Use of stable isotopes and trace elements to determine harvest composition and wintering assemblages of belugas at a contemporary ecological scale
Bibliographic record
Abstract
Stable isotopes and trace elements reflect interactions between individuals and their environment over shorter periods than genetic tracers and may capture contemporary patterns relevant to stock conservation and management.The endangered eastern Hudson Bay (EHB) belugas Delphinapterus leucas and those from the non-endangered western Hudson Bay (WHB) population are harvested during migration through Hudson Strait (HS), making protection of the endangered stock difficult.We assessed whether chemical tracers of beluga feeding ecology, i.e. carbon and nitrogen isotope ratios and concentrations of 27 trace elements, can help delineate wintering assemblages and successfully define summering stocks and their relative contributions to aboriginal harvests in HS.Skin was obtained from 1032 belugas in 9 regions of Hudson Bay, HS and southeast Baffin Island from 1989 to 2009.Isotopic signatures and trace element concentrations varied regionally and seasonally and suggest that several summering stocks and at least 3 winter assemblages exist.The use of isotopically defined summering stocks as sources in a discriminant function analysis indicates that the endangered EHB belugas account for 20 to 49% of the southern HS fall harvest.Low misclassification rates (≤10%) when using haplotypes unique to, or typical of, EHB belugas as a validation indicate that the isotopic approach is reliable.The analysis combining isotopes with trace elements is promising, although sample size is currently too small to define summering stocks.Spring signatures suggest that Cumberland Sound belugas winter in a separate area and may be differentiated from belugas found elsewhere in southeast Baffin Island, a contemporary pattern relevant to management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".