Chemical and C and N stable isotope compositions of three species of epiphytic <i>Tillandsia</i> in a Caribbean coastal zone: air pollution sources and biomonitoring implications
Bibliographic record
Abstract
We characterized the elemental and C and N stable isotope compositions of Tillandsia fasciculata Sw., Tillandsia balbisiana Schult. & Schult.f. and Tillandsia recurvata (L.) L. samples collected in Cienfuegos (Cuba). Results showed high enrichment factors for S, Hg, Cd, Pb, P, Zn, Cu, Mo, Sb and Ca in all Tillandsia species, indicating inputs from local anthropogenic activities (road traffic, industries and cement production). Carbon concentrations and δ13C varied from 38.3–47.7 % and –20.4 to –13.4 ‰ within the three species, respectively. δ13C showed seasonal dependence with the dry and wet periods and more 13C-depleted values in urban/industrial areas, coherent with the input of anthropogenic emissions. Nitrogen concentrations (0.4–1.3 %) and δ15N values (–9.9–4.4 ‰) exhibit larger variations and are positively correlated in the three species. The most positive δ15N in T. recurvata (–0.2–4.4 ‰) are attributed to contributions from industrial activities and road traffic. In fact, both δ15N and total nitrogen (TN) values increase in sites with higher road traffic and show significant correlations with typical road traffic and industrial tracers. Finally, we calculate an average total nitrogen deposition rate of 4.4 ± 2.3 kg ha–1 a–1 from N content in T. recurvata, similar to the existing values determined in the region by field measurements, but higher than the global terrestrial average.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".