Role of habitat complexity in predator–prey dynamics between an introduced fish and larval Long-toed Salamanders (<i>Ambystoma</i> <i>macrodactylum</i>)
Bibliographic record
Abstract
Predation by nonnative fishes has reduced abundance and increased extinction risk for amphibian populations worldwide. Although rare, fish and palatable amphibians have been observed to coexist where aquatic vegetation and structural complexity provide suitable refugia. We examined whether larval Long-toed Salamanders (Ambystoma macrodactylum Baird, 1850) increased use of vegetation cover in lakes with trout and whether adding vegetation structure could reduce predation risk and nonconsumptive effects (NCEs), such as reductions in body size and delayed metamorphosis. We compared use of vegetation cover by larval salamanders in lakes with and without trout and conducted a field experiment to investigate the influence of added vegetation structure on salamander body morphology and life history. The probability of catching salamanders in traps in lakes with trout was positively correlated with the proportion of submerged vegetation and surface cover. Growth rates of salamanders in enclosures with trout cues decreased as much as 85% and the probability of metamorphosis decreased by 56%. We did not find evidence that adding vegetation reduced NCEs in experimental enclosures, but salamanders in lakes with trout used more highly vegetated areas, which suggests that adding vegetation structure at the scale of the whole lake may facilitate coexistence between salamanders and introduced trout.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 |
| 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 | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".