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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 | [RECHARGE 2018 - 2020 Microbiome Data] - Sequence read accession (SRA) numbers and collection metadata for coral microbiome collected in Moorea, French Polynesia from Jul 2018 to Aug 2020 (Collaborative Research: Tipping points in coral reefs and their associated microbiomes: interactive effects of herbivory, nutrient enrichment, and temperature) | This dataset contains the complete sample information for the 16S rRNA gene V4 region amplicon sequencing data associated with the NCBI SRA accession from BioProject PRJNA994532. All raw sequencing data can be found at this publicly available NCBI SRA BioProject. \n\nThe associated samples were collected from an in situ coral manipulative experiment in Moorea, French Polynesia between 2018-2020 from Acropora retusa, Porites lobata, and Pocillopora spp. Data collection was a multi-university collaborative effort between the Vega Thurber Laboratory, at Oregon State University during the time of the experiment, and the Burkepile Community Ecology Laboratory at UC Santa Barbara. The experiment, conducted on the fore reef on the north shore of the island, evaluated the interaction of consumer pressure level (termed \"Herbivory\" in the dataset and in Vompe et al., 2023) and nutrient enrichment on coral microbiome composition and host success. The experiment also captured two severe and sequential marine heatwaves in 2019 and 2020. This experiment aimed to evaluate whether managing local inputs, including water column nutrient levels and fishing regimes, interacts with heat stress to affect coral success. Coral microbiomes were sampled as these microbial communities are known to interact with host health during heat stress. The data herein correspond to the microbiomes of the sampled corals.\n\ncdm_data_type = Other\nVARIABLES:\nSample (unitless)\nDate_MonthYear (unitless)\nCoral_Code (unitless)\nHerbivory (unitless)\nNutrients (unitless)\nPlot (unitless)\nTag (unitless)\nBatch (unitless)\nRun (unitless)\nAssayType (unitless)\nAvgSpotLen (unitless)\nBases (unitless)\n... (32 more variables)\n | BCO-DMO | bcodmo_dataset_954262_v1 | ||||||||||||
| log in | [RECHARGE 2018 - 2020 Microbiome Host Bleaching and Mortality Data] - Microbiome Host Bleaching and Mortality Data for coral hosts collected in Moorea, French Polynesia from Jul 2018 to Aug 2020 (Collaborative Research: Tipping points in coral reefs and their associated microbiomes: interactive effects of herbivory, nutrient enrichment, and temperature) | This dataset contains bleaching and mortality levels for the coral hosts associated with the 16S rRNA gene V4 region amplicon sequencing data, NCBI SRA accession from BioProject PRJNA994532. Orthorectified photomosaics were assembled from photos taken of experimental plots from an in situ coral manipulative experiment in Moorea, French Polynesia between 2018-2020. Partial bleaching and mortality was assigned from these photomosaics to Acropora retusa, Porites lobata, and Pocillopora spp. coral colonies associated with the microbiome sampling described above, whenever possible. Data collection was a multi-university collaborative effort between the Vega Thurber Laboratory, at Oregon State University during the time of the experiment, and the Burkepile Community Ecology Laboratory at UC Santa Barbara. \n\nThe experiment, conducted on the fore reef on the north shore of the island, evaluated the interaction of consumer pressure level (termed \"Herbivory\" in the dataset and in Vompe et al., 2023) and nutrient enrichment on coral microbiome composition and host bleaching and mortality. The experiment also captured two severe and sequential marine heatwaves in 2019 and 2020. This experiment aimed to evaluate whether managing local inputs, including water column nutrient levels and fishing regimes, interacts with heat stress to affect coral success. Coral colony partial bleaching and partial mortality data were collected for hosts sampled for microbiome analyses, because we aimed to correlate microbiome changes to changes in host phenotypes.\n\ncdm_data_type = Other\nVARIABLES:\nSample (unitless)\nDate (unitless)\nCoral (unitless)\nHerbivory (unitless)\nNutrients (unitless)\nPlot (unitless)\nTag (unitless)\nRun (unitless)\nColony (unitless)\npercent_bleached (percent)\npercent_dead (percent)\n | BCO-DMO | bcodmo_dataset_954197_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 |