Hydrogeological controls on post-fire moss recovery in peatlands
Bibliographic record
Abstract
Summary Wildfire is the largest disturbance affecting boreal peatlands, however, little is known about the controls on post-fire peatland vegetation recovery. While small-scale variation in burn severity can reduce post-fire moss water availability, high water table (WT) positions following wildfire are also critical to enable the re-establishment of keystone peatland mosses ( i.e. Sphagnum ). Thus, post-fire moss water availability is also likely a function of landscape-scale controls on peatland WT dynamics, specifically, connectivity to groundwater flow systems ( i.e. hydrogeological setting). For this reason, we assessed the interacting controls of hydrogeological setting and burn severity on post-fire moss water availability in three burned, Sphagnum -dominated peatlands in Alberta’s Boreal Plains. At all sites, variation in burn severity resulted in a dichotomy between post-fire surface covers that: (1) exhibited low water availability, regardless of WT position, and had minimal ( i.e. lightly burned feather mosses and severely burned Sphagnum fuscum ) or (2) exhibited high water availability, depending on WT position, and had substantial (>50%) moss re-establishment ( i.e. lightly burned S. fuscum and where depth of burn was >0.05 m). Notably, hydrogeological setting influenced the spatial coverage of these post-fire surface covers by influencing pre-fire WTs and stand characteristics ( e.g. , shading). Because feather moss cover is controlled by tree shading, lightly burned feather mosses were ubiquitous (>25%) in drier peatlands (deeper pre-fire WTs) that were densely treed and had little connection to large groundwater flow systems. Moreover, hydrogeological setting also controlled post-fire WT positions, thereby affecting moss re-establishment in post-fire surface covers that were dependent on WT position ( e.g. , lightly burned S. fuscum ). Accordingly, higher recolonization rates were observed in a peatland located in a groundwater flow through system that had a shallow post-fire WT. Therefore, we argue that hydrogeological setting influences post-fire recovery in two ways: (1) by influencing vegetation structure prior to wildfire, thereby controlling the coverage of post-fire surface covers and (2) by influencing post-fire WT positions. These results suggest that post-fire moss recovery in peatlands isolated from groundwater flow systems may be particularly susceptible to droughts and future climate change.
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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 | 0.001 | 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 | 0.001 |
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 teacher head, 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".