Geospatial Ecology of Marine Megafauna Laboratory

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

Investigators: Dr. Leigh Torres, Dr. KC Bierlich, Clara Bird, Dr. 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.

Current projects:

• In collaboration with the Innovation Lab (iLab) and Dr. Mauricio Cantor, we are developing an inexpensive LiDAR (laser altimeter) housing that can be transferable across different off-the-shelf drones
• Assessing measurement errors introduced from animal body position and depth
• Evaluating how weather influences the accuracy of altitude recorded by barometers
• GRANITE: Gray whale Response to Ambient Noise Informed by Technology and Ecology
• AMBER: Assessing morphometric and behavior of Eschrichtius Robustus  
• SAPPHIRE: Synthesis of Acoustics, Physiology, Prey, and Habitat in Rapidly changing Environments

Publications:

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-Populatio.

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

 

Blogs: 

• The many dimensions of a fat whale: Using drones to measure the body condition of baleen whales
• Drones with laser: almost as cool as “sharks with laser beams attached to their heads"
• Memoirs from above: drone observations of blue, humpback, Antarctic minke, and gray whales
• Little whale, big whale, swimming in the water: A quick history on how aerial photogrammetry has revolutionized the ability to obtain non-invasive measurements of whales
• More blogs about our work using drones to study whales

 

Media:

• Three years of monitoring of Oregon’s gray whales shows changes in health
• Researchers say climate change is impacting diet of whales
• Surface feeding could provide more than just snacks for New Zealand blue whales
• The scientists who study whale "defecation events"
• Researcher Uses Drones To Learn How Whales Respond To Noise Pollution
• Drone Footage Captures The Insane Moment A Gray Whale Takes A Giant Poop
• New video shows how blue whales employ strategy before feeding
• New technologies – and a dash of whale poop – help scientists monitor whale health

 

Software: 

MorphoMetriX

Source: Torres, W.I., and Bierlich, K.C (2020). MorphoMetriX: a photogrammetric measurement GUI for morphometric analysis of megafauna.. Journal of Open Source Software, 4(44), 1825. https://doi.org/10.21105/joss.01825

CollatriX

Source: Bird, C.N., and Bierlich, K.C. (2020). CollatriX: A GUI to collate MorphoMetriX outputs. Journal of Open Source Software, 5(51), 2328. https://doi:10.21105/joss.02328

Incorporating Photogrammetric Uncertainty

Bierlich, K. C., Schick, R. S., Hewitt, J., Dale, J., Goldbogen, J. A., Friedlaender, A. S., & Johnston, D. W. (2020). Data and scripts from: A Bayesian approach for predicting photogrammetric uncertainty in morphometric measurements derived from UAS. Duke Research Data Repository. V2 https://doi.org/10.7924/r4sj1jj6s

Uncertainty associated with photogrammetry-based body condition

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. doi: 10.3389/fmars.2021.749943  

Whale photogrammetry analysis code

Source: Appendix S2 from Burnett, J. D., L. Lemos, D. Barlow, M. G. Wing, T. Chandler, and L. G. Torres. Estimating morphometric attributes of baleen whales with photogrammetry from small UASs: A case study with blue and gray whales. Marine Mammal Science. https://doi.org/10.1111/mms.12527

Whale photogrammetry tutorial video

 

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