Datasource Groups
A list of datafiles from the EMERGE and IsoGenie projects that can be downloaded directly, organized thematically. If you use this data in your research, please cite the accompanying manuscript(s) and contact the contributing PI.
Each dataset may have multiple versions and/or quality levels available. The most easily accessible files listed on this page should be the latest versions, but older versions (if applicable) can also be downloaded under "Old version(s)".
Expand the panels below for detailed descriptions of our version and quality level systems.
Data versioning is distinct from quality levels; it refers to the version of a dataset. As the data files are updated and published on the Data Downloads page, the database team (Ben Bolduc & Suzanne Hodgkins) assigns version numbers as "x.y.z" (0.0.0, 1.0.1, 2.0.0, etc.), starting from 0.0.0, with the following numbering convention:
- The first two numbers (x & y) indicate the version number of the contributed files
submitted
to the database by the contact/contributor:
- "x" denotes major revisions, e.g. reflecting different quality levels)
- "y" denotes minor revisions, e.g. reflecting minor adjustments to headers, minor error corrections, etc.
- The third number (z) indicates the format-standardized versions of
the contributed files, generated by the database team. These standard-format
code-readable files are an essential step of loading the data into the
graph database, and are also useful to project team members who code (and
e.g. want metadata in a standardized format for import into R).
There are three main steps to this format-standardization. These steps are given specific names, defined below, which are used in the download links to indicate the degree and type of processing applied to the contributed (i.e. original) file:- corrected (if applicable): Corrections to the data itself, based on careful communication with the original data generator(s), but actually edited and saved by the database team.
- formatted: Formatting changes to simplify the original (or corrected) files. These include things like removal of merged cells and conversion of color-coded shading to text columns.
- standardized: Formatted text files with additional columns added (ending in __), which contain metadata in the database's standardized naming convention for Sites, Habitats, etc.
In addition to versions, the data should also be assigned quality levels. As this requires intimate knowledge of the dataset and its respective discipline, we request that project members specify each data file’s quality level during submission to the EMERGE-DB.
In a nutshell, the quality numbers indicate the level of confidence that the data reflects "reality". Note that unlike version numbers, the quality level of a given dataset may be changed retroactively. For example, a Quality 1 dataset may be downgraded to Quality 0 if errors are discovered late in the processing pipeline, or upgraded to Quality 2 after passing peer-review. The basic definitions of the three quality levels are as follows:
- Quality 0: Unprocessed, raw data.
- Quality 1: An internally-consistent dataset with basic processing, such as calibrations, background corrections, and quality control.
- Quality 2: An externally-consistent dataset that is highly curated, in addition to undergoing the processing necessary for Quality 1. This should include all datasets that are part of peer-reviewed publications. DOIs are assigned to datasets in the Quality 2 category. The public side of the database will house mostly Quality Level 2 data.
Use the buttons below to jump to specific dataset categories. You can also search for datasets by title and identifiers, or use the checkboxes to filter by Metadata node labels (these checkboxes use "or" logic).
Coring Sheets
Image credit: Virginia Rich
0000_Coring20102011 |
Field Sampling/Coring Sheet (2010-2011) |
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0001_Coring2012 |
Field Sampling/Coring Sheet (2012) |
0046_Coring2018 |
Field Sampling/Coring Sheet (2018) |
0047_Coring2019 |
Field Sampling/Coring Sheet (2019) |
0036_Coring2017 |
Field Sampling/Coring Sheet (2017) |
0037_Coring2015 |
Field Sampling/Coring Sheet (2015) |
0004_Coring2016 |
Field Sampling/Coring Sheet (2016) |
0002_Coring2013 |
Field Sampling/Coring Sheet (2013) |
0003_Coring2014 |
Field Sampling/Coring Sheet (2014) |
0137_Coring2020 |
Field Sampling/Coring Sheet (2020) |
0139_Coring2021 |
Field Sampling/Coring Sheet (2021) |
0152_Coring2022 |
Field Sampling/Coring Sheet (2022) |
0160_Coring2023 |
Field Sampling/Coring Sheet (2023) |
Terrestrial Biogeochemistry
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbUlEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--0c987178ab6bc285d8a5ff15b3b11b921749b710/IMG_1548.jpeg)
Image credit: Claire Wilson
0007_GeochemPoregas20102012 |
Pore gas geochemistry 2010-2012 |
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0008_ErrorsGeochemSolid20102012 |
Standard errors: Peat geochemistry 2010-2012 |
0009_ErrorsGeochemPorewater20102012 |
Standard errors: Pore water geochemistry 2010-2012 |
0010_ErrorsGeochemPoregas20102012 |
Standard errors: Pore gas geochemistry 2010-2012 |
0005_GeochemSolid20102012 |
Peat geochemistry 2010-2012 |
0006_GeochemPorewater20102012 |
Pore water geochemistry 2010-2012 |
0067_CH4Oxidation_ChemicalConcentrations_transects |
Methane oxidation data from Malhotra and Roulet (2015) transects, including incubation-derived oxidation rates, and in situ pH, Eh, and concentrations of dissolved CH4 and electron acceptors (O2, SO4, NO3, Mn, & Fe) |
0068_CH4Oxidation_AdditionalExperiments |
Methane oxidation data from Malhotra and Roulet (2015) transects, additional experiments |
0070_210Pb_14C_2011-2014_2016 |
210Pb, 14C, and bulk density for cores and porewater collected in 2011-2014 and 2016 |
0071_IncubationJuly2014peat |
Incubation CH4 and CO2 production and δ13C for peat collected in July 2014 |
0087_incubations-vs-field_geochem |
Comparison of microbial processes in anaerobic incubations and field samples: Geochemical data, including greenhouse gases (CO2/CH4 production and δ13C) and organic matter chemistry (FTIR, FT-ICR MS, UV/Vis, and EEMS) |
0140_Wilson-etal-2022-STOTEN_FTIR-peat-plants |
Area-normalized FT-IR absorbances for the peat and plant species across the three main habitat types (palsa, bog, fen) |
0142_Wilson-etal-2022-STOTEN_ICR-peat-porewater |
Log-transformed FT-ICR MS peak intensities for the dissolved organic matter and the extracts of solid peat across the three main habitat types (palsa, bog, fen) |
0144_Wilson-etal-2022-STOTEN_DOC-TON |
Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) in the porewater from the fen (E) and bog (S) sites |
0148_MainAutochamber_2016_FTICRMS |
EMERGE 2016 Autochamber Sites FT-ICRMS |
0149_MainAutochamber_2016_EnzymeAssays |
EMERGE 2016 Autochamber Sites Enzyme Assays |
0150_MainAutochamber_2016_NMR |
EMERGE 2016 Autochamber Sites NMR |
0151_MainAutochamber_2016_LCMS |
EMERGE 2016 Autochamber Sites LC-MS |
0157_FTICRMS_GCMS_June2012 |
June 2012 FT-ICR MS and GC-MS data from: "Controls on soil organic matter degradation and subsequent greenhouse gas emissions across a permafrost thaw gradient in Northern Sweden" |
Terrestrial Gas Fluxes
Image credit: Patrick Crill
0033_Flux20022007 |
Autochamber Fluxes 2002-2007 |
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0073_ThawPondBubbles20122015 |
Thaw pond bubble fluxes (2012-2015) |
0074_ThawPondTemps20132018 |
Thaw pond temperatures (2013-2018) |
0138_DailyFlux_20122018 |
Daily CH4 and CO2 fluxes (from LGR at autochamber sites) and peat temperatures (from InterAct Fen tower), 2012-2018 |
0072_IsoFluxQCL_public |
Autochamber CH4 Fluxes and δ13C Values from QCL (public release) |
Environmental Data from the Mire
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbXNEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--6b68f4e6e73ea9a866c7de2fea929b87e46c25ad/ICOS_STO_flux2.jpg)
Image credit: ICOS Sweden (http://www.icos-sweden.se/station_stordalen.html)
0062_Manual_ALD_WTD |
Manual ALD and WTD measurements from autochamber sites (2003-2017 mostly) |
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Lake Data
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbUVEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--edefa68bd4f58beeac1ade2b7bdc6f8cff6c754f/fieldwk2_stordalenmire_lg.jpg)
Image credit: Ruth Varner
0024_LakeTemps111020120529 |
Lake water temperatures (5- to 60-minute resolution): Oct 2011 - May 2012 |
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0023_LakeTemps110611111020 |
Lake water temperatures (5- to 60-minute resolution): June 2011 - Oct 2011 |
0022_LakeTemps100928110610 |
Lake water temperatures (5- to 60-minute resolution): Sept 2010 - June 2011 |
0020_LakeTemps100721100828 |
Lake water temperatures (5- to 60-minute resolution): July 2010 - Aug 2010 |
0021_LakeTemps100829100927 |
Lake water temperatures (5- to 60-minute resolution): Aug 2010 - Sept 2010 |
0019_LakeTemps100609100720 |
Lake water temperatures (5- to 60-minute resolution): June 2010 - July 2010 |
0016_LakeTemps090611090828 |
Lake water temperatures (5- to 60-minute resolution): June 2009 - Aug 2009 |
0017_LakeTemps090829091012 |
Lake water temperatures (5- to 60-minute resolution): Aug 2009 - Oct 2009 |
0018_LakeTemps091015100602 |
Lake water temperatures (5- to 60-minute resolution): Oct 2009 - June 2010 |
0039_LakeTemps151001160607 |
Lake water temperatures (5- to 60-minute resolution): Oct 2015 - June 2016 |
0040_LakeTemps160607161016 |
Lake water temperatures (5- to 60-minute resolution): June 2016 - Oct 2016 |
0041_LakeTemps161016170316 |
Lake water temperatures (5- to 60-minute resolution): Oct 2016 - Mar 2017 |
0042_LakeTemps170610170929 |
Lake water temperatures (5- to 60-minute resolution): June 2017 - Sept 2017 |
0043_LakeTemps170930180615 |
Lake water temperatures (5- to 60-minute resolution): Sept 2017 - June 2018 |
0044_LakeTemps180615181016 |
Lake water temperatures (5- to 60-minute resolution): June 2018 - Oct 2018 |
0045_LakeTemps181018190606 |
Lake water temperatures (5- to 60-minute resolution): Oct 2018 - June 2019 |
0025_LakeTemps120530120928 |
Lake water temperatures (5- to 60-minute resolution): May 2012 - Sept 2012 |
0026_LakeTemps120928130627 |
Lake water temperatures (5- to 60-minute resolution): Sept 2012 - June 2013 |
0027_LakeTemps130620130923 |
Lake water temperatures (5- to 60-minute resolution): June 2013 - Sept 2013 |
0028_LakeTemps130923140609 |
Lake water temperatures (5- to 60-minute resolution): Sept 2013 - June 2014 |
0029_LakeTemps140609140829 |
Lake water temperatures (5- to 60-minute resolution): June 2014 - Aug 2014 |
0030_LakeTemps140829141003 |
Lake water temperatures (5- to 60-minute resolution): Aug 2014 - Oct 2014 |
0031_LakeTemps141003150620 |
Lake water temperatures (5- to 60-minute resolution): Oct 2014 - June 2014 |
0032_LakeTemps150620151001 |
Lake water temperatures (5- to 60-minute resolution): June 2015 - Oct 2015 |
0094_Lake_sediment_microbiota_16S-reads |
Lake sediment microbiota: Raw 16S rRNA sequencing reads |
0095_Lake_sediment_microbiota_metaG-reads |
Lake sediment microbiota: Metagenomic sequencing reads |
0096_Lake_sediment_microbiota_assemblies |
Lake sediment microbiota: Assemblies |
Microbial Sequencing
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbVFEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--23422eceb17f32ba9553e555ebe2a80a075d9813/dna-1370603787LgY.jpg)
Image credit: stock image (public domain)
0059_IsoGenie_sequence_samplecodes |
Mapping of sequencing sample names to standardized sample metadata from the DB |
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0060_IsoGenieDB-Sequencing_Imports |
Microbial and viral sequencing metadata |
0075_M-stor |
Candidatus 'Methanoflorens stordalenmirensis' draft genome (built from bog metagenomes in BioProject PRJNA215012) |
0076_iTags_20102011 |
iTags (2010-2011) (BioProject PRJNA215012) |
0077_iTags_2011 |
iTags (2011) (BioProject PRJNA235935) |
0078_metaGs_20102012 |
Metagenomes (2010-2012) (BioProject PRJNA386568) |
0079_MAGs_20102012 |
Metagenome-assembled genomes (MAGs) (2010-2012) (BioProject PRJNA386568) |
0080_metaTs_20102012 |
Metatranscriptomes (2010-2012) (BioProject PRJNA386568) |
0081_CaldisericaCryosericum_MAGs |
Caldiserica/Cryosericum MAGs (BioProject PRJNA482249) |
0082_CaldisericaCryosericum_iTags |
iTags associated with Caldiserica/Cryosericum MAGs (BioProject PRJNA482249) |
0083_metaPs_fen2010 |
Fen metaproteomes (2010) (PXD000410) |
0084_metaPs_2012 |
Metaproteomes (2012) (PXD009096) |
0085_incubations-vs-field_sequencing-reads |
Comparison of microbial processes in anaerobic incubations and field samples: iTag and metagenome raw reads |
0086_incubations-vs-field_PICRUSt |
Comparison of microbial processes in anaerobic incubations and field samples: PICRUSt analysis code and input data (processed iTags) |
0099_MicrobiomeMetadataSheet_public |
Sample Metadata Sheet for Samples with Microbiomes: Detailed field and geochemical (meta)data for samples with linked metaGs (formerly "Microbiome Metadata Sheet") - Public edition |
0153_MAGs_pre-release |
Metagenome-assembled genomes (MAGs) from Stordalen Mire, Sweden |
Viral Sequencing
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbVVEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--f42b18f3f57106385be65cd5ece879efb7e4f8df/BJ1_EM.png)
Image credit: Pagaling and Haigh et al., 2007 (DOI:10.1186/1471-2164-8-410)
0088_QuantAmp_dsDNA_Viromes_2014 |
Quantitatively-amplified dsDNA viromes, collected 2014 |
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0089_ViralPopulationContigs |
Viral population contigs (1907 total), based on:
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0090_TrublSoilViromes |
Trubl Soil Viromes (QC reads) |
0091_QuantAmp_ssDNA_dsDNA_Viromes_20162017 |
Quantitatively-amplified ssDNA and dsDNA viromes, Nextera XT and Accel-NGS 1S Plus libraries, collected 2016-2017 |
0155_VirusGenomes_vOTUs |
Virus operational taxonomic units (vOTUs) from Stordalen Mire, Sweden |
Plant-Associated Data
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbWNEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--ae312e4358c9839e5b1ce33d1cd275c79ca03527/cloudberry_1.jpg)
Image credit: Nicole Raab
0092_iTags_rhizosphere_phyllosphere_processed |
iTag-based microbial abundances from the rhizosphere and phyllosphere, and comparison with bulk peat (2016): Processed data |
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0093_iTags_rhizosphere_phyllosphere_raw |
iTag-based microbial abundances from the rhizosphere and phyllosphere, and comparison with bulk peat (2016): Raw data |
0141_Wilson-etal-2022-STOTEN_ICR-plants |
Log-transformed FT-ICR MS peak intensities for plant samples across the three main habitat types (palsa, bog, fen) |
0143_Wilson-etal-2022-STOTEN_plant-tissue-proportions |
Biomass coverage of plant species across the three main habitat types (palsa, bog, fen) |
Remote Sensing
Image credit: Nicole Raab
0145_Wv2-2014_GroundCoverClassifications |
Stordalen Mire ground cover classifications, based on 2014 WorldView-2 satellite imagery |
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0146_Wv2-2014_GroundCoverProbabilities |
For the Stordalen Mire ground cover classifications, probability of the neural network assigning each cover class (see publication for details): H2O, HM, OT, RK, SW, TG, TS, WT |
0147_Drone-2014 |
Drone imagery (2014) over Stordalen Mire |
0147_Drone-2015 |
Drone imagery (2015) over Stordalen Mire |
0147_Drone-2016 |
Drone imagery (2016) over Stordalen Mire |
0147_Drone-2017 |
Drone imagery (2017) over Stordalen Mire |
Modeling
![](/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBbWtEIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--999460aadac7ff025ab05fe10e2802e08f7e9077/C_cycling.png)
Image credit: Virginia Rich
0098_Ecosys_2011 |
Ecosys model products for Stordalen, 2011 |
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0097_Ecosys_19012010 |
Ecosys model products for Stordalen, 1901-2010 |
0156_IncubationSimulation |
Data from: "Soil incubation methods lead to large differences in inferred methane production temperature sensitivity" |
A2A Historical Datasets: APEX (Alaska)
0505_ApexAlphaMeteorology11 |
APEX Alpha Meteorology (2011) |
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0504_ApexAlphaMeteorology10 |
APEX Alpha Meteorology (2010) |
0503_ApexAlphaMeteorology09 |
APEX Alpha Meteorology (2009) |
0502_ApexAlphaMeteorology08 |
APEX Alpha Meteorology (2008) |
0501_ApexAlphaMeteorology07 |
APEX Alpha Meteorology (2007) |
A2A Summary Files
0154_A2A_Summary_Files |
Data summaries from the five peatland complexes sampled by the A2A project (APEX, Lutose, Smith Creek, Kaamanen, Stordalen Mire). Data includes: CH4 fluxes and δ13C values, porewater CH4 and CO2 concentrations and δ13C and δD values, vegetation cover (by species and functional type), environmental data (pH, water table depth, and soil temperatures), and BAWLD landcover classifications (Olefeldt et al. 2021 ESSD) for each sampled site. |
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