NCCOS Assessment: Groundfish biodiversity hotspots off the Pacific Coast of Oregon from 1971-09-05 to 2010-09-20 (NCEI Accession 0156467)

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This data set comprises maps of predicted long-term groundfish biodiversity hotspot probabilities off the Pacific Coast of Oregon. Predicted hotspot probabilities are given for four biodiversity indices: 1) relative abundance, 2) relative biomass, and 3) species number for all groundfishes, and 4) relative abundance for only nearshore groundfishes. The nearshore species assemblage includes: Sand Sole, English Sole, Pacific Sanddab, Speckled Sanddab, Petrale Sole, Starry Flounder, and Butter Sole. Hotspots were defined as areas with predictions in the top 10% of values of at-sea observations.

Areas of relatively high biodiversity were predicted using at-sea groundfish observations collected from 1971 to 2010 and associative models linking species observations with environmental covariates. Groundfish observations were taken from existing fishery-independent trawl data collected by NOAA’s National Marine Fisheries Service and flatfish trawl data collected by the Oregon Department of Fish and Wildlife. Environmental predictors included position on the shelf, sea floor habitat, depth, slope, aspect, slope of slope, and oceanographic productivity were used to predict areas with relatively high groundfish biodiversity. Binary logistic regression trees were used to associate species observations with environmental covariates and predict categorical results (Hotspot/Low classes). Mapped values indicate the probability of a raster cell belonging in the hotspot class.
  • Cite as: Menza, Charles; Pittman, Simon; Clark, Randy; Bauer, Laurie; Fox, David; Donnellan, Michael; Merems, Arlene (2016). NCCOS Assessment: Groundfish biodiversity hotspots off the Pacific Coast of Oregon from 1971-09-05 to 2010-09-20 (NCEI Accession 0156467). Version 1.1. NOAA National Centers for Environmental Information. Dataset. doi:10.7289/V5MK69Z3 [access date]
gov.noaa.nodc:0156467
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Ordering Instructions Data may be searched and downloaded using online services provided by NCEI using the online resource URLs in this record. Contact NCEI Information Services for custom orders. When requesting data from NCEI, the desired data set may be referred to by the unique package identification number listed in this metadata record.
Distributor DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
301-713-3277
NCEI.Info@noaa.gov
Dataset Point of Contact Information Services
DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
301-713-3277
NCEI.Info@noaa.gov
Time Period 1971-09-05 to 2010-09-20
Spatial Bounding Box Coordinates
N: 48.7
S: 40
E: -123
W: -126
Spatial Coverage Map
General Documentation
Associated Resources
Publication Dates
  • publication: 2016-09-13
Edition 1.1
Data Presentation Form Digital table - digital representation of facts or figures systematically displayed, especially in columns
Dataset Progress Status Complete - production of the data has been completed
Data Update Frequency As needed
Supplemental Information
Submission Package ID: 1F4JYX
Purpose This data set was used to support the Oregon Territorial Sea Plan. It was used to define ecologically important areas in the Nearshore Ecological Data Atlas Marxan Analysis conducted by The Nature Conservancy of Oregon.
Use Limitations
  • accessLevel: Public
  • Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
Dataset Citation
  • Cite as: Menza, Charles; Pittman, Simon; Clark, Randy; Bauer, Laurie; Fox, David; Donnellan, Michael; Merems, Arlene (2016). NCCOS Assessment: Groundfish biodiversity hotspots off the Pacific Coast of Oregon from 1971-09-05 to 2010-09-20 (NCEI Accession 0156467). Version 1.1. NOAA National Centers for Environmental Information. Dataset. doi:10.7289/V5MK69Z3 [access date]
Cited Authors
  • Menza, Charles
  • Pittman, Simon
  • Clark, Randy
  • Bauer, Laurie
  • Fox, David
  • Donnellan, Michael
  • Merems, Arlene
Principal Investigators
  • Charles Menza
    US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
Collaborators
  • Pittman Simon
    National Centers for Coastal Ocean Science (NCCOS)
  • Randy Clark
    National Centers for Coastal Ocean Science (NCCOS)
  • Laurie Bauer
    National Centers for Coastal Ocean Science (NCCOS)
  • David Fox
    State of Oregon; Oregon Department of Fish and Wildlife
  • Michael Donnellan
    State of Oregon; Oregon Department of Fish and Wildlife
  • Arlene Merems
    State of Oregon; Oregon Department of Fish and Wildlife
Resource Providers
Publishers
Theme keywords NODC DATA TYPES THESAURUS NODC OBSERVATION TYPES THESAURUS WMO_CategoryCode
  • oceanography
Global Change Master Directory (GCMD) Science and Services Keywords
  • EARTH SCIENCE > AGRICULTURE > AGRICULTURAL AQUATIC SCIENCES > FISHERIES
  • EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > FISH
NCCOS Keywords
  • NCCOS Research Data Type > Derived Data Product
  • NCCOS Research Data Type > Geospatial
  • NCCOS Research Data Type > Model
  • NCCOS Research Priority > Marine Spatial Ecology (MSE)
  • NCCOS Research Topic > Ecological/Biological Characterization
  • NCCOS Research Topic > Predictive/Spatial Modeling
Submitter Keywords
  • Groundfish abundance
  • Groundfish biomass
  • Groundfish species number
  • Nearshore groundfish abundance
Data Center keywords Global Change Master Directory (GCMD) Data Center Keywords
  • DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce
  • DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
  • DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce
NODC SUBMITTING INSTITUTION NAMES THESAURUS
Place keywords NODC SEA AREA NAMES THESAURUS Global Change Master Directory (GCMD) Location Keywords
  • OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN
NCCOS Location Keywords
  • NCCOS Research Location > Geographic Area > Coastal Ocean
  • NCCOS Research Location > Geographic Area > Continental Shelf
  • NCCOS Research Location > Geographic Area > Deep Sea
  • NCCOS Research Location > Region > West Coast
  • NCCOS Research Location > U.S. States and Territories > Oregon
Submitter Place Keywords
  • California Current
  • Eastern Pacific
  • Pacific Northwest
Project keywords Projects
  • Spatial Analysis of Groundfish to Support Oregon’s Territorial Sea Plan
Keywords NCEI ACCESSION NUMBER
Use Constraints
  • Cite as: Menza, Charles; Pittman, Simon; Clark, Randy; Bauer, Laurie; Fox, David; Donnellan, Michael; Merems, Arlene (2016). NCCOS Assessment: Groundfish biodiversity hotspots off the Pacific Coast of Oregon from 1971-09-05 to 2010-09-20 (NCEI Accession 0156467). Version 1.1. NOAA National Centers for Environmental Information. Dataset. doi:10.7289/V5MK69Z3 [access date]
Access Constraints
  • NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
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Lineage information for: dataset
Processing Steps
  • 2016-09-13T13:03:08 - NCEI Accession 0156467 v1.1 was published.
Output Datasets
Lineage information for: dataset
Processing Steps
  • Data Type: Groundfish abundance hotspot (calculated); Units: probability; Observation Type: model output; Sampling Instrument: documentation only - no instrument type; Sampling and Analyzing Method: The data describe spatially-explicit predicted long-term groundfish abundance hotspot probabilities. Predictions were made using at-sea groundfish observations collected from 1971 to 2010 and associative models linking species observations with environmental covariates. Classification accuracy is 74%.; Data Quality Information: Predictive biomass hotspot maps were reviewed and accepted by subject matter experts. Processing and analysis methods are described in the data documentation.
  • Data Type: Groundfish biomass hotspot (calculated); Units: probability; Observation Type: model output; Sampling Instrument: documentation only - no instrument type; Sampling and Analyzing Method: The data describe spatially-explicit predicted long-term groundfish biomass hotspot probabilities. Predictions were made using at-sea groundfish observations collected from 1971 to 2010 and associative models linking species observations with environmental covariates. Classification accuracy is 82%.; Data Quality Information: Predictive biomass hotspot maps were reviewed and accepted by subject matter experts. Processing and analysis methods are described in the data documentation.
  • Data Type: Groundfish species number hotspot (calculated); Units: probability; Observation Type: model output; Sampling Instrument: documentation only - no instrument type; Sampling and Analyzing Method: The data describe spatially-explicit predicted long-term groundfish species number hotspot probabilities. Predictions were made using at-sea groundfish observations collected from 1971 to 2010 and associative models linking species observations with environmental covariates. Classification accuracy is 64%.; Data Quality Information: Predictive biomass hotspot maps were reviewed and accepted by subject matter experts. Processing and analysis methods are described in the data documentation.
  • Data Type: Nearshore groundfish abundance hotspot (calculated); Units: probability; Observation Type: model output; Sampling Instrument: documentation only - no instrument type; Sampling and Analyzing Method: The data describe spatially-explicit predicted long-term nearshore groundfish abundance hotspot probabilities. Predictions were made using at-sea groundfish observations collected from 1971 to 2010 and associative models linking species observations with environmental covariates. Classification accuracy is 83%.; Data Quality Information: Predictive biomass hotspot maps were reviewed and accepted by subject matter experts. Processing and analysis methods are described in the data documentation.
  • Data Type: NCCOS Research Priority > Marine Spatial Ecology (MSE) (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Topic > Ecological/Biological Characterization (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Topic > Predictive/Spatial Modeling (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Location > Region > West Coast (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Location > U.S. States and Territories> Oregon (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Location > Geographic Area > Deep Sea (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Location > Geographic Area > Coastal Ocean (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Location > Geographic Area > Continental Shelf (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Data Type > Model (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Data Type > Geospatial (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
  • Data Type: NCCOS Research Data Type > Derived Data Product (calculated); Units: n/a; Observation Type: other; Sampling Instrument: n/a.
Last Modified: 2018-08-10T19:01:22
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