Boreal forest soil chemistry drives soil organic carbon bioreactivity along a 314-year fire chronosequence
Bibliographic record
Abstract
Abstract. Following wildfire, organic carbon (C) accumulates in boreal forest soils. The long-term patterns of accumulation as well as the mechanisms responsible for continuous soil C stabilization or sequestration are poorly known. We evaluated post-fire C stock changes in functional reservoirs (bioreactive and recalcitrant) using the proportion of C mineralized in CO2 by microbes in a long-term lab incubation, as well as the proportion of C resistant to acid hydrolysis. We found that all soil C pools increased linearly with time since fire. The bioreactive and acid-insoluble soil C pools increased at a rate of 0.02 MgC ha−1 yr−1 and 0.12 MgC ha−1 yr−1, respectively, and their proportions relative to total soil C stock remained constant with time since fire (8 % and 46 %, respectively). We quantified direct and indirect causal relationships among variables and carbon bioreactivity to disentangle the relative contribution of climate, moss dominance, soil particle size distribution and soil chemical properties (pH, exchangeable Mn and Al, and metal oxides) to the variation structure of in vitro soil carbon bioreactivity. Our analyses showed that the chemical properties of Podzolic soils that characterise the study area were the best predictors of soil carbon bioreactivity. For the FH horizon (O-layer), pH and exchangeable Mn were the most important (model-averaged estimator for both: 0.34) factors directly related to soil organic C bioreactivity, followed by time since fire (0.24), moss dominance (0.08) and climate and texture (0 for both). For the mineral soil, exchangeable aluminum was the most important factor (model-averaged estimator: −0.32), followed by metal oxide (−0.27), pH (−0.25), time since fire (0.05), climate and texture (~ 0 for both). Of the four climate factors examined in this study (i.e., mean annual temperature, growing degree-days above 5 °C, mean annual precipitation and water balance) only those related to water availability, and not to temperature, had indirect effect (FH horizon) or a marginal indirect effect (mineral soil) on soil carbon bioreactivity. Given that predictions of the impact of climate change on soil carbon balance are strongly linked to the size and the bioreactivity of soil C pools, our study stresses the need to include the direct effects of soil chemistry and the indirect effects of climate and soil texture on soil C decomposition in Earth System Models to forecast the response of boreal soils to global warming.
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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 | 0.000 | 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".