A High Arctic soil ecosystem resists long‐term environmental manipulations
Bibliographic record
Abstract
Abstract We evaluated above‐ and belowground ecosystem changes in a 16 year, combined fertilization and warming experiment in a High Arctic tundra deciduous shrub heath (Alexandra Fiord, Ellesmere Island, NU, Canada). Soil emissions of the three key greenhouse gases (GHGs) (carbon dioxide, methane, and nitrous oxide) were measured in mid‐July 2009 using soil respiration chambers attached to a FTIR system. Soil chemical and biochemical properties including Q10 values for CO2, CH4, and N2O, Bacteria and Archaea assemblage composition, and the diversity and prevalence of key nitrogen cycling genes including bacterial amoA, crenarchaeal amoA, and nosZ were measured. Warming and fertilization caused strong increases in plant community cover and height but had limited effects on GHG fluxes and no substantial effect on soil chemistry or biochemistry. Similarly, there was a surprising lack of directional shifts in the soil microbial community as a whole or any change at all in microbial functional groups associated with CH4 consumption or N2O cycling in any treatment. Thus, it appears that while warming and increased nutrient availability have strongly affected the plant community over the last 16 years, the belowground ecosystem has not yet responded. This resistance of the soil ecosystem has resulted in limited changes in GHG fluxes in response to the experimental treatments.
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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 | 0.000 | 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".