Hatching Spread in a Cooperative Breeding Bird, the Pūkeko (Porphyrio melanotus melanotus)
Bibliographic record
Abstract
In birds, the onset incubation determines the hatch spread. Many studies have explored the role of hatch spreads in solitary breeding species, but there is little research on cooperative breeding species. Joint-laying is a rare form of cooperative breeding in which more than one female lay eggs in the same communal nest, and the group collectively cares for the clutch. This system addresses new questions about hatch spreads since joint nests are larger, contain eggs from multiple females, and have more caretakers than single female nests. Here, we present our research on hatch spreads in joint-laying pūkeko (Porphyrio melanotus melanotus). In our first study, we used an eleven-year data set to describe patterns and interactions between clutch size, hatch spread, and hatch order on hatching success and survival. Larger clutch sizes and longer hatch spreads increased the predicted number of fledglings. Lay order was strongly correlated with hatching order and incubation typically started after five eggs were laid. Chicks from earlier hatching eggs had greater rates of survival but the effect of hatch order on survival decreased in synchronous hatching nests. We suggest further exploration on roles of hatch spread on lifetime inclusive fitness. For our second study, we transferred eggs between nests to create artificially synchronous and asynchronous hatching treatment nests. Synchronous nests showed a trend of greater hatching success although this was not statistically significant. There was also no significant difference in offspring survival between treatments. While our results were largely inconclusive, we make recommendations for how to improve future experimental studies on hatching spread.
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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 | 0.001 | 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".