Assessing potential spawning locations of Silver Chub in Lake Erie
Bibliographic record
Abstract
Abstract Objective Silver Chub Macrhybopsis storeriana, a predominately riverine species throughout its native range, exists within Lake Erie as the only known lake population. Its population declined in the 1950s and never fully recovered. Canada has listed Silver Chub in the Great Lakes–St. Lawrence River as endangered and has initiated a recovery plan that recognized the identification of spawning areas as a critical component to inform Silver Chub's recovery potential. Methods We investigated potential spawning locations of Silver Chub using capture records, otolith microchemistry, and daily age analysis. Lapillus otolith Sr:Ca ratios from 27 age-0 Silver Chub were used to identify potential spawning areas. Daily ages estimated from lapilli were used to calculate hatch dates, which then were compared with capture data of adults and river flows to further inform potential spawning areas. Result The Detroit River (and its nearshore area) was all but ruled out as a potential spawning location. The Maumee, Portage, and Sandusky rivers or their nearshore areas were all possible spawning locations. Projected hatch dates spanned the end of May through the end of June and occurred across a wide range of flows, although some peaks in hatch dates corresponded to flow peaks, indicating recruitment is potentially enhanced by high flows. Conclusion Silver Chub spawning period and hypothesized spawning rivers or lacustuaries overlap those of invasive Grass Carp Ctenopharyngodon idella, creating a need to jointly consider Grass Carp control efforts with conservation of Silver Chub when assessing management alternatives. Further research on spawning guild and the use of rivers themselves or nearshore areas influenced by rivers as spawning areas are required to maximize potential for conservation and recovery of Silver Chub.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".