Local‐scale synchrony and variability in mast seed production patterns of<i>Picea glauca</i>
Bibliographic record
Abstract
1 Mast seeding is the synchronous and highly variable production of seed by a population of plants. Mast seeding results from the behaviour of individuals; however, little is known about the synchrony of individuals at local scales. 2 We address two primary questions at a within-population (17–36 ha study plots) and individual level: (i) How variable is seed production between and within years? (ii) How synchronized is seed production between individuals? 3 We monitored annual cone production of 356 Picea glauca (white spruce) from 1990 to 2005 within four plots spanning a total distance of 5.3 km in the Yukon Territory, Canada. 4 Spearman correlations (rs) were conducted to test for synchrony. Overall, the trees were moderately synchronous (mean rs (± SE) of 0.52 ± 0.14), and synchrony was statistically detectable (rs > 0) over all distances. Individuals < 75 m apart were highly synchronous (0.64 ± 0.18), and correlations dropped to 0.33 ± 0.07 for trees > 3 km apart. There was considerable variation in cone production patterns among pairs of individuals. 5 The number of mast years per plot varied from one to three. During a mast year, many individuals within plots produced large cone crops, with more variability between individuals in low mean cone years. Individual trees had dominant endogenous cycles varying from none to 1–5 years. Forty-four per cent of trees had no significant lag, 23% a negative 1-year lag, and 20% a positive 3-year lag. Basal area did not influence lags, but trees with higher mean cone production throughout the study were more likely to have a 3-year lag compared with no lag. 6 The scale of highest synchrony coincided with the scale at which the dominant seed predator in the area, the territorial red squirrel (Tamiasciurus hudsonicus), operates. This may be the scale at which selection for synchrony occurs. 7 Based on high synchrony locally, high synchrony within a mast year, and multiple lags in cone production by individuals, both available resources and strong weather cues appear to play roles in the observed patterns.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".