Soil carbon, nitrogen and phosphorus in modified rangeland communities
Bibliographic record
Abstract
Rangelands contain between 10 and 30% of global soil organic C reserves and may be an important sink for atmospheric CO2, but less C tends to be stored in rangelands cultivated for agricultural use than undisturbed rangelands. Establishing perennial plant communities on formerly cultivated rangelands is expected to stabilize soil properties and increase the amount of C stored in rangeland soils, but there is little information on what plant communities are most effective at building soil C reserves. The purpose of this study was to compare soil C, N, and P pools in ungrazed native rangelands with ungrazed, unfertilized rangelands that were cultivated and then 1) abandoned, 2) seeded with non-native perennial grasses or legumes, or 3) cropped annually for 5 to 6 years. Three study sites in southern Alberta, Canada with native Stipa-Bouteloua, Stipa-Bouteloua-Agropyron and Festuca campestris plant communities represented the major ecotypes of the Northern Great Plains. The total C, N, and P content of rangeland soils were greatest at the Festuca campestris site, followed by the Stipa-Bouteloua-Agropyron and Stipa-Bouteloua sites, probably due to climatic conditions (precipitation and temperature). Generally, soils under modified plant communities contained less total C and N than soils under native rangeland, but the total P content was related more to site preparation than experimental treatments. Soils under alfalfa, orchardgrass and bromegrass tended to have more total C and N than soils cultivated annually in continuous wheat or wheat-fallow systems. The accumulation of C and N in soils under permanent cover was not related to net primary productivity and may be influenced more by the chemical composition and rate of decomposition of plant residues.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".