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  6. Predicted Annual Probability of Observing at least One Great Black-backed Gull

Predicted Annual Probability of Observing at least One Great Black-backed Gull

Dates

Release Date
2015
Date Collected
2002-07
Date Collected
2010-11

Citation

Predicted Annual Probability of Observing at least One Great Black-backed Gull: .

Summary

NOTE: Two data download links are provided. The first includes the data described below as a geographic point layer and as a .csv file. The second link is a data package containing: the annual probability of observing one individual, the annual probability of encountering a large flock, and the monthly probability of observing one individual, for the full set of 24 species (in .csv format), and the associated report “Mapping the distribution, abundance and risk assessment of marine birds in the Northwest Atlantic.” To improve display of this data on Data Basin the point data was converted to a raster grid. This map depicts the mean predicted probability of observing at least one individual Great Black-backed Gull (Larus marinus) [...]

Contacts

Contact :
Earvin Balderama, North Carolina State University, Department of Forestry and Environmental Resources

Attached Files

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GBBG_p1_md.xml
Original FGDC Metadata
View 		6.02 KB application/fgdc+xml
mb_GBBG_p1.zip 555.41 KB application/zip
Extension: great_blackbacked_gull.zip
great_blackbacked_gull.sd 936.62 KB
thumbnail.png thumbnail 8.57 KB

Purpose

This map depicts the mean predicted probability of observing at least one individual Great Black-backed Gull (Larus marinus) throughout the Northeastern and Mid-Atlantic coast of the United States based on the "double-hurdle model" of the probability distribution of avian count data. The model was developed to better handle the excessive amount of observed zeros and the few but relatively extreme counts simultaneously within a single framework.
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Map

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Communities

  • LC MAP - Landscape Conservation Management and Analysis Portal
  • North Atlantic Landscape Conservation Cooperative

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Provenance

Data source
Input directly
Earvin Balderama (now of Loyola University Chicago, Dept of Mathematics and Statistics) worked to develop this map and the statistical models used to produce them, with Beth Gardner (NCSU Dept of Forestry and Environmental Resources) and Brian Reich (NCSU Dept of Statistics).

Additional Information

ArcGIS Service Definition Extension

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Citation Extension

citationTypevector digital data
parts
typeFGDC Metadata Citation Facet
valueRemove This Facet To Recreate From Metadata File

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