Subpopulations of an imperiled freshwater fish show behavioural adaptation that informs survival in the Anthropocene
Bibliographic record
Abstract
Freshwater fishes are amongst the most threatened group of animals. Changes in river flows are an important driver in this. To gauge the ability of a common freshwater fish to respond to altered flows, we examined how sculpins from rivers with different flow regimes behaviourally responded to increasing water speeds. We chose the imperiled Rocky Mountain Sculpin, since within their restricted geographic distribution, there are endemic subpopulations that inhabit rivers with high and low flow volumes, and an introduced subpopulation that inhabits a river with moderate flow volume. Sculpins were collected from these rivers, acclimated to laboratory conditions, and their swimming behaviour was observed in a three-chambered flume. Swimming activity did not differ between the subpopulations, but stream place preference did: sculpins from high flow volume preferred upstream, while sculpins from moderate flow volume preferred downstream, and sculpins from low flow volume were indifferent. An exploratory phenotype was present in each subpopulation. This study suggests that altered river flows may change upstream and downstream place preference, which in turn could affect species distributions and interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".