Extreme climate conditions limit seed availability to successfully attain natural regeneration of <i>Pinus pinaster</i> in sandy areas of central Spain
Bibliographic record
Abstract
Natural regeneration comprises different subprocesses, each of them driven by specific climatic and stand-related factors, which determine the success of natural regeneration. The objective of this study was to investigate the seed availability of maritime pine (Pinus pinaster Aiton). To meet this objective, seed rain was monitored for four different levels of stand density at the experimental site of Cuéllar, Spain, during a 10-year period. A generalized linear mixed-effects model was fitted to test the effects of climatic variables and stand density on the annual seed production and seed rain. The climatic covariates were chosen among those that are thought to affect the key physiological phases governing these subprocesses: minimum temperature in October 2 years before dispersal (cone growing), April precipitation 1 year before dispersal (cone growing), and October–November precipitation 1 year before dispersal (cone maturation). No climate variable related to flowering or seed rain process was significant. Moreover, stand density was considered through a spatially explicit index called the seed-source index. Primary cone growth was limited by extreme cold events. Absence of precipitation limits secondary growth and hinders final cone ripening. It turns out that seed production and seed rain may be a bottleneck for natural regeneration of P. pinaster under low stand densities, especially under extreme climatic scenarios.
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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 | 0.001 | 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".