Evaluation of Native and Introduced Grasses for Reclamation and Production
Bibliographic record
Abstract
Crested wheatgrass (Agropyron cristatum [L.] Gaertn.) and Russian wildrye (Elymus junceus Fisch.) are commonly used for reseeding in the more xeric Mixed Prairie of the Canadian prairies because they are perceived to be more productive than native species. However, they have been implicated in soil deterioration. The objectives of our study were to compare the aboveground net primary production and soil organic carbon (C) among monoculture communities of selected native grass species, crested wheatgrass, and Russian wildrye and to compare the native grass monocultures with their mixtures. In 1995, a 5-year study was initiated on Dark Brown Chernozemic (Typic Haploboroll) soil near Lethbridge, Alberta. Ten treatments consisting of monocultures of introduced and selected native species and mixtures of native species were established in a randomized complete block design with 4 replications. Aboveground net primary production and soil organic C were measured. Monocultures of 2 native species, green needlegrass (Stipa viridula Trin.) and blue grama (Bouteloua gracilis [H.B.K.] Lag. ex Steud.), were more productive than crested wheatgrass or Russian wildrye under both normal moisture and drought conditions. Monocultures of these native species also tended to be more productive than their mixtures. The western wheatgrass (A. smithii Rydb.) monoculture and the western wheatgrass-blue grama mixture experienced the greatest yield reduction as a result of drought. Treatment effects on soil organic C were not detected (P > 0.05) 5 years after seeding. Soils of the June grass (Koeleria macrantha [Ledeb.] J.A. Schultes f.) community had less (P < 0.05) macro-organic C than most other treatments.
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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 | 0.001 | 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".