Soil greenhouse gas and nutrient dynamics in fertilized western Canadian plantation forests
Bibliographic record
Abstract
We explored the impacts of fertilization on soil greenhouse gas fluxes and underlying soil nutrient transformations using short-term (up to 7 months) simulated operational fertilization with urea-nitrogen or nitrogen, phosphorus, potassium, and micronutrients in lodgepole pine ( Pinus contorta Dougl. ex Loud. var. latifolia Engelm.), western hemlock ( Tsuga heterophylla (Raf.) Sarge.), and Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) forests in British Columbia. Urea appeared to be rapidly mineralized to ammonium, and nitrification (relative to controls) was only observed at the lodgepole pine site and represented only 0.5% of added nitrogen. All sites were small net sinks for atmospheric methane, and fertilization effects, both stimulatory and inhibitory, were short-lived. 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 0, with the exception of one efflux rate of 1.5 µg·m–2·h–1on the warmest day in the study. We 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, ammonium, or a combination of nutrients, the dynamics of soil greenhouse-gas fluxes are generally not disturbed over the short-term, with soils remaining small sinks for atmospheric methane and neutral with regard 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".