Parentage analysis reveals reproductive behaviors in a wild population of White Sturgeon
Bibliographic record
Abstract
ABSTRACT Objective Reproductive activity is rarely observed directly in the White Sturgeon Acipenser transmontanus because spawning generally occurs over benthic habitats in fast-flowing rivers. Aspects of reproductive ecology have been inferred from indirect lines of evidence, with results often being imprecise. Here we performed parentage analysis within the population of the upper Columbia River, associating adults with offspring that had been collected from multiple years and locations, to precisely characterize spawning periodicity across years, spawning duration within years, and spawning site fidelity across locations. Methods We identified parent–offspring relationships by integrating Mendelian-mismatch-based exclusion, likelihood-based assignment, and relationship coefficient analysis, using tetrasomic single-nucleotide polymorphism genotypes that were produced through genotyping-in-thousands by sequencing. The thresholds for each approach were determined from known parent–offspring relationships in a cultured population. Results Parent–offspring relationships associated adults of both sexes with multiple spawning events across years, within years, and across locations. Among adults that were linked to multiple years, spawning periodicity ranged from 1 to 5 years in males and 4 to 5 years in females. Among adults that were associated with multiple spawning dates within years, we observed spawning durations of up to 26 d in males, whereas females largely displayed durations up to 4 d. Individuals of both sexes were associated with different sites in different years, whereas males were further linked to different sites within years, suggesting incomplete spawning site fidelity. Conclusions These findings inform an ongoing conservation aquaculture program for supplementing this population and demonstrate the utility of parentage analysis for inferring reproductive behaviors in high detail, particularly in systems where thorough sampling of parents and offspring is feasible.
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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 | 0.001 |
| 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".