NOAA ESRI Grid - predictions of seabird diversity in the New York offshore planning area made by the NOAA Biogeography Branch

This dataset represents seabird diversity predictions from spatial models developed for the New York offshore spatial planning area. This raster was derived from multiple individual species season models. The model also includes spatially-explicit uncertainty estimates represented in another raster dataset. Raster values represent the annual predicted seabird Shannon diversity index. The Shannon index incorporates both presence and relative abundance. Species and groups that were not modeled in any season did not contribute to index calculation.

These seabird diversity predictions were developed to be viewed along with model uncertainty estimates. Together seabird diversity predictions and uncertainty estimates were made to identify seabird hotspots and coldspots. These data are intended to support offshore spatial planning.

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Raster values correspond to estimates of seabird diversity. Estimates are based on a spatial statistical model developed using seabird sighting data. We report diversity as the common Shannon diversity index (H') (Krebs, 1989).

For more information see Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

These data were prepared by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, make any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed in this report, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. Any views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. Although all data have been used by NOAA, no warranty, expressed or implied, is made by NOAA as to the accuracy of the data and/or related materials. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by NOAA in the use of these data or related materials.

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Please reference NOAA/NOS/NCCOS/CCMA/Biogeography Branch when utilizing these data in a report or peer reviewed publication. Additionally, knowledge of how this dataset has been of use and which organizations are utilizing it is of great benefit for ensuring this information continues to meet the needs of the management and research communities. Therefore, it is requested but not mandatory, that any user of this data supply this information to the Project Manager: Charles Menza (charles.menza@noaa.gov)

The accuracy of this raster depends on the source and resolution of the data samples. See the following report for more information: Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

The following reference provides information on omissions, selection criteria, generalization, definitions used, and other rules used to derive the data set: Menza, C., B.P. Kinlan, D.S. Dorfman, M. Poti and C. Caldow (eds.). 2012. A Biogeographic Assessment of Seabirds, Deep Sea Corals and Ocean Habitats of the New York Bight: Science to Support Offshore Spatial Planning. NOAA Technical Memorandum NOS NCCOS 141. Silver Spring, MD. 224 pp.

All users should independently analyze the dataset according to their own needs and standards to determine data usability.