Colloid-bound and dissolved phosphorus species in topsoil water extracts along a grassland transect from Cambisol to Stagnosol
Bibliographic record
Abstract
Abstract. Phosphorus (P) species in colloidal and dissolved soil fractions may have different distributions. To understand which P species are potentially involved, we obtained water extracts from the surface soils of a gradient from Cambisol, Stagnic Cambisol to Stagnosol from temperate grassland in Germany. These were filtered to < 450 nm, and divided into three procedurally defined fractions: small-sized colloids (20–450 nm), nano-sized colloids (1–20 nm), and dissolved P (< 1 nm), using asymmetric flow field-flow fractionation (AF4), as well as filtration for solution 31P-nuclear magnetic resonance (NMR) spectroscopy. The total P of soil water extracts increased in the order Cambisol < Stagnic Cambisol < Stagnosol due to increasing contributions from the dissolved P fraction. Associations of C–Fe/Al–PO43−/pyrophosphate were absent in nano-sized (1–20 nm) colloids from the Cambisol but not in the Stagnosol. The 31P-NMR results indicated that this was accompanied by elevated portions of organic P in the order Cambisol > Stagnic Cambisol > Stagnosol. Across all soil types, elevated proportions of inositol hexakisphosphate (IHP) species (e.g., myo-, scyllo- and D-chiro-IHP) were associated with soil mineral particles (i.e., bulk soil and small-sized soil colloids), whereas other orthophosphate monoesters and phosphonates were found in the dissolved P fraction. We conclude that P species composition varies among colloidal and dissolved soil fractions after characterization using advanced techniques, i.e., AF4 and NMR. Furthermore, stagnic properties affect P speciation and availability by potentially releasing dissolved inorganic and ester-bound P forms as well as nano-sized organic matter–Fe/Al–P colloids.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".