Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| griddap | Subset | tabledap | Make A Graph | wms | files | Accessible | Title | Summary | FGDC | ISO 19115 | Info | Background Info | RSS | Institution | Dataset ID | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_904895_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_904895_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_904895_v1/ | public | [GN01 Element quotas of individual phytoplankton cells] - Element quotas of individual phytoplankton cells from samples collected on the US GEOTRACES Arctic cruise GN01 (HLY1502) on USCGC Healy in August-October 2015 (U.S. Arctic GEOTRACES Study (GN01)) | Individual phytoplankton cells were collected on the US GEOTRACES Arctic cruise GN01 (HLY1502) on USCGC Healy in August-October 2015. The elemental (Si, P, S, Mn, Fe, Co, Ni, Cu, Zn) content of each cell was measured with synchrotron x-ray fluorescence (SXRF). Carbon was calculated from biovolume. Data can be used to assess biogenic particulate metal fraction, as well as changes in the accumulation of these elements across environmental gradients. Data are part of the larger international GEOTRACES dataset.\n\ncdm_data_type = Other\nVARIABLES:\nRun (unitless)\nCruise (unitless)\nStation (unitless)\nlatitude (Lat_n, degrees_north)\nlongitude (Lon_e, degrees_east)\nDate (unitless)\nStart_time (unitless)\ntime (Iso_datetime_utc, seconds since 1970-01-01T00:00:00Z)\nDepth (meters (m))\nDepthDescr (unitless)\nParticleSampleID (unitless)\nCellType (unitless)\nMDA (unitless)\nUniqueCell (unitless)\nGridType (unitless)\nVolume (cubic microns)\ncellC (moles)\ncellSi (moles)\ncellP (moles)\ncellS (moles)\ncellMn (moles)\ncellFe (moles)\n... (7 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_904895_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_904895_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_904895_v1/index.htmlTable | https://www.bco-dmo.org/dataset/904895
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_904895_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_904895_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_904895_v1 | |||
| log in | [Kelletia kelletii: DNA and RNA sequence] - Full genome and transcriptome sequence assembly of the non-model organism Kellet’s whelk, Kelletia kelletii (Collaborative Research: RUI: Combined spatial and temporal analyses of population connectivity during a northern range expansion) | Understanding the genomic characteristics of non-model organisms can bridge research gaps between ecology and evolution. However, the lack of a reference genome and transcriptome for these species makes their study challenging. Here, we complete the first full genome and transcriptome sequence assembly of the non-model organism Kellet's whelk, Kelletia kelletii, a marine gastropod exhibiting a poleward range expansion coincident with climate change. We used a combination of Oxford Nanopore Technologies, PacBio, and Illumina sequencing platforms and integrated a set of bioinformatic pipelines to create the most complete and contiguous genome documented among the Buccinoidea superfamily to date. Genome validation revealed relatively high completeness with low missing metazoan Benchmarking Universal Single-Copy Orthologs (BUSCO) and an average coverage of ∼70x for all contigs. Genome annotation identified a large number of protein-coding genes similar to some other closely related species, suggesting the presence of a complex genome structure. Transcriptome assembly and analysis of individuals during their period of peak embryonic development revealed highly expressed genes associated with specific Gene Ontology (GO) terms and metabolic pathways, most notably lipid, carbohydrate, glycan, and phospholipid metabolism. We also identified numerous heat shock proteins (HSPs) in the transcriptome and genome that may be related to coping with thermal stress during the sessile life history stage. A robust reference genome and transcriptome for the non-model organism K. kelletii provide resources to enhance our understanding of its ecology and evolution and potential mechanisms of range expansion for marine species facing environmental changes.\n\ncdm_data_type = Other\nVARIABLES:\nRun (unitless)\nAssay_Type (unitless)\nAvgSpotLen (unitless)\nBases (unitless)\nBioProject (unitless)\nBioSample (unitless)\nBioSampleModel (unitless)\nBytes (unitless)\nCenter_Name (unitless)\n... (29 more variables)\n | BCO-DMO | bcodmo_dataset_945292_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936069_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_936069_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_936069_v1/ | public | [Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities] - Metagenome and metatranscriptome sequences from deep-sea hydrothermal vent microbial communities collected on cruises AT42-22, TN405, and NA108 from May 2019 to Jun 2022 (Collaborative Research: Microbes need frenemies: unveiling microbial relationships with protists and viruses that support deep-sea hydrothermal vent food webs) | This dataset is a collection of sample metadata, identified for all samples, and NCBI accession information for samples and sequence runs produced as part of the \"Microbes need frenemies\" project. This project examines trophic interactions among microbial eukaryotes, viruses, bacteria, and archaea at deep-sea hydrothermal vents using metagenomics and metatranscriptomics and characterizes these ecologically-significant interactions, such as mutualism, predator-prey, or virus-host. \n\nWe sequenced samples collected during the 2020 expedition AT42-22 to the Mid-Cayman Rise hydrothermal vent fields, as well as from the 2019 expedition NA108 to the Gorda Ridge and the 2022 expedition TN405 to the Axial seamount. Sequencing targeted archaea, bacteria, and viruses with metagenomics and microbial eukaryotes with metatranscriptomics. We plan to use these data to identify ecologically-significant interactions among protists, viruses, bacteria, and archaea, with a specific emphasis on microbial mortality via viral lysis and eukaryotic grazing. Archived samples were also included in the analysis.\n\ncdm_data_type = Other\nVARIABLES:\nSAMPLE_ID (unitless)\nSHORT_SAMPLE_ID (unitless)\nSAMPLE_NAME (unitless)\nLAB_NUM (unitless)\nCRUISE_ID (unitless)\nFIELD_REGION (unitless)\nYEAR (unitless)\nFIELD_YEAR (unitless)\nVENT (unitless)\nlatitude (degrees_north)\nlongitude (degrees_east)\nORIGIN_TYPE (unitless)\nORIGIN_DESCRIPTION (unitless)\nFRENEMIES_PROJ (unitless)\n... (11 more variables)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_936069_v1_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_936069_v1_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_936069_v1/index.htmlTable | https://www.bco-dmo.org/dataset/936069
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_936069_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_936069_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_936069_v1 | |||
| log in | [Seagrass Microbiome Data] - (Collaborative Research: The role of a keystone pathogen in the geographic and local-scale ecology of eelgrass decline in the eastern Pacific) | This dataset includes sample collection information and sequence accessions for 16S rRNA amplicon sequencing of eelgrass leaf and surrounding water column bacteria from 32 eelgrass meadows across latitudes from 55 to 32° N in the Northeastern Pacific during July and August 2019. Sequence Read Archive (SRA) Experiments and BioSamples can be accessed from the NCBI BioProject PRJNA802566 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA802566/)\n\nEelgrass, Zostera marina, is impacted by outbreaks of wasting disease caused by the opportunistic pathogen Labyrinthula zosterae. We investigated how Z. marina phyllosphere microbial communities vary with rising wasting disease lesion prevalence and severity relative to plant and meadow characteristics like shoot density, longest leaf length, and temperature across 23° latitude in the Northeastern Pacific. We sampled 32 eelgrass meadows across latitudes from 55 to 32° N in the Northeastern Pacific during July and August 2019. This range included six regions (AK=Alaska, BC=British Columbia, WA=Washington, OR=Oregon, BB=Bodega Bay Northern California, SD=San Diego Southern California), with 5–6 meadows per region. The location of each region is AK: N 55° 32' 27.124” W 133° 11' 1.0546, BC: N 51° 48' 30.1469” W 128° 13' 27.2182, WA: N 48° 36' 4.9725” W 122° 59' 56.4203, OR: N 44° 69 43.717” W 124° 89 22.7337, BB: N 38° 14' 30.3218” W 122° 58' 32.5723, SD: N 32° 47' 37.5929” W 117° 12' 57.1071”. We selected eelgrass meadows within each region that had consistently high cover of eelgrass in recent years.\n\ncdm_data_type = Other\nVARIABLES:\nsample_title (unitless)\nSampleType (unitless)\nRegionName (unitless)\nSiteCode (unitless)\nTissueType (unitless)\nLesionStatus (unitless)\ncollection_date (unitless)\nLocationName (unitless)\nTidalHeight (unitless)\nTransect (unitless)\n... (8 more variables)\n | BCO-DMO | bcodmo_dataset_933635_v1 | ||||||||||||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_806957 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_806957.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_806957/ | public | [Trace elements in CaCO3 and fluid] - Table 2. Elemental ratios and partition coefficients for CaCO3 in deepsea conditions: Mg, S, Sr, and Ba between crystallized solids and fluid. (Biologically induced methane oxidation and precipitation of carbonate minerals: An experimental study) | Trace elements in CaCO3 and fluid. Table 2. Elemental ratios and partition coefficients for CaCO3 in deepsea conditions: Mg, S, Sr, and Ba between crystallized solids and fluid.\n\ncdm_data_type = Other\nVARIABLES:\nanalysis (unitless)\nrun (unitless)\npress (bars)\nminerals (unitless)\nMg_Ca (millimole per mole of calcium)\nMg_Ca_2sd (millimole per mole of calcium)\nS_Ca (millimole per mole of calcium)\nS_Ca_2sd (micromole per mole of calcium)\nSr_Ca (millimole per mole of calcium)\nSr_Ca_2sd (millimole per mole of calcium)\nBa_Ca (millimole per mole of calcium)\nBa_Ca_2sd (micromole per mole of calcium)\nKMg (unitless)\nKMg_2sd (unitless)\nKS (unitless)\nKS_2sd (unitless)\nKSr (unitless)\nKSr_2sd (unitless)\nKBa (unitless)\nKba_2sd (unitless)\n | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_806957/index.htmlTable | https://www.bco-dmo.org/dataset/806957
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_806957.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_806957&showErrors=false&email= | BCO-DMO | bcodmo_dataset_806957 |