Phosphorus fractions and speciation in an alkaline, manured soil amended with alum, gypsum, and Epsom salt
Bibliographic record
Abstract
Abstract Snowmelt runoff is a dominant pathway of phosphorus (P) losses from agricultural lands in cold climatic regions. Soil amendments effectively reduce P losses from soils by converting P to less soluble forms; however, changes in P speciation in cold climatic regions with fall‐applied amendments have not been investigated. This study evaluated P composition in soils from a manured field with fall‐amended alum (Al 2 (SO 4 ) 3 ·18H 2 O), gypsum (CaSO 4 ·2H 2 O), or Epsom salt (MgSO 4 ·7H 2 O) using three complementary methods: sequential P fractionation, scanning electron microscopy with energy‐dispersive X‐rays (SEM‐EDX) spectroscopy, and P K‐edge X‐ray absorption near‐edge structure spectroscopy (XANES). Plots were established in an annual crop field in southern Manitoba, Canada, with unamended and amended (2.5 Mg ha −1 ) treatments having four replicates in 2020 fall. Soil samples (0–10 cm) taken from each plot soon after spring snowmelt in 2021 were subjected to P fractionation. A composite soil sample for each treatment was analyzed using SEM‐EDX and XANES. Alum‐ and Epsom salt‐treated soils had significantly greater residual P fraction with a higher proportion of apatite‐like P and a correspondingly lower proportion of P sorbed to calcite (CaCO 3 ) than unamended and gypsum‐amended soils. Backscattered electron imaging of SEM‐EDX revealed that alum‐ and Epsom salt‐amended treatments had P‐enriched microsites frequently associated with aluminum (Al), iron (Fe), magnesium (Mg), and calcium (Ca), which was not observed in other treatments. Induced precipitation of apatite‐like species may have been responsible for reduced P loss to snowmelt previously reported with fall application of amendments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.001 |
| 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 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".