Douglas-fir soil C and N properties a decade after termination of urea fertilization
Bibliographic record
Abstract
Chemical and microbial soil properties were assessed in paired unfertilized and urea fertilized (>89 g N·m2) plots in 13 second-growth Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) stands distributed throughout western Washington and Oregon. A decade following the termination of fertilization, fertilized plots averaged 28% higher total N in the O layer than unfertilized plots, 24% higher total N in surface (05 cm) mineral soil, and up to four times the amount of extractable ammonium and nitrate. Decreased pH (0.2 pH units) caused by fertilization may have been due to nitrification or enhanced cation uptake. In some soil layers, fertilization decreased cellulase activity and soil respiration but increased wood decomposition. There was no effect of fertilization on concentrations of light and heavy fractions, labile carbohydrates, and phosphatase and xylanase activities. No increase in soil organic C was detected, although variability precluded observing an increase of less than ~15%. Lack of a regionwide fertilization influence on soil organic C contrasts with several site-specific forest and agricultural studies that have shown C increases resulting from fertilization. Overall, the results indicate a substantial residual influence on soil N a decade after urea fertilization but much more limited influence on soil C processes and pools.
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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) | 0.000 | 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 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".