Historical summer distribution of the endangered North Atlantic right whale (<i>Eubalaena glacialis</i>): a hypothesis based on environmental preferences of a congeneric species
Bibliographic record
Abstract
Abstract Aim To obtain a plausible hypothesis for the historical distribution of North Atlantic right whales (NARWs) (Eubalaena glacialis) in their summer feeding grounds. Previously widespread in the North Atlantic, after centuries of hunting, these whales survive as a small population off eastern North America. Because their exploitation began before formal records started, information about their historical distribution is fragmentary. Location North Atlantic and North Pacific oceans. Methods We linked historical records of North Pacific right whales (E. japonica; from 19th‐century American whaling logbooks) with oceanographic data to generate a species distribution model. Assuming that the two species have similar environmental preferences, the model was projected into the North Atlantic to predict environmental suitability for NARWs. The reliability of these predictions was assessed by comparing the model results with historical and recent records in the North Atlantic. Results The model predicts suitable environmental conditions over a wide, mostly offshore band across the North Atlantic. Predictions are well supported by historical and recent records, but discrepancies in some areas indicate lower discriminative ability in coastal, shallow‐depth areas, suggesting that this model mainly describes the summer offshore distribution of right whales. Main conclusions Our results suggest that the summer range of the NARW consisted of a relatively narrow band (width c. 10° in latitude), extending from the eastern coast of North America to northern Norway, over the Grand Banks of Newfoundland, south of Greenland and Iceland, north of the British Isles and in the Norwegian Sea. These results highlight possibilities for additional research both on the history of exploitation and on the current summer distribution of this species. In particular, better survey coverage of historical whaling grounds could help inform conservation efforts for this endangered species. More generally, this study illustrates the challenges and opportunities in using historical data to understand the original distribution of highly depleted species.
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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) | 0.002 | 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".