Beaked Whale Habitat Characterization and Prediction
Abstract
The objective of this study was to characterize known beaked whale habitat and create a predictive beaked whale habitat model of the Gulf of Mexico and east coast of the United States using available beaked whale sighting data in combination with bathymetry and remotely sensed oceanographic data. To accomplish this objective, three specific tasks were required: establish a sighting and stranding database in a Geographic Information System framework, create a database of oceanographic data on a corresponding spatial and temporal scale, and create/optimize a spatial statistical model for predicting beaked whale presence and absence. Beaked whale habitat optimal classification rates varied from 73.3% to 81.3% for the static models and from 75.5% to 80.3% for the dynamic models of each study area. The classification rate for correctly predicting beaked whale presence ranged from 79.3% to 100.0% for the static models and 85.7% to 94.5% for the dynamic models. Beaked whale habitat prediction has been demonstrated as a promising and effective statistical technique for defining beaked whale habitat in regions where minimal or incomplete survey coverage exists.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 2005
- Accession Number
- ADA443533
Entities
People
- Amy M. Farak
- Ellen P. Keane
- Glenn H. Mitchell
- Jessica A. Ward
Organizations
- Naval Undersea Warfare Center