Resource use of crucian carp along a lake productivity gradient is related to body size, predation risk, and resource competition
Bibliographic record
Abstract
Abstract Generalist fish species can feed on a wide resource spectrum and across trophic levels depending on resource availability and trophic interactions. Crucian carp (Carassius carassius) represents a good candidate species to investigate variation in the trophic ecology of generalist fish as it can be found in highly variable fish communities and its resource use is well documented. In this study, we explored the trophic ecology of crucian carp at the individual and population levels using stable isotope and gut content analysis. We tested if trophic resource use varied according to lake productivity, predation risk, intra‐ and interspecific competition, or individual fish size. We found that crucian carp resource preference was highly variable among and within lakes. In predator‐free lakes, small crucian carp occurred in high densities, showed increased interindividual specialisation, and relied mainly on pelagic zooplankton. In presence of predators, large crucian carp occurred in low densities and included greater proportions of benthic macroinvertebrates in their diet. This shift in resource use was further favoured in productive, shallow lakes where littoral prey were probably abundant. Resource partitioning was an important factor determining crucian carp niche use, as fish had higher trophic position in absence of other cyprinids. Crucian carp showed highly dynamic resource use and food preferences in response to variable environmental conditions. Overlooking complex diet preferences of generalist fish may lead to an oversimplification of freshwater community dynamics.
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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 | 0.001 | 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".