Vegetation phenology and nest survival: Diagnosing heterogeneous effects through time
Bibliographic record
Abstract
Birds should select nest sites that minimize predation risk, but understanding the influence of vegetation on nest survival has proven problematic. Specifically, the common practice of measuring vegetation on nest fate date can overestimate its effect on nest survival, simply because vegetation at hatched nests grows for a longer period of time than vegetation at nests that were depredated. Here, we sampled the literature to determine the prevalence of this bias in studies of duck breeding ecology. We then used survival data collected from ~2,800 duck nests to empirically evaluate evidence of bias in four different vegetation metrics: vegetation density measured when the nest was found, density when the nest was fated, and date-corrected regression residuals of these two. We also diagnosed the magnitude of vegetation effects on nest survival by restricting our analysis to only nests which were fated contemporaneously (thereby removing potential bias in the timing of measurement). Finally, we examined whether systematic phenological differences exist between vegetation at hatched and depredated nests that have the potential to further obfuscate the relationship between vegetation and nest survival. We found evidence for a true-positive effect of vegetation density on nest survival that appeared to be inflated when using raw vegetation measurements collected at fate date. However, taken in combination with the literature review, our results suggest that the majority of duck nesting studies have evaluated the role of vegetation on nest survival using a relatively less biased metric-vegetation density when the nest was found. Finally, we found that over the course of a nesting attempt, vegetation increased in density at successful nests, but decreased in density at depredated nests. As a consequence, duck researchers using vegetation data collected when the nest was found may actually be underestimating the magnitude of the effect. This seasonal change potentially points to an important new metric for understanding predation risk, but further experimental research is required to fully eliminate potential biases in the timing of vegetation measurements.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".