Vorticity and circulation: spatial metrics for evaluating flow complexity in stream habitats
Bibliographic record
Abstract
Channel topography, formed by boulders, submerged bars, and meanders, creates complex flow patterns. These flow patterns exist over a variety of spatial scales and provide habitat for many aquatic organisms. Spatial flow features cannot be adequately characterized with qualitative descriptions or hydraulic metrics such as depth and velocity. Two-dimensional hydraulic model simulations, based on detailed channel geometry, are used to develop and test vorticity (a point metric) and a circulation-based metric (an area metric) as means of quantifying spatial flows occurring within micro-, meso-, and macro-habitat features. The proposed spatial metrics are computed throughout distinctly different regions of a study site. The vorticity metric produces small absolute values in uniform flows and large absolute values in complex flows. Circulation metric values varied by a factor of 11.7 within distinctly different regions of the modeled study site and suggest that the metric provides a means of quantifying flow complexity within a study reach or within individual mesoscale habitats such as pools, eddies, riffles, and transverse flows. The circulation metric is used to quantify flow complexity around three brown trout (Salmo trutta) redds to provide an example of how the proposed metric might be employed in habitat studies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".