The ecology of 3‐D space use in a sexually dimorphic mammal
Bibliographic record
Abstract
The distribution of animals is the result of habitat selection according to sex, reproductive status and resource availability. Little is known about how marine predators investigate their 3‐dimensional space along both the horizontal and vertical axes and how temporal variation affects space use. In this study, we assessed the spatio‐temporal movement of a sexually dimorphic marine mammal, the grey seal Halichoerus grypus by 1) determining seasonal home range size, 2) testing whether space use of seals was affected by water depth, and 3) investigating the vertical movement of seals according to the maximum depth of each dive. Between 1993 and 2005, we fitted 49 grey seals in the Gulf of St. Lawrence with satellite transmitters. We estimated seasonal 95% fixed‐kernel home ranges for each individual. For each seal, we tested for selectivity and preference for 4 water depth classes at the home range scale and within the home range. We also evaluated the proportional number of dives made in each water depth classes according to the maximum depth of each dive. Home ranges were 10 times larger in winter than in summer. Seals generally selected habitats <50 m deep. They also mainly dove to depths of 40 m or less. At both scales of selection, preference for shallow areas decreased in winter. We also observed that adults used shallow habitats more than juveniles to establish their home range. A spatial segregation based on sex also occurred at the finer scale of selection where females were more concentrated in the shallowest parts of their home range than males. Segregation in space use according to age and sex classes occurred at both the horizontal and vertical scales. Our results emphasise the importance of studying habitat selection of marine predators in 3‐dimensional space, in addition to the temporal scale.
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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 | 0.000 |
| 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".