Effects of local changes in active layer and soil climate on seasonal foliar nitrogen concentrations of three boreal forest shrubs
Bibliographic record
Abstract
Caribou Poker Creeks Research Watershed is a boreal forest watershed in Interior Alaska that is susceptible to regional warming and permafrost thaw. We measured seasonal foliar N concentrations of the black spruce understory shrubs, Vaccinium uliginosum L., Vaccinium vitis-idaea L., and Ledum palustre L. on north- and south-facing sides of the watershed. We predicted that the shrubs would respond to small-scale changes in active layer and soil climate, and we expected similar responses according to growth strategy (evergreen or deciduous). Overall, foliar N in shrubs was higher on warmer, drier soils with deep active layers: +7.9% N in V. uliginosum, +11.1% N in V. vitis-idaea, and +9.4% N in L. palustre. Each shrub had species-specific foliar N patterns that could not be categorized by growth strategy and were not well explained by soil climate or active layer. Leaf mineral nutrition is influenced by multiple processes, and foliar N was best explained by the combination of environmental variables operating at the study site. For Caribou Poker Creeks Research Watershed, we can expect increased N status of the black spruce understory along with continued climate warming, but changes cannot be predicted based on growth strategy.
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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 | 0.001 | 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".