Scots Pines (Pinus sylvestris) as Sources of Biological Ice-Nucleating Macromolecules (INMs)
Bibliographic record
Abstract
Scots pine (Pinus sylvestris) is the most widespread pine species in the world. It grows in the largest forest system in the northern hemisphere and, together with birch trees, occupies a major part of the boreal forests. Recently, birch trees have been discovered as important emission sources of terrestrial ice-nucleating macromolecules (INMs) coming from pollen, bark, leaves, petioles, branches, and stem surfaces. It is known that pine pollen nucleate ice; however, the potential of other tree parts releasing INMs and contributing to the emission of ice-active aerosols is unknown. Here, we investigated the distribution of INMs in, on, and around Scots pines (Pinus sylvestris) in a laboratory and field study. We collected bark, branch wood, and needle samples from six pine trees in an urban park in Vienna, Austria. The concentration of INMs from aqueous extracts of milled (powder extracts) and intact surfaces (surface extracts) were determined. In addition, we collected rainwater rinsed off from three pines during a rainfall event and analyzed its INM content. All investigated samples contained INMs with freezing onset temperatures ranging from −16 °C to −29 °C. The number concentration of INMs in powder extracts at −25 °C (nINMs−25 °C) ranged from 105 to 109 per mg dry weight. Surface extracts showed concentrations from 105 to 108 INMs per cm2 of extracted surface, with needle samples exhibiting the lowest concentrations. In the rain samples, we found 106 and 107 INMs per cm2 of rain-collector area at −25 °C, with freezing onset temperatures similar to those observed in powder and surface extracts. With our data, we estimate that one square meter of pine stand can release about 4.1 × 109 to 4.6 × 1012 INMs active at −25 °C and higher, revealing pine forests as an extensive reservoir of INMs. Since pines are evergreen and release INMs not only from pollen grains, pines and the boreal forest in general need to be considered as a dominant source of INMs in high latitude and high-altitude locations, where other species are rare and other ice nuclei transported over long distances are diluted. Finally, we propose pine trees as an INM emission source which can trigger immersion freezing events in cloud droplets at moderate supercooled temperatures and therefore may have a significant impact on altering mixed phase clouds.
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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".