Predictive Spatial Analysis of Marine Mammal Habitats
Abstract
We developed a data management, statistical modeling and decision support system describing habitat use of marine mammals in the North Atlantic and Gulf of Mexico. Our objective was to make this information available in a comprehensive manner to environmental planners and decision makers in the Navy and elsewhere. The system uses data on the distribution of marine mammals from dedicated surveys contained in the online OBIS-SEAMAP marine data archive. We used these data to develop predictive habitat models for guilds of marine mammals in these two regions. We delivered model outputs in an online, flexible Spatial Decision Support System (SDSS). The SDSS is a browser-based, interactive mapping application that enables users to view model results with original survey effort and marine mammal observations. In total, we generated 33 models, representing 16 cetacean guilds, using environmental data from the JPL physical oceanographic data archive. Predictive maps for the likelihood of encounter with marine mammals comprise the results, along with estimates of standard errors.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2010
- Accession Number
- ADA520623
Entities
People
- Andrew Read
- Benjamin Best
- Caroline Good
- Ei Fujioka
- Erin Labrecque
- Lucie Hazen
- Patrick Halpin
- Robert S Schick
- Song Qian
Organizations
- Duke University