Multidecadal changes in home range characteristics of grey seals in a context of environmental changes and population growth in the Northwest Atlantic
Bibliographic record
Abstract
Most marine ecosystems are experiencing increasing cumulative impacts from climate change, fishing, shipping and land-based pollution. The resulting ecosystem responses are challenging to monitor. Studying the space use of top marine predators may provide insight into how these ecosystems react to these impacts. However, natural populations are composed of unique individuals that differ in many ways, including how they use space. Here, we used data from a multidecadal biotelemetry research program on grey seals in the Northwest Atlantic to investigate temporal changes in space use in the context of environmental changes and increasing population size. We quantified temporal changes in monthly home range size, shape and distribution of grey seals in the Gulf of St. Lawrence between 1992 and 2022, while also quantifying interindividual differences. We found that the monthly home ranges of grey seals have increased in size and shifted in distribution over the last 3 decades, indicating that the seals appear to have expanded their space use. We detected individual differences in mean home range characteristics and their level of variability, suggesting that individual identity plays a role in the large-scale space use of grey seals. We also found negative correlations between the mean and level of variability in both home range size and shape, hinting at the potential presence of different tactics within the population. This study highlights how top marine predators can modify their behaviour to adapt to environmental changes and illustrates the importance of considering interindividual differences when exploring population space use patterns.
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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 | 0.000 | 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 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".