<i>In situ</i> zooplankton density estimates at a foraging site in the Canadian Arctic are below minimum prey thresholds for adult bowhead whales (<i>Balaena mysticetus</i>)
Bibliographic record
Abstract
Abstract Bowhead whales (Balaena mysticetus) are an iconic Arctic species with a critical ecological role as a top predator. Bowheads can reach up to 80 tonnes and 20 m, yet feed on zooplankton four orders of magnitude smaller. Arctic zooplankton community composition and distribution are changing, which may have direct impacts on bowhead foraging. Data on the threshold prey density for successful bowhead feeding are needed to predict these impacts. However, zooplankton densities are patchy temporally and spatially, influenced by oceanographic conditions that alter the location of energetically profitable patches. We assessed spatio-temporal patterns in zooplankton abundance and distribution using a multi-frequency echosounder following a systematic and opportunistic survey near feeding whales in Iqalujjuaq Fjord, Cumberland Sound, Nunavut (65.66°N, 65.20°W) during August 2023. Zooplankton net samples were used to validate the acoustic data. There was a strong link between copepod distribution and environmental variables (e.g. water depth and tidal cycle) (generalized additive models, P < .001). Copepods were present in 49.8% of the fjord, with a median density of 3240 copepods m−3 and 0.26 g C m−3. Based on published prey density requirements, this site provides feeding opportunities for juveniles but is insufficient for the needs of adults (>0.44 g C m−3).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".