Does Local Bed Shear Stress Predict the Occurrence of Freshwater Mussels?
Bibliographic record
Abstract
ABSTRACT The relationship between near‐bed hydrodynamics, pore‐water chemistry and the presence of unionids was examined in a well‐characterized multispecies mussel bed (26 species; ~24 mussels m −2 ; 70% gravel, 20% cobble and 10% sand) within a lowland river (Sydenham River) in southern Ontario, Canada. Local bed shear stress ( τ b ) was determined from velocity profiles at ~1‐m intervals along four laterals and three longitudinal transects in the reach providing 118, 14.3‐cm diameter quadrats in which porewater was sampled and sediments were excavated for unionids. Ninety‐four unionids (10–135 mm long) from 14 species were found in 56 quadrat locations that had significantly higher mass of very fine gravel (2000‐μm sieve) and lower dissolved oxygen in a comparison of individual environmental factors. Larger adult mussels (i.e., > 30 mm long; n = 68) were found in quadrats with τ b = 0.022–1.34 Pa and an excavated very fine gravel mass = 616–2821 g, but smaller, juvenile mussels (< 30 mm; n = 26) were found in a more restricted range of τ b and sediment content (0.075–0.77 Pa and 1151–2561 g, respectively). Using forward and backward stepwise habitat variable selection in logistic regression, models incorporating τ b , τ b 2 and/or very fine gravel mass provided the highest probability of locating juvenile mussels. The final model, which is based on body size, is informative at the community level rather than on a species‐specific basis. These results provide insights into the relationship between near‐bed hydrodynamics and these important benthic invertebrates, the location of small juvenile and larger adult unionids and their habitats in riverbeds. Conservation efforts should focus on preserving and enhancing these habitats and those of the most vulnerable early life stages of freshwater mussels.
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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 | 0.000 | 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) | 0.002 | 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".