Drivers of legacy soil organic matter decomposition after fire in boreal forests
Bibliographic record
Abstract
Abstract Boreal forests harbor as much carbon (C) as the atmosphere and significant amounts of organic nitrogen (N), the nutrient most likely to limit plant productivity in high‐latitude ecosystems. In the boreal biome, the primary disturbance is wildfire, which consumes plant biomass and soil material, emits greenhouse gasses, and influences long‐term C and N cycling. Climate warming and drying is increasing wildfire severity and frequency and is combusting more soil organic matter (SOM). Combustion of surface SOM exposes deeper older layers of accumulated soil material that previously escaped combustion during past fires, here termed legacy SOM. Postfire SOM decomposition and nutrient availability are determined by these layers, but the drivers of legacy SOM decomposition are unknown. We collected soils from plots after the largest fire year on record in the Northwest Territories, Canada, in 2014. We used radiocarbon dating to measure Δ 14 C (soil age index), soil extractions to quantify N pools and microbial biomass, and a 90‐day laboratory incubation to measure the potential rate of element mineralization and understand patterns and drivers of legacy SOM C decomposition and N availability. We discovered that bulk soil C age predicted C decomposition, where cumulatively, older soil (approximately −450.0‰) produced 230% less C during the incubation than younger soil (~0.0‰). Soil age also predicted C turnover times, with old soil turnover 10 times slower than young soil. We found respired C was younger than bulk soil C, indicating most C enters and leaves relatively quickly, while the older portion remains a stable C sink. Soil age and other indices were unrelated to N availability, but microbial biomass influenced N availability, with more microbial biomass immobilizing soil N pools. Our results stress the importance of legacy SOM as a stable C sink and highlight that soil age drives the pace and magnitude of soil C contributions to the atmosphere between wildfires.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.012 | 0.016 |
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; both teacher heads agree on what is shown here.
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".