Activity‐specific metabolic rates for diving, transiting, and resting at sea can be estimated from time–activity budgets in free‐ranging marine mammals
Bibliographic record
Abstract
Abstract Time and energy are the two most important currencies in animal bioenergetics. How much time animals spend engaged in different activities with specific energetic costs ultimately defines their likelihood of surviving and successfully reproducing. However, it is extremely difficult to determine the energetic costs of independent activities for free‐ranging animals. In this study, we developed a new method to calculate activity‐specific metabolic rates, and applied it to female fur seals. We attached biologgers (that recorded GPS locations, depth profiles, and triaxial acceleration) to 12 northern (Callorhinus ursinus) and 13 Antarctic fur seals (Arctocephalus gazella), and used a hierarchical decision tree algorithm to determine time allocation between diving, transiting, resting, and performing slow movements at the surface (grooming, etc.). We concomitantly measured the total energy expenditure using the doubly‐labelled water method. We used a general least‐square model to establish the relationship between time–activity budgets and the total energy spent by each individual during their foraging trip to predict activity‐specific metabolic rates. Results show that both species allocated similar time to diving (~29%), transiting to and from their foraging grounds (~26–30%), and resting (~8–11%). However, Antarctic fur seals spent significantly more time grooming and moving slowly at the surface than northern fur seals (36% vs. 29%). Diving was the most expensive activity (~30 MJ/day if done non‐stop for 24 hr), followed by transiting at the surface (~21 MJ/day). Interestingly, metabolic rates were similar between species while on land or while slowly moving at the surface (~13 MJ/day). Overall, the average field metabolic rate was ~20 MJ/day (for all activities combined). The method we developed to calculate activity‐specific metabolic rates can be applied to terrestrial and marine species to determine the energetic costs of daily activities, as well as to predict the energetic consequences for animals forced to change their time allocations in response to environmental shifts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".