Animal‐Based Organic Amendments and Their Potential for Excessive Nitrogen Leaching and Phosphorus Loading
Bibliographic record
Abstract
Nitrate contamination of groundwater has been attributed to application of poultry litter to amend soil organic matter on raspberry farms in British Columbia, Canada. A field study assessed the risk of organic amendments that cause nitrate leaching and nutrient accumulation. The amendments, poultry litter, municipal compost, horse manure, and three types of dairy manure solids, were applied at 25 or 50 Mg dry matter ha–1 to match farm rates before new plantings. Plots were either unseeded or seeded with a grass mix to simulate berry establishment with grass alley crop. Soil was sampled at 0‐ to 15‐, 15‐ to 30‐, and 30‐ to 60‐cm depths 15 times over 14 mo and analyzed for concentrations of NH4+ and NO3–, and at 0 to 15 cm for total C, N, and P at 6 mo after application. Three grass harvests were analyzed for yield and N offtake. Poultry litter supplied more than twice the total mineral N and total P compared to the dairy solids and horse manure, while the compost was intermediate. At 25 Mg ha–1, poultry litter increased concentrations of soil (0–15 cm) NH4+ and NO3– (>150 and >300 mg kg–1, respectively), compared with small short‐term increases by compost (∼70 and 100 mg kg–1, respectively). There was almost no increase from dairy and horse amendments. Grass N offtake reduced soil NO3– concentrations but did not eliminate the risk of leaching from poultry litter. We conclude that dairy solids and horse manure present less risk of nitrate leaching and P loading than poultry litter or municipal compost. Core Ideas Poultry manure and compost amendments greatly increased soil NH4+, NO3– and P. Grass ‘alley’ crop did no sufficiently mitigate soil mineral N from poultry manure. Little risk of nitrate leaching or P loading with dairy solids or horse amendments.
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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".