Using cover crops to establish white and black spruce on abandoned agricultural lands
Bibliographic record
Abstract
Vegetation control is a critical factor in reforestation. On abandoned agricultural lands, an alternative to herbicide application is the use of cover crops to compete with the weeds and to improve survival and growth rates of transplanted species. A factorial experiment was carried out on four sites to test this hypothesis. The experiment included three factors. The first factor consisted of lime versus no lime application. The second factor included four cover crop combinations and a control. Cover crop combinations were winter barley ( Hordeum vulgare ) underseeded with either birdsfoot trefoil ( Lotus corniculatus ), Kentucky bluegrass ( Poa pratensis ), ladino clover ( Trifolium repens ), or a mixture of Kentucky bluegrass and ladino clover. The third factor consisted in planting either white ( Picea glauc a) or black ( Picea mariana ) spruce seedlings. Winter barley did not establish as rapidly and vigorously as expected. Nevertheless, the cereal reduced weed populations in the establishment year. For broadleaf weeds, this reduction was not large enough to allow a carryover during subsequent years. In contrast, subsequent increase of the grassy weed populations was slowed down in the presence of cover crops. The establishment of the other cover crops was poor and highly variable from site to site. It is not clear whether this relative failure was due to growing conditions, poor establishment of the cereal cover crop, or to other factors. Liming and cover crops had little effect on spruce growth but black spruce seedlings grew taller than white spruce seedlings at two out of four sites, and basal diameter of white spruce reached larger values than did black spruce. For white spruce, this might constitute an advantage in old fields where seedlings are prone to lodging under weed pressure. Finally, it was noted that seedling survival was exceptionally high in all treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".