Mapping the Distribution, Abundance, and Risk Assessment of Marine Birds in the Northwest Atlantic

• Activity Number: 645
• Type: Contributed
• Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics and the Environment
• Author(s): Earvin Balderama*+ and Beth Gardner and Brian J. Reich
• Companies: NC State University and NC State University and North Carolina State University
• Keywords: Conditional autoregressive models ; Ecology ; Sea birds ; Space-time models

Abstract

A multi-scale approach is used to develop models for the spatio-temporal distribution and abundance of sea birds to identify sensitive and high-use areas in need of protection. With data taken from past and ongoing survey efforts, we provide abundance and density estimates for marine birds over a wide geographical area during multiple years. Biophysical covariates (e.g., bathymetry, chlorophyll, sea surface temperature) are used as a proxy for the variability in food resources that influence where birds occur. For sea bird count data, the natural model to consider is an auto-Poisson conditional specification. Spatial correlation is incorporated in this model explicitly with the conditional auto regressive (CAR) model. Mixture models incorporating the CAR prior are also considered. We provide risk maps of predictive sea bird relative abundances. Spatial extremes of distributions are examined and maps are accompanied by estimates of uncertainty.