Soil genesis and mineralogy alter the stability and activity of hydrolytic enzymes
Bibliographic record
Abstract
Hydrolases are a main group of enzymes that catalyze soil organic matter (SOM) decomposition, thus influencing the fate of organic carbon and nutrient release rates in soils. The rate of enzyme-catalyzed processes depends on the pool size and lifespan of enzymes. Both are strongly affected by soil genesis and mineralogy, yet this remains poorly documented by experimental data. In this study, we added three pure enzymes (β-glucosidase, acid phosphatase, and leucine aminopeptidase) to three soil horizons from a podzolic chronosequence with contrasting pedogenic characteristics: BC horizon: mainly primary minerals; Ae: quartz and organic matter enriched; and Bf: organo-metallic complexes and iron oxide enriched. Although the addition of pure enzymes increased enzyme activities by 1.3–2.3 times, only 7–22% of enzymes remained active one day after their addition into soil, moreover the active portion of added enzymes dropped to 5–12% over one week. The decay of enzymes followed the first-order model with rates ranging from 0.047 to 0.104 day–1. The lack of enzyme stabilization processes in BC horizon mainly comprised of primary minerals with lower specific surface area and reactivity led to greater activity loss of acid phosphatase compared to horizons enriched with organic matter (Ae) and/or pedogenic iron subproducts (Bf). The adsorption of leucine aminopeptidase on the surface of iron oxides in Bf horizon decreased enzyme activity but prolonged the persistence of enzyme activity. However, the catalytic efficiency of enzymes adsorbed on the surface of iron oxides was lower than that of enzymes associated with organic matter (Ae) or existed in a free form (BC). Our findings highlight the need to (i) further investigate the relationship between enzyme activity and SOM decomposition rate, especially if soil minerals reduce enzyme catalytic efficiency, and (ii) carefully consider incorporating soil genesis into enzyme activity-based models to improve the predictions, for example, of SOM decomposition.
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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 | 0.001 | 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".