Chernozemic soils of Canada: Genesis, distribution, and classification
Bibliographic record
Abstract
Pennock, D., Bedard-Haughn, A. and Viaud, V. 2011. Chernozemic soils of Canada: Genesis, distribution, and classification. Can. J. Soil Sci. 91: 719–747. Chernozemic soils in Canada have a characteristic biomantle that fully expresses the effect of organisms on soil formation. Additions of large amounts of below-ground biomass from grasses are transformed into complex organic compounds through the activities of meso- and macro-fauna, microbial degradation and combustion by fires. Degradation is regulated by (a) climatic influences on plant inputs and microbial activity, (b) the chemical and biochemical nature of the residues, (c) encapsulation of organic matter within aggregates by soil micro-faunal activities and freeze–thaw processes and (d) protection against decomposition by Ca 2+ and clay minerals. These organic compounds are mixed with the mineral matrix through the action of organisms from mites to badgers. Regional differences in the regulators cause differences in soil organic carbon (SOC) storage and the colour value of the surface Chernozemic A horizon. The storage of SOC is lowest in the Brown soil zone (≈60 to 80 Mg ha −1 ) and greatest in the Black soil zone (≈120 to 150 Mg ha −1 ); this corresponds to a decrease in the annual water deficit from ≈200 mm (Brown) to 70 to 100 mm (Black). Where soil CaCO 3 contents are high either through initial concentration in the parent material or by the precipitation of secondary CaCO 3 , substantially higher SOC storage than the regional norms can result. A repetitive catenary pattern occurs throughout the region. The primary controls on this pattern are hydrological – a lateral component to water flow in hillslopes leads to more developed horizonation downslope, and discharge surrounding wetlands causes precipitation of secondary carbonate minerals and more soluble salts in a fringe surrounding the wetlands. Chernozemic landscapes have been highly altered by humans through their conversion to agricultural production. Loss of the dense root network of the native grasslands causes a substantial decrease in SOC. This loss of carbon and reduction in A horizon thickness is accelerated by erosion; the effects of tillage erosion are now recognized as being ubiquitous through the agricultural region. The substantial amounts of SOC storage and our ability to increase storage through altered management practices make these soils a particular focus of interest in a future made more uncertain by the possibility of human-induced climatic change.
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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".