MAR Lab uses analytical methods to work on interdisciplinary questions related to animal behavior and communication with a focus on acoustic methods.  These range from detecting and characterizing animal calls to determining how the calls are used in various behavioral and environmental contexts.  This work has numerous applications in the study of ecosystems, population estimation, and mitigating the effects of human activities on animals.

Our work on detection and classification has focused on calls from toothed whales, and we have developed software to detect echolocation clicks and whistles as well as supervised learning methods to classify these calls to determine species.  These methods can be used in context to learn about animal distribution or to better understand interactions with natural and human-generated phenomena.

We use unsupervised learning methods to better understand differences between populations, develop methods for surveying remote and understudied areas, and to address questions of communication.

Finally, we believe that studying species that live in habitats that have underlying mechanisms that drive population success at decadal-long time scales or longer requires the establishment of flexible representations of acoustic descriptions of natural sounds and to that end we are leading the development of national standards on ways to represent sounds in the animal kingdom as well as the human-generated and natural sounds around them.

We are part of the Scripps Institution of Oceanography Marine Acoustics Laboratories and collaborate with a variety of institutions including Cornell University, NOAA’s National Marine Fisheries Science Centers, Oregon State University, and The University of California Los Angeles.

Our work has been supported by the following agencies and programs:

  • US Office of Naval Research (Dr. Michael Weiss)
  • US Bureau of Ocean Energy Management (Drs. Jill Lewandowski and Jim Price)
  • National Oceanographic Parnership Program (ONR/BOEM)
  • US Navy Living Marine Resource Program (Dr. Anu Kumar)
  • US National Science Foundation subaward from HPWREN (Mr. Hans-Werner Braun, UCSD)