Phosphorus sorption capacity of alkaline Manitoba soils and its relationship to soil properties
Bibliographic record
Abstract
The establishment of the P retention capacity of soil in Manitoba is essential for effective management of P in the region. However, the methods for determining the P retention capacity for neutral to calcareous soils in the Eastern Prairies are not well developed. The objectives of this study were to determine the P retention capacity of Manitoba soils and to generate equations that relate these capacities to other soil properties. One hundred and fifteen archived surface soils were selected and their physico-chemical properties were measured. These soils were used to generate a single-point P adsorption index by equilibrating 2 g of soil in 20 mL of 0.01 M KCl solution containing either 150 (P 150 ) or 400 (P 400 ) mg P L -1 . A subset of 26 of these soils was used for multipoint isotherms with P concentrations in the range of 0–1000 mg P L -1 . The data obtained were fitted to the Langmuir isotherm and the adsorption indices were correlated with the various soil properties that were then used to developed predictive equations of the P retention capacity of the soil. The values of the adsorption index, P 150 , obtained from the single point adsorption study using 150 mg P L -1 , ranged between 88 and 891 mg P kg -1 , while that of P 400 ranged between 100 and 1250 mg P kg -1 . A better correlation was obtained between P 150 and soil properties compared with P 400 . For the 26 soil subset, the adsorption indices, S max1 to S max 6 , obtained from the Langmuir isotherm, ranged from 300 to 1330 mg kg -1 . A good correlation was obtained between the single point index and the multipoint isotherm (r = 0.93). Hence, S max for the 115 soils was estimated from the relationship between P 150 and S max 3 of the 26 soils. The best relationships between the adsorption parameters, P 150 and S max , and the soil properties were obtained with the sum of Mehlich-3 extractable Ca and Mg (R2= 0.66) and the sum of exchangeable Ca and Mg (R 2 = 0.64). Mehlich-3-Ca and -Mg each explained 56% of the variation, while clay content explained 40% of the variation in the P retention capacity of these soils. Unlike the widely reported influence of Al and Fe in acid soils, our study showed that the retention of P in Manitoba soils was influenced more by Ca and Mg and soil texture. Key words: Phosphorus, phosphorus retention capacity, phosphorus adsorption capacity, phosphorus sorption, single-point index
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".