Ecohydrological Controls on post-fire Sphagnum moss recovery in Boreal Shield peatlands
Bibliographic record
Abstract
Northern peatlands are critical carbon sinks, and wildfire is the largest disturbance within the Boreal ecozone. The return of a peatland to a carbon sink and the post disturbance resilience of peatlands depends greatly on the ecohydrological recovery and reestablishment of Sphagnum mosses.We examined post-fire moss accumulation and moss moisture stress (soil water tension, soil moisture) in triplicate burned and unburned Boreal Shield Sphagnum dominated peatland types (shallow, deep peatland middle, and deep peatland margin). Additional climatological and geophysical measurements were taken to identify ecohydrological controls on post-fire Sphagnum recovery.The soil water tension exceeded 100 mbar (an established physiological threshold for Sphagnum) when the water table was lost from the peat profile, which only occurred in the shallowest peatlands. We found no significant difference in the moss moisture stress between the burned and unburned landscapes 5-years post fire. Depth of burn, remnant post-fire soil depth, and post-fire soil accumulation did not show a significant relationship with soil water tension 5-years post fire. Rather, current peat depth best explained moss moisture stress in burned and unburned landscapes, suggesting a peat depth threshold, above which Sphagnum drought resilience increases. Our ongoing research seeks to identify the critical depth threshold for greater moss resilience in a natural, disturbed, and recovering environment through Hydrus-1D modelling with the aim to provide researchers and practitioners information to maximise peatland ecosystem recovery through post-fire restoration.
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 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".