Inverse relationship between understory light and foliar nitrogen along productivity gradients of boreal forests
Bibliographic record
Abstract
The constraints of light and N on sapling growth in forest understories can covary with site productivity, but this reciprocal relationship is not always recognized when describing stand dynamics. To facilitate this, we examined light availability and foliar N status of understory subalpine fir ( Abies lasiocarpa (Hook.) Nutt.) along natural productivity gradients of old-growth boreal forests in British Columbia, Canada. Understory light declined with soil fertility, from a high of 30% of full sun on poor sites to as low as 15% on very rich sites. In contrast, understory foliar N concentration (N%) of subalpine fir increased with soil fertility (ranging from 9.3 to 14.2 g·kg–1) and paralleled asymptotic stand height, despite growing in the shade. Trends in foliar N% of the understory were comparable with overstory subalpine fir, and both increased in foliar N% with soil fertility more so than lodgepole pine ( Pinus contorta Dougl. ex Loud.). Foliar N per unit leaf area of the suppressed understory was fairly consistent and relatively low (approximately 2.0 g N·m–2), suggesting no net change in the resource constraints to growth along the productivity gradient. The inherent linkages between soil fertility, light attenuation, and species N nutrition provides a useful framework for understanding regeneration dynamics over a full range of site potential.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".