Variability in the growth rates and foliage δ<sup>15</sup>N values of black spruce trees across a slope gradient in the Alaskan Interior
Bibliographic record
Abstract
Black spruce (Picea mariana (Mill.) B.S.P.) is a dominant species on north-facing slopes located on the permafrost in the Alaskan Interior, where tree growth rates vary significantly across slope gradients. To better understand the effects of nitrogen (N) and mycorrhizal associations on plant growth, we investigated the relationships between tree growth and isotope ratios of nitrogen (δ15N) in foliage and roots, because plant δ15N values reflect tree dependencies on N uptake by mycorrhizae. We established two transects (one along a slope gradient, and a second on a north-to-east axis at a fixed elevation) and four plots on the slope gradient transect. We measured current shoot growth of saplings on transects and aboveground biomass (AGB) in the plots. We collected foliage and fine root samples and measured their δ15N signatures and N concentrations. The AGB and shoot growth varied widely across the gradient: values were higher at high elevations and at the east–northeast aspect. Foliage δ15N values and N concentrations were positively correlated with tree growth, but growth rate was negatively correlated with the dependency on mycorrhizae for N uptake. Thus, black spruce had a reduced dependency on mycorrhizae for N uptake on the upper slope, where conditions were N-rich. On the lower slope, where the soil active layer was shallow, black spruce growth was limited and had an elevated dependency on mycorrhizae for N uptake.
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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".