North Atlantic right whale (Eubalaena glacialis) and its food: (II) interannual variations in biomass of Calanus spp. on western North Atlantic shelves
Bibliographic record
Abstract
Abstract The North Atlantic right whale (NARW), Eubalaena glacialis, feeds on zooplankton, particularly copepods of the genus Calanus. We quantified interannual variation in anomalies of abundance and biomass of Calanus spp. and near-surface and near-bottom ocean temperature and salinity from 19 subregions spanning the Gulf of Maine–Georges Bank (GoM–GBK), Scotian Shelf (SS), Gulf of St. Lawrence (GSL) and Newfoundland and Labrador Shelves. We analyzed time series from 1977 to 2016 in GoM–GBK, 1982 to 2016 in southwest GSL and 1999 to 2016 in remaining areas. Calanus finmarchicus dominated abundance and biomass, except in the GSL where Calanus hyperboreus was abundant. The biomass of Calanus spp. declined in many subregions over years 1999–2016 and was negatively correlated with sea surface temperature in GoM–GBK and on the SS. We detected ``regime shifts” to lower biomass of Calanus spp. in the GoM–GBK in 2010 and on the SS in 2011. In the GoM–GBK, shifts to lower biomass of C. finmarchicus coincided with shifts to warmer ocean temperature and with published reports of changes in spatial distribution and reduced calving rate of NARW. We hypothesize that warming has negatively impacted population levels of Calanus spp. near their southern range limit, reducing the availability of prey to NARW.
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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 | 0.000 | 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) | 0.001 | 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".