Boreal river impoundments caused little change in fish diversity but clear community assemblage shifts: A multi-scale analysis
Bibliographic record
Abstract
Abstract Hydroelectricity is often presented as a clean and renewable energy source, but river flow regulation and fragmentation caused by dams are recognized to impact aquatic biodiversity in temperate and tropical ecosystems. However, the effects of boreal river impoundment are not clear as the few studies that exist have not been able to separate the hydrological changes brought about by dams from other factors ( e.g. fish stocking, and species introduction). We adopted a multi-scale analysis to examine changes in nearshore fish communities over 20 years (spanning before and after impoundment) using a network of 24 sampling stations spread across from four reservoirs and two hydroelectricity complexes located in the boreal region (Northern Québec, Canada). Given the remote location, confounding factors were minimal. We found no strong temporal trends in alpha- and gamma-diversity in impacted stations (upstream and downstream of the dam) relative to reference sites across the three spatial scales. Using beta-diversity analyses, we also detected a high stability in fish composition over time and space at the complex and reservoir scales. At the scale of the sampling stations, we observed higher rates of species turnover (beta-diversity) coincident with the time of reservoir filling and shortly after. Likewise, we detected species assemblage shifts that correlated with time since impoundment only at the sampling station scale. This pattern was masked at the complex and reservoir scales. Synthesis and applications . Overall, the isolated effect of impoundment in these remote boreal ecosystems caused no loss of species and little change in fish diversity over 20 years, but resulted in substantial species assemblage shifts. Our work shows that examining community data at different scales is key to understand the anthropogenic impacts on fish biodiversity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".