Response of boreal ecosystems to varying modes of permafrost degradation
Bibliographic record
Abstract
Permafrost degradation associated with a warming climate is second only to wildfires as a major disturbance to boreal forests. Permafrost temperatures have risen to 4 °C since the “Little Ice Age”, resulting in widespread thawing of permafrost. The mode of permafrost degradation is highly variable, and its topographic and ecological consequences depend on the interaction of slope position, soil texture, hydrology, and ice content. We partitioned this variability into 16 primary modes: (1) thermokarst lakes from lateral thermomechanical erosion; (2) thermokarst basins after lake drainage; (3) thaw sinks from subsurface drainage of lakes; (4) glacial thermokarst of ice-cored moraines; (5) linear collapse-scar fens associated with shallow groundwater movement; (6) round isolated collapse-scar bogs from slow lateral degradation; (7) small round isolated thermokarst pits from surface thawing; (8) polygonal thermokarst mounds from advanced ice-wedge degradation; (9) mixed thermokarst pits and polygons from initial ice-wedge degradation; (10) irregular thermokarst mounds from thawing of ice-poor silty soils; (11) sinkholes and pipes resulting from groundwater flow; (12) thermokarst gullies and water tracks from surface-water flow; (13) thaw slumps related to slope failure and thawing; (14) thermo-erosional niches from water undercutting of ice-rich shores; (15) collapsed pingos from thawing of massive ice in pingos; and (16) nonpatterned ground from thawing of ice-poor soils. These modes greatly influence how thermokarst changes or disrupts the ground surface, ecosystems, human activities, infrastructure, and the fluxes of energy, moisture, and gases across the landair interface.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".