Regulation of Root Distribution and Depth by Phosphorus Localization in Agrostis stolonifera
Bibliographic record
Abstract
Root distribution in turfgrass systems influences drought tolerance and resource competition with undesirable species. We hypothesized that spatial localization of phosphorus (P) supply would permit manipulation of turfgrass root distribution. To test this hypothesis, creeping bentgrass ( Agrostis stolonifera L.) plants were exposed to localized P supply in two experiments. The first experiment split the root zone horizontally into two different growth tubes and the second used alumina-buffered P (Al-P) to localize P availability deeper within a continuous root zone. In the horizontally split root zones, heterogeneous P availability led to no difference in shoot growth compared with uniform P availability. Root proliferation was greatest in the growth tube with available P compared with the growth tube without P. The use of Al-P, regardless of its spatial distribution, doubled root-to-shoot ratios compared with soluble P. Much of the increase in the ratio was accounted for by reduced shoot growth. Use of Al-P increased rooting deeper in the root zone, especially when the Al-P was mixed only in the lower portion of the root zone. Our results are consistent with the hypothesis that root distribution of creeping bentgrass can be manipulated by spatial localization of P supply in the root zone and indicate that relative biomass allocation to roots and shoots may be manipulated with buffered P sources.
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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) | 0.000 | 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".