Open Collections

Colson, Kate M.

University of British Columbia

Biologging tags that record high-resolution tri-axial accelerometry data are proving to be integral to the study of foraging ecology of large, free-roaming marine mammals, such as whales. They have been applied to a number of baleen whale species that feed pelagically through lunges or ram filtration to quantitatively define behaviours and estimate energetic costs. However, few behavioural ecology studies using accelerometry data have been conducted on grey whales, a unique baleen whale that performs benthic suction feeding. Using suction cup tri-axial accelerometer tag deployments on 10 Pacific Coast Feeding Group (PCFG) grey whales along the Oregon and Washington coasts, I defined signals of foraging behaviour at both the broad state (dive) and foraging tactic (roll event) scales. I then estimated the relative energetic cost of these behaviours using energy expenditure proxies derived from the accelerometry data—Overall Dynamic Body Acceleration (ODBA; ms⁻²), stroke rate (Hz), stroke amplitude (radians per s), and duration of dives with different foraging tactics performed (min). Hidden Markov Models (HMMs) defined three biologically distinct states—forage, search, and transit—using turn angle, dive duration, dive tortuosity and presence of roll events. Classification and Regression Tree (CART) models best defined the foraging tactics of headstands, benthic digs, and side swims using median pitch, depth to body length ratio, and absolute value of the median roll. These definitions of grey whale foraging signals using accelerometry data add to the quantitative descriptions of foraging behaviours previously described for baleen whales. Stroke rate identified foraging and headstanding as being the most energetically costly activities at the broad state and foraging tactic scales. These findings contribute to the foundational understanding of grey whale foraging energetics needed to assess the impacts of various conservation concerns on the fitness and interpret patterns of behaviour choice of this unique group of grey whales.

Text; Moving Image

2023-08-29

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/85655

Oceans and Fisheries

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/