Circumpolar assessment of permafrost C quality and its vulnerability over time using long‐term incubation data
Bibliographic record
Abstract
High-latitude ecosystems store approximately 1700 Pg of soil carbon (C), which is twice as much C as is currently contained in the atmosphere. Permafrost thaw and subsequent microbial decomposition of permafrost organic matter could add large amounts of C to the atmosphere, thereby influencing the global C cycle. The rates at which C is being released from the permafrost zone at different soil depths and across different physiographic regions are poorly understood but crucial in understanding future changes in permafrost C storage with climate change. We assessed the inherent decomposability of C from the permafrost zone by assembling a database of long-term (>1 year) aerobic soil incubations from 121 individual samples from 23 high-latitude ecosystems located across the northern circumpolar permafrost zone. Using a three-pool (i.e., fast, slow and passive) decomposition model, we estimated pool sizes for C fractions with different turnover times and their inherent decomposition rates using a reference temperature of 5 °C. Fast cycling C accounted for less than 5% of all C in both organic and mineral soils whereas the pool size of slow cycling C increased with C : N. Turnover time at 5 °C of fast cycling C typically was below 1 year, between 5 and 15 years for slow turning over C, and more than 500 years for passive C. We project that between 20 and 90% of the organic C could potentially be mineralized to CO2 within 50 incubation years at a constant temperature of 5 °C, with vulnerability to loss increasing in soils with higher C : N. These results demonstrate the variation in the vulnerability of C stored in permafrost soils based on inherent differences in organic matter decomposability, and point toward C : N as an index of decomposability that has the potential to be used to scale permafrost C loss across landscapes.
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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 | 0.002 |
| 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) | 0.001 | 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".