Assessing the effects of fish density, habitat complexity, and current velocity on interference competition between bull trout (<i>Salvelinus confluentus</i>) and brook trout (<i>Salvelinus fontinalis</i>) in an artificial stream
Bibliographic record
Abstract
In this experiment, competition was observed among native bull trout (Salvelinus confluentus (Suckley, 1859)) and non-native brook trout (Salvelinus fontinalis (Mitchill, 1814)) in artificial streams. In intraspecific competitions, brook trout engaged in territorial interference foraging strategies, and their foraging success was correlated with occupancy of the lead position in the stream. No correlation was apparent for bull trout, most of which engaged in nonterritorial scramble foraging tactics. In interspecific competitions, four stream environments were constructed in which fish density, habitat complexity, and current velocity were altered. Bull trout outcompeted brook trout for food in simple pool habitat devoid of cover when competition was head-to-head (density = 3 fish·m−2) between the species. When competitor number was doubled in this habitat, the two became equal competitors. At this higher density, bull trout again outcompeted brook trout for food when the habitat was changed to a complex riffle with substrate cover. Brook trout were more aggressive towards bull trout than vice versa, and interspecific aggression was decreased by low density, cover, and high stream velocity. Territorial brook trout aggressively interfere with their competitor for access to resources, but the success and intensity of this tactic against bull trout may be mitigated by environmental factors.
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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".