Phosphate Mean ConcentrationData Set (DS) | Office for Coastal Management (OCM)
GUID: gov.noaa.nmfs.inport:66169 | Updated: August 9, 2022 | Published / External
|Title:||Phosphate Mean Concentration|
Nutrient data were obtained from the Bio-ORACLE project and represent a long-term composite of data from 2000 to 2014. The map layer represents mean phosphate concentration (micromoles per liter) in surface waters of the U.S. Exclusive Economic Zone. Additional data available for download here provide six nutrient concentrations at three different depths within the water column (surface, mean depth, and maximum depth). Data have a common spatial resolution of 5 arc minutes and were assessed using a cross‐validation framework against in situ quality‐controlled data.
To support ocean planning activities pursuant to the Executive Order Regarding the Ocean Policy to Advance the Economic, Security, and Environmental Interests of the United States, the Energy Policy Act, the National Environmental Policy Act, the Rivers and Harbors Act, and the Coastal Zone Management Act.
|Global Change Master Directory (GCMD) Science Keywords||
EARTH SCIENCE > HUMAN DIMENSIONS > ENVIRONMENTAL GOVERNANCE/MANAGEMENT
|ISO 19115 Topic Category||environment|
|ISO 19115 Topic Category||farming|
|ISO 19115 Topic Category||oceans|
|ISO 19115 Topic Category||planningCadastre|
|None||alternative energy planning|
|None||coastal energy planning|
|None||environmental energy planning|
|None||marine spatial planning|
|None||ocean energy planning|
|None||offshore energy planning|
|None||renewable energy planning|
|Global Change Master Directory (GCMD) Location Keywords||
CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA
|None||Gulf of Mexico|
Data Set Information
|Data Set Scope Code:||Data Set|
|Maintenance Frequency:||As Needed|
|Data Presentation Form:||Map (digital)|
|Data Set Credit:||NOAA National Centers for Coastal Ocean Science, Bureau of Ocean Energy Management, NOAA Office for Coastal Management|
Point of Contact
|Date Effective From:||2020-06|
|Date Effective To:|
|Contact (Organization):||NOAA Office for Coastal Management (NOAA/OCM)|
2234 South Hobson Ave
Charleston, SC 29405-2413
|Currentness Reference:||Publication Date|
Extent Group 1
Extent Group 1 / Geographic Area 1
|Data Use Constraints:||
For coastal and ocean planning
MarineCadastre.gov Data Registry
Esri ArcGIS 10.4.1.5686
The attributes in this dataset are believed to be accurate.
|Horizontal Positional Accuracy:||
Maximum scale of intended use is 1:80,000.
Spatial and attribute properties are believed to be complete, although attribute information has been simplified. Geometric thresholds from original data are preserved. No tests have been completed for exhaustiveness.
These data are believed to be logically consistent. Geometry is topologically clean.
Bio-ORACLE: Marine Data Layers for Ecological Modelling
|Contact Role Type:||Publisher|
|Extent Start Date/Time:||2020-02-01|
|Citation URL Name:||Source Online Linkage|
|Citation URL Description:||
URL where the source data were originally accessed.
Provided modeled phosphate data at depth for the US EEZ.
Process Step 1
1) Data sets were derived from Bio‐ORACLE (ocean rasters for analysis of climate and environment) global data set.
2) Phosphate concentrations (micromoles per litre) are reported as six statistical measures including Lt. Max, Lt. Min, Min, Max, mean, and range over three depths (surface, mean, maximum). *Lt. (long-term) for average of the minimum and maximum records per year (e.g., temperature of the warmest month, on average). For the Marine Cadastre National Viewer, only the mean surface depth concentration is displayed as an example.
3) The Bio-ORACLE “Present data set” (2000 - 2014) was downloaded as Tiff Raster files (.tif) using Bio-ORACLE’s download manager.
4) This surface and benthic layers, for each of the three nutrients were then entered as a geodatabase into ArcGIS 10.7. Each .tif file was then clipped to the United States Exclusive Economic Zone (EEZ) using the marinecadastre.gov EEZ shapefile.
5) Data were then given a continuous color schema to avoid issues with color-blind audiences (e.g. red to green) over the range of data values for each statistical measure. The lighter shade of a color represents areas with lower phosphate concentrations relative to the darker shades where higher phosphate values occur.
6) Surface, mean, and maximum concentration values were QA/QC’ed for any elements lacking in the data description or attributes, illogical values, spatial accuracy, and overall consistency across the data within the US EEZ.
7) Each data layer was then projected to WGS 1984 Web Mercator Auxiliary Sphere (EPSG: 3857) projection
8) Permission to use this data was received from the authors prior to use in marinecadastre.gov. Comparisons were also made to the ESRI Ecological Marine Unit (EMU) nutrient data where spatial overlap occurred, to ensure likeness in data over geographical space.
9) The Bio-ORACLE data are modeled and have been statistically downscaled and therefore have inherit biases associated with these types of analyses occur. However, methodology implemented here create a more spatially resolved data set for nutrients in US waters than any other known by the authors. However, these data lack high temporal resolution.
10) While the Bio-Oracle Nutrient data may have higher horizontal spatial resolution, the Esri EMU data has higher number of depth levels (102 depth levels). There are pros and cons of both data sets and users are recommended to compare the data sets before deciding which is best for their own analyses.
11) The pros to the ESRI EMU nutrient data is data are present over 102 depth levels, and can be used to statistically differentiate different portions of the water column. The cons lie its course spatial resolution, no temporal component, and no nearshore values (as of 2020). Sayre et al. (2019) (https://www.tandfonline.com/doi/full/10.1080/1755876X.2018.1529714 ) are working towards coastal EMUs, which will increase the spatial coverage of the EMU data. It is recommended that users view the pros and cons of applying the various data sets (Bio-ORACLE vs. EMU) to their own analyses.
More information about methodology used can be found in these resources:
Assis, J., Tyberghein, L., Bosh, S., Verbruggen, H., Serrão, E. A., & De Clerck, O. (2017). Bio-ORACLE v2.0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography.
Tyberghein L, Verbruggen H, Pauly K, Troupin C, Mineur F, De Clerck O (2012) Bio-ORACLE: A global environmental dataset for marine species distribution modelling. Global Ecology and Biogeography, 21, 272–281.
|Process Date/Time:||2020-01-01 00:00:00|
|Catalog Item ID:||66169|
|Metadata Record Created By:||Brianna Key|
|Metadata Record Created:||2021-12-22 04:42+0000|
|Metadata Record Last Modified By:||SysAdmin InPortAdmin|
|Metadata Record Last Modified:||2022-08-09 17:11+0000|
|Metadata Record Published:||2021-12-22|
|Metadata Publication Status:||Published Externally|
|Do Not Publish?:||N|
|Metadata Last Review Date:||2021-12-22|
|Metadata Review Frequency:||1 Year|
|Metadata Next Review Date:||2022-12-22|