Applying drones and developing novel tools to assess whale behavior, morphology, and body condition

Investigators: Dr. Leigh Torres,  Dr. KC Bierlich, Clara Bird, Dawn Barlow, Todd Chandler

From our traditional boat-based horizontal perspective, cetacean behavioral observations are typically limited to when the animal is at the surface, and health assessment is constrained to photographs captured of this limited body view. Previously, achieving an aerial perspective has been restricted to brief helicopter- or plane-based observations that are costly, noisy, and risky. The emergence of commercial drones (also called Unoccupied Aircraft Systems, UAS) has significantly reduced these constraints, and provide a stable, relatively quiet, and inexpensive platform that enables replicate cetacean observations for prolonged periods with minimal disturbance. With the imminent proliferation of using drones in cetacean studies comes the need for robust quantitative methods of image analysis.

The GEMM Lab has been pioneering the use of UAS technology to study marine mammal health and behavior. Since 2015 we have conducted drone flights over gray whales in Oregon and Alaska and pygmy blue whales in New Zealand to document behavior and assess body condition through photogrammetry. Through these efforts we have developed new analytical methods that allow robust quantification and comparability of metrics. This also includes developing open-source hardware and software packages designed to help researchers obtain accurate measurements. We continue to employ these methods across projects, compare methodological approaches, and evaluate sources contributing to photogrammetric error. We also link these datasets with multiple habitat quality measurements to gain a better understanding of the impacts due to disturbance events and environmental change. As new technologies emerge, we look for new applications to help us non-invasively study multiple marine megafauna species to better assess their health in changing oceans.

The GEMM Lab is partnering with the Marine Mammal Institute’s Center of Drone Excellence (CODEX), which focuses on developing analytical methods for using drones to non-invasively monitor marine mammal populations. CODEX has developed several open-source hardware and software tools, including automated tools, to help researchers obtain high-quality morphological measurements of marine mammals from drone imagery with greater speed and accuracy. See this blog for an overview of some of these tools.

See CODEX hardware and software.

 

Current projects:

Blogs: 

 

Publications:

Pirotta, E., Bierlich, K. C., New, L., Hildebrand, L., Bird, C. N., Fernandez Ajó, A., & Torres, L. G. (2024). Modeling individual growth reveals decreasing gray whale body length and correlations with ocean climate indices at multiple scales. Global Chanhttps://doi.org/10.1111/gcb.17366

Bierlich, K. C., Karki, S., Bird, C. N., Fern, A., & Torres, L. G. (2024). Automated body length and body condition measurements of whales from drone videos for rapid assessment of population health. Marine Mammal Science, e13137. https://doi.org/10.1111/mms.13137

 Bierlich, K., Wengrove, D., Bird, C. N., Davidson, R., Chandler, T., Torres, L. G., & Cantor, M. (2023). LidarBoX: a 3D-printed, open-source altimeter system to improve photogrammetric accuracy for off-the-shelf drones. Drone Systems and Applications. https://doi.org/10.1139/dsa-2023-0051

Bierlich, K. C., Kane, A., Hildebrand, L., Bird, C. N., Fernandez Ajo, A., Stewart, J. D., Hewitt, J., Hildebrand, I., Sumich, J., & Torres, L. G. (2023). Downsized: gray whales using an alternative foraging ground have smaller morphology. Biology Lettershttps://doi.org/10.1098/rsbl.2023.0043

Torres, L.G., Bird, C.N., Rodriguez-Gonzalez, F., Christiansen, F., Bejder, L., Lemos, L., Urban, J.R., Swartz, S., Willoughby, A., Hewitt, J., and Bierlich, K.C. (2022). Range-Wide Comparison of Gray Whale Body Condition Reveals Contrasting Sub-Population.

Bierlich, K.C., Hewitt, J., Bird, C.N., Schick R.S., Friedlaender, A.S., Torres, L.G., Dale, J., Goldbogen, J.A., Read, A., Calambokidis J., Johnston, D.W., (2021). Comparing uncertainty associated with 1-, 2-, and 3D aerial photogrammetry-based body condition measurements of baleen whales. Frontiers in Marine Science. 8:749943. 

Savoca, M. S. Czapanskiy, M. F., Kahane-Rapport, S. R., Gough, W. T., Falhbusch, J. A., Bierlich, K. C., Segre, P. S., Di Clemente, J., Penry G. S., Wiley, D. N., Calambokids, J., Nowacek, D. P., Johnston, D. W., Pyenson, N. D., Friedlaender, A. S., Hazen, E. L., & Goldbogen, J.A. (2021). Baleen whale prey consumption based on high-resolution foraging measurements. Nature, 599, 85–90.

Bierlich, K.C., Schick, R.S., Hewitt, J., Dale, J., Goldbogen, J.A., Friedlaender, A.S., Johnston D.J. (2021). A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. Marine Ecology Progress Series. 

Lemos, L. S., Olsen, A., Smith, A., Burnett, J. D., Chandler, T. E., Larson, S., Hunt, K. E., Torres, L. G. (2021). Stressed and slim or relaxed and chubby? A simultaneous assessment of gray whale body condition and hormone variability. Marine Mammal Science.

Bird, C.N., and Bierlich, K.C. (2020). CollatriX: A GUI to collate MorphoMetriX outputs. Journal of Open Source Software, 5(51), 2328.

Torres, W.I., & Bierlich, K.C. (2020). MorphoMetriX: a photogrammetric measurement GUI for morphometric analysis of megafauna. Journal of Open Source Software, 5(45), 1825.

Lemos, L., Burnett, J. D., Chandler, T. E., Sumich, J. L., and Torres, L. G. (2020). Intra‐and inter‐annual variation in gray whale body condition on a foraging ground. Ecosphere, 11(4), e03094.

Torres L.G., Barlow D.R., Chandler T.E., Burnett J.D. (2020) Insight into the kinematics of blue whale surface foraging through drone observations and prey data. PeerJ 8:e8906.

Torres, L. G., S. Nieukirk, L. Lemos, and T. Chandler (2018). Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Frontiers in Marine Science, 5, 319.

Burnett, J. D., L. Lemos, D. Barlow, M. G. Wing, T. Chandler, and L. G. Torres (2018). Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales. Marine Mammal Science. doi:10.1111/mms.12527

 

Media:

 

Project Collaborators:

Innovation Lab (iLab)

Dr. Mauricio Cantor

Dr. Josh Hewitt

Dr. Leila Lemos

Dr. Jon Burnett

Duke University Marine Robotics and Remote Sensing Lab (MaRRS) Lab

We are using drones and developing new tools and methods to help obtain accurate morphological measurements of marine megafauna to better monitor the health of populations in changing oceans.