Are frog calls modulated by the environment? An analysis with anuran species from Bolivia
Bibliographic record
Abstract
Studies have shown that long-range songs of birds and primates are structurally adapted to local habitat acoustics. The evolution of frog calls, however, seems to be less influenced by habitat. Frogs are extremely dependent on energetically costly acoustic signals, which frequently have to be transmitted over large distances to elicit an encounter with the opposite sex. Different acoustic properties of advertisement calls from 95 Bolivian anuran species were analyzed according to their taxonomic position and the habitat characteristics where each species occurred. The majority of call characteristics, such as diversity of notes, number of pulses per note, or dominant frequency, appear strongly related to taxonomic position. Large-scale habitat characteristics (ecoregion and macrohabitat type) were not related to call characteristics, whereas small-scale habitat (microhabitat) complexity appeared to explain some of the variation in dominant frequency modulation. Species that call in closed microhabitats are more likely to use frequency-modulated calls, which may allow for more efficient sound transmission. To further the understanding of frog-call evolution in response to habitat selection, this and other studies have indicated that studies at finer spatial scales are needed, as well as additional studies restricted to the genus or species level.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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, 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".