Identifying important habitat for northern bottlenose and Sowerby's beaked whales in the western North Atlantic
Bibliographic record
Abstract
Abstract Understanding habitat requirements for species at risk is crucial for effective conservation management, even though the location and extent of vital habitats may be unknown for rare or elusive species. In the case of marine species, determining important habitat often relies on limited occurrence data or extrapolation from species distribution models (SDMs). SDMs predict habitat by associating species records with environmental variables, assuming a functional ecological relationship. This study focuses on northern bottlenose whales (NBW; Hyperoodon ampullatus ) and Sowerby's beaked whales (SBW; Mesoplodon bidens ) in the western North Atlantic. As both NBW and SBW are at risk in Canada, the objective was to identify the extent and function of important habitats to guide conservation efforts. The analysis mapped all available geographic occurrence data and used passive acoustic monitoring (PAM) data to inform the development of ensemble SDMs to predict potential habitat and assess the persistence of realized habitat use. Important habitats for NBW and SBW were found primarily concentrated along the continental shelf edges, at an average depth of 1200 m ± 460 SD. All habitat areas support foraging and movement and critical life history functions for both species. The Gully and other submarine canyons off eastern Nova Scotia emerged as important areas for both species, validating the existing Critical Habitat for NBW. However, spatial–temporal patterns diverged on either side of this region. North‐eastern Newfoundland was identified as the next closest area of near‐year‐round presence for NBW, whereas the south‐western Scotian Shelf region, Georges Bank and the Fundian Channel supported persistent foraging by SBW. By integrating multiple data sources (sightings, acoustic detections and SDMs) and demonstrating the temporal persistence of habitat use by NBW and SBW, this study provides valuable insights for identifying, protecting and managing important habitat for beaked whales.
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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".