Masting in whitebark pine ( <i>Pinus albicaulis</i> ) depletes stored nutrients
Bibliographic record
Abstract
• In masting trees, synchronized, heavy reproductive events are thought to deplete stored resources and to impose a replenishment period before subsequent masting. However, direct evidence of resource depletion in wild, masting trees is very rare. Here, we examined the timing and magnitude (local vs individual-level) of stored nutrient depletion after a heavy mast event in Pinus albicaulis. • In 2005, the mast year, we compared seasonal changes in leaf and sapwood nitrogen (N) and phosphorus (P) concentrations and leaf photosynthetic rates in cone-bearing branches, branches that never produced cones, and branches with experimentally removed cones. We also compared nutrient concentrations in cone branches and branches that had never had cones between 2005 and 2006, and measured tree ring width and new shoot growth during 2005. • During the mast year, N or P depletion occurred only in tissue fractions of reproductive branches, where photosynthetic rates were reduced. However, by the end of the following year, nutrients were depleted in all branches, indicating individual-level resource depletion. New shoot and radial growth were not affected by masting. • We provide direct evidence that mast events in wild trees deplete stored nutrients. Our results highlight the importance of evaluating reproductive costs over time and at the individual level.
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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 | 0.000 | 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 | 0.000 |
| 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 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".