Growing short rotation woody crops in a tree-based intercropping system in southern Ontario, Canada
Bibliographic record
Abstract
This study investigated the growth potential of three varieties of short rotation willow, used as bioenergy feedstock, on marginal land in both a conventional monocrop system and in an agroforestry intercropping system. Microclimatic differences between systems and their effects on willow growth were compared during the 2006 and 2007 growing seasons. Willow yields were significantly higher in the agroforestry field during both years of the study, with 3.0 and 1.1 odt ha-1 for the agroforestry and control fields, respectively, in 2007. Daily average photosynthetically-active radiation (PAR) was 210 [mu]mol m2 s-1 (16%) lower in the agroforestry system, and PAR was correlated with soil temperatures that were on average 0.4°C-2.7°C lower in the agroforestry field. Soil temperatures were negatively correlated with soil moisture values that were on average 1.4%-1.9% higher in the agroforestry field, and soil moisture content was positively correlated with willow yields. Results of this study suggest that moderate shading in an intercropping setup can result in a buffering effect on microclimate conditions, where there is less variation in soil moisture content and soil temperature across a range of weather conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 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".