Short-rotation willow productivity and nutrient dynamics after three years of irrigation and fertilization
Bibliographic record
Abstract
Purpose-grown shrub willow (Salix spp.) represents a viable bioenergy feedstock; however, there needs to be sufficient biomass production to support the economic viability of these plantations. The objective of this three-year study was to determine the effect of irrigation and fertilization on willow biomass feedstock quantity. A split-split-plot experimental design was used on a Sutherland clay soil in Saskatoon, SK and consisted of two willow varieties (SV1 and Charlie), three irrigation treatments (no irrigation, 75%, and 100% field capacity), and three fertilization treatments (no fertilizer, 1x, and 2x recommended fertilizer rate). During the final growing season, 15N-labelled fertilizer was used to determine the fate of the applied fertilizer. For both willow varieties, after the three-year rotation there was a highly significant (P values < 0.0001) growth response to irrigation, with no significant (P values > 0.05) effects of fertilization or irrigation x fertilization. Sixty-seven percent of the applied fertilizer N was accounted for, with approximately 30% present within the willow tissues (e.g., stems, leaves, and roots). The positive willow growth response to irrigation is indicative of the importance of soil moisture within the semi-arid climate of Saskatchewan. The lack of fertilizer effect probably reflects the fertile soil at the site and the apparently low nutrient requirement of willow.
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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 | 0.001 |
| 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".