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Dataset Title:  Alkaline phosphatase activities for in situ and incubation samples from RV/
Atlantic Explorer cruise AE1812 cruise transect from Bermuda to Rhode Island in
May 2018.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_739973)
Range: longitude = -70.58 to -56.56°E, latitude = 31.42 to 40.42°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  incubation {
    String bcodmo_name "replicate";
    String description "Incubation replicate or in situ sampling";
    String long_name "Incubation";
    String units "unitless";
  sample {
    String bcodmo_name "sample";
    String description "Sample identifier";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  station {
    String bcodmo_name "station";
    String description "Station identification number";
    String long_name "Station";
    String units "unitless";
  cast {
    String bcodmo_name "cast";
    String description "Cast number on cruise";
    String long_name "Cast";
    String units "unitless";
  date_harvest {
    String bcodmo_name "date";
    String description "Day on which samples were filtered and stored; formatted as yyyy-mm-dd";
    String long_name "Date Harvest";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date_harvest";
    String time_precision "1970-01-01";
    String units "unitless";
  APA_nmolP_hr_liter {
    String bcodmo_name "unknown";
    String description "Alkaline phosphatase activity; volume normalized";
    String long_name "APA Nmol P Hr Liter";
    String units "nanomol Phosphate/hour/liter [nmol P/h/L]";
  APA_nmolP_hr_ug_chla {
    String bcodmo_name "unknown";
    String description "Alkaline phosphatase activity; chl a normalized";
    String long_name "APA Nmol P Hr Ug Chla";
    String units "nanomol Phosphate/hour/microgram chlorophyll-a [nmol P/h/µg Chl a]";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 31.42, 40.42;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -70.58, -56.56;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"For APA analysis, triplicate biological samples (250 mL) from in situ and
incubation samples were filtered onto 47-mm polycarbonate membranes (0.2
\\u03bcm). Stored at \\u221220\\u00b0C until analysis.
APA was assayed after Dyhrman and Ruttenberg (2006) using the fluorogenic
phosphatase substrate 6,8-difluoro-4-methylumbelliferyl phosphate. Values were
normalized to both volume and chl a. Reagents/Abs/Em used:
D-6567 6,8-difluoro-4-methylumbelliferyl phosphate (DiFMUP):  
 - Storage upon receipt: \\u2264 20\\u00b0C; Desiccate  
 - Abs/Em = 358/455  
 - Molecular Formula: C10H7F2O6P  
 - Molecular Weight: 292.1  
 - CAS Name/Number: 2H-1-Benzopyran-2-one,
6,8-difluoro-4-methyl-7-(phosphonooxy)-/ 214491-43-7
D-6566 6,8-difluoro-7-Hydroxy-4-Methylcoumarin (DiFMU) - Reference Standard:  
 - Storage upon receipt: Room temp.; protect from light  
 - Molecular Formula: C10H6F2O3  
 - Molecular Weight: 212.15  
 - CAS Name/Number: 2H-1-Benzopyran-2-one, 6,8-difluoro-7-hydroxy-4-methyl-/
Incubation key:  
 Control = no addition of nutrients or deep water  
 DSW = deep seawater addition (added 20% deep seawater (700 m))  
 +P = Added phosphate only (0.5 \\u00b5M final for incubations 1 and 2, 1
\\u00b5M final for incubation 3)  
 +N = Added nitrate only (6 \\u00b5M final for incubations 1 and 2, 12 \\u00b5M
final for incubation 3)  
 phi_P = All but P added (N, Si, Fe, B12)  
 \\u00a0phi_N = All but N added (P, Si, Fe, B12)  
 -1, -2, -3 = biological replicates
In situ key:  
 IS = in situ  
 -1, -2, -3 = biological replicates
Lost = sample was lost";
    String awards_0_award_nid "704773";
    String awards_0_award_number "OCE-1558506";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1558506";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"AE1812 Alkaline phosphatase activity 
    in situs and incubation samples from AE1812 cruise transect from Bermuda to Rhode Island in May 2018 
   PI: S. Dyhrman (LDEO) 
   version: 2018-07-17";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String dataset_current_state "Final and no updates";
    String date_created "2018-07-16T15:35:18Z";
    String date_modified "2020-06-29T18:48:11Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.739973.1";
    Float64 Easternmost_Easting -56.56;
    Float64 geospatial_lat_max 40.42;
    Float64 geospatial_lat_min 31.42;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -56.56;
    Float64 geospatial_lon_min -70.58;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-07-12T17:07:52Z (local files)
2024-07-12T17:07:52Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_739973.das";
    String infoUrl "https://www.bco-dmo.org/dataset/739973";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_description "Samples were run on a Biotek Synergy fluorescent plate reader using black plates";
    String instruments_0_dataset_instrument_nid "739977";
    String instruments_0_description "Plate readers (also known as microplate readers) are laboratory instruments designed to detect biological, chemical or physical events of samples in microtiter plates. They are widely used in research, drug discovery, bioassay validation, quality control and manufacturing processes in the pharmaceutical and biotechnological industry and academic organizations. Sample reactions can be assayed in 6-1536 well format microtiter plates. The most common microplate format used in academic research laboratories or clinical diagnostic laboratories is 96-well (8 by 12 matrix) with a typical reaction volume between 100 and 200 uL per well. Higher density microplates (384- or 1536-well microplates) are typically used for screening applications, when throughput (number of samples per day processed) and assay cost per sample become critical parameters, with a typical assay volume between 5 and 50 µL per well. Common detection modes for microplate assays are absorbance, fluorescence intensity, luminescence, time-resolved fluorescence, and fluorescence polarization. From: https://en.wikipedia.org/wiki/Plate_reader, 2014-09-0-23.";
    String instruments_0_instrument_name "plate reader";
    String instruments_0_instrument_nid "528693";
    String instruments_0_supplied_name "Biotek Synergy fluorescent plate reader";
    String keywords "apa, APA_nmolP_hr_liter, APA_nmolP_hr_ug_chla, bco, bco-dmo, biological, cast, chemical, chla, chlorophyll, chlorophyll-a, data, dataset, date, dmo, erddap, harvest, incubation, latitude, liter, longitude, management, nmol, oceanography, office, preliminary, sample, station, time";
    String license "https://www.bco-dmo.org/dataset/739973/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/739973";
    Float64 Northernmost_Northing 40.42;
    String param_mapping "{'739973': {'lat': 'flag - latitude', 'lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/739973/parameters";
    String people_0_affiliation "Lamont-Doherty Earth Observatory";
    String people_0_affiliation_acronym "LDEO";
    String people_0_person_name "Sonya T. Dyhrman";
    String people_0_person_nid "51101";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Rhode Island";
    String people_1_affiliation_acronym "URI-GSO";
    String people_1_person_name "Bethany D. Jenkins";
    String people_1_person_nid "558172";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Rhode Island";
    String people_2_affiliation_acronym "URI-GSO";
    String people_2_person_name "Tatiana Rynearson";
    String people_2_person_nid "511706";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "North Atlantic Diatoms";
    String projects_0_acronym "North Atlantic Diatoms";
    String projects_0_description 
"NSF abstract:
About half of photosynthesis on earth is generated by marine phytoplankton, single celled organisms that drift with tides and currents. Within the phytoplankton, the diatoms conduct nearly half of this photosynthesis, exerting profound control over global carbon cycling. Despite their importance, there are surprisingly fundamental gaps in understanding how diatoms function in their natural environment, in part because methods to assess in situ physiology are lacking. This project focuses on the application of a powerful new approach, called Quantitative Metabolic Fingerprinting (QMF), to address this knowledge gap and examine species-specific physiology in the field. The project will provide transformative insights into how ocean geochemistry controls the distribution of diatoms, the metabolic responses of individual diatom species, and how metabolic potential is partitioned between diatom species, thus providing new insights into the structure and function of marine systems. The overarching goal is to examine how diatom species respond to changes in biogeochemistry across marine provinces, from the coast to the open ocean, by following shifts in diatom physiology using QMF. This research is critical to understand future changes in oceanic phytoplankton in response to climate and environmental change. Furthermore, activities on this project will include supporting a graduate student and postdoctoral fellow and delivering the Artistic Oceanographer Program (AOP) to diverse middle school age children and teachers in the NYC metropolitan area and to middle-school girls in the Girl Scouts of RI, reaching an anticipated 60 children and 30 teachers annually. The programs will foster multidisciplinary hands-on learning and will directly impact STEM education at a critical point in the pipeline by targeting diverse middle-school aged groups in both NY and RI.
In laboratory studies with cultured isolates, there are profound differences among diatom species' responses to nutrient limitation. Thus, it is likely that different species contribute differently to nutrient uptake, carbon flux and burial. However, marine ecosystem models often rely on physiological attributes drawn from just one species and apply those attributes globally (e.g. coastal species used to model open ocean dynamics) or choose a single average value to represent all species across the world's oceans. In part, this is due to a relatively poor understanding of diatom physiological ecology and a limited tool set for assessing in situ diatom physiological ecology. This research project will address this specific challenge by explicitly tracking metabolic pathways, measuring their regulation and determining their taxonomic distribution in a suite of environmentally significant diatoms using a state of the art, species-specific approach. A research expedition is set in the North Atlantic, a system that plays a major role in carbon cycling. Starting with a New England coastal shelf site, samples will be collected from the coast where diatoms thrive, to the open ocean and a site of a long term ocean time series station (the Bermuda Atlantic Time Series) where diatom growth is muted by nutrient limitation. This research takes advantage of new ocean observatories initiative (OOI) and time series information. Through the research expedition and downstream laboratory experiments, the molecular pathways of nutrient metabolism and related gene expression in a suite of environmentally significant diatoms will be identified. Data will be combined to predict major limiting factors and potentially important substrates for diatoms across marine provinces. Importantly, this integrated approach takes advantage of new advances in molecular and bioinformatics tools to examine in situ physiological ecology at the species-specific level, a key knowledge gap in the field.";
    String projects_0_end_date "2019-08";
    String projects_0_geolocation "North Atlantic";
    String projects_0_name "Collaborative Research: Defining the biogeochemical drivers of diatom physiological ecology in the North Atlantic";
    String projects_0_project_nid "704768";
    String projects_0_start_date "2016-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 31.42;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset reports alkaline phosphatase activities (APA) for 3 incubation runs and 33 in situ samples collected on RV/Atlantic Explorer cruise AE1812 in May 2018. The samples were collected between Bermuda and Rhode Island.";
    String title "Alkaline phosphatase activities for in situ and incubation samples from RV/Atlantic Explorer cruise AE1812 cruise transect from Bermuda to Rhode Island in May 2018.";
    String version "1";
    Float64 Westernmost_Easting -70.58;
    String xml_source "osprey2erddap.update_xml() v1.5";


Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
For example,
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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