Summertime Soil-Atmosphere Ammonia Exchange in the Colorado Rocky Mountain Front Range Pine Forest
Bibliographic record
Abstract
Understanding the NH3 exchange between forest ecosystems and the atmosphere is important due to its role in the nitrogen cycle. However, NH3 exchange is dynamic and difficult to measure. The goal of this study was to characterize this exchange by measuring the atmosphere, soil, and vegetation. Compensation point modeling was used to evaluate the direction and magnitude of surface-atmosphere exchange. Measurements were performed at the Manitou Experimental Forest Observatory (MEFO) site in the Colorado Front Range by continuous online monitoring of gas and particle phase NH3-NH4+ with an ambient ion monitoring system coupled with ion chromatographs (AIM-IC), direct measurements of [NH4+] and pH in soil extracts to determine ground emission potential (Γg), and measurements of [NH4+]bulk in pine needles to derive leaf emission potential (Γst). Two different soil types were measured multiple times throughout the study, in which Γg ranged from 5 to 2122. Γst values ranged from 29 to 54. Inferred fluxes (Fg) from each soil type predicted intervals of emission and deposition. By accounting for the total [NH4+] pool in each compartment, the lifetime of NH3 with respect to the surface-atmosphere exchange in the soil is on the order of years compared to much faster naturally occurring processes, i.e., mineralization and nitrification.
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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".