04xm1d337</a>) and the Environmental Molecular Sciences Laboratory (<a href="https://www.google.com/url?q=https://ror.org/04rc0xn13&sa=D&source=docs&ust=1674859614742655&usg=AOvVaw3UXdoHIFmVjc-mXUhDXYQt">https://ror.org/04rc0xn13</a>), which are DOE Office of Science User Facilities operated under Contract Nos. DE-AC02-05CH11231 (JGI) and DE-AC05-76RL01830 (EMSL).

opencc-by-4.0Jan 2023View details →

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