No carbon “bet hedging” in pine seedlings under prolonged summer drought and elevated <scp>CO</scp><sub>2</sub>
Bibliographic record
Abstract
Abstract More frequent drought episodes are expected to cause higher mortality in isohydric tree species such as pines, because individuals close their stomata early during drought in order to maintain constant needle water potentials. It has been suggested that trees delay the ensuing carbon starvation by actively storing carbon at the expense of growth (“bet hedging”). Because such a strategy is only adaptive in drought‐prone regions, we hypothesise that the degree of carbon “bet hedging” should differ between ecotypes. We repeatedly measured the allocation of biomass, starch and soluble sugars to needles, stem and roots in seedlings of nine populations of Pinus sylvestris and Pinus nigra along a gradient from Central Europe to the Mediterranean. During two consecutive growing seasons, seedlings grown from seed were exposed to factorial combinations of 4 months of drought (D1, D2) and ambient/elevated CO2 (aCO2/eCO2). Drought‐stressed pine seedlings did neither increase starch concentrations, nor change biomass production or experience lower mortality under eCO2 compared to aCO2. By the end of D2, seedlings from drier origin had accumulated more starch but at the same time also more biomass than seedlings from wetter origin. Surprisingly, seedlings acclimatised to dry conditions after D1 so that mortality dropped to zero and drought effects on needle starch (P. sylvestris) and overall starch (P. nigra), respectively, disappeared after D2. Synthesis. The absence of a trade‐off between carbon storage (starch) and growth (biomass), and the patterns of mortality observed in seedlings growing under combined drought and eCO2 do not support the theory of carbon “bet hedging” in isohydric Pinus sylvestris and Pinus nigra. Results suggest that reduced growth and acclimatisation minimised seedling mortality in the second year. Acclimatisation might thus enable pine seedlings to resist a moderate increase in summer drought frequency expected in the future.
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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) | 0.001 | 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".