Experimental nitrogen, phosphorus, and potassium deposition decreases summer soil temperatures, water contents, and soil CO <sub>2</sub> concentrations in a northern bog
Bibliographic record
Abstract
Abstract. Ombrotrophic peatlands depend on airborne nitrogen (N), whose deposition has increased in the past and lead to disappearance of mosses and increased shrub biomass in fertilization experiments. The response of soil water content, temperature, and carbon gas concentrations to increased nutrient loading is poorly known and we thus determined these data at the long-term N fertilization site Mer Bleue bog, Ontario, during a two month period in summer. Soil temperatures decreased with NPK addition in shallow peat soil primarily during the daytime (t-test, p < 0.05) owing to increased shading, whereas they increased in deeper peat soil (t-test, p < 0.05), probably by enhanced thermal conductivity. These effects were confirmed by RMANOVA, which also suggested an influence of volumetric water contents as co-variable on soil temperature and vice versa (p < 0.05). Averaged over all fertilized treatments, the mean soil temperatures at 5 cm depth decreased by 1.3 °C and by 4.7 °C (standard deviation 0.9 °C) at noon. Water content was most strongly affected by within-plot spatial heterogeneity but also responded to both N and PK load according to RMANOVA (p < 0.05). Overall, water content and CO2 concentrations in the near-surface peat (t-test, p < 0.05) were lower with increasing N load, suggesting more rapid soil gas exchange. The results thus suggest that changes in bog ecosystem structure with N deposition have significant ramifications for physical parameters that in turn control biogeochemical processes.
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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 | 0.000 | 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) | 0.001 | 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".