0690 Effects of native and tame grassland species reintroduction on carbon sequestration potential on the Canadian Prairies
Bibliographic record
Abstract
Rising concentration of carbon dioxide in the atmosphere has prompted interest in implementing improved grassland management practices that could lead to a net accumulation of carbon in grassland soils. Converting cropland into native or tame perennial grasslands may result in substantial increase in soil C sequestration. Two studies were started in southern Saskatchewan where semiarid cropland was converted to perennial grasslands: Study 1 (2000–2014) seeded two different native pasture mixes (Simple, 7 species, and Diverse, 12 species) and Study 2 (2006–2011) seeded four different pasture types (meadow bromegrass + alfalfa [A], native grass mix [NG], NG + A, and NG + native legume). The objective of the studies was to determine the change in soil organic carbon (SOC) levels as affected by type of forage pasture mix and form of disturbance (grazing and nongrazing). In Study 1, the disturbance treatments were continuous, rotational, and nongrazing and the stocking rates were 0.8 and 1.9 animal unit (AU) ha−1, respectively. In Study 2, continuous grazing occurred and the stocking rate ranged from 2.0 to 4.0 AU ha−1 depending on which pasture treatment was used. All pastures were grazed to a utilization rate of 50 to 60%. Soil samples from each pasture were collected from three locations and at each location, a five radial (star pattern) sampling pattern occurred. From each of the five microsites, core samples were taken at five depths (0–7.5, 7.5–15, 15–30, 30–45, and 45–60 cm). Soil sampling for study 1 occurred in 2000, 2004, 2008, 2011, and 2014, whereas in study 2, it occurred in 2008 and 2011. In study 1, no SOC level (0–15 cm) differences were observed between disturbance and pasture mix combinations and interaction after 14 production years. Soil organic C levels were affected by year (P < 0.0001), which was expected with the different environmental conditions experienced among the different soil sampling years. In study 2, no SOC level (0–15 cm) differences were observed for interaction or main effects after three production years. Our studies did not support our hypothesis that a more diverse native mix (higher species richness) and tame grass + alfalfa would have higher SOC level than other treatments. Detecting small SOC change is difficult due to spatial heterogeneity in initial SOC, soil texture, bulk density, and plant productivity. Using our results, we develop criteria for measurement systems to detect changes design to detect SOC change.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".