<i>Salix arctica</i> changes root distribution and nutrient uptake in response to subsurface nutrients in High Arctic deserts
Bibliographic record
Abstract
Abstract Moisture is critical for plant success in polar deserts but not by the obvious pathway of reduced water stress. We hypothesized that an indirect, nutrient‐linked, pathway resulting from unique water/frozen soil interactions in polar deserts creates nutrient‐rich patches critical for plant growth. These nutrient‐rich patches (diapirs) form deep in High Arctic polar deserts soils from water accumulating at the permafrost freezing front and ultimately rising into the upper soil horizons through cryoturbated convective landforms (frost boils). To determine if diapirs provide an enhanced source of plant‐available N for Salix arctica (Arctic willow), we characterized soil, root, stem, and leaf 15N natural abundance across 24 diapir and non‐diapir frost boils in a High Arctic granitic semi‐desert. When diapir horizons were available, S. arctica increased its subsurface (i.e., diapir) N uptake and plant root biomass doubled within diapir. Plant uptake of enriched 15N injected into organic rich soil patches was 2.5‐fold greater in diapir than in non‐diapir frost boils. S. arctica percent cover was often higher (7.3 ± 1.0 [mean ± SE]) on diapiric frost boils, compared to frost boils without diapirs (4.4 ± 0.7), potentially reflecting the additional 20% nitrogen available in the subsurface of diapiric frost boils. Selective N acquisition from diapirs is a mechanism by which soil moisture indirectly enhances plant growth. Our work suggests that diapirs may be one mechanism contributing to Arctic greening by shrub expansion.
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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) | 0.001 | 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".