An evaluation of biological soil health indicators in four long‐term continuous agroecosystems in Canada
Bibliographic record
Abstract
Abstract The soil microbial community (SMC) and soil organic matter (SOM) are inherently related and are sensitive to land‐use changes. Microorganisms regulate essential soil functions that are key to SOM dynamics, whereas SOM dynamics define the SMC. To expand our understanding of soil health, we evaluated biological and SOM indicators in long‐term (18‐yr) continuous silage corn ( Zea mays L.), continuous soybean [ Glycine max (L.) Merr.], and perennial grass ecosystems in Ontario, Canada. The SMC was evaluated via ester‐linked fatty acid methyl ester (EL‐FAME) and amplicon sequencing. Soil organic matter was evaluated via a new combined enzyme assay that provides a single biogeochemical cycling value for C, N, P, and S cycling activity (CNPS), as well as loss‐on‐ignition, permanganate oxidizable C (POXC), and total C and N. Overall, soil health indicators followed the trend of grasses > corn > soybean. Grass systems had up to 8.1 times more arbuscular mycorrhizal fungi, increased fungal/bacteria ratios (via EL‐FAME), and higher microbial diversity (via sequencing). The POXC was highly variable within treatments and did not significantly differ between systems. The novel CNPS activity assay, however, was highly sensitive to management (up to 2.2 and 3.2 times higher under grasses than corn and soybean, respectively) and was positively correlated ( ρ > .92) to SOM, total C, and total N. Following the “more is better” model, where higher values of the measured parameters indicate a healthier soil, our study showed decreased soil health under monocultures, especially soybean, and highlights the need to implement sustainable agriculture practices that maintain soil health.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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 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".