Low resolution accelerometers can be used to develop time-energy budgets of wild fur seals from captive surrogates
- Published
- Accepted
- Subject Areas
- Animal Behavior, Ecology, Marine Biology, Data Mining and Machine Learning
- Keywords
- Accelerometer, otariid, activity budget, time-energy budget, fitness, daily energy expenditure (DEE), machine learning
- Copyright
- © 2018 Ladds et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. Low resolution accelerometers can be used to develop time-energy budgets of wild fur seals from captive surrogates. PeerJ Preprints 6:e26570v1 https://doi.org/10.7287/peerj.preprints.26570v1
Abstract
Background. Accurate time-energy budgets summarise an animal’s energy expenditure in a given environment and are potentially a sensitive indicator of how an animal responds to changing resources. Deriving accurate time-energy budgets requires a precise measure of time spent in different activities, and an estimate of the energetic cost of that activity. Bio-loggers such as accelerometers may provide a solution for monitoring animals such as fur seals that make long-duration foraging trips over multiple days or weeks. Monitoring such behaviour may require low resolution recording due to the memory constraints of bio-loggers. The aim of this study was to evaluate if accelerometers recording at a low resolution could accurately classify and determine the cost of fur seal activity.
Methods. Diving and movement data were collected from nine wild juvenile Australian fur seals equipped with tri-axial accelerometers. To validate time-energy budgets for the fur seals, energy consumption during a range of behaviours was determined from twelve captive surrogates. The time wild fur seals spent in four behavioural states - foraging, grooming, travelling and resting - was quantified with low- and high-resolution data from accelerometers using gradient boosting models (GBM). The daily energy expenditure (DEE) from these four activities was estimated using a relatively simple energetics model developed using their location (land, surface or underwater) and estimates of the energetic cost of each behaviour. Models developed from captive seals were applied to accelerometry data collected from wild juvenile Australian fur seals and their time-energy budgets were reconstructed.
Results. Low resolution accelerometery was better at classifying fur seal behaviour over long durations than high resolution accelerometry in captive surrogates. The low resolution model was therefore applied to wild data. This revealed that Juvenile fur seals expended more energy than adults of similar species, but there was no significant difference in DEE across sex or season (winter or summer). Juvenile fur seals used behavioural compensatory techniques to conserve energy during activities that were expected to have high energetic outputs (such as diving).
Discussion. Behaviours that are displayed over a long duration can be captured accurately by low-resolution accelerometry and these models can be used to develop time-energy budgets of wild animals. In this study we were able to use such models to monitor juvenile fur seals over multiple foraging trips. This revealed that juvenile fur seals appear to be working energetically harder than their adult counterparts, likely due to the relative novelty of diving and foraging, their smaller body size and the additional cost of growth they sustain. Developing time-energy budgets from accelerometers is an efficient method of estimating energy expenditure from individuals over time.
Author Comment
This is a submission to PeerJ for review.
Supplemental Information
Summary statistics of daily energy expenditure (DEE MJ d-1) and dive trip details for nine juvenile Australian fur seals
Fur seal details and average, standard deviation, minimum and maximum DEE for the length of deployment.
Details of the calculations and assumptions for the energetic models
An example of 12 hours of diving from a 40kg juvenile Australian fur seal
Panels show VeDBA, raw acceleration, location (underwater or surface), behaviour category (travelling, resting, foraging, grooming) and depth.
