Seasonal Dynamics and Defoliation Impact on Herbage Yield in Aspen Boreal Habitats of Alberta
Bibliographic record
Abstract
Within the aspen boreal ecosystems, little information exists on the seasonal dynamics of available herbage and the effects of varying defoliation regimes on accumulated herbage growth and associated opportunities for animal production. We examined seasonal changes in herbage phytomass in conjunction with defoliation treatments in Bromus inermis-Poa pratensis grasslands in central Alberta. Changes in herbage pools were examined by sampling at five monthly intervals from April to September 1997 and 1998, inclusive. Vegetation was also subjected to a factorial experiment with an initial defoliation in late-May, June or July, at heights of 2.5, 7.5, or 15 cm, and repeated at 3-, 6- or 9-week intervals until the end of September. Green herbage, standing dead and fallen litter increased from spring to summer and decreased from summer to fall. Average growing conditions resulted in a peak phytomass of 350 g m-2, and varied by year. Weathering losses of green herbage, standing dead and fallen litter over winter were 34%, 52% and 51%, respectively. Dry matter losses of total herbage (all three pools) over winter were 58% of 1997 summer green phytomass. Initial timing, height, and frequency of clipping all affected accumulated herbage yield (P < 0.001). The greatest accumulated herbage yield was from clipping initiated in May. Light clipping resulted in less phytomass accumulation relative to moderate and heavy clipping. Clipping frequencies of six and nine weeks resulted in similar phytomass removal, but were greater than herbage removal associated with three weeks frequency. The interaction between clipping date and frequency of clipping demonstrates the importance of temporal rest and sensitivity of forage plants to defoliation, and lends support to the use of rotational grazing systems.
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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".