Response of the residential piscivorous fish community to introduction of a new predator type in a mesotrophic lake
Bibliographic record
Abstract
Although the effects of introduced predators on prey populations in aquatic ecosystems have been studied frequently, less is known about the interactions between predators. We performed a whole-lake experiment by stocking a non-native top predator (pikeperch (Sander lucioperca)) to two residential piscivores (Eurasian perch (Perca fluviatilis) and northern pike (Esox lucius)). By analyzing spatial distribution, diet composition, growth, and consumption rates of the piscivores before and after pikeperch introduction, we tested how both density-dependent and trait-mediated responses affected interactions between the three predators. Total piscivore biomass increased 1.5 times and annual consumption by the piscivores increased 1.7 times after stocking, attributable to the stocked pikeperch and increased northern pike abundances. Abundance, distribution, and consumption data indicated that northern pike was hardly affected by pikeperch stocking and even increased its biomass, whereas piscivorous perch shifted its habitat use towards the littoral lake areas in response to competition with pikeperch. Furthermore, all piscivores increasingly fed on small perch. The forced habitat shift of piscivorous perch in combination with increased predation on small perch led to a decreased abundance of large perch, attributable to the compensatory effects of intraguild predation and cannibalism.
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 | 0.001 |
| 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".