Evidence for Carbon Saturation in a Highly Structured and Organic‐Matter‐Rich Soil
Bibliographic record
Abstract
Recent studies suggest that mineral soils of temperate ecosystems have a limit in C sequestration capacity, and we reasoned that C saturation will be most evident in soils that are already rich in soil organic C (SOC) and have been exposed to a broad range of C inputs. Therefore, we determined soil C saturation in an agricultural experiment located in Ellerslie, AB, Canada, where organic‐matter‐rich soils have been cropped to cereal grain for 25 yr. In this experiment, the soils were subject to a broad range of soil C inputs due to a combination of straw retention, tillage, and N fertilization treatments. We determined if C saturation is occurring in soil size fractions that are functionally different. Soils were highly aggregated, with >85% of the soils consisting of macroaggregates. Straw retention, tillage, and N fertilization had no significant effect on the SOC concentration of most soil fractions. Soil organic C concentration of whole soil and soil aggregates isolated from whole soil did not increase with greater soil C inputs. Most of the soil fractions within the large or small macroaggregates did not sequester additional SOC in response to higher soil C inputs. Conversely, SOC concentration in experimental plot soils was significantly lower than that of adjacent grassland soils, which suggests that the maximum C sequestration level for a specific soil type depends on the management practices used. We conclude that C sequestration is governed by C saturation in this highly structured and high‐C soil. Our study suggests that soils of temperate ecosystems that are closer to their C saturation capacity may store additional C less effectively than soils that are further away from their saturation capacity.
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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) | 0.001 | 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".