Influence of thermal fronts on habitat selection by four rorqual whale species in the Gulf of St. Lawrence
Bibliographic record
Abstract
MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 335:207-216 (2007) - doi:10.3354/meps335207 Influence of thermal fronts on habitat selection by four rorqual whale species in the Gulf of St. Lawrence Thomas Doniol-Valcroze1,2,3,*, Dominique Berteaux3, Pierre Larouche4, Richard Sears2 1Department of Natural Resource Sciences, McGill University, 21111 Lakeshore Road, Ste.-Anne-de-Bellevue, Quebec H9X 3V9, Canada 2Mingan Island Cetacean Study, 285 Green, St. Lambert, Quebec J4P 1T3, Canada 3Canada Research Chair in Conservation of Northern Ecosystems and Centre d'etudes nordiques, Université du Québec à Rimouski, 300 allée des Ursulines, Rimouski, Quebec G5L 3A1, Canada 4Institut Maurice-Lamontagne, 850 route de la Mer, PO Box 1000, Mont-Joli, Quebec G5H 3Z4, Canada *Email: thomas.doniol-valcroze@mail.mcgill.ca ABSTRACT: Understanding the factors influencing habitat selection is critical to improving management and conservation plans for large whales. Many studies have linked the distribution of cetaceans to basic environmental features such as underwater topography and sea surface temperature (SST), but the mechanisms underlying these relationships are poorly understood. Dynamic mesoscale processes like thermal fronts are prime candidates to link physiographic factors to whale distribution because they increase biological productivity and aggregate prey. However, previous studies of large whales have found little evidence of such associations, possibly because they were not at the appropriate spatio-temporal scales. We quantified the relationship between SST fronts and the distribution of blue Balaenoptera musculus, finback B. physalus, humpback Megaptera novaeangliae and minke B. acutorostrata whales in the northern Gulf of St. Lawrence. We compared the distribution of 1094 whale sightings collected from boat surveys conducted in 1996 to 2000 to the locations of frontal areas determined from 61 satellite maps. The distributions of whales and thermal fronts were highly correlated (random resampling and Mantel tests of matrix similarity). Spatial distributions differed among species, probably reflecting differences in feeding strategies. Identification of surface fronts from satellite imagery thus effectively complemented field observations of whales. These findings significantly increase our understanding of habitat quality in rorqual whales, and encourage a greater use of dynamic environmental variables in future studies of whale habitat use. KEY WORDS: Sea surface temperature · Thermal fronts · Blue whale · Finback whale · Humpback whale · Minke whale · Habitat selection · Gulf of St. Lawrence Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 335. Online publication date: April 16, 2007 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2007 Inter-Research.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".