Declines in soil-water nitrate in nitrogen-saturated watersheds
Bibliographic record
Abstract
Two forested watersheds (WS3 and WS9) in the central Appalachians were artificially acidified with ammonium sulfate fertilizer. WS9 was treated for 8 years, whereas WS3 has been treated for approximately 15 years. Soil leachate was collected from a depth of 46 cm (B horizon) in WS9 and below the A, B, and C horizons in WS3. Nitrate concentrations from WS3 increased for approximately 10–12 years (depending upon horizon) and then did not increase from 2000 through 2003 despite continued fertilizer treatments. Nitrate concentrations in WS9 soil water increased for the first 3 years of fertilization, and then declined for another 2 years. After that time, the concentrations remained relatively constant at approximately 15 µequiv.·L–1; this period of low nitrate concentrations included 2.3 years of fertilization followed by 8.2 years of no fertilization. Stream-water nitrate concentrations from both watersheds indicate they were in stage 2 of nitrogen saturation; however, the soil-water nitrate behavior observed within the setting of continued elevated nitrogen inputs is at odds with responses predicted in current nitrogen saturation theory. We believe that the cessation of nitrate increases in at least the B and C horizons were due primarily to abiotic retention, with recalcitrant forms of dissolved organic carbon providing the carbon needed to induce retention. These results show that nitrogen cycling in forest soil ecosystems is more complex than current nitrogen saturation theory suggests.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".