Bibliographic record
Abstract
Mosquitoes ( Culex pipiens L., 1758) are important vectors for diseases of both wildlife and humans. Understanding how natural factors influence mosquito abundance may provide insights into the ecology of various diseases, as well as solutions to controlling disease vectors. One of the natural factors regulating mosquito distributions and population sizes is predation. A poorly understood source of natural mosquito predation is amphibians. We determined the mosquito consumption capability of two amphibians, adult Red-spotted Newts ( Notophthalmus viridescens viridescens (Rafinesque, 1820)) and larval Mole Salamanders ( Ambystoma talpoideum (Holbrook, 1838)). We also compared mosquito consumption of eastern mosquitofish ( Gambusia holbrooki Girard, 1859), a known predator of mosquitoes, and A. talpoideum. Both salamander species were capable of consuming large numbers of mosquito larvae per day (least-square means ± 1 SE = 439 ± 20 and 316 ± 35 mosquitoes/day consumed by A. talpoideum and N. v. viridescens, respectively). In A. talpoideum, mosquito consumption scaled with body size, with the largest individual (4.4 g) ingesting 902 mosquitoes in 1 day. Gambusia holbrooki consumed 3.5× more mosquitoes during a 24 h feeding trial than similar-sized A. talpoideum. Our findings suggest that amphibians could have a substantial impact on mosquito larvae abundance, especially considering that amphibians can reach densities of up to 500 000 individuals/ha. Furthermore, we hypothesize that introduction of G. holbrooki could reduce abundances of native mosquito predators (e.g., salamanders) indirectly, through competition for invertebrate prey.
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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) | 0.002 | 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".