Field-scale heterogeneity overrides management impacts following conversion to no-till within an arable system
Bibliographic record
Abstract
Crop establishment in no-till arable systems benefits from soil health conducive for growth. Combined with the incorporation of crop residues and manures, no-till can influence soil organic carbon (SOC) and organic matter (SOM) dynamics, crop productivity and nutrient cycling. These processes are shaped by spatial and temporal factors including associated microbial activity. This study aimed to investigate the interaction between microbial and soil physicochemical properties during the transition from full-inversion to no-till soil management. Assessments were conducted over a two-year period and included a combination of soil microbial assays (microbial biomass carbon and nitrogen with physicochemical analyses, SOC, SOM, textural class, pH, gravimetric water content, and macronutrients). Two experiments were established within the same four-hectare field: one on a relatively level area (Experiment-1) and another on a slope (Experiment-2). Experiment-1 treatments consisted of Farmyard Manure (FYM and N-fertiliser), Green Manure (GM, Raphanus sativus and Vicia sp. mix) and Standard Practice (SP = Control, N-fertiliser only). Experiment-2 was a repeat of Experiment-1, but without the FYM treatment. Soil was sampled twice per crop season, in Spring and Autumn, in Experiment-1, and in Autumn only in Experiment-2. The results were influenced by spatial (i.e. where the same was collected from) and temporal (i.e. the time at which the same was collected) variations that were not always linked to management practices. This study demonstrated that the quantification of SOC and SOM were poor predictors of change in management practices over two years, while microbial biomass responded quickly to the incorporation of FYM. SOC and SOM were affected by soil texture, but not significantly by inputs, and were associated with extractable Ca2+ and total-N. Diachronic studies increase our understanding of biological and physicochemical dynamics in response to short-term change in soil management practices. This study emphasises the impact of soil texture within a single heterogenous field, and how it affects management outcomes. It highlights the importance of considering spatial differences to develop effective and sustainable agricultural solutions.
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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 | 0.001 |
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".