The cost of a meal: factors influencing prey profitability in Australian fur seals
Bibliographic record
Abstract
Knowledge of the factors shaping the foraging behaviour of species is central to understanding their ecosystem role and predicting their response to environmental variability. To maximise survival and reproduction, foraging strategies must balance the costs and benefits related to energy needed to pursue, manipulate, and consume prey with the nutritional reward obtained. While such information is vital for understanding how changes in prey assemblages may affect predators, determining these components is inherently difficult in cryptic predators. The present study used animal-borne video data loggers to investigate the costs and benefits related to different prey types for female Australian fur seals ( Arctocephalus pusillus doriferus ), a primarily benthic foraging species in the low productivity Bass Strait, south-eastern Australia. A total of 1,263 prey captures, resulting from 2,027 prey detections, were observed in 84.5 h of video recordings from 23 individuals. Substantial differences in prey pursuit and handling times, gross energy gain and total energy expenditure were observed between prey types. Importantly, the profitability of prey was not significantly different between prey types, with the exception of elasmobranchs. This study highlights the benefit of animal-borne video data loggers for understanding the factors that influence foraging decisions in predators. Further studies incorporating search times for different prey types would further elucidate how profitability differs with prey type.
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How this classification was reachedexpand
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 | 0.000 |
| 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 teacher head, 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".