Fish response to modified flow regimes in regulated rivers: research methods, effects and opportunities
Bibliographic record
Abstract
Abstract Globally, rivers are increasingly being subjected to various levels of physical alteration and river regulation to provide humans with services such as hydropower, freshwater, flood control, irrigation and recreation. Although river regulation plays an important role in modern society, there are potential consequences which may negatively affect fish and fish habitat. While much effort has been expended examining the response of fish to fluctuating flow regimes in different systems, there has been little in the way of a comprehensive synthesis. In an effort to better understand the effects of river regulation on fish and fish habitat, we conducted a systematic review of available literature with three goals: (1) summarize the various research methodologies used by regulated river researchers, (2) summarize the effects found on fish and fish habitat and (3) identify opportunities for future research. The results of the synthesis indicate that a wide variety of methodologies are being employed to study regulated river science, yet there is a gap in incorporating methodologies that examine effects on fish at a cellular level or those techniques that are interdisciplinary (e.g. behaviour and physiology). There is a clear consensus that modified flow regimes in regulated rivers are affecting fish and fish habitat, but the severity and direction of the response varies widely. Future study designs should include methods that target all biological levels of fish response, and in which detailed statistical analyses can be performed. There is also a need for more rigorous study designs including the use of appropriate controls and replicates. Data on physical variables that co‐vary with flow should be collected and examined to add explanatory power to the results. Increased multi‐stakeholder collaborations provide the greatest promise of balancing ecological concerns with economic needs. Copyright © 2008 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 | 0.032 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".