Effects of chronic N fertilization on foliar membranes, cold tolerance, and carbon storage in montane red spruce
Bibliographic record
Abstract
We evaluated the influence of protracted low-level nitrogen (N) fertilization on foliar membrane-associated calcium (mCa), sugar and starch concentrations, membrane stability, winter cold tolerance, and freezing injury of red spruce (Picea rubens Sarg.) trees growing in six experimental plots on Mount Ascutney, Vermont. For 12 consecutive years before this evaluation, each plot received one of three treatments: 0, 15.7, or 31.4 kg N·ha1·year1supplied as NH4Cl. In comparison with trees from control plots, the current-year foliage of trees from N-addition plots had lower mCa concentrations, higher levels of electrolyte leakage, reduced cold tolerance, and greater freezing injury. Levels of mCa, membrane stability, and cold tolerance did not differ between N treatments, but trees in high-N treated plots experienced greater freezing injury. Although no differences in carbohydrate nutrition were detected in September, foliar sugar and starch concentrations from trees in N-treated plots were higher than control plot trees in January. We propose that foliar mCa deficiencies reduced cell membrane stability, decreased cold tolerance, and increased freezing injury for trees in N addition plots relative to controls. Declines in mCa may also help account for increases in respiration previously measured. Because soil, root, and mycorryhizal conditions were not evaluated, it is unknown how treatment-induced changes in these compartments may have influenced the alterations in foliar mCa and physiological parameters measured in this study.
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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".