Of fleas and geese: the impact of an increasing nest ectoparasite on reproductive success
Bibliographic record
Abstract
Past studies on the relationship between nest ectoparasites and avian fitness have been primarily limited to altricial hosts. Life history strategies of precocial and altricial birds vary considerably, limiting our ability to infer the effect of nest parasites on fitness of precocial species. Ross's Chen rossii and lesser snow goose Chen caerulescens caerulescens populations have been growing at unprecedented high rates. New limiting factors on vital rates of these precocial birds may arise after populations have been released from previously regulating factors. The flea Ceratophyllus vagabundus vagabundus is an apparently newly emerging nest parasite in the arctic goose colony at Karrak Lake, Nunavut, Canada. We examined the relationship between flea abundance (measured by the proportion of goose eggs covered by blood in each nest) and goose reproductive success from 2001–2004. In three of four years of study, nest success was inversely related to flea abundance in nests. Despite the potential for high costs to individuals, the overall effects of fleas on goose nesting success have thus far been small. We demonstrated that nest parasites negatively influence reproductive success of precocial bird hosts despite host life history strategy of leaving the nest quickly after hatch, which results in minimal exposure to nest parasites compared to altricial birds that raise their young in the nest.
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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 | 0.000 | 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".