Phosphorus Leaching from Soil Cores from a Twenty‐Year Study Evaluating Alum Treatment of Poultry Litter
Bibliographic record
Abstract
Adding alum to poultry litter is a best management practice used to stabilize P in less soluble forms, reducing nonpoint‐source P runoff. However, little research has been conducted on how alum additions to litter affect subsequent leaching of P from soil. The objective of this study was to evaluate the effects of alum‐treated versus untreated poultry litter on P leaching from soil cores receiving long‐term poultry litter applications. Two intact soil cores were taken from each of 52 plots in a long‐term study with 13 treatments: a control, four rates each of untreated and alum‐treated litter (2.24, 4.49, 6.72, and 8.96 Mg ha −1 ), and four rates of ammonium nitrate (65, 130, 195, and 260 kg N ha −1 ). One core from each plot received the same fertilizer as for the previous 20 yr, whereas the other was unfertilized in the study year, resulting in a total of 25 treatments. Cores were exposed to natural rainfall, and P leaching was measured for 1 yr. The average soluble reactive P concentrations in the leachate varied from 0.16 to 0.44 mg P L −1 in fertilized alum‐treated cores, whereas leachate from cores fertilized with untreated litter ranged from 0.40 to 2.64 mg P L −1 . At the highest litter rate (8.96 Mg ha −1 ), alum reduced total dissolved P and total P concentrations in leachate by 83 and 80%, respectively, compared with untreated litter. These results indicate that alum additions to poultry litter significantly reduced soluble and total P fractions in leachate. Core Ideas This study used soil cores from a 20‐yr small plot study. Alum additions to poultry litter have a legacy effect on soil‐test P. Soils fertilized with alum had significantly lower Mehlich‐3 P values below 10 cm. Alum additions bind organic P in poultry litter and soil. Total P leachate losses were reduced by 86% with alum.
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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 | 0.001 | 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) | 0.001 | 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 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".