Carbohydrate transfer through root grafts to support shaded trees
Bibliographic record
Abstract
We investigated whether root grafts between lodgepole pine (Pinus contorta var. latifolia Dougl. ex. Loud.) trees can transfer sufficient carbohydrate reserves from a source tree to a grafted sink tree to affect the vigor of trees growing in a light-limited environment. Eleven plots were established in early spring and two grafted tree pairs and two independent non-grafted trees were selected at each plot. One tree in a grafted pair and one non-grafted tree were shaded at each plot, whereas the remaining trees were non-shaded during the experimental period. Shaded trees had significantly lower carbohydrate reserves and smaller crowns than non-shaded trees following one growing season. Grafted shaded trees had significantly higher root total nonstructural carbohydrate concentrations than non-grafted shaded trees, indicating that root grafts partially offset the effects of shading. Also, large root grafts transferred proportionately more carbohydrates to the shaded trees than small root grafts. Carbohydrates transferred through root grafts could allow grafted trees to persist under conditions where non-grafted trees would be removed by competition.
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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".