Degree of Phosphorus Saturation as a Predictor of Redox‐Induced Phosphorus Release from Flooded Soils to Floodwater
Bibliographic record
Abstract
Phosphorus (P) loss from soils is often enhanced under flooded, anaerobic conditions, increasing the risk of freshwater eutrophication. We aimed to develop a predictive tool to identify soils with greater P release potential under summer‐flooded conditions, which would help in developing strategies to mitigate P losses. One in situ mesocosm study was conducted in field plots with three treatments: cattle manure amended, monoammonium phosphate amended, and unamended. Two ex situ field mesocosm studies were conducted, each having 12 surface soils from agricultural fields. Prior to flooding, soils were analyzed for various soil test P (STP, intensity) and P sorption measures (capacity), and degree of P saturation (DPS) indices were calculated using different intensity and capacity combinations. Mesocosms were flooded and redox potential, pore water, and floodwater dissolved reactive P (DRP) concentrations were determined periodically up to 42 (in situ) and 56 d (ex situ) after the onset of flooding. Floodwater DRP increased significantly in most soils with flooding time, and the maximum DRP (DRPmax) was considered as the flooding‐induced P release risk. Relationships between floodwater DRPmax and STP or DPS indices were established separately for low‐P (Olsen P ≤ 30 mg kg−1) and high‐P (>30 mg kg−1) soils. Several STP indices effectively predicted the P release risk from high‐P soils, but not from low‐P soils. However, DPS calculated using Olsen P (intensity) and P sorption capacity or P saturation index (capacity) performed better in predicting summer flooding‐induced P release across all soil categories, with a higher predictive power. Core Ideas Floodwater P concentration increased with flooding time in most soils. High P release risk with flooding was shown even in soils with low soil test P. Soil test P was not a good predictor of flooding‐induced risk of P release from soils. Several degree of P saturation indices were better predictors than soil test P. Identifying soils with high P release risk can help in efforts to mitigate P losses.
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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 | 0.001 |
| 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) | 0.000 | 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 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".