A multi-metric approach to characterize variability in Yellow Perch (Perca flavescens) use of Lake Ontario and two barrier-protected coastal wetlands
Bibliographic record
Abstract
Abstract Yellow Perch (Perca flavescens) inhabit both nearshore and coastal wetland habitats of the Laurentian Great Lakes throughout their lifetime and are known to exhibit different movement life histories. However, uncertainty persists in the spatial extent of this variation and in the duration of habitat use. To explore these uncertainties, we used a multi-metric approach that included water and otolith microchemistry and tissue stable isotope ratios (δ13C, δ15N). The ratio of manganese to calcium in otoliths was used to identify transitional movements between nearshore Lake Ontario and wetland habitats while carbon and nitrogen tissue isotope ratios revealed variable duration of wetland inhabitance. Our research suggests that the multi-metric approach was useful for addressing questions that could not be answered by one method alone. Our results demonstrate individual differences in duration of coastal wetland habitat residence among Yellow Perch, which may influence their susceptibility to recreational harvest. As Yellow Perch are an important species of consideration for management agencies such as the Great Lakes Fishery Commission, exposing such diversity is important when considering the potential for differential contributions of individuals with variable movement life histories to overall population stability and resilience over time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".