The effect of harvesting on size structured predatory and competitive interactions between rainbow trout («Oncorhynchus mykiss») and northern pikeminnow («Ptychocheilus oregonensis»)
Bibliographic record
Abstract
A reduction in the consumptive and nonconsumptive effects of predation resulting from harvesting of top predators has been hypothesized to result in failure of harvested species to recover from low abundance, even if harvesting is reduced or ceases. I examined size-structured predatory and competitive interactions between northern pikeminnow (Ptychocheilus oregonensis) and its potential predator rainbow trout (Oncorhynchus mykiss). Specifically, I investigated diel habitat use by northern pikeminnow, the effect of harvesting and community structure on recovery of rainbow trout, and trophic consequences of removing either species. Theoretical predictions were tested with replicated whole-lake manipulations of fish density: adult rainbow trout were removed from two single-species lakes, and from two lakes that also supported northern pikeminnow (two-species lakes), and northern pikeminnow were removed from three two-species lakes. In Chapter 1, I hypothesized that diel horizontal migrations undertaken by northern pikeminnow result from a trade-off between foraging opportunities and predation risk. Although adult rainbow trout removals did not alter northern pikeminnow migratory behaviour, tethering experiments showed that rainbow trout present a risk of predation in pelagic habitats during the day and crepuscular periods. Chapter 2 identified Chaoborus larvae as the most important prey of northern pikeminnow in the pelagic zone. Chaoborus is only available as prey in the pelagic zone at night, and its importance provides evidence that foraging opportunities may reinforce diel horizontal migrations. In Chapter 3, I compared trophic responses to removals of either adult rainbow trout or its potential forage species, northern pikeminnow. While northern pikeminnow removals led to a predicted four-level trophic cascade, the trophic responses to rainbow trout removals were inconsistent among lakes. In Chapter 4 I tested predictions from the cultivation-depensation hypoth
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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".