Data from: Piscivore addition causes a trophic cascade within and across ecosystem boundaries
Bibliographic record
Abstract
The addition of predators can play a key role in structuring ecological communities through both consumptive and non-consumptive effects. Stocking of piscivorous fish in lakes and similar experimental introductions have provided fundamental evidence in support of trophic cascade theory. Yet, the impact of piscivore addition on cross ecosystem subsidies and meso-predator resource use has not been well studied. Here, we use a replicated pond experiment to document the trophic impacts of a piscivore, cutthroat trout Onchorhynchus clarkii, on aquatic communities already containing a meso-predatory fish (threespine stickleback Gasterosteus aculeatus) and neighbouring terrestrial ecosystems. We find that piscivore addition led to a trophic cascade that extended across an ecosystem boundary: trout addition increased the biomass and average size of insects emerging into the terrestrial system. Piscivores caused a diet shift in stickleback, a non-consumptive effect that was likely mainly responsible for the increase in emerging insect biomass. We additionally show that heterogeneity in the strength of the pelagic trophic cascade was more closely correlated with the magnitude of diet shift (reflecting a non-consumptive effect) than decreases in stickleback abundance (a consumptive effect). Taken together, our experiment demonstrates that the addition of a piscivore causes a trophic cascade that can extend beyond the aquatic system and suggests that non-consumptive effects may more strongly influence the strength of a trophic cascade than has been previously recognized.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.147 | 0.037 |
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".