Nitrate stimulates root suckering in trembling aspen (Populus tremuloides)
Bibliographic record
Abstract
In a greenhouse experiment, we tested whether the initiation, density, and growth of trembling aspen ( Populus tremuloides Michx.) root suckers are related to postdisturbance soil nutrient availability. After decapitation of functional 2-year-old aspen root systems, nutrient solutions adjusted for various concentrations and forms of mineral N, different concentrations of Ca2+, K+, or PO43–, and different pH were applied to the roots and their suckering response was assessed after 35 days. Root systems treated with NO3– at concentrations of 1.5 and 7.5 mmol/L produced nearly double the sucker density compared with an unfertilized control, while fertilizing with N in the form of NH4+ did not affect sucker numbers, regardless of concentrations. The best growth of suckers was achieved with a mixture of 15 mmol/L NO3– + NH4+whereas the lowest growth was observed with 15 mmol/L NH4+. Neither Ca2+, K+, and PO43– nor the pH tested in this study impacted sucker density or growth. This has implications for understanding the impacts of disturbance on forest succession and the subsequent regeneration of aspen stands. The results suggest that the amount of nitrification, depending on the type and severity of disturbances, will influence the regeneration density of aspen.
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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".