Effects of liming on soil physical and chemical properties in Europe and North America: A review
Bibliographic record
Abstract
Abstract Soil acidity is one of the major constraints limiting crop production worldwide. About 50% of the global arable land is acidic. Liming remains an effective strategy for soil acidity amelioration and improvement of soil fertility. The objective of this review was to summarize information on liming effects on soil physical and chemical properties in the North American and European contexts. We reviewed how different lime products influence soil pH and various soil processes that contribute to soil physical and chemical health. Our findings were that, when applied at appropriate rates, liming materials generally increased soil pH, cation exchange capacity (CEC), exchangeable calcium and magnesium, nutrient availability and reduced toxicities of aluminum (Al), manganese (Mn), and heavy metals. Many studies showed that liming modifies soil properties and processes both in the short‐ and long‐term. While most studies reported improvements in nutrient availability, there were some differences in liming impacts on phosphorus (P) and potassium (K), mostly due to differences in soil type and composition. Liming improves structural properties including aggregate stability, soil friability, porosity, and water infiltration. Knowledge about liming impacts on soil physical and chemical properties is essential for optimizing liming rates to enhance soil health and improve productivity. Future studies should explore liming effects on CEC, associations of P and K with cations supplied by liming (e.g., Ca 2+ ), and use of some waste materials as lime alternatives.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".