Macroinvertebrate community structure along gradients of hydraulic and sedimentary conditions in a large gravel‐bed river
Bibliographic record
Abstract
1. The spatial distribution of macroinvertebrate species was examined in relation to hydraulic and sedimentary conditions in a large gravel‐bed river, the Fraser River, Canada. Mean annual discharge in the Fraser River is 2900 m3 s−1 and annual flood discharge, due to snowmelt in May and June, averages 8760 m3 s−1. 2. Invertebrates were sampled from four water depths (0.2, 0.5, 1.5, 3.0 m) at various levels of discharge that together captured the spatial and temporal variability of the physical habitat. Several hydraulic (near‐bed shear velocity, Boundary Reynolds number, turbulence intensity, depth‐averaged velocity, Froude number, Reynolds number) and substratum variables (mean grain size, Trask's sorting coefficient, Nikuradse's roughness, percentage of fine sediment, and Shields entrainment function) were measured for each sample of macroinvertebrates. Concentrations of fine and coarse particulate organic matter were also assessed. 3. The physical habitat was characterized by a major gradient of hydraulic conditions that corresponded positively with increasing water depth and accounted for 52% of the total variation in the habitat data. Substratum conditions and the concentration of organic matter explained 24% of the total variation in the habitat data. 4. The distribution of invertebrates was correlated significantly with hydraulic variables and suggests that hydraulic conditions represent a major physical gradient along which the benthic community is organized. The distribution of organic matter and substratum texture were also important for some species. The spatial distribution of most species reflected morphological and trophic suitability to particular habitat conditions. 5. Hydraulic stress associated with foraging and maintaining position, as well as organic matter retention in coarse substrata, are probable mechanisms affecting the spatial distribution of macroinvertebrates.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".