Seasonal dynamics of non-structural carbon pools and their relationship to growth in two boreal conifer tree species
Bibliographic record
Abstract
In an attempt to comprehensively study the dynamics of non-structural carbon compounds (NCCs), we measured the seasonal changes of soluble sugars, starch, lipids and sugar alcohols in the leaves, branches, stem and roots of the fast-growing Pinus contorta (Loudon) (pine) and slow-growing Picea glauca (Moench) Voss (spruce) trees growing in a boreal climate. In addition to measuring the seasonal concentrations of these compounds, the relative contribution of these compounds to the total NCC pool within the organs of trees (~8 m tall) was estimated and compared across different phenological and growth stages. Both species showed large seasonal shifts from starch to sugars from spring to fall in nearly all organs and tissues; most likely an adaptation to the cold winters. For both species, the total fluctuation of sugar + starch across the year (i.e., the difference between the minimum and maximum observed across collection times) was estimated to be between 1.6 and 1.8 kg for all NCCs. The fluctuation, however, was 1.40 times greater than the minimum reserves in pine, while only 0.72 times the minimum reserves in spruce. By tissue type, NCC fluctuations were greatest in the roots of both species. Roots showed a large build-up of reserves in late spring, but these reserves were depleted over summer and fall. Storage reserves in needles and branches declined over the summer, and this decline may be linked to the sink strength of the stem during diameter growth. Some notable highlights of this holistic study: a late winter build-up of sugars in the stem xylem of both species, but especially spruce; and an increase in sugar alcohols in the bark of spruce in very late winter, which could indicate mobilization to support early growth in spring and high lipid reserves in the bark of pine, which appeared not to be impacted by seasonal changes between summer and winter. Collectively, these observations point toward a more conservative NCC reserve strategy in spruce compared with pine, which is consistent with its stress tolerance and greater longevity.
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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".