The Effects of Regional Hydrologic Alteration on Fish Community Structure in Regulated Rivers
Bibliographic record
Abstract
Abstract Alterations to temporal patterns of river flow regimes resulting from damming and flow regulation practices may have negative consequences for freshwater communities. However, little has been performed to develop a holistic approach to assess the effects of hydrologic alterations on fish communities across a wide range of rivers and between different regulation strategies. To address this, we used daily and hourly hydrologic data from gauges in 10 regulated and 14 unregulated Canadian rivers. Building on the Ecological Limits of Hydrologic Alteration concept, hydrologic alterations for many ecologically relevant flow indices were combined to obtain river‐specific hydrologic alteration scores. Extensive community surveys to estimate fish abundance, biomass, diversity indices and habitat guild representation provided data for the derivation of similar river‐specific biotic alteration scores relative to unregulated river conditions. Our results indicate that biological impairment consisting of significant biotic alteration relative to the means from unregulated rivers was directly related to increasing flow alteration scores, with the smallest fish and flow alteration scores observed in run‐of‐river systems and the greatest alteration scores under hydro‐peaking regimes. Our approach not only examined the relationship between river‐specific hydrologic alteration scores and the associated biotic responses, but also provided a more comprehensive assessment of the flow‐response alteration relationship between regulation practices, which may better inform future environmental flow management guidelines. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".