Decreased photosynthetic efficiency in plant species exposed to multiple airborne pollutants along the Russian-Norwegian border
Bibliographic record
Abstract
Photosynthetic efficiency was estimated by chlorophyll fluorescence measurements (Fv/Fm) in 11 plant species growing along a steep gradient of airborne pollution along the Russian-Norwegian border (70°N, 30°E). Photosynthetic efficiency was positively correlated with environmental variables including annual temperature and a maritime gradient and was negatively correlated with the airborne concentrations of Cu, Ni, and SO2 from the Cu-Ni smelters. Photosynthetic efficiency in six plant species from the mixed forest, but not pine (Pinus sylvestris L.), and three species from the birch forest was inversely correlated with SO2 and the concentrations of Ni and Cu in lichens. Measurement of fluorescence in these species was a sensitive indicator of pollutant impact. Plant cover at the 16 study sites and the photosynthetic efficiency of five target species correlated with normalized difference vegetation index (NDVI) values. This study demonstrated that it is possible to detect relations among field-measured ecophysiological responses in plants, levels of airborne pollutants, and satellite remote-sensed data.Key words: chlorophyll fluorescence, smelters, sulfur dioxide, nickel, copper, normalized difference vegetation index (NDVI).
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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) | 0.000 | 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 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".