Effects of fire at two frequencies on nitrogen transformations and soil chemistry in a nitrogen-enriched forest landscape
Bibliographic record
Abstract
This study reports results of the application of dormant-season prescribed fire at two frequencies (periodic (two fires in 4 years) and annual) at four southern Ohio mixed-oak (Quercus spp.) forest sites to restore the ecosystem functional properties these sites had before the onset of fire suppression and chronic atmospheric deposition. Each forest site comprised three contiguous watershed-scale treatment units: one burned in 1996 and 1999, one burned annually from 1996 through 1999, and an unburned control. Soil organic matter, available P, net N mineralization, and nitrification were not significantly changed by fire at either frequency, though values for the latter two properties increased 4- to 10-fold from the period 19951997 to the period 19992000. Fire at both frequencies resulted in increased soil pH and exchangeable Ca2+. Exchangeable Al3+ was reduced by fire at two of four sites, and the molar ratio of Ca/Al was increased by fire at three of four sites. In contrast to results in most studies of fire, N transformations and availability were not increased by fire in this N-enriched region (deposition of N averaged about 6 kg·ha1·year1 over the last 20 years). We hypothesize that the large observed increase in nitrification is an indication of the onset of N saturation. Although fire appears to offset the effect of atmospheric deposition in this region by increasing soil pH, Ca2+, and Ca/Al ratio and reducing available Al3+, increased NO3 fluxes through the soil from continued N deposition may negate the positive effect of fire.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".