Water storage dynamics of boreal shield peatlands: Implications for runoff and peat formation
Bibliographic record
Abstract
Northern peatlands are globally significant carbon stores that serve a number of hydrological, ecological and biogeochemical functions on the landscape, in close association with their water table (WT) position. While generally considered resilient to disturbance, thanks to autogenic feedbacks that regulate the WT, previous work suggests that not all peatlands are equal in this regard. That is, this ecohydrological resilience may vary with peatland depth and catchment size. There appear to be thresholds of peat depth, after which there are significant shifts in resilience, including the susceptibility of the WT falling below the peat profile and greater depths of burn from wildfire. We investigated the role of factors at the peatland to catchment scale on WT behaviour across a continuum of peatland and catchment sizes on the Boreal Shield. While the mean WT depth was not associated with any such factors, WT variability was greater in shallower peatlands, with the effect more pronounced during seasonal moisture deficit. On the other hand, the role of catchment and topographic position was more seasonally variable. With respect to hydrological functions of storage and runoff, deeper peatlands always maintained their saturated zone and were generally more ‘filled’, leading to greater hydrological connectivity. While the WT in deeper peatlands more closely followed seasonal moisture deficits and surpluses (i.e., precipitation less potential evapotranspiration; P-PET), shallow peatlands experienced greater WT drawdown rates during drying events. This research contributes to a growing body of work supporting the importance of peat depth to ecohydrological resilience, and identifying the thresholds at which peatlands may accumulate sufficient peat thickness and feedbacks for long-term persistence.
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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 | 0.000 | 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".