.jpg)
Photo Credit: ©Neil Hammerschlag
Scientific Frontline: Extended "At a Glance" Summary: Ocean Forecasting with Shark-Borne Sensors
The Core Concept: The integration of electronically tagged marine predators, such as sharks, as mobile sensors to collect subsurface ocean temperature and depth data for improving the accuracy of seasonal climate models.
Key Distinction/Mechanism: Unlike traditional stationary or conventional ocean observing tools that often miss rapidly changing regions, this method leverages the natural movement of marine predators through dynamic, data-poor areas (like fronts and eddies) to transmit real-time, in-situ location, depth, and temperature data directly into forecast models.
Major Frameworks/Components:
- Animal-Borne Satellite Tags: Advanced sensors attached to sharks that record and transmit depth, temperature, and highly accurate location data throughout the water column.
- Seasonal Climate Modeling: The computational frameworks used to predict ocean conditions, which saw up to a 40 percent reduction in surface forecast errors when integrating the shark-derived data.
- In-Situ Observation Systems: The broader network of direct environmental data collection, which is expanded and complemented by the mobile nature of tagged marine life.
Branch of Science: Oceanography, Marine Ecology, Climate Science, and Atmospheric Science.
Future Application: The potential operational scale-up of using various marine species to fill critical observational gaps, ultimately supporting proactive climate adaptation planning, safer marine operations, and more resilient seafood supply chains.
Why It Matters: Forecasts are often least reliable in dynamic coastal and shelf regions. By improving prediction accuracy, this research directly reduces uncertainty for fisheries management and helps coastal communities better respond to climate variability and changing ocean conditions.
.jpg)
Photo Credit: ©Neil Hammerschlag
Interdisciplinary collaboration fuels innovation
The idea of using sharks as ocean observers grew out of an interdisciplinary collaboration that connected marine ecology with climate science between former Rosenstiel School shark scientist Neil Hammerschlag and atmospheric scientist Ben Kirtman, now dean of the Rosenstiel School. In 2018, they recognized that the data from shark-tagging studies used by Hammerschlag’s lab to study shark ecology could also benefit climate modeling. McDonnell, who began her doctoral studies that same year, was drawn to the project by the opportunity to bridge biology, oceanography, and climate science — exploring how tagging data could help answer questions beyond its usual ecological scope.
Satellite tags attached to sharks record depth and temperature as they travel through the ocean, collecting and transmitting this data in near real time. While these tags have long helped scientists track shark movements, the collaboration opened a new application and a chance to create a novel proof of concept: using the same data to improve ocean forecast.models.
“Marine predators like sharks naturally seek out dynamic ocean features such as fronts and eddies,” said Kirtman. “These are areas where models often lack sufficient observations.”
Testing sharks as ocean observers
McDonnell and Hammerschlag, working closely with WHOI oceanographer and study co-author Camrin Braun along with a local fisherman, tagged 18 blue sharks (Prionace glauca) and one shortfin mako shark (Isurus oxyrinchus) in the Northwest Atlantic. Over the next 6 months, the sharks transmitted more than 8,200 temperature-depth profiles across a wide range of locations and depths—down to nearly 2,000 meters (approximately 6,500 feet).
“Key to this study was repurposing a more advanced tag capable of transmitting location data along with temperature and depth information,” said Hammerschlag, co-author of the study and Executive Director of the Shark Research Foundation. “This allowed us to link subsurface ocean conditions directly to specific locations with known accuracy.”
The team compared observed ocean temperatures with forecasted temperatures from models with and without shark-derived data.
The results showed measurable improvements in forecast performance, particularly in dynamic coastal and shelf regions that are important for marine ecosystems and fisheries.
“Tagged sharks won’t replace conventional observing systems,” added McDonnell. “These preliminary results show that tagged marine predators can provide complementary in-situ observations as they move throughout the water column.”
Accurate ocean forecasts are critical for fisheries management, marine operations, and understanding how climate variability affects coastal communities. However, forecasts are often least reliable in regions where conditions change rapidly and observational data are lacking.
Animal-borne sensors could enhance predictions that support decision-making across multiple sectors, from seafood supply chains to climate adaptation planning.
“For fisheries and coastal communities, small improvements in ocean forecasts can make a big difference,” said Braun. “Reducing uncertainty helps people plan, whether that’s where to fish, how to manage resources, or how to respond to changing conditions.”
Funding: Funding for the research was provided by Cisco Systems, the University of Miami Abess Center, the NASA Biological Diversity and Ecological Conservation Program, NOAA, NSF, and the Robert L. James Early Career Scientist Chair at Woods Hole Oceanographic Institution.
Published in journal: npj Climate and Atmospheric Science
Title: Improved seasonal climate forecasting using shark-borne sensor data in a dynamic ocean
Authors: Laura H. McDonnell, Ben P. Kirtman, Camrin D. Braun, and Neil Hammerschlag
Source/Credit: Woods Hole Oceanographic Institution
Reference Number: es043026_01
.jpg)