Rangeland management impacts on soil biological indicators in southern Alberta
Why this work is in the frame
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Bibliographic record
Abstract
Quantitative techniques are needed to determine the effects of cultivation and livestock grazing on biological indicators of soils of the Northern Great Plains. Our objective was to determine how various management practices, which were representative of those used since European settlement in the 1880's, affected 3 biological indicators of soil quality. The study was conducted at 3 sites that are representative of the major grassland ecosystems in Canada: a Mixed Prairie site with Stipa comota Trin. Rupr. dominant in the Brown (Aridic Haploboroll) Soil Zone, a Mixed Prairie site with S. comata Trin. Rupr. and S. viridula Trin. dominant in the Dark Brown (Typic Haploboroll) Soil Zone, and a Fescue Prairie site with Festuca campestris Rydb. dominant in the Black (Udic Haploboroll) Soil Zone. At each site, 6 treatments representing common production practices were imposed and compared with the native community in a randomized complete block design with 4 replicates and a plot size of 3 x 10 m. The treatments included: 1) monoculture seeding of 2 grass species; 2) alfalfa (Medicago sativa L. 'Beaver'); 3) continuous spring wheat (Triticum aestivum L. 'Katepwa'): 4) spring wheat and fallow rotation; and 5) abandoned cultivated land. Our hypothesis that mineralizable-N, and phosphatase and dehydrogenase activities would be influenced by cultivation was confirmed by significant changes in these indicators that were detected after only 180 days after treatment establishment. The pool of readily decomposable organic matter was reduced with cultivation and not replenished over the period of the study. The 3 biological indicators were sensitive to not only time following external management changes, but also to seasonal fluctuations. We conclude that soil biological indicators can be used to quantify temporal and botanical changes in diverse ecotypes within the Northern Great Plains.
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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 | 0.001 |
| 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 it