Habitat differences in allocation of eggs between successive breeding attempts in great tits (<i>Parus major</i>)
Bibliographic record
Abstract
:The effect of habitat heterogeneity on animal behaviour and reproduction has recently captured serious attention in population and conservation biology. The great tit (Parus major) is a facultative double-brooded species that prefers deciduous forests as breeding habitats. However, it is able to reproduce in managed coniferous forests where nest boxes are provided. During 1999–2002, we measured various reproductive parameters of great tits, including double breeding, in a heterogeneous habitat complex consisting of both deciduous and coniferous forests. Probability of laying a second clutch after the hatch of the first clutch did not differ significantly between habitats. However, clutch size was allocated between two successive breeding attempts more equally in coniferous than in deciduous forests. To our knowledge, this is the first time that such a difference in seasonal breeding patterns between adjacent habitats has been demonstrated in birds. However, the total number of offspring fledged per pair did not differ significantly between habitats. Possible proximate and ultimate causes of the observed habitat differences are discussed. We suggest that habitat-specific allocation of reproductive investment between successive breeding attempts plays an important role in optimizing breeding tactics by facultative multiple-brooded bird species in a heterogeneous environment, potentially serving as a useful mechanism facilitating their adaptation to novel habitats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".