Positive rhizosphere priming accelerates carbon release from permafrost soils
Bibliographic record
Abstract
Abstract Thawing permafrost soils are predicted to release substantial amounts of carbon by 2100. In addition to this, warming-induced active-layer deepening and increased rooting depth may result in further carbon losses from previously-frozen soil by stimulating microbial communities through fresh carbon inputs inducing positive rhizosphere priming. While models based on temperate data predict significant permafrost carbon loss through rhizosphere priming, data from permafrost soils are lacking. Here, we provide direct evidence of live plant-induced positive rhizosphere priming in permafrost and active-layer soils across diverse soil types from Arctic and Subarctic Canada. By 13CO2 labelling plants in a controlled environment, we show that root activity increases carbon loss from previously frozen soils by 31%. This rhizosphere priming effect persists longer in permafrost than in active-layer soils, suggesting greater vulnerability of permafrost carbon. These findings underscore the urgency of incorporating plant–soil–microbe interactions into models predicting greenhouse gas emissions from thawing permafrost.
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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) | 0.001 | 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".