Vegetation height and egg coloration differentially affect predation rate and overheating risk: an experimental test mimicking a ground-nesting bird
Bibliographic record
Abstract
Avian eggs need to be laid in protected environments to develop and survive. Nest predation is known as the main cause of breeding failure for many birds, but nest microclimate conditions are also important for embryo development. These two selective pressures are particularly marked in ground-nesting birds. Vegetation height has been shown to be a critical factor for nest-site selection in ground-nesting birds because it can counteract predation and overheating simultaneously. It is therefore difficult to disentangle the respective influences of these risks on selection of a particular nest vegetation height. To develop a conceptual framework for understanding and predicting the relative effects of vegetation on predation and nest microclimate during a breeding season, we used vegetation height to manipulate differentially these two risks. We therefore exposed artificial nests to a wide range of vegetation heights, replicated the experimental tests during spring, and manipulated egg color to estimate predation risk. We confirmed that tall vegetation is relevant to protect unattended eggs against both risks. Whereas predation risk is stable for a given vegetation height, overheating risk presents inter- and intra-seasonal variations. Therefore, over a breeding season, for a given vegetation height, the respective strengths of the two risks are unbalanced and depends on egg coloration. The breeding strategy of ground-nesting birds thus should have been shaped by both selective pressures, but the ultimate choice may depend on the species-specific laying dates and alternative behavioral strategies for protecting the clutch. This study provides new perspectives to investigate avian parental behaviour.
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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 | 0.000 |
| 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".