Carbon and nitrogen stocks and distributions associated with different vegetation covers and soil profiles in Abisko, northern Sweden
Bibliographic record
Abstract
The composition of vegetation cover in Arctic environments is evolving due to climate change. This study focused on estimating carbon and nitrogen stocks in vegetation and soil for different Arctic habitats (i.e., sub-ecosystem environments) with contrasted plant communities and soil profiles, to better understand the spatial variation of these stocks and the relationships between aboveground vegetation and soil characteristics in these environments. Vegetation composition and soil characteristics were measured in different habitats in a mire and a heathland ecosystem in northern Sweden. Multivariate analyses were used to define dominant vegetation and soil profile types, and carbon and nitrogen stocks were computed and compared across these types. Shrub-dominated and graminoid-dominated vegetation types presented similar carbon stocks but different nitrogen stocks, and shrub-dominated environments presented significantly higher proportions of their stocks distributed in the long-lived (i.e., woody) compartment. Soil stocks varied considerably between ecosystems. However, no clear relationships could be established between current vegetation community composition and soil carbon and nitrogen stocks across environments. The increase in shrub or graminoid abundance may affect carbon and nitrogen cycles most through biomass distribution between plant compartments rather than through the absolute stocks they represent. Ultimately, in Arctic and subarctic ecosystems experiencing climate change, the interactions between plant biomass composition and soil characteristics could have contrasted consequences for ecological functioning and C and N cycles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".