Modeling of phosphorus dynamics in contrasting agroecosystems using long-term field experiments
Bibliographic record
Abstract
Morel, C., Ziadi, N., Messiga, A., Bélanger, G., Denoroy, P., Jeangros, B., Jouany, C., Fardeau, J. C., Mollier, A., Parent, L. E., Proix, N., Rabeharisoa, L. and Sinaj, S. 2014. Modeling of phosphorus dynamics in contrasting agroecosystems using long-term field experiments. Can. J. Soil Sci. 94: 377–387. Long-term field experiments on phosphorus (P) fertilization were originally designed to study crop needs in different soil types by analyzing the effects of several rates of P fertilization on yields, their P concentrations and dynamics of plant-available soil P. The objective of this study was to test a computer-based model to simulate the P dynamics at the field scale using plant database and analyzing for plant-available P by a hierarchical process-based approach. It predicts both the concentration (C P ) of phosphate ions (Pi) in soil solution and the associated Pi amounts that in time equilibrate with Pi in solution. Five experiments, representative of contrasting soil types, land-use, and climates were selected. Our model equilibrates the change in plant-available P in the upper soil layer to the P budget between annual P inputs and outputs. Rates of P fertilization affected simulations following the same expected pattern across sites. Field-observed and simulated values are in good agreements in all sites. The field-observed variations of C P per unit of P budget ranged from 0.007 to 2.49 (µg P L −1 ) (kg P ha −1 ) −1 . The predictions are of the same order of magnitude. Predictions were compared with empirical long-term data and mismatches were discussed. This investigation highlights the scientific interest of long-term field P experiments to test and validate models describing P dynamics at the scale of the agricultural fields under different agricultural management practices.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".