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Analyzing whale calls through spatiotemporal exciting processes

Abstract Number:

3531 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Bokgyeong Kang (1), Erin Schliep (2), Alan Gelfand (1), Robert Schick (3)

Institutions:

(1) Duke University, Durham, NC, (2) North Carolina State University, Raleigh, NC, (3) Southall Environmental Associates, Aptos, CA

Co-Author(s):

Erin Schliep  
North Carolina State University
Alan Gelfand  
Duke University
Robert Schick  
Southall Environmental Associates

First Author:

Bokgyeong Kang  
Duke University

Presenting Author:

Bokgyeong Kang  
N/A

Abstract Text:

Sound is the primary mode of communication among many marine species. To better understand the communication process, we propose a new spatiotemporal mutually exciting process model consisting of background and countercall processes over an array of monitors. The background process describes the intensity of contact calls and provides inference for the diurnal patterns of and impact of noise on animals' acoustic behavior. The countercall process accounts for the potential self-excitement. We fit the model in a hierarchical Bayes framework. We consider model adequacy, extending the random time change theorem to a fully Bayesian modeling setting and model comparison through the posterior log-likelihood. We study calls made by North Atlantic right whales, an endangered large baleen whale, in Cape Cod Bay in MA in the US. We find strong evidence of mutual excitement. Further, we find evidence that whales are likely to remain quiet in the presence of loud noises, make calls during twilight hours, and respond to other whales nearby.

Keywords:

Gaussian process|Markov chain Monte Carlo|North Atlantic right whales|random time change theorem|spatial process|temporal point patterns

Sponsors:

Section on Statistics and the Environment

Tracks:

Ecology

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