Trends in dissolved phosphorus in Gray Luvisol soil profiles after forest harvest
Bibliographic record
Abstract
Forest disturbances that increase P export from hillslopes will have negative consequences for site productivity and regional water quality. We studied P behavior in Gray Luvisols to understand the soil profile’s influence on P export from typical hillslopes of the Boreal Plain ecozone. We hypothesized that (1) P concentration is highest in upper horizons, (2) solution P is primarily in the dissolved and organic form, and (3) forest harvest will increase solution P concentration. We analyzed the soil solution, with emphasis on P, and determined P sorption properties of key soil horizons. Mean soluble reactive phosphorus concentration decreased with depth, ranging from 64 mg L-1 in the forest floor to 0.01 mg L-1 in the groundwater zone; solution P was mostly orthophosphate. Water soluble phosphorus decreased from 74 ± 9 to 41 ± 9 mg L-1 and extractable phosphorus was reduced in the forest floor only on two of four sampling occasions after harvest. Dissolved organic carbon may indirectly promote orthophosphate dominance in solution by complexing metal cations that would otherwise precipitate metal-P from solution. Gray Luvisols probably export P to soils lower on the hillslope catena, such as those of the Gleysolic and Organic Orders, both commonly associated with wetlands. Key words: Forest soil, phosphorus, orthophosphate, Gray Luvisol, biogeochemistry, sorption
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".