No support for relatedness and kin selection to explain high rates of conspecific brood parasitism in colonial Red-breasted Mergansers (<i>Mergus serrator</i>)
Bibliographic record
Abstract
Conspecific brood parasitism (CBP) has been observed in approximately half of all species of waterfowl, a philopatric group in which breeding females are frequently locally related. It has been suggested that kin selection can facilitate the evolution of CBP in waterfowl via fitness benefits for the host and parasite. One model demonstrates that discrimination of related and unrelated parasites by the host must be sufficient for kinship to promote CBP, provided that costs of brood parasitism to host fitness are sufficiently low. We parameterized the model using demographic data and behavioural observations from a population of colonial Red-breasted Mergansers (Mergus serrator Linnaeus, 1758) in which 47% of nests were parasitized by conspecifics. The costs of 1–3 foreign eggs to host hatching success were generally small (decline of 1.8% per additional egg). Nevertheless, model outputs revealed that brood parasites maximize their inclusive fitness by avoiding nests of relatives, primarily because of constraints on a host’s ability to detect parasites at the nest. Indeed, hosts spent <8% of the diurnal period at the nest during egg laying, a period when parasite activity is greatest. It is thus highly unlikely that relatedness and kin selection promote brood parasitism in this population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".