Soil properties in northern temperate pastures do not vary with management practices and are independent of rangeland health
Bibliographic record
Abstract
Studies examining the influence of disturbance and management history on pasture soils across a large sampling area are uncommon. We report on the soil properties found in 102 northern temperate pastures sampled in central Alberta, Canada, and relate these attributes to ongoing pasture management practices compiled from producer surveys and aboveground measures of rangeland health (RH). Tame pastures, typically seeded to introduced forages, were associated with higher soil fertility (total carbon, nitrogen, and organic matter) than semi-native grasslands, which were associated with coarse-textured soils. Soil properties remained independent of most grazing and pasture management practices, including the grazing systems, class of livestock, fertilization, and stocking rate. However, manure application, often combined with harrowing, was associated with improved soil fertility and increased electrical conductivity (salinity). Soils with a fire history reported by land managers, largely in the Boreal natural region, were characterized by a greater soil C:N ratio. Soil surface properties (litter cover, litter depth, and bare soil) were responsive to grazing management, with growing season and year-round grazing associated with a thinner litter layer having less cover, and bare ground twice as high under continuous grazing compared with pastures rotationally grazed. Further, variation in soil surface cover was associated with contrasting RH classes (healthy, healthy with problems, and unhealthy), whereas soil attributes remained unrelated to RH. This study demonstrates that soils within these northern temperate grasslands are relatively insensitive to many pasture management practices, and highlights that existing RH assessments may provide limited insight into differences in mineral soil properties.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".