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Predicted Annual Probability of Observing at least One Great Shearwater

Dates

Release Date
2015
Date Collected
2002
Date Collected
2010

Citation

Predicted Annual Probability of Observing at least One Great Shearwater: .

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 Shearwater (Puffinus gravis) throughout [...]

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Attached Files

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mb_GRSH_p1.zip 592.45 KB application/zip
Extension: great_shearwater.zip
thumbnail.png thumbnail 7.36 KB

Purpose

This map depicts the mean predicted probability of observing at least one individual Great Shearwater (Puffinus gravis) 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

Spatial Services

ArcGIS Mapping Service

WMS Service

Communities

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

Associated Items

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Provenance

Data source
Input directly
Earvin Baladerama (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

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