Responses of the mosses <i>Sphagnum capillifolium</i> and <i>Polytrichum strictum</i> to nitrogen deposition in a bog: growth, ground cover, and CO<sub>2</sub> exchange
Bibliographic record
Abstract
Previous studies have shown that atmospheric nitrogen (N) deposition is detrimental to sphagna, which are a group of mosses that are important for carbon cycling in northern peatlands. Little is known about species interactions, such as relative responses of tall moss Polytrichum strictum Menzies ex Brid. and sphagna. We studied the effects of N deposition on growth, abundance, and CO2 exchange of the moss species Sphagnum capillifolium (Ehrh.) Hedw. and Polytrichum strictum in an experiment at a temperate bog. Sphagnum growth and cover decreased significantly with high-dose N treatment (6.4 g N·m−2·year−1) in years 4 and 5 of treatment, whereas the same parameters increased for Polytrichum compared with the control. Net CO2 exchange, gross photosynthesis (Pg), and dark respiration (R) in the intact moss cores, which were measured in year 5 of treatment, were elevated in the cores that had been treated with the high-dose of N, compared with the control, and this was associated with increased abundance of Polytrichum. The moss cores where Polytrichum was removed, however, had increased mass-based R with the high-dose N treatment. Our results showed that S. capillifolium at Mer Bleue may be close to N saturation, as 5 years of high-dose N loading (6.4 g N·m−2·year−1 + background) was harmful to this species, possibly as a result of increased respiratory cost. Polytrichum strictum had a competitive advantage, at least in the short-term, through allocating excess N to growth. This change in moss layer composition deserves further attention, as a shift to more easily decomposable litter, without corresponding increases in plant production, could reduce the carbon sequestration of the bog.
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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".