Abundance and distribution of Antarctic krill (Euphausia superba) nearshore of Cape Shirreff, Livingston Island, Antarctica, during six austral summers between 2000 and 2007
Bibliographic record
Abstract
Abundance and distribution of Antarctic krill ( Euphausia superba ) in the nearshore waters north of Livingston Island, Antarctica, were characterized from six small-boat surveys conducted in late January or early February from 2000 to 2007. The first three surveys (2000, 2002, 2004) were conducted using a 120 kHz split-beam echosounder to measure water column acoustic backscatter. The last three surveys (2005–2007) were conducted using 38 kHz and 200 kHz single-beam echosounders. A portion of the acoustic backscatter was attributed to Antarctic krill based on the results of net tows, underwater video observations, and a multiple-frequency acoustic classification algorithm. The annual mean krill biomass density in the survey area ranged from 11 to 84 g·m–2. Results are compared with the western Scotia Sea area of the US Antarctic Marine Living Resources (AMLR) program’s acoustic surveys of krill biomass density for the same years. Nearshore krill biomass densities were significantly larger (t test, p < 0.05), more stable, and the coefficients of variation were smaller than the much larger AMLR surveys. Increased competition between seals, penguins, and humans for the nearshore krill resource, especially during the austral summer months, could impact the recruitment success of these land-based krill predators. Implications of nearshore krill biomass on small-scale management units are discussed.
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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 | 0.000 | 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".