Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity

During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noi...

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Main Authors: Leigh G. Torres, Sharon L. Nieukirk, Leila Lemos, Todd E. Chandler
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-09-01
Series:Frontiers in Marine Science
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fmars.2018.00319/full
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author Leigh G. Torres
Sharon L. Nieukirk
Leila Lemos
Todd E. Chandler
author_facet Leigh G. Torres
Sharon L. Nieukirk
Leila Lemos
Todd E. Chandler
author_sort Leigh G. Torres
collection DOAJ
description During traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance.
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spelling doaj.art-23746e33c90944448f4e13f8322d35172022-12-22T01:06:21ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452018-09-01510.3389/fmars.2018.00319394495Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational CapacityLeigh G. Torres0Sharon L. Nieukirk1Leila Lemos2Todd E. Chandler3Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, Newport, OR, United StatesCooperative Institute for Marine Resources Studies, Oregon State University and Pacific Marine Environmental Laboratory, National Oceanic and Atmospheric Administration, Newport, OR, United StatesGeospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, Newport, OR, United StatesGeospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, Department of Fisheries and Wildlife, Hatfield Marine Science Center, Oregon State University, Newport, OR, United StatesDuring traditional boat-based surveys of marine megafauna, behavioral observations are typically limited to records of animal surfacings obtained from a horizontal perspective. Achieving an aerial perspective has been restricted to brief helicopter or airplane based observations that are costly, noisy, and risky. The emergence of commercial small unmanned aerial systems (UAS) has significantly reduced these constraints to provide a stable, relatively quiet, and inexpensive platform that enables replicate observations for prolonged periods with minimal disturbance. The potential of UAS for behavioral observation appears immense, yet quantitative proof of utility as an observational tool is required. We use UAS footage of gray whales foraging in the coastal waters of Oregon, United States to develop video behavior analysis methods, determine the change in observation time enabled by UAS, and describe unique behaviors observed via UAS. Boat-based behavioral observations from 53 gray whale sightings between May and October 2016 were compared to behavioral data extracted from video analysis of UAS flights during those sightings. We used a DJI Phantom 3 Pro or 4 Advanced, recorded video from an altitude ≥25 m, and detected no behavioral response by whales to the UAS. Two experienced whale ethologists conducted UAS video behavioral analysis, including tabulation of whale behavior states and events, and whale surface time and whale visible time (total time the whale was visible including underwater). UAS provided three times more observational capacity than boat-based observations alone (300 vs. 103 min). When observation time is accounted for, UAS data provided more and longer observations of all primary behavior states (travel, forage, social, and rest) relative to boat-based data, especially foraging. Furthermore, UAS enable documentation of multiple novel gray whale foraging tactics (e.g., headstands: n = 58; side-swimming: n = 17; jaw snapping and flexing: n = 10) and 33 social events (nursing and pair coordinated surfacings) not identified from boat-based observation. This study demonstrates the significant added value of UAS to marine megafauna behavior and ecological studies. With technological advances, robust study designs, and effective analytical tools, we foresee increased UAS applications to marine megafauna studies to elucidate foraging strategies, habitat associations, social patterns, and response to human disturbance.https://www.frontiersin.org/article/10.3389/fmars.2018.00319/fullunmanned aerial systems (UAS)behaviorgray whaleforagingcetacean
spellingShingle Leigh G. Torres
Sharon L. Nieukirk
Leila Lemos
Todd E. Chandler
Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
Frontiers in Marine Science
unmanned aerial systems (UAS)
behavior
gray whale
foraging
cetacean
title Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
title_full Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
title_fullStr Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
title_full_unstemmed Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
title_short Drone Up! Quantifying Whale Behavior From a New Perspective Improves Observational Capacity
title_sort drone up quantifying whale behavior from a new perspective improves observational capacity
topic unmanned aerial systems (UAS)
behavior
gray whale
foraging
cetacean
url https://www.frontiersin.org/article/10.3389/fmars.2018.00319/full
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AT sharonlnieukirk droneupquantifyingwhalebehaviorfromanewperspectiveimprovesobservationalcapacity
AT leilalemos droneupquantifyingwhalebehaviorfromanewperspectiveimprovesobservationalcapacity
AT toddechandler droneupquantifyingwhalebehaviorfromanewperspectiveimprovesobservationalcapacity