Territorial and foraging behaviour of juvenile Mediterranean trout under changing conditions of food and competitors
Bibliographic record
Abstract
Territoriality is probably the most important ecological mechanism regulating densities in stream-living salmonids. Body size is typically regarded as the best predictor of territory size, but food abundance and competitor density may be key driving factors. However, a global analysis of literature data showed no clear patterns on the relative causal role of those factors on determining territory size in juvenile salmonids. Thus, in a factorial experiment, we estimated to what extent simultaneous variations of fish size, competitor density, and food abundance affected the size of foraging and defended areas of Mediterranean brown trout (Salmo trutta). In contrast with former studies, we found that foraging areas were larger than defended territories. Foraging and territorial behaviour changed significantly under varying density and feeding regimes. Foraging areas decreased with increasing competitor density and food availability, and there was a strong interaction between these two factors. Defended territories decreased with increasing density, irrespective of food abundance. Although our findings showed a significant allometric relationship between fish length and territory size, the data contained much unexplained variability. Our findings suggest that defended areas are relatively fixed for a given trout length. However, at extremely high population densities, defended areas decreased. Thus, under extreme competition, such as during critical periods right after emergence, trout may subdivide available habitat and thereby moderate density declines.
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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 | 0.000 |
| 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) | 0.001 | 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".