Differential behavioral responses of benthic and nektonic tadpoles to predation at varying water depths
Bibliographic record
Abstract
Predators influence microhabitat selection and activity level of tadpoles, but it is still unclear how such responses to predators differ among species and how water column's depth influences this predator–prey interaction. Here, we experimentally tested whether the presence of Odonata water nymphs influenced the spatial use and activity of benthic and nektonic tadpoles in different food availability contexts. Benthic tadpoles occupied and consumed more food at the bottom level, irrespective of predator's presence. However, when predators were at the bottom, benthic tadpoles remained close to the cages, suggesting a typical “stay-still” defensive behavior known for Physalaemus nattereri (Steindachner, 1863). Nektonic tadpoles occupied shallower depths on predator presence, and they also consumed less food and avoided the predator by selecting food sources far from it. When the predator was at the bottom level and food was available, the distance of tadpoles to the cage tended to be smaller. Scinax fuscovarius (Lutz, 1925) tadpoles were more active when food was absent regardless of predator's presence. When food was available, these tadpoles generally occupied and consumed more food at the bottom level. Tadpole responses depended not only on predator presence but also on a complex net of factors, which included tadpole habit, antipredatory behavior, and availability and location of food.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".