Photoinduced Evolutions of Permafrost-Derived Carbon in Subarctic Thermokarst Pond Surface Waters
Bibliographic record
Abstract
In subarctic regions, rising temperature and permafrost thaw lead to the formation of thermokarst ponds, where organics from eroding permafrost accumulate. Despite its environmental significance, limited knowledge exists regarding the photosensitivity of permafrost-derived carbon in these ponds. In this study, laboratory experiments were conducted to explore the photochemical transformations of organic matter in surface water samples from thermokarst ponds from different environments in northern Quebec, Canada. One pond near Kuujjuarapik is characterized by the presence of a collapsing palsa and is therefore organically rich, while the other pond near Umiujaq is adjacent to a collapsing lithalsa and thus contains fewer organic matters. Photobleaching occurred in the Umiujaq sample upon irradiation, whereas the Kuujjuarapik sample exhibited an increase in light absorbance at wavelength related to aromatic functionalities, indicating different photochemical aging processes. Ultrahigh-resolution mass spectrometry analysis reveals that the Kuujjuarapik sample preferentially photoproduced highly unsaturated CHO compounds with great aromaticity, while the irradiated Umiujaq sample produced a higher proportion of CHON aromatics with reduced nitrogen functionalities. Overall, this study illustrates that the photochemical reactivity of thermokarst pond water varies with the source of organic matter. The observed differences in reactivity contribute to an improved understanding of the photochemical emission of volatile organic compounds discovered earlier. Further insights into the photoinduced evolutions in thermokarst ponds may require the classification of permafrost-derived carbon therein.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".