Subsoils—a sink for excess fertilizer P but a minor contribution to P plant nutrition: evidence from long-term fertilization trials
Bibliographic record
Abstract
Abstract Background The phosphorus (P) stocks of arable subsoils not only influence crop production but also fertilizer P sequestration. However, the extent of this influence is largely unknown. This study aimed to (i) determine the extent of P sequestration with soil depth, (ii) analyze P speciation after long-term P fertilization, and (iii) compare soil P tests in predicting crop yields. We analyzed four long-term fertilizer trials in Germany to a depth of 90 cm. Treatments received either mineral or organic P, or a combination of both, for 16 to 113 years. We determined inorganic and organic P pools using sequential extraction, and P speciation using 31P nuclear magnetic resonance (NMR) and X-ray absorption near edge structure (XANES) spectroscopy. In addition, we applied three P soil tests, double-lactate (DL), calcium acetate lactate (CAL), and diffusive gradients in thin films (DGT). Results The results suggested that plants are capable of mobilizing P from deeper soil layers when there is a negative P budget of the topsoil. However, fertilization mostly only showed insignificant effects on P pools, which were most pronounced in the topsoil, with a 1.6- to 4.4-fold increase in labile inorganic P (Pi; resin-P, NaHCO3–Pi) after mineral fertilization and a 0- to 1.9-fold increase of organic P (Po; NaHCO3–Po, NaOH–Po) after organic P fertilization. The differences in Po and Pi speciation were mainly controlled by site-specific factors, e.g., soil properties or soil management practice rather than by fertilization. When modeling crop yield response using the Mitscherlich equation, we obtained the highest R2 (R2 = 0.61, P < 0.001) among the soil P tests when using topsoil PDGT. However, the fit became less pronounced when incorporating the subsoil. Conclusion We conclude that if the soil has a good P supply, the majority of P taken up by plants originates from the topsoil and that the DGT method is a mechanistic surrogate of P plant uptake. Thus, DGT is a basis for optimization of P fertilizer recommendation to add as much P fertilizer as required to sustain crop yields but as low as necessary to prevent harmful P leaching of excess fertilizer P.
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 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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".