Effects of predaceous and nonpredaceous introduced fish on the survival, growth, and antipredation behaviours of long-toed salamanders
Bibliographic record
Abstract
Simultaneous introduction of complex suites of exotic organisms into indigenous populations have poorly known magnitudes and consequences. We compared the effects of introduced piscivorous rainbow trout ( Oncorhynchus mykiss (Walbaum, 1792)) and nonpiscivorous fathead minnows ( Pimephales promelas Rafinesque, 1820) on growth, survival, susceptibility to predation, and antipredator behaviours of naïve long-toed salamanders ( Ambystoma macrodactylum Baird, 1850). Trout reduced salamander hatchling and larvae survival to nearly zero in predation trials and caused a 39% reduction in salamander survival within outdoor mesocosms. Salamander larvae did not increase their refuge use or alter activity patterns in the presence of trout. These results imply that allotopic distributions of trout and salamanders observed in several field surveys likely result from the inability of larvae to recognize introduced predators as a threat. Minnows also caused significant reductions in salamander survival (41%) and growth (37%) in mesocosms, and exposure to minnow cues caused larvae to spend more time within a refuge. Reduced salamander survivorship and growth in the mesocosms was likely due to competition for limiting zooplankton and (or) cannibalism. These results indicate that introductions of small-bodied, nonpiscivorous fishes can reduce amphibian survival and growth to at least the same extent as introduced trout.
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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".