Laying-Stage Nest Attendance and Onset of Incubation in Prairie Nesting Ducks
Bibliographic record
Abstract
Abstract We used microprocessor data loggers to document patterns of nest attendance during the laying stage and to quantify temperatures of dummy eggs during laying for Mallard (Anas platyrhynchos), Blue-winged Teal (A. discors), Northern Shoveler (A. clypeata), Northern Pintail (A. acuta), Gadwall (A. strepera), Green-winged Teal (A. crecca), American Wigeon (A. americana), and Lesser Scaup (Aythya affinis) nesting in southern Manitoba in 1994 and in northeastern North Dakota in 1995–1997 and 2000–2002. Females of all species increased the time they spent on the nest as laying progressed, but species differed in their pattern of increased attendance. Female Blue-winged Teal and Northern Shoveler that laid smaller clutches increased the time they spent on the nest more rapidly than conspecifics that laid larger clutches, but large- and small-clutch conspecifics had similar attendance at the end of the laying period. Attendance during laying was not influenced by low ambient temperature, precipitation, or nest initiation date. For all species combined, maximum egg temperatures increased as laying progressed. Eggs were heated to temperatures sufficient for embryonic development as early as the day that the second egg was laid. Our findings contradict the prevailing paradigm that incubation in waterfowl begins after clutch completion and raise questions about how hatching synchrony is achieved. We relate our findings to two hypotheses (nutrient limitation and viability–predation) that have been proposed to explain the limits to clutch size in ducks.
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 | 0.001 |
| 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) | 0.001 | 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".