The roles of parent material, climate, and geomorphology in soil organic carbon response to short-term climate change in moist boreal forests
Bibliographic record
Abstract
Boreal forests store significant soil organic carbon (SOC) where increasing temperature and extreme precipitation are expected with climate change. Yet, the impact on subsoil SOC is unclear. Dissolved organic matter (DOM) facilitates Al weathering to precipitate Al organo-metal complexes (AlOMC) that stabilize mineral horizon SOC. An enhanced DOM input is expected with climate change, however, a high water-flux associated with extreme precipitation may limit AlOMC precipitation. This thesis investigates the roles of parent material composition, climate and geomorphology in boreal SOC dynamics using climate and hillslope transects to enhance: (1) subsoil SOC predictions and (2) its response to short-term climate change. A SOC content predictive model was developed using soils from four climate regions with varying parent material. Unsurprisingly, AlOMC content was the main predictor, with greater SOC in regions with high Al availability. Further interactions with depth-dependent factors, C saturation of AlOMC (C:AlOMC) and their proportion of SOC, suggested infiltration depth is key within a region. As such, greater SOC is supported on gentle slopes via deeper infiltration. Controls on SOC response to extreme precipitation were evaluated experimentally with increasing soil moisture to emulate events occurring on dry summer soils to wet late autumn soils. Antecedent soil moisture and C:AlOMC controlled SOC response under high water flux regardless of parent material or climate. I present a simple predictive model demonstrating shallow SOC loss but deeper storage potential, with greater potential on gentle slopes. Further, enhanced loss from dry soils indicates late summer SOC is most vulnerable to loss (~1‰). Therefore, event timing and infiltration depth are key for SOC response to extreme precipitation. Weathering profiles (mass transfer coefficients), AlOMC and SOC distributions suggest that Al availability sets the water flux threshold for AlOMC precipitation. Extreme events surpass this threshold, limiting new SOC storage. Enhanced SOC storage is expected with an increasing DOM flux with climate change in Al-rich regions supporting higher AlOMC precipitation thresholds, while Al-poor regions may experience SOC loss. These results find regional parent material overrides climate controls on boreal SOC, and this will inform carbon feedbacks to improve Earth Systems models.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".