Geographical differences in habitat relationships of cetaceans across an ocean basin
Bibliographic record
Abstract
The distributions of highly mobile marine species such as cetaceans are increasingly modeled at basin scale by combining data from multiple regions. However, these basin‐wide models often overlook geographical variations in species habitat relationships between regions. We tested for geographical variations in habitat relationships for a suite of cetacean taxa between the two sides of the North Atlantic basin. Using cetacean visual survey data and remote sensing data from the western and eastern basin in summer, we related the probability of presence of twelve cetacean taxa from three guilds to seafloor depth, sea surface temperature and primary productivity. In a generalized additive model framework, we fitted 1) basin‐wide (BW) models, assuming a single global relationship, 2) region‐specific intercepts (RI) models, assuming relationships with the same shape in both regions, but allowing a region‐specific intercept and 3) region‐specific shape (RS) models, assuming relationships with different shapes between regions. RS models mostly yielded significantly better fits than BW models, indicating cetacean occurrences were better modeled with region‐specific than with global relationships. The better fits of RS models over RI models further provided statistical evidence for differences in the shapes of region‐specific relationships. Baleen whales showed striking differences in both the shapes of relationships and their mean presence probabilities between regions. Deep diving whales and delphinoids showed contrasting relationships between regions with few exceptions (e.g. non‐statistically different shapes of region‐specific relationships for harbor porpoise and beaked whales with depth). Our findings stress the need to account for geographical differences in habitat relationships between regions when modeling species distributions from combined data at the basin scale. Our proposed hypotheses offer a roadmap for understanding why habitat relationships may geographically vary in cetaceans and other highly mobile marine species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".