Spatial patterns of the humpback whale (Megaptera novaeangliae) and its summer habitat in the North Atlantic Ocean
Bibliographic record
Abstract
The humpback whale (Megaptera novaeangliae) is found in all oceans of the world, migrating between low-latitude breeding grounds in the winter and high-latitude feeding grounds in the summer. In addition to these broad-scale spatial patterns, individuals in the North Atlantic Ocean exhibit fine-scale site fidelity, with median re-sighting distances of less than 40 km in consecutive years. Because they occur close to coasts and demonstrate a predictable distribution, humpback whales are particularly susceptible to disturbance from human activities. A clear understanding of the geographic pattern of summer sightings, along with the environmental features that characterize areas of concentrated distribution, could further management objectives. I analyzed the spatial pattern of summer humpback whale sightings and survey effort in three feeding grounds of the North Atlantic Ocean. Controlling for the spatial pattern of effort, sightings were clustered, with peaks at radial distances of 300 km, 600 km, and 1500 km. Fine-scale clustering at distances of 300 km and 600 km is compatible with the current hypothesis of multiple populations consisting of the Gulf of Maine, eastern Canada, western Greenland, and Iceland. Broad-scale clustering at distances of 1500 km may represent divisions between the western and eastern North Atlantic. I also conducted a broad-scale study of the environmental factors that influenced the summer distributions of humpback whales in the North Atlantic Ocean over the past several decades. Sightings in the Gulf of Maine, eastern Canada, and Iceland were modeled with static and ephemeral landscape features to develop logistic regression models of habitat. The global model including month; year; depth; slope; sea surface temperature (SST); SST gradient; and distances to shore, the 100-m isobath, and the 200-m isobath explained the greatest amount of variability in distribution at both the ocean-basin- and feeding-ground-scales. The variability explained by the ocean-basin-scale model was 17% as compared to the regional models that explained 33% to 38% of the variation in whale sightings. The spatial scale of the feeding ground, therefore, represents a crucial geographic extent for managing humpback whale activity. I suggest priority research and management activities given our present state of knowledge.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".