Linking fish assemblages to hydro‐morphological units in a large regulated river
Bibliographic record
Abstract
Abstract Flow‐related changes of physical habitat represent a potentially significant environmental filter determining the presence and composition of fish assemblages in rivers. The mesoscale (10 0 –10 3 m) of river habitat has been identified as an appropriate resolution to model linkages between fish and their abiotic environment that are relevant yet logistically feasible for management of large rivers with complex habitats and diverse fish assemblages. This study identified well‐defined mesohabitat types (i.e. hydro‐morphological units) that influence the fish community of the lower Saint John River, New Brunswick, downstream of a large hydropower generating station (the Mactaquac Generating Station). Four hydro‐morphological units or habitats (i.e. pool, riffle, run and slack water) were identified and linked to three distinct fish assemblages. Eurytopic species represent habitat generalists that were common among all habitats throughout the study area. Rheophilic species preferred fast‐flowing run habitat, whereas limnophilic species were mainly associated with slack water habitat. Riffle habitats that frequently run dry during low flows were mostly vacant of fish species, suggesting that fish assemblages that would naturally occur in these environments could be affected by fluctuations in flow (i.e. hydropeaking) due to dam operation. Our improved understanding of the relationship between fish assemblages and hydro‐morphological units is a fundamental first step to develop meaningful habitat models that can facilitate the effective evaluation of flow management options regarding hydropower and other flow manipulation activities in large rivers with diverse fish fauna.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".