Effects of short‐term N addition on plant biomass allocation and C and N pools of the <i>Sibiraea angustata</i> scrub ecosystem
Bibliographic record
Abstract
Summary To explain the effects of short‐term N addition on plant biomass allocation and on carbon (C) and nitrogen (N) pools in an alpine scrub ecosystem, we carried out a field experiment in Sibiraea angustata scrubland on the eastern margin of the Qinghai‐Tibetan Plateau of China. After one and a half years of N addition at four rates (N 0 , control; N 20 , 20; N 50 , 50; N 100 , 100 kg N ha −1 year −1 ), we investigated the amount and allocation of biomass and the C and N pools in several parts of the ecosystem, including shrubs (leaves, shoots and branches, coarse roots and fine roots), grass (above‐ and below‐ground) and litter (wood and leaf debris) components, and seven depth intervals within the soil (0–5, 5–10, 10–20, 20–30, 30–50, 50–70 and 70–100 cm). The results were as follows: (i) total vegetation biomass showed a linear increase with the increase in N ( P < 0.05), mainly from the increased root biomass in both shrubs and grasses, (ii) the ecosystem C and N storage were 36 and 3.26 kg m −2 , respectively, of which the shrub, grass, litter and soil components contributed 11.08, 0.47, 0.25 and 88%, respectively, to the C pool and 3.07, 0.16, 0.08 and 97%, respectively, to the N pool, (iii) the ecosystem N pool did not change in response to the addition of N, whereas the ecosystem C pool responded linearly to increasing N ( P < 0.05). These results suggest that the alpine scrub ecosystem functions as a net C sink under increasing atmospheric N deposition, mainly by promoting belowground C sequestration. Highlights Effects of short‐term N addition on biomass allocation and C and N pools in alpine scrub. Response to N addition in C pool of components of the ecosystem and soil at depth (0–100 cm). Root:shoot ratio of vegetation and ecosystem C pool increased linearly with increasing N. Alpine scrub ecosystem may function as a net C sink under increasing atmospheric N deposition.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".