The proposed project will look for acoustic and environmental cues associated with mses that could be used in the development of an advance warning system, to improve stranding outcomes

Project Grant Award Summary

The National Oceanic and Atmospheric Administration (NOAA) awarded Woods Hole Oceanographic Institution $133,417 under the Marine Mammal Data Program (CFDA 11.439) for a one-year project period (October 1, 2025–September 30, 2026). The institution will develop a predictive model for mass stranding events (MSEs) in marine mammals by analyzing acoustic and environmental data collected over approximately 10 years, with continued data collection during the award period. The primary deliverable is a quantitative model incorporating both acoustic and environmental variables that could inform the development of an advance warning system for MSEs to improve stranding response outcomes and animal welfare.

As a secondary objective, the project includes in-depth analysis of dolphin vocal behavior and communication signals in pre-stranding versus non-stranding contexts, focusing on Atlantic white-sided dolphins and common dolphins that typically mass strand in Wellfleet, Massachusetts. This acoustic behavioral analysis aims to identify stress indicators or health correlates that may provide insights into the underlying causes of MSEs. The work is conducted at Woods Hole, Massachusetts, and represents Phase 1 of a multi-component research initiative, with future phases planned to incorporate the predictive model into a real-time acoustic alert system.

In addition, in-depth analysis of dolphin vocal behavior prior to mses could potentially enhance our understanding of these mysterious events. The proposed work would have significant value toward improving both our understanding of these events and welfare outcomes. The proposed work consists of several components, and funding for the first of these is requested in this proposal. This first phase involves continued collection of acoustic data, as well as analysis of past (approximately 10 years of duty cycled data) and current data, to look for cues that could be used both to learn about mses and to develop an advance warning system. This component will also involve analysis of possible environmental correlates of mses. The primary goal of this first component of the work, which is the main objective of this project, is to produce a predictive model for mass stranding events that incorporates both acoustic and environmental variables. Future components will incorporate this model into a real-time acoustic mass stranding alert system. A secondary objective of the proposed work is to study features of dolphin signals in pre-stranding VS. Non-prestranding contexts in order to learn more about the communication of species that typically mass strand in wellfleet (atlantic white-sided dolphins, lagenorhynchus acutus, and common dolphins, delphinus delphis), and to potentially glean clues from these signals about stress or other health correlates that might provide insights into causes of mses