Behavioral responses of the Strawberry Poison Frog (<i>Oophaga pumilio</i>) to herbicide olfactory cues: possible implications for habitat selection and movement in altered landscapes
Bibliographic record
Abstract
Recent research has focused on the importance of behavior in mediating the effects of landscape change on amphibian populations and communities. Factors such as chemical contaminants may affect habitat selection and movement of amphibians in human-altered habitats and contribute to landscape-level patterns of distribution and abundance. The objective of this study was to determine if the Strawberry Poison Frog (Oophaga pumilio (Schmidt, 1857)) can use olfactory cues to detect and avoid the glyphosate-based herbicide Roundup™. Fifty frogs were captured in the field in Costa Rica and tested in experimental arenas where they were given a choice between a control and an herbicide treatment. Analysis of time spent in treatment areas revealed a significant interaction between sex and treatment. Analyses of choice at the start and end of the trials indicated that sex and cardinal direction were important factors influencing orientation behavior. These results suggest that males and females differed in their behavioral responses, and that male O. pumilio may use olfactory cues to detect and avoid areas treated with glyphosate-based herbicide. However, the sampled population was male-biased, which resulted in a lower sample size and lower power to detect an effect for females. Further work is needed to better understand amphibian behavioral responses to herbicides, as well as the role of sex and individual variation in modifying these responses.
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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".