Significant delays in Aleppo pine phenology induced by a rain-exclusion experiment to emulate climate of 2100
Bibliographic record
Abstract
Introduction: Global climate models agree in predicting a faster warming in the Mediterranean than in most of other continental regions, along with a reduction of spring and summer precipitations. By increasing drought stress and changing phenology patterns, global warming and its corollaries, as heat waves and extensive droughts, are direct threats to forest productivity, health and survival. Expected stress-related changes in phenology are delays in flowering, fruiting, dormancy and needle growth. The objective of this research was to assess tree phenological responses in a 2100 rainfall context. \n\nMethods: We used an experimental forest site were 30% of rainfalls are excluded using gutters, along with a control. Scaffoldings were built up to the forest canopy to monitor tree phenology and crown development on 16 trees. Phenological surveys were performed monthly between 2009 and 2015. Evaluations of budburst, shoot and needle elongation and fruiting were made on five to eight branches on the whole crown of each tree. \n\nResults: A significant delay in fruiting, needle extension and shoot growth was observed in the rain exclusion plot. Delays can be as long as two months for frail branches in opposition to vigorous branches in the control plot. Some years, bud burst never occurred for some frail branches. The most significant result is that some trees never reached dormancy in the top crown, as a result of mild winters allowing a continuous growth, exposing the active shoots to frost damages. \n\nDiscussion: A warmer climate is supposed to lengthen the growth season, what was observed for some trees. But drought stress may offset this gain by opposite effects, significantly delaying bud burst, shoot growth and needle development. We also expect severe damages in the future for trees growing yearlong in case of unusual low temperature during winter, such as in 2012 in our case.
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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 | 0.001 |
| 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".