Scots pine provenance affects the emission rate and chemical composition of volatile organic compounds of forest floor
Bibliographic record
Abstract
Scots pine (Pinus sylvestris L.) is an important source of biogenic volatile organic compounds (BVOCs) in the boreal zone. BVOC emission rate and profile affect air quality, climate forcing, plant stress tolerance, and thus the growing conditions of forests. BVOC emission profile of shoots and forest floor, as well as emission rates from forest floor, were studied in a latitudinal provenance experiment with 19-year-old Scots pine common garden in Central Finland. The provenances studied were Saaremaa (SAA, 58°22′), Korpilahti (KOR, 62°0′), Suomussalmi (SUO, 65°10′), and Muonio (MUO, 67°56′). A chemotype with high proportion of Δ-3-carene, terpinolene, sabinene, γ-terpinene, and α-terpinene was significantly more common for the southern SAA than the northern SUO and MUO provenances. A chemotype with high proportion of α-pinene, β-pinene, limonene, and myrcene was more common in the three northernmost provenances. The main compounds emitted by forest floor were α-pinene, Δ-3-carene, and camphene. Similarly to shoot emissions, forest floor emissions from SAA had highest proportion of Δ-3-carene. Average total VOC emission rate from forest floor was 50 μg·m−2·h−1 at the end of August. Total emission rates were 65% higher in KOR than in MUO. High emission rates were explained by the high amount of decomposing needle litter and low moss coverage.
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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".