Nitrous oxide emissions, nutrient dynamics and nitrifier communities following fertilization of western hemlock, lodgepole pine and Douglas-fir forests
Bibliographic record
Abstract
I explored effects of fertilization on soil N₂O fluxes and underlying soil nutrients using short-term (up to 7 mo.) simulated operational fertilization with urea-nitrogen or nitrogen, phosphorus, potassium, and micronutrients (a N + micronutrients mix) in lodgepole pine, western hemlock, and Douglas-fir forests in British Columbia. The effect on the structure of ammonia- oxidizing bacterial (AOB) communities in the three forest ecosystems was also studied using polymerase chain reaction coupled with denaturing gradient gel electrophoresis (PCR-DGGE). Urea appeared to be rapidly mineralized to ammonium, and nitrification (relative to controls) was only observed in the lodgepole pine site and represented only 0.5% of added nitrogen. Across all sites and treatments, soils were as likely to consume as emit nitrous oxide, and among treatment replicates, rates were never significantly different from zero, with the exception of one efflux of 1.5 μg m-² hr-¹ on the warmest day in the study. I conclude from this pilot study that in acidic, unpolluted (with regard to nitrogen deposition) upland conifer forest soils in western Canada fertilized once or infrequently with urea or ammonium or a combination of nutrients, soil greenhouse-gas flux dynamics are generally not altered over the short-term, with soils remaining neutral with regards to flux of nitrous oxide.
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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 | 0.001 | 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".