Accelerometers can measure total and activity‐specific energy expenditures in free‐ranging marine mammals only if linked to time‐activity budgets
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Bibliographic record
Abstract
Summary Energy expenditure is an important component of foraging ecology, but is extremely difficult to estimate in free‐ranging animals and depends on how animals partition their time between different activities during foraging. Acceleration data have emerged as a new way to determine energy expenditure at a fine scale but this needs to be tested and validated in wild animals. This study investigated whether vectorial dynamic body acceleration (Ve DBA ) could accurately predict the energy expended by marine predators during a full foraging trip. We also aimed to determine whether the accuracy of predictions of energy expenditure derived from acceleration increased when partitioned by different types of at‐sea activities (i.e. diving, transiting, resting and surface activities). To do so, we equipped 20 lactating northern ( Callorhinus ursinus) and 20 lactating Antarctic fur seals ( Arctocephalus gazella ) with GPS , time‐depth recorders and tri‐axial accelerometers and obtained estimates of field metabolic rates using the doubly labelled water ( DLW ) method. Ve DBA was derived from tri‐axial acceleration, and at‐sea activities (diving, transiting, resting and surface activities) were determined using dive depth, tri‐axial acceleration and travelling speed. We found that Ve DBA did not accurately predict the total energy expended by fur seals during their full foraging trips ( R 2 = 0·36). However, the accuracy of Ve DBA as a predictor of total energy expenditure increased significantly when foraging trips were partitioned by activity and when activity‐specific Ve DBA was paired with time‐activity budgets ( R 2 = 0·70). Activity‐specific Ve DBA also accurately predicted the energy expenditures of each activity independent of each other ( R 2 > 0·85). Our study confirms that acceleration is a promising way to estimate energy expenditures of free‐ranging marine mammals at a fine scale never attained before. However, it shows that it needs to be based on the time‐activity budgets that make up foraging trips rather than being derived as a single measure of Ve DBA applied to entire foraging trips. Our activity‐based method provides a cost‐effective means to accurately calculate energy expenditures of fur seals using acceleration and time‐activity budgets, that can be transfered to studies on other species.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it