Environmental complexity reduces tadpole predation by water bugs
Bibliographic record
Abstract
We assessed the role of habitat structure in the outcome of predation by measuring how aquatic vegetation influences predation rates of water bugs (Belostoma oxyurum (Dufour, 1863), Hemiptera, Belostomatidae) on tadpoles of Dendropsophus minutus (Peters, 1872) and Scinax curicica Pugliese, Pombal, and Sazima, 2004 (Anura, Hylidae). Considering that previous studies have shown that some tadpole species preferentially use microhabitats with aquatic vegetation at sites in southeastern Brazil, we hypothesized that these tadpoles may select such complex microhabitats because they can offer some protection against co-occurring predatory aquatic insects. We used field enclosures containing tadpoles of D. minutus and S. curicica and one predator (B. oxyurum), placed on natural substrata in sites both with and without aquatic vegetation, according to treatment. We measured the combined effects of predation and habitat structure on the survivorship of tadpoles, monitoring each enclosure daily during 10 days to survey surviving tadpoles. Treatments with predators reduced tadpole survivorship significantly in relation to controls for both tadpole species. The interaction between predator and vegetation was also significant, predation rates being lower when vegetation was present.
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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 | 0.001 |
| 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 | 0.000 | 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".