Isoprene and monoterpene emissions from secondary forest in northern Benin
Bibliographic record
Abstract
Abstract. The biogenic volatile organic compound (BVOC) composition of ambient air at a rural field site near Djougou, Benin has been studied as part of the AMMA (African Monsoon Multidisciplinary Analysis) project. Ambient air was sampled during day and night during the period 2 June 2006 to 13 June 2006. Gas samples from within the forest canopy and from branch and cuvette enclosure systems for four vegetation species were also obtained and emissions flux estimates made. All samples were analysed for the presence of isoprene, monoterpenes and sesquiterpenes by either gas chromatography-time of flight mass spectrometry (GC-TOF/MS) or comprehensive gas chromatography-time of flight mass spectrometry (GCxGC-TOF/MS). Concentrations of isoprene ranged from a few tens of pptV to in excess of 3000 pptV. Similar concentration ranges for certain monoterpenes were also observed. Limonene was seen at a maximum concentration in ambient air of 5000 pptV. The combination of leaf-level observations and direct analysis of dried vegetation samples suggest that emissions of terpene species from indigenous species are unlikely to account for the unexpectedly high ambient concentrations of monoterpenes. Leaf scale emission measurements and biological sample analysis indicated that Anacardium occidentale, a non-native crop species found throughout the tropics, was the dominant source of monoterpenes at this location. These preliminary findings suggest that activities involving species replacement have potential implications for the chemistry of the African troposphere that have not been widely considered previously.
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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 | 0.000 | 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".