Sexual segregation of seasonal foraging habitats in a non-migratory marine mammal
Bibliographic record
Abstract
Many animal species segregate by sex. Such segregation may be social in nature, or ecological, or both. Grey seals (Halichoerus grypus), like many large mammals, are sexually size dimorphic. In size dimorphic species, allometric differences in morphology, metabolic rate and reproductive costs are likely. Such differences may require the sexes to use different foraging strategies or different habitats. To investigate sexual segregation of habitat in grey seals, we used satellite tracks from 95 (male 46; female 49) adults breeding at Sable Island, Nova Scotia (44 degrees N, 60 degrees W) collected from 1995 to 2005. Location estimates were made from satellite fixes using a state-space movement model to estimate true locations and regularize them in time. Location estimates were used to calculate home range kernels of male and female habitat use each month. Month by sex kernel home ranges revealed striking differences and dynamics in habitat use between males and females on spatial scales broader than most terrestrial examples and at temporal and spatial resolutions rarely available for marine species. Differences were most pronounced just before (October-December) and immediately after breeding (February-March). During both periods, males primarily used areas along the continental shelf break, while females mainly used mid-shelf regions. Coupled with previously identified sex-specific seasonal patterns of energy storage, diving and diet, our findings suggest that males and females differ profoundly in their spatial foraging strategies. These differences may serve to maximize fitness by reducing intersexual competition during key foraging periods.
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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".