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_705556 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_705556.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_705556/ | public | [Net tow data] - IKMT samples and underwater video recordings collected in the Drake Passage from R/V Laurence M. Gould (LMG1504, LMG1509, LMG1410) from 2014-2015 (Pilot Study: Addition of Biological Sampling to Drake Passage Transits of the \"L.M. Gould\") | IKMT samples and underwater video recordings collected in the Drake Passage from R/V Laurence M. Gould (LMG1504, LMG1509, LMG1410) from 2014-2015\n\ncdm_data_type = Other\nVARIABLES:\nstation (unitless)\ntime (ISO Date Time UTC, seconds since 1970-01-01T00:00:00Z)\ndate (unitless)\nstart_GMT (unitless)\nend_GMT (unitless)\nlat_deg (Latitude, degrees minutes)\nlat_min (Latitude, degrees minutes)\nlatitude (degrees_north)\nlon_deg (Longitude, degrees minutes)\nlon_min (Longitude, degrees minutes)\nlongitude (degrees_east)\nbiogeographic_zone (unitless)\nDIEL (unitless)\nvolume_filtered (meters cubed)\nSST (Sea Surface Temperature, celsius)\nbottom_depth (meters)\nwind_speed (knots)\nwind_direction (Wind From Direction, degrees)\ndepth (Tow Depth, m)\nunderwater_video (unitless)\nnotes (unitless)\n | https://erddap.bco-dmo.org/erddap/metadata/fgdc/xml/bcodmo_dataset_705556_fgdc.xml | https://erddap.bco-dmo.org/erddap/metadata/iso19115/xml/bcodmo_dataset_705556_iso19115.xml | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_705556/index.htmlTable | https://www.bco-dmo.org/dataset/705556
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_705556.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_705556&showErrors=false&email= | BCO-DMO | bcodmo_dataset_705556 | |||
| https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_918841_v1 | https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_918841_v1.graph | https://erddap.bco-dmo.org/erddap/files/bcodmo_dataset_918841_v1/ | public | [T. pseudonana starve-recover experiments: Physiological data] - Diatom (Thalassiosira pseudonana) physiological data from experiments designed to study single-cell transcriptional profiling of nutrient acquisition heterogeneity in diatoms conducted in December of 2022 (EAGER: Diatom Programmed Cell Death at Single-Cell Resolution) | This dataset includes physiological data for diatom Thalassiosira pseudonana grown during experiments conducted as part of a study of \"Single-Cell transcriptional profiling of nutrient acquisition heterogeneity in diatoms.\" See \"Related Datasets\" section for T. pseudonana gene and cell information collected as part of the same study and experiments.\n\n\nStudy description: \n\nDiatoms (Bacillariophyceae) are unicellular photosynthetic algae, accounting for about 40% of total marine primary production (equivalent to terrestrial rainforests) and critical ecological players in the contemporary ocean. Diatoms can form enormous blooms in the ocean that can be seen from space and are the base of food webs in coastal and upwelling systems, support essential fisheries, and are central to the biogeochemical cycling of important nutrients such as carbon and silicon. Over geological time, diatoms have influenced the world's climate by changing the carbon flux into the oceans. \n\nDiatoms have traditionally been studied on a population level. Growth is often measured by the total increase in biomass, and gene expression is analyzed by isolating mRNA from thousands or millions of cells. These methods generate a valuable analysis on the population's average functioning; however, they fail to show how each individual diatom cell contributes to the population phenotype. Bulk transcriptomes confound different stages and variability of cell states in heterogeneous populations. By contrast, single-cell transcriptomics measures gene expression in thousands of individual diatoms providing a quantitative and ultrahigh-resolution picture of transient cell states in population fractions enabling the reconstruction of the various phenotypic trajectories. Thus, the single-cell physiological and molecular parameters analysis allows an unsupervised assessment of cell heterogeneity within a population—a new dimension in diatoms and phytoplankton in general. \n\nIn this dataset, we examine the model diatom Thalassiosira pseudonana clonal cells grown in different nitrogen conditions, at the single cell level when grown in a light: dark cycle (12:12 h). Nitrogen is the major limiting nutrient for primary production and growth in the ocean's surface, specifically for diatoms and the food webs they support. We investigate nutrient limitation, starvation and recovery. We used droplet-based, single-cell transcriptomics to analyze ten samples in two stages. In the first stage (\"starvation\"), six samples were collected over four days of culture as nutrient levels decreased. In the second stage (\"recovery\"), four samples were collected over twelve hours after nutrients were replenished.\n\ncdm_data_type = Other\nVARIABLES:\nSpecies (unitless)\n... (29 more variables)\n | https://erddap.bco-dmo.org/erddap/info/bcodmo_dataset_918841_v1/index.htmlTable | https://www.bco-dmo.org/dataset/918841
| https://erddap.bco-dmo.org/erddap/rss/bcodmo_dataset_918841_v1.rss | https://erddap.bco-dmo.org/erddap/subscriptions/add.html?datasetID=bcodmo_dataset_918841_v1&showErrors=false&email= | BCO-DMO | bcodmo_dataset_918841_v1 |