Distribution and Life History of Spawning Capelin in Subarctic Alaska
Bibliographic record
Abstract
Abstract Capelin Mallotus villosus is a coldwater, marine forage fish that responds quickly to environmental fluctuations; however, little is known about Capelin in Alaskan waters. The objective of the current study was to better understand the distribution and life history of spawning Capelin in northern Norton Sound, Alaska. Surveys were conducted from May through July 2018 to locate and estimate the size of nearshore Capelin aggregations prior to spawning, identify the location and timing of spawning events, characterize spawning habitat, and collect actively spawning fish to examine life history characteristics (e.g., body size, age, fecundity, etc.). Most (85.9%) of the nearshore aggregations were less than 12 m2 in surface area. Spawning Capelin were collected in Norton Sound between June 15 and June 21. At spawning locations, gravel and coarse sand accounted for over 70% of the proportional weight of sediment collected within a beach, and all sediment samples contained Capelin eggs. Spawning males were larger than spawning females in TL (mean ± SD = 148.8 ± 6.7 mm versus 137.0 ± 8.4 mm, respectively) and total weight (21.2 ± 2.9 g versus 13.7 ± 3.0 g), and both sexes were predominately age 3 (age range = 2–4 years). Absolute fecundity was 9,219 ± 4,529 eggs, and the gonadosomatic index was 1.09 ± 0.32% for males and 21.69 ± 8.21% for females. Nearshore aggregation sizes in Norton Sound were smaller than those reported for Newfoundland, but spawning behavior, timing, and water conditions were similar to observations from other Capelin spawning regions (e.g., Greenland), as were size, age, fecundity, and gonadosomatic index estimates. Although the results from the current study update baseline information on spawning Capelin in northern Norton Sound, continued research on their distribution and life history is needed to better understand ecosystem function in the North Pacific Ocean.
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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 | 0.000 |
| 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".