Seasonal variability of leaf area index and foliar nitrogen in contrasting dry–mesic tundras
Bibliographic record
Abstract
Assimilation and exchange of carbon for arctic ecosystems depend strongly on leaf area index (LAI) and total foliar nitrogen (TFN). For dry–mesic tundras, the seasonality of these characteristics is unexplored. We addressed this knowledge gap by measuring variations of LAI and TFN at five contrasting subarctic heaths during the growing season 2007, from about 2 weeks after bud burst until about 2 weeks before senescence. The communities generally showed an early season LAI and TFN increase, owing to leaf development of deciduous shrubs, and limited variations later on, owing to concurrent leaf growth and mortality of evergreen shrubs. For most of the communities, the TFN:LAI ratio was constant along the entire sampling period, indicating that leaf growth and mortality, triggers for both LAI and TFN, are more important than leaf N retranslocation, which only affects TFN. A constant TFN:LAI ratio facilitates the determination of TFN from LAI, which is easier to measure or simulate. However, a sheltered community showed an increment in the LAI of the deciduous canopy in mid–late season, paralleled by a decreased TFN:LAI ratio.
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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 | 0.001 | 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".