The Behavioral Response of Larval Amphibians (Ranidae) to Threats from Predators and Parasites
Bibliographic record
Abstract
Organisms are exposed to strong selective pressures from several sources, including predators and pathogens. Response to such interacting selective pressures may vary among species that differ in life history and ecology in predictable ways. We consider the impact of multiple enemies (fish predators and trematode parasites) on the behavior of larvae of three anuran species (Lithobates (=Rana) sylvaticus, L. clamitans and L. catesbeianus). We show that the three ranid species differ in response to the trade-off imposed by the simultaneous presence of fish predators and trematode parasites in the environment. Two more permanent pond breeders (L. clamitans and L. catesbeianus), which commonly encounter parasites and fish, increased activity when in the combined presence of parasites and a fish predator, resulting in a relatively lower parasite encystment rate. In contrast, the temporary pond breeder (L. sylvaticus), which does not commonly encounter fish in the wild, decreased activity in the combined presence of a fish predator and parasites similar to when only the predator was present. For L. sylvaticus, this suggests that the presence of an unknown predator poses a greater threat than parasites. Further, the presence of fish along with parasites increased the susceptibility of both L. sylvaticus and L. clamitans to trematode infection, whereas parasite infection in L. catesbeianus was unaffected by the presence of fish. Unpalatability to fish may allow some species to respond more freely to attacking parasites in the presence of fish. The results from this study highlight the importance of considering multiple selective pressures faced by organisms and how this shapes their behavior.
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 | 0.000 |
| 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".