Soil water regimes of annual and perennial forages during drought years in the Aspen Parkland ecoregion of Alberta
Bibliographic record
Abstract
Periodic and prolonged drought can be devastating to pasture production, which increases the financial risk for grazing enterprises. A study was conducted during 2 drought years (2002 and 2003) in the aspen parkland at Lacombe, Alberta, Canada, to compare the soil water regime of meadow bromegrass (Bromus riparius Rhem.), alfalfa (Medicago sativa L.), and annual [oat (Avena sativa L.) and winter triticale (X Triticosecale Wittmack)] pastures with a naturalized, old grass pasture consisting of quackgrass (Elytrigia repens L.), smooth bromegrass (Bromus inermis Leyss.), and Kentucky bluegrass (Poa partensis L.). The pasture soil was an Orthic Black Chernozem of fine sandy loam to loam texture. Soil water measurements were conducted between May and October over 2 yr using a neutron scattering hydroprobe to a depth of 1.6 m. Annual and meadow bromegrass had similar and highest cumulative and volumetric water contents and old grass had the lowest. All pastures tended to use all water available by the end of the season, but annual pasture had higher soil water in spring and early summer due to delayed canopy development. Soil in the upper 40 cm of annual and meadow bromegrass pastures was at wilting point 5 to 10% of all measurement times compared with 65 to 71% of measurement times for alfalfa and old grass. Annual and meadow bromegrass pastures did not extract water below 1.2 m, while the other pastures did, and on the basis of soil water regimes, appear to be lower risk options than status quo old grass and alfalfa pastures during drought. Key words: Soil water, forages, rotational grazing, drought, wilting point, field capacity
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".