Changes in sea ice and range expansion of sperm whales in the eclipse sound region of Baffin Bay, Canada
Bibliographic record
Abstract
Sperm whales (Physeter macrocephalus) are a cosmopolitan species but are only found in ice-free regions of the ocean. It is unknown how their distribution might change in regions undergoing rapid loss of sea ice and ocean warming like Baffin Bay in the eastern Canadian Arctic. In 2014 and 2018, sperm whales were sighted near Eclipse Sound, Baffin Bay: the first recorded uses of this region by sperm whales. In this study, we investigate the spatiotemporal distribution of sperm whales near Eclipse Sound using visual and acoustic data. We combine several published open-source, data sets to create a map of historical sperm whale presence in the region. We use passive acoustic data from two recording sites between 2015 and 2019 to investigate more recent presence in the region. We also analyze regional trends in sea ice concentration (SIC) dating back to 1901 and relate acoustic presence of sperm whales to the mean SIC near the recording sites. We found no records of sperm whale sightings near Eclipse Sound outside of the 2014/2018 observations. Our acoustic data told a different story, with sperm whales recorded yearly from 2015 to 2019 with presence in the late summer and fall months. Sperm whale acoustic presence increased over the 5-year study duration and was closely related to the minimum SIC each year. Sperm whales, like other cetaceans, are ecosystem sentinels, or indicators of ecosystem change. Increasing number of days with sperm whale presence in the Eclipse Sound region could indicate range expansion of sperm whales as a result of changes in sea ice. Monitoring climate change-induced range expansion in this region is important to understand how increasing presence of a top-predator might impact the Arctic food web.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".