Growth variation along a dispersal gradient in juvenile rainbow trout
Bibliographic record
Abstract
Abstract The behavioural and metabolic attributes that favour post‐emergence dispersal by larval fish may differentiate juvenile phenotypes along downstream ecological gradients in riverine systems, but the extent to which fish with contrasting dispersal capacities differ in underlying metabolic, behavioural and life‐history traits remains unclear. In this study, we used common environment experiments to evaluate the extent of inter‐individual differentiation in growth rate, metabolic performance (active metabolism [maximum metabolic rate, MMR], temperature tolerance [CTmax]) and behaviour (emergence time, exploration, sociability) associated with the downstream dispersal of juvenile trout along a 50 km reach of the Lardeau River (British Columbia) characterised by multiple ecological gradients (i.e. distance from the emergence area, water temperature and prey abundance). Growth rate of fish reared under common environment satiation conditions in the laboratory was significantly lower at the most downstream site, which was consistent with an upstream‐to‐downstream gradient of decreasing prey availability, whereby faster‐growing fry were present in the more productive upstream habitats of the upper Lardeau River. In contrast with growth, temperature tolerance (i.e. CTmax) and traits associated with active movement (i.e. MMR, boldness, exploration, sociability) did not differ among individuals or clearly map onto upstream‐to‐downstream gradients of water temperature and distance travelled during dispersal. These results suggest that spatial differentiation of juvenile phenotypes following post‐emergence dispersal may reflect a sorting process where variation in attributes like growth matches the productivity of the terminal habitat, rather than behavioural or metabolic attributes that might promote dispersal (e.g. proactive behaviours and active metabolism).
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 | 0.001 | 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".