Physiological and growth responses to defoliation of older needles in Abies alba trees grown under two light regimes
Bibliographic record
Abstract
In most defoliation experiments with evergreen trees, leaves are removed proportionally across all leaf age classes or only the younger ones are removed. However, it remains unclear how the ecophysiological functions of older foliage potentially differ from those of younger leaves. Hence, we conducted a field experiment with five intensities of artificial defoliation (0%, 11% needle biomass loss = all ≥ 5-year-old needles removed, 27% loss = all ≥ 4-year-old needles removed, 46% loss = all ≥ 3-year-old needles removed, and 71% loss = all ≥ 2-year-old needles removed) of Abies alba trees grown under low-light (LL, 28% of full sunlight) and high-light conditions (HL, 70%). Photosynthesis of the remaining one-year-old needles; concentrations of non-structural carbohydrates (NSCs = soluble sugars + starch), total nitrogen (N), and soluble protein (SP) in stem sapwood and one-year-old needles; and tree height and stem radial growth rates were measured. We found that growth light conditions, rather than old needle defoliation up to a needle biomass loss of 70%, significantly affected growth, photosynthetic capacity and concentrations of tissue N, SP, and NSCs, with levels of all parameters greater in HL trees than in LL tress. Defoliation-induced compensatory growth was found in HL trees only, whereas tree height growth rates tended to decrease with increasing defoliation intensity in LL trees. Our results indicate that light availability, rather than damage to older foliage, plays an important role in determining plant physiology and growth. These results from A. alba trees suggest that the resource uptake by older foliage almost balances their resource consumption, leading to the conclusion that the older needles from evergreen trees physiologically contribute less to the whole-tree carbon and nitrogen balance. Our findings also suggest that the effects of older foliage defoliation on forest survival and productivity may have been overestimated in past forest ecosystem management practices, while the physiological functions of the youngest foliage may have been underestimated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".