Soil phosphorus dynamics on terrestrial natural ecosystems
Bibliographic record
Abstract
Abstract. Soil organic and inorganic phosphorus (P) compounds can be modified by distinctive ecosystems properties. This study aims to analyze soil P dynamics on terrestrial natural ecosystems, relating its organic (monoesters, diesters, and phosphonate) and inorganic (orthophosphate, polyphosphate and pyrophosphate) functional groups with important temporal, edaphic and climatic characteristics. A dataset including 88 sites was assembled from published papers that have determined soil P composition by liquid state one-dimensional 31P nuclear magnetic resonance of soils extracted with NaOH EDTA. Bivariate and multivariate regression models were used to enable a comprehensive understanding of soil P dynamics at an unprecedented geographical scale. In bivariate relationships, soil P compounds had overall similar behaviors on mineral and organic layers but with different slopes. Temporal (weathering), edaphic and climatic properties of ecosystems, together explain up to 78 % (diester) and 57 % (orthophosphate) of the variation of organic and inorganic P forms across ecosystems. Soil, particularly pH, total carbon, and carbon-to-phosphorus ratio, over climate and weathering, were the predominant drivers to explain P variation. Only, the diester-to-monoester ratio was controlled by independent and combined effects of soil weathering and soil properties, likely deriving from parent material differences. We conclude that soil organic and inorganic P pools as well as their functional groups composition are determined by distinctive drivers that regulate key ecological processes governing their presence, transformation and persistence on terrestrial natural ecosystems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".