Intraspecific variation in the relationship between weather and masting behavior in valley oak, <i>Quercus lobata</i>
Bibliographic record
Abstract
Masting behavior — variable and synchronized reproduction by a population of plants — has long been recognized as correlating with weather. How and why weather conditions influence seed production is, however, poorly understood. We investigated the relationships between acorn production and both local weather and long-term climate in 10 populations across the geographic range of the valley oak (Quercus lobata Née), a California endemic that matures acorns in a single season. Acorn production was larger following a cold spring in the prior year and dry conditions in the winter and spring immediately preceding acorn maturation; similar patterns were also found, with minor differences, at all 10 individual sites. The strength of the relationships varied geographically in the case of the correlation between winter rainfall and annual acorn production, which was stronger (more negative) at wetter sites. Thus, in contrast to a recent study in Quercus petraea (Matt.) Liebl., weather had generally similar effects on acorn production throughout the range of Q. lobata. Similar to Q. petraea, however, the strength of the relationship between site-level annual acorn production and one of the weather factors affecting acorn production (winter rainfall in the case of Q. lobata) varied geographically in ways that may be related to differences among sites in the degree of pollen limitation. Understanding the mechanisms by which weather affects seed production is challenging but critical if we are to understand how climate change will affect masting behavior in the future.
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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 | 0.002 | 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 | 0.001 |
| 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".