Soil Organic Carbon Changes to Increasing Cropping Intensity and No‐Till in a Semiarid Climate
Bibliographic record
Abstract
Core Ideas After 10‐yr, NT annual cropping systems resulted in greater soil organic C mass relative to tilled fallow‐wheat. Cropping system intensity was more important to SOC mass than tillage. Changes in SOC mass were directly related to NPP and total C inputs. Annual cropping with NT management resulted in greater SOC mass (0–30 cm) than F‐W systems. SOC accretion was greatest in the CRP system. Soil organic C (SOC) in the semiarid Northern Great Plains (NGP) can benefit from increasing cropping intensity. We evaluated the effect of annual cropping on stocks of SOC adjusted for equivalent mass (SOC EM ; 0–30 cm) and the change in SOC adjusted for equivalent mass (ΔSOC EM ) over 10‐yr at a field site (45°40′N, 111°09′ W) near Bozeman, MT. The experiment consisted of two fallow‐wheat ( Triticum aestivum L.; F‐W) rotations under till and no‐till (NT), and five annual cropping systems under NT factored with two N levels (moderate and high), and alfalfa–perennial grass system (Conservation Reserve Program, CRP). After 10‐yr, we found SOC EM of five NT annual cropping ( = 37.4 Mg ha –1 ) was significantly ( P < 0.01) greater than NT F‐W (35.1 Mg ha –1 ), and till F‐W (33.7 Mg ha –1 ). The greatest SOC EM was found in CRP (39.9 Mg ha –1 ). Accretion of SOC EM was observed in three systems with the largest gains occurring in the CRP (0.24 Mg ha –1 yr –1 ), followed by NT continuous wheat (0.13 Mg ha –1 yr –1 ) and NT pea ( Pisum sativum L.)/oil seed–wheat (0.09 Mg ha –1 yr –1 ). Soil organic C loss was observed in all other systems with the largest loss in the till F‐W (–0.29 Mg ha –1 yr –1 ). Among the cropping systems, ∆SOC EM was directly related to net primary productivity (NPP; r 2 = 0.73) and total C (TC; shoot + root + rhizodeposit) inputs ( r 2 = 0.86). We found SOC EM was maintained at 7.0 Mg ha –1 yr –1 of net primary productivity (NPP) and 2.6 Mg ha –1 yr –1 of TC inputs with accretion and loss occurring above and below these thresholds.
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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 | 0.000 | 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) | 0.001 | 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".