<i>Bromus-Poa</i>response to defoliation intensity and frequency under three soil moisture levels
Bibliographic record
Abstract
Smooth brome (Bromus inermis Leyss.) and Kentucky bluegrass (Poa pratensis L.) are important herbage for livestock and wildlife in Aspen-Boreal ecosystems in central Alberta, but there is paucity of information on the relationship between soil moisture and defoliation regimes on herbage production in these ecosystems. In a greenhouse experiment, we evaluated the effect of Bromus-Poa defoliation frequencies (2 or 4 wk) and intensities (2.5, 7.5, or 15 cm above the soil surface) under three soil moisture regimes [field capacity (wet), 50% field capacity (moist), 20% field capacity (dry)] on dry matter (DM) yield. Crude protein (CP) content, crude protein yield (CPY) and neutral detergent fiber (NDF) were also determined for herbage harvested. Total accumulated shoot DM decreased under defoliation compared to the undefoliated control, was higher if plants were clipped every 4 wk, rather than 2 wk, and increased with increasing soil moisture availability. Defoliation regimes decreased root DM Compared to the undefoliated control. Soil moisture regime did not significantly affect below-ground DM production, but root:shoot ratio increased significantly with decreasing moisture supply. The average CP content of grasses ranged from 12 to 23%, but was adequate to meet crude protein requirements of growing, pregnant or lactating grazing cattle (Bos spp.) The CPY decreased with increasing moisture stress, and was greatest when plants were clipped at a 7.5-cm height. Shoot NDF concentration increased with decreasing clipping frequency. These result indicate the need to investigate the relationship between soil moisture and management practices that affect the productivity of tame pastures in Aspen-Boreal ecosystems. Key words: Bromus inermis, Poa pratensis, crude protein, neutral detergent fiber, water
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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".