Validation of the Use of Otoliths to Estimate Age and Growth of Larval Lake Whitefish, Coregonus clupeaformis
Bibliographic record
Abstract
Understanding drivers of recruitment variation in fish populations requires research conducted on early life stages. Examination of fish otoliths provides useful information for estimating hatching dates, growth, and survival rates of larvae and for investigating the relationship between early life stage phenology and variation in environmental factors such as climate and food availability. In the Laurentian (i.e., North American) Great Lakes, significant reductions in the number of young (ages 1–4 years) lake whitefish (Coregonus clupeaformis) recruiting into the population and commercial fishery have raised questions about factors affecting growth and survival of the larval life stage. Here, we investigate the utility of using otoliths to estimate the age and growth of larval lake whitefish. We raised offspring of wild-caught parents from Lake Simcoe (Ontario, Canada) in a hatchery environment and analyzed otoliths of these known age fish for 75 days posthatch. We further examined otoliths of wild-sampled larvae and age 0 lake whitefish from Lake Huron. We found a strong linear relationship between known age and number of postcheck increments on the otolith and between growth of the otolith and fish length. Increments formed at nearly 1 (0.9) per day beginning at day 20 after hatch. Check and subsequent increment formation was associated with disappearance of the yolk sac. Wild fish had more prominent checkmarks and grew slower than hatchery fish. Thus, otolith analysis represents a promising tool to examine dynamics of early life stages of lake whitefish, although further research is required on the effects of environmental conditions on otolith microstructure.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".