Run‐of‐river dams as a barrier to the movement of a stream‐dwelling amphibian
Bibliographic record
Abstract
Abstract Human activities frequently create structures that alter the connectivity among habitats or act as barriers to the natural movement of animals. Movement allows individuals to access different habitats, connect life history stages, and maintain genetic diversity. Here, we evaluated whether run‐of‐river (RoR) hydropower projects, an emerging renewable energy source in British Columbia, interrupt the longitudinal connectivity among larval stream amphibians, by altering larval rearing densities, with possible repercussions on growth and survival. In three watersheds, we tested for differences in the average upstream and downstream density of larval coastal tailed frog (Ascaphus truei), as well as changes to their longitudinal distribution upstream of the dams, as would be expected if RoR dams or their headponds act as barriers to the natural downstream drift of larvae. We found a 60% decrease in larval densities downstream compared to upstream of dams, consistent with RoR dams interrupting the natural pattern of downstream A. truei drift. Larval densities in the first 10 m above RoR headponds were 3 times higher compared to 100 m upstream, and when expressed in terms of relative abundance, we find a similar pattern, with between 2.5 and 3 times more larvae in the first 10 m above of the headpond than expected if larvae followed a uniform distribution. Our results are consistent with the hypothesis that RoR dams alter the spatial connectivity of A. truei larvae, leading to an accumulation of larvae directly above the dam, with unknown consequences for larval growth and survival. Our findings suggest caution is warranted when interpreting before–after monitoring studies that are often used to evaluate the impact of dams, whereby we find that reductions in downstream densities could be due to interruptions of downstream movement as opposed to direct mortality.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".